THE JOURNAL OF THE ALABAMA ACADEMY OF SCIENCE VOLUME 78 NO. 1 JANUARY 2007 Cover Photograph: Little River Canyon Waterfall (Fort Payne Alabama) Photo courtesy of: Dr. Frank A. Romano, 111, Professor of Biology, Jacksonville State University Editorial Comment: On behalf of the Alabama Academy of Science, 1 would like to express my gratitude and appreciation to the following for their valuable contributions in reviewing the manuscripts of this issue: Dr. Robert Carter, Jacksonville State University Dr. George Cline, Jacksonville State University Dr. George Folkerts, Auburn University Dr. William French, Mississippi State University Dr. Richard Hudiburg, University of North Alabama Mr. David Myer, Jacksonville State University Dr. James Rayburn, Jacksonville State University Mr. Dan Spaulding, Anniston Museum of Natural History Dr. Nader Vahdat, Tuskegee University Dr. Thane Wibbels, University of Alabama at Birmingham Dr. David Whetstone, Jacksonville State University Safaa Al-Hamtlani Editor, Alabama Academy of Science Journal THE JOURNAL OFTHE ALABAMA ACADEMY OF SCIENCE AFFILIATED WITH THE AMERICAN ASSOCIATION FOR THE ADVANCEMENT OF SCIENCE VOLUME 78 JANUARY 2007 NO.l EDITOR: Safaa Al-Hamdani, Biology Department, Jacksonville State University, Jacksonville, AE 36265 ARCHIVIST; Troy Best, Department of Zoology and Wildlife Science, Auburn University, Auburn, AL 36849 EDITORIAL BOARD: Thane Wibbels, Department of Biology, University of Alabama at Birmingham, Birmingham, AL 35294 David H. Myer, English Department, Jacksonville State University, Jacksonville, AL 36265-1602 Prakash Sharma, Department of Physics, Tuskegee University, Tuskegee, AL 36088 Publication and Subscription Policies: Submit all manuscripts and pertinent correspondence to the Editor. Each manuscript will receive at least two simultaneous reviews. For style details, follow instructions to Authors (see inside back cover). Reprints requests must be addressed to Authors. Subscriptions and Journal Exchanges: Address all Correspondence to the Chairman of the Editorial Board. ISSN 002-41 12 BENEFACTORS OF THE JOURNAL OF THE ALABAMA ACADEMY OF SCIENCE The following have provided financial support to partially defray publication costs of the journal. AUBURN UNIVERSITY AUBURN UNIVERSITY AT MONTGOMERY BIRMINGHAM-SOUTHERN COLLEGE JACKSONVILLE STATE UNIVERSITY SAMFORD UNIVERSITY TROY STATE UNIVERSITY TUSKEGEE UNIVERSITY UNIVERSITY OF ALABAMA UNIVERSITY OF ALABAMA AT BIRMINGHAM UNIVERSITY OF MONTEVALLO UNIVERSITY OF NORTH ALABAMA UNIVERSITY OF SOUTH ALABAMA CONTENTS ARTICLES: Interactions Between the Red Hills Salamander and its Potential Invertebrate Prey Kristin A. Bakkegard . 1 Effect of Various Photosensitive Dyes on the Growth of Tetrahymena in Vitro Misty A. Chapman, Jonathan C. Beavers, Mark E. Meade, Benjie G. Blair, and Charles P. Olander . 13 Pteridophytes of Southeast Alabama Alvin R. Diamond, Jr. and Michael Woods . 21 Heterogenous Modeling and Simulation of Activated Sludge Processes Gamal M. Ibrahim, Ahmed H. El-Ahwany, Abdel K. Mazher and Hisham 1. Ibrahim . 29 Note: Science and the Understanding of Consciousness Gerard Elfstrom . 53 MINUTES of the Executive Committee Meeting . 67 MEMBERSHIP LIST 87 Journal of Alabama Academy of Science Vol. 78, No. 1, January 2007 INTERACTIONS BETWEEN THE RED HILLS SALAMANDER AND ITS POTENTIAL INVERTEBRATE PREY Kristin A. Bakkegard Department of Biology, Utah State University, Logan, UT 84322-5305, U.S.A. Correspondence;kbakkegard@biology. usu.edu ABSTRACT The foraging habits of Red Hills Salamanders {Phaeognathus Inibrichti) at their burrow entrances were observed using a video camera. The number of prey available and the number of times salamanders oriented were counted, attempted and prey items were successfully eaptured. Red Hills Salamanders were sit and-wait predators that suecessfully eaptured and consumed earthworms and unidentifiable insect larvae. They oriented toward but did not eapture camel crickets {Ceiithopliiliis sp.) and did not visibly react to harvestmen {Leiobiinwn sp. ). Camel criekets immediately hopped away when they touched a salamander with their long antennae, and harvestmen did not visibly react to a salamander, even at distances less than 2 em. This study is unique in documenting the foraging behavior of a salamander in the field, over a long time period, with minimal disturbance to either the salamander or its prey. INTRODUCTION Salamanders are predators on a wide variety of invertebrates. Many species are sit-and- wait type predators, whereas a few aetively forage (Duellman and Trueb, 1986). Sit-and- wait type predators generally consume aetive prey whereas widely foraging predators eat sedentary prey. Prey must disrupt one or several of these phases to avoid being eaten: deteetion, identifieation, approach, subjugation and/or consumption (Endler, 1986). Thus in any predator-prey system, there are physiological, ecological and behavioral interaetions that influenee the types of prey eaten by the predator and the rate of consumption of the individual prey types. Typieally noeturnal, terrestrial salamanders are seeretive, living under roeks, logs, leaf litter, or in burrows (Petranka, 1998). However, the natural history of the Red Hills Salamander (Pbaeognatbus bubricbti, Highton, 1961) allows for direct field observation of this salamander’s foraging behaviors and the behaviors of its potential prey in response to the presenee of a salamander. The monotypic Red Hills Salamander is a large (total length to 25.5cm) fossorial plethodontid endemic to the Red Hills region of south-eentral Alabama (Mount, 1975). Bakkegard. K— Red Hills Salamanders and Its Invertebrate Prey Entirely terrestrial, it lives in burrows found in the sides of steep ravines, composed of a soft siltstone/mudstone, well shaded by a hardwood overstory (Brandon, 1965; Schwaner and Mount, 1970; Dodd, 1991). All aspects of its life history are associated with these e.xtensively branched and interconnecting burrows which the salamanders have not been observed to dig (Brandon, 1965; Jordan, 1975). Each burrow entrance is oval in shape (approximately 20% higher than wide) with a smooth rounded rim and smooth packed floors and walls (Valentine, 1963; Schwaner and Mount, 1970). Salamanders are found at burrow entrances, on average 12.3 hrs, mainly during darkness, although there is limited diurnal activity, and they rarely leave their burrows (Bakkegard, 2002). This burrow centric behavior allows for continuous, direct observation in the field, using a video camera, of the foraging habits at a burrow entrance and the behavioral interactions between the salamander (a predator of the local invertebrate community) and its prey. This study is unique among studies of salamanders in that it documents foraging behavior in the field over a long period of time with minimal disturbance to the animals being observed. 1 studied the foraging behavior of the Red Hills Salamander by documenting the total prey availability, the prey types toward which salamanders oriented and the prey types that salamanders successfully captured and consumed at or near their burrow entrances. 1 also examined the behavioral interactions between the predatory salamander and two of its potential prey, camel crickets and harvestmen. 1 focused on these two potential prey because they were abundant and had contrasting behaviors. Foraging by this salamander has only been observed in the field twice (Jordan, 1975), although there are some dietary data based on analyses of stomach contents and fecal pellets (Brandon, 1965; Gunzburger, 1 999) which 1 consolidated here to make this the most complete record of foraging behavior in this salamander to date. MATERIALS AND METHODS A population of Red Hills Salamanders was studied and located at Haines Island Park, a United States Army Corps of Engineering property in Monroe County, Alabama, USA from July 1998 to December 1999. Videotaping details are described in Bakkegard (2002), and the data for this study are from the same video tapes used to quantify activity patterns in that study. To summarize: A Sony™ 8 mm TR-940 camcorder was used, mounted on a tripod and equipped with infrared illumination to record all events at and around a burrow entrance occupied by a Red Hills Salamander. Typically, videotaped burrows had a salamander present, were located so that the camera and tripod could be set up, and had not been previously videotaped. However, about 20% of the time, salamanders were not present at start time. Therefore, a burrow that was known to have been occupied based on a previous survey was chosen. Once the camera was positioned, the site was departed from, returning every 4 h to change the tape. Thirty seven different burrows were videotaped in 40 sessions. One burrow was videotaped three times, but only two sessions had salamander/ potential prey interactions. These two sessions were temporally separated by eight months. Another burrow was videotaped twice, with a 1 .5 month separation between sessions. Thus, 2 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 was assumed that each videotaped burrow represents a different salamander (exeept for the exceptions noted above) because I never saw more than one salamander in an entrance and recapture data from this site (Carroll et ah, 2000) suggests that burrows are usually occupied by a single individual. Videotaping occurred for an average of 1 5.03 h per session (range 7.98-19.14 h) for a total of 545 h (320 h sunset to sunrise (night time) and 225 h sunrise to sunset (daytime) of which 303 h had a salamander visible on tape (250 h night time, 53 h daytime). Daytime and night time hours were distributed throughout all months, except April 1 999 when no videotaping occurred. Salamander responses to prey: Three categories were used to define salamander behavior: orientation (N^^), attempt (N^) and suceess (N^,). Orientation, a rapid movement of a salamander’s head or body in the direction of a stimulus on or off camera, was used as a measure of salamander interest in an item. 1 only analyzed instances in which salamanders oriented towards potential prey visible on camera. An attempt was when a salamander snapped, lunged or extended its tongue toward a potential prey item. A success occurred when the salamander captured and eonsumed a prey item. The invertebrates (potential prey) seen on the videotapes were counted and identified. For unidentifiable items, three categories were created based on the general form or type of locomotion: flying, crawling (with legs) and unidentifiable (wiggling in the soil). Potential prey seen at the same time as a salamander were also counted at an entrance (a subset of the total number of potential prey). Beeause the distributions of the two data sets did not differ, 1 only report the latter here. On two oceasions, salamanders oriented multiple times toward the same trapdoor spider (Myrmekiaphila sp.). All such orientations were counted as one event. Moths and other flying insects were counted only if they flew into the side of the slope or tangentially along it near enough that a salamander eould have potentially preyed upon it. Prey availability and feeding rate were calculated by dividing the number of prey or suecesses by the number of hour’s salamanders were visible at entranees. Total success rate based on the total number of items salamanders captured was divided by the total number of attempts. To determine if there was a relationship between salamander and potential prey temporal activity patterns, 1 ealeulated a Spearman correlation coefficient (.data non¬ normal; Zar 1999) between measures of salamander and inseet activity computed for each one-hour period in a day. Salamander activity was taken from Bakkegard (2002) and was computed as the number of hours that salamanders were present at entrances divided by the number of hours the camera was operational during each one hour period. Insect activity was determined similarly using the number of prey items (excluding harvestmen) observed during a particular one-hour period of the day as the numerator. Statistical analyses were conducted with SAS version 8.01 (SAS Institute, Inc., Cary, NC, USA) and P values less than 0.05 were considered significant. Ideally, any statistical analysis of these data would use burrows (and thus salamanders) as independent replicating units. However, for this observational study, 1 3 i Bakkegard, K— Red Hills Salamanders and Its Invertebrate Prey I used potential prey items as independent observations beeause of substantial differenees in 1 the types of prey appearing at eaeh burrow, in eombinations with low prey eounts. For the ! two burrows that were videotaped twiee, there were no repeated measures on salamander/ I opilionid/orthopteran interaetions. For responses of salamanders to prey, the strueture of the data (high variability in the types of potential prey eoupled with low prey eounts) dietated a I deseriptive approaeh. However, based on observation, there appeared to be little variability j in response among salamanders to potential prey items. Only one salamander (not the foeal I animal but one from a nearby burrow) was observed leaving burrow (twiee). I Prey responses to salamanders: 1 The interaction between Red Hills Salamanders and orthopterans (exclusively I camel crickets, Ceuthophiliis sp.) and opilionids (harvestmen, Leiohunum sp.) proved I noteworthy as these arthropods were the two most abundant potential prey, active I throughout the study, and easy to observe and identify on the videotape. I characterized I camel cricket behavior into one of three classes: the salamander orients toward the cricket but the cricket does not touch the salamander with its antennae; the salamander orients and the cricket touches the salamander with its antennae; and the salamander does not orient but the cricket touches the salamander with its antennae. Behavior of harvestmen was not easily quantifiable, but is best described as searching or locomotion from one point j to another. I noted the behavior of harvestmen that walked near (within approx. 2 cm) or directly over a salamander burrow with a salamander present, and compared that to the I behavior of harvestmen that were seen on camera but were not near (> approx. 2 cm) to a salamander. RESULTS Salamander responses to prey: A total of 250 potential prey items were observed; 190 of these were present simultaneously with a salamander at an entrance. The most abundant potential prey items ' were Orthopterans (camel crickets, Ceuthophiliis sp. ), Opiliones (harvestmen, Leiohunum sp.), crawling arthropods, and Hymenoptera (ants and 1 wasp; Table 1). More prey was I present during nighttime than daylight hours (Fig. 1 ). There was a positive and significant : correlation between salamander activity and insect activity (r^ = 0.57, P = 0.004, N = 24). ' The rate of prey availability (when salamanders present) was 15.0 items/day including I Opilionids, and 1 1 .6 items/day, excluding Opilionids. I I Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 Table 1 . Prey items consumed by Phaeogtiathus hubrichti, Monroe County, Alabama. Item E N No Na Ns N| Ng Nb Arachnida 5 5 2 2 0 - 3 Blatteria — — — — - 1 1 - Colcoptera 3 3 2 1 0 - 6 7 Diplopoda - - - - - - 3 6 Diptera - - - - - - - 1 Gastropoda - - - - - - 10 7 Hemiptera - - - - - - 1 - Hymenoptera 8 18 5 0 0 - 9 6 Lepidoptera 5 8 3 2 0 - - — Oligochaeta 1 7 3 2 2 - 1 - Opiliones 13 44 3 0 0 - - - Orthoptera 17 52 24 3 0 U - - Insect larvae 9 14 14 8 6 - 1 - Crawling 15 24 8 4 0 - - - Flying 5 6 2 1 0 - - - Unidentifiable 8 9 9 7 2 - 10 9 *Only leg of the Tettigoniidae was successfully consumed, remainder of insect escaped. **E is the number of salamanders exposed to eaeh potential prey item. N is the total number of potential prey items available when a salamander was present at an entrance. N^, and are the number of prey items salamanders oriented toward, attempted to eat, and successfully eaptured. Nj is the number of prey items captured by salamanders at a burrow entrance as observed by Jordan ( 1975). N^, and are the number of prey items found in the guts and fecal samples by Gunzburger ( 1999) and Brandon ( 1965) respectively. Twenty five salamanders oriented toward 75 potential prey. On an additional 97 occasions, salamanders oriented toward objects outside the eamera’s field of view. Salamanders oriented toward all types of potential prey and attempted to capture all prey types except for Opilionids and Hymenoptera (Table 1 ). The orientations observed for inseet larvae and the unidentifiable category may be artificially high because many of these prey were noted only because salamanders oriented toward them. Earthworms (Oligochaeta) were visible only one night when there was heavy rain and also may be overrepresented. Salamanders do not orient equally towards Opilionids and Orthopterans. Seven salamanders were exposed to both Opilionids ( 17 per salamander, 2 1 total Opilionids) and Orthopterans (2-5 per salamander, 25 total Orthopterans). These seven salamanders oriented toward zero Opilionids and 13 Orthopterans. Table 1 show that selectivity is largely restricted to the avoidance of Opilionids and preference for insect larvae, and orientation towards other prey in rough proportion to their occurrences at burrow entrances. 5 ! I I Bakkegard, K— Red Hills Salamanders and Its Invertebrate Prey Figure 1. Activity pattern oi' Phaeognath us hubrichti (from Bakkegard, 2002) and prey items (excluding harvestmen) by hour of day. Salamander activity represents the number of hours salamanders were present at entrances divided by the number of hours the camera was operational during that period. Prey activity is the number of prey items (excluding harvestmen) divided by ii the number of hours the camera was operational during that period. Thirty feeding attempts resulted in 10 successful prey captures (33%) by seven salamanders. There were two additional attempts (a crawling item and an unidentifiable item) in which 1 was unable to detemiine if the salamander successfully captured it. No salamander left the field of view of the camera during videotaping so no prey items were captured off camera. Salamanders were successful in capturing and consuming oligochaetes, insect larvae and unidentifiable items (Table 1 ). Salamanders fed at a rate of 0.79 prey items/day. ' Prey responses to salamanders: ‘ Of 14 camel crickets whose antennae touched a salamander, 13 hopped away I (immediately to 9 s, X= 1.7 s, SD = 2.21). One cricket continued to walk normally after I touching the salamander with one antenna. Of the 13 occasions where the salamander I oriented but the cricket did not touch the salamander, three of those hopped away or left I the camera’s field of view in apparent response to the salamander. Of the remaining 10, »' the cricket moved normally through the area ( 1 s to 7.42 min, X= 2.45 min, SD = 3.36 I min) and did not appear to notice the salamander (7 of 10) or only antennae (3 of 10) were visible on the videotape. Of the three predation attempts salamanders made on crickets, the cricket escaped by hopping away. None flew to escape because Ceuthophiliis are wingless i (Scudder, 1894). 6 Journal of Alabama Academy of Science Vol. 78, No. 1, January 2007 Ten harvestmen walked next to a burrow with a salamander present at an entrance, four walked over a burrow with a salamander present and may have touched the salamander, and two clearly touched a salamander with their walking legs. Of these 16 close encounters between a salamander and a harvestman, only one salamander oriented toward a harvestman. In all instances, harvestmen did not appear to move more quickly, change posture or respond in any fashion to the presence of salamanders. No salamander attempted to capture a harvestman. DISCUSSION Salamander response to prey: Red Hills salamanders were active when prey activity was high, although activity of each may be independent of the other as the same factors that favor salamander activity may also favor prey activity. With the exception of harvestmen, salamanders oriented toward invertebrates moving near their burrow entrances in the same proportion that prey items were available. Salamanders oriented towards beetles, camel crickets and earthwomis, prey that move actively through the environment. Salamanders in general ignore stationary prey objects, although the complex relationship between prey size, movement pattern and olfactory cues determines if a salamander will attack a prey item (Roth, 1987). Salamanders also oriented toward insects that flew near their burrows. These observations suggest that Red Hills Salamanders have good visual acuity or is at least responsive to small moving objects, even in darkness, a result similar to that reported in other salamander species (Roth, 1987). At burrow entrances. Red Hills Salamanders appear to be exclusively sit-and wait predators as they did not leave their burrows to search the forest floor for prey. The usual position of a Red Hills Salamander at its burrow entrance was with the head and front legs outside the entrance and the body and tail inside the burrow (Bakkegard, 2002). To capture prey, a salamander slowly advanced and, if required, anchored its hind legs in the burrow entrance, then attacked. Salamanders also would snap at prey without an advance, especially if the prey was moving rapidly. Only once did a salamander leave its burrow to pursue a prey item, an insect larvae crawling across the surface near its burrow. When the salamander failed to capture the larvae, it quickly returned to its burrow, entering head first but turning around to face outward again in approx 3 sec. Red Hills Salamanders used tongue extensions and jaw snaps singly or in concert to capture prey. This method of prey capture conforms with the morphological observations of Lombard and Wake ( 1977). When salamanders were successful, they retracted into the burrow immediately after grasping the prey, reappearing at the burrow entrance after consuming the prey as Jordan ( 1975) also observed. The success rate of Red Hills Salamanders (33%) was comparable to that of Salanuindra salamandra, which captured 39% of the crickets presented to it in a laboratory setting (Luthardt-Laimer, 1983), but less than the success rates of other plethodontids, including Plethodon, Eitrycea, and Balmchoseps (> 50%; Roth, 1987). At the burrow entrance. Red Hills Salamanders captured slow and soft-bodied 7 Bakkegard, K— Red Hills Salamanders and Its Invertebrate Prey j prey. These salamanders are capable of catching fast and hard bodied prey (Brandon, 1965; Jordan, 1975; Gunzburger, 1999) and in captivity, consume domestic crickets /Ic/terc/ domesticus (Bakkegard, pers obs.). However, the majority of the prey items (ants, snails, millipedes, insect larvae and earthworms) listed in dietary studies are relatively slow. In contrast, other sit-and~wait predators, such as lizards and tropical litter frogs, capture a low number of large mobile prey (Huey and Pianka, 1981; Toft, 1981). 1 would classify spiders (except for the trapdoor spiders present at the site), harvestmen, camel crickets, moths and beetles as mobile prey that move actively through the environment. However, Red Hills Salamanders were ineffective at capturing these prey items at the surface. Thus I the diet of Red Hills Salamanders is not consistent with predictions based on foraging theory. This inability to capture faster prey may be due to their limited tongue projection I capability (Lombard and Wake, 1977), their lack of pursuit of prey items further away from i the burrow entrance than the body length of the salamander, or because the prey itself is difficult to capture, as appears to be the case with camel crickets. My observations, coupled with the dietary studies (Brandon, 1965; Jordan, 1975; Gunzburger, 1999), suggest that when salamanders capture mobile prey, it may be inside the burrow. Red Hills salamanders displayed selective foraging in that the frequency of orientation toward harvestmen was conspicuously less than the frequency with which they were available in the environment. Salamanders do not appear to recognize (detection and/ i or identification phase of a predation event) harvestmen as prey items. This was surprising because when a harvestman walks, its body bobs up and down providing a strong visual stimulus. Harvestmen secrete a variety of volatile defensive compounds (disrupting subjugation) but do so only when disturbed (Edgar, 197 1 ; Eisner et al., 1978; Blum, 1981). Salamanders will reject aversive tasting stimuli (Bowerman and Kinnamon 1994; Takeuchi et al. 1994). Although studies of learning in amphibians are scarce (Suboski, 1992; Muzio, 1999), Bufo terrestris avoided eating bee mimics after earlier being stung when feeding on true bees (Brower et al., 1960; Brower and Brower, 1962). Thus, Red Hills salamanders may learn that harvestmen are unpalatable. Because they live approximately 1 1 yr (Parham et al., 1996), study of the long-term retention of an avoidance behavior in salamanders may I prove interesting. Prey response to salamanders: When moving normally through the environment, camel crickets constantly I touched the area ahead of them with their long antennae. They appeared to recognize 1 that Red Hills Salamanders were a potential threat as evidenced by immediately hopping i away upon contacting a salamander with their antennae, disrupting the approach phase of ; a predation event. Orthopteran antennae are sensory and tactile appendages containing a I variety of sensilla that function as mechano, chemo, and olfactory receptors (Zacharuk, ] 1985; Bland, 1989). When the antenna of the cockroach Peripkmeta americana was 1 touched by a predator (spider, toad, mantis, or mouse), the cockroach turned away and • displayed escape behavior, even in the absence of simultaneous wind or visual predatory I cues (Comer et al., 1994). They also observed that in some trials, the roach would touch 8 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 the predator with its antennae first and then run. There was no obvious movement by the predator and they speculated that tactile, proprioceptive and chemical cues were probably being processed. Similarly, camel crickets (with a sensory system similar to cockroaches) reacted to Red Hills Salamanders with no discernable movement by a salamander. The stimulus was the cricket’s antennae contacting a salamander’s head or body. Perhaps these camel crickets have evolved an innate reaction to contact with Red Hills Salamanders or to amphibians in general. Alternatively, the camel crickets at this site may have escaped previous predation attempts and associate a salamander cue with an imminent attack. In contrast, harvestmen did not noticeably change their behavior when in close vicinity to a salamander. Harvestmen defensive mechanisms include playing dead, losing a leg, secreting a foul smelling/tasting substance from a pair of glands (an option of last resort), or running away (Edgar, 1971; Eisner et ak, 1978). None of these behaviors were observed. This suggests that they did not perceive Red Hills Salamanders as a threat or that the harvestmen at this site display defensive behaviors only when attacked. Maiorana (1978) evaluated several indirect methods used to determine diet selectivity in salamanders because “One cannot watch salamanders select food directly in the field’’. However, this observational study, conducted in the field, exposes the complexity of predator-prey interactions. Camel crickets are difficult prey items for Red Hills Salamanders to capture at the surface, but this may change when a cricket enters a burrow (1 observed one crawling into a salamander burrow during daylight). The camel cricket’s escape method, hopping away, is probably ineffective in a confined space. Interactions between Red Hills Salamanders and harvestmen could be described as a mutual ignoring of each other. This suggests either learning by individual salamanders and/or the inability of harvestmen to recognize salamanders as a potential predator or the salamander to recognize harvestmen as a potential prey. Although valuable, dietary studies of gut contents, even when coupled with analyses of available prey and other variables (often morphological), cannot capture the nuances of predator-prey interactions. ACKNOWLEDGEMENTS I would like to thank C. Guyer for his invaluable guidance and support in all aspects of this study. E. D. Brodie, Jr., the USU herpetology group and several anonymous reviewers contributed useful comments on the manuscript. G. Mullen assisted in the identification of the Opilionids. S. Durham provided statistical assistance. The U.S. Army Corps of Engineers, Mobile District provided a campsite at Isaac Creek Campground. Funding was provided by the Nature Conservancy. This study was conducted under a permit provided by K. 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Aprendizaje instrumental en anfibios. Revista Latinoamericana de Psicologia. 31: 35-47. Parham, J. F., C. K. Dodd, Jr., and G. R. Zug. 1996. Skeletochronological age estimate for the Red Hills Salamander, Phaeoguathus Inihrichti. Journal of Herpetology'. 30: 401-404. Petranka, J. W. 1 998. Salamanders of the United States and Canada. Smithsonian Institution Press, Washington, D.C. USA. Roth, G. 1987. Visual behavior in salamanders. Springer- Verlag, Berlin, Germany. Schwaner, T. D. and R. H. Mount. 1970. Notes on the distribution, habits and ecology of the salamander Inihrichti Highton. Copeia. 1970: 571-573. ScLidder, S. H. 1894. The North American ceuthophili. American Academy of Arts and Sciences. 30: 17-113. Suboski, M. D. 1992. Releaser-induced recognition learning by amphibians and reptiles. Animal Learning and Behavior. 20: 63-82. Takeuchi, H., T. Masuda, and T. Nagai. 1994. Electrophysiological and behavioral studies of taste discrimination in the axolotl (Ambystoma me.xicaniim). Physiology and Behaviour. 56: 121-127. Toft, C. A. 1981. Feeding ecology of Panamanian litter anurans: Patterns in diet and foraging moAt. Journal of Herpetology'. 15: 139-144. Valentine, B. D. 1963. The plethodontid salamander Phaeognathus: collecting techniques and habits. Journal of the Ohio Herpetological Society. 4: 49-54. Zacharuk, R.Y. 1985. Antennae and sensilla. In G. Kerkut and L.l. Gilbert [eds.]. Comprehensive insect physiology, biochemistry and pharmacology. Vol. 6. Nervous system: Sensory, 1-69. Pergamon Press, New York, New York, USA. 11 Bakkegard, K— Red Hills Salamanders and Its Invertebrate Prey Zar, J. H. 1999. Biostatistieal analysis. 4‘'’ edn. Prentiee-Hall, Englewood Cliffs, New Jersey, USA. 12 Journal of Alabama Academy of Science Vol. 78, No. 1. January 2007 EFFECT OF VARIOUS PHOTOSENSITIVE DYES ON THE GROWTH OFTETRAHYMENA IN VITRO Misty A. Chapman, Jonathan C. Beavers, Mark E. Meade, Benjie G. Blair, and Charles P. Olander Department of Biology, Jacksonville State University, 700 North Pelham Road, Jaeksonville, AL 36265. Correspondenee: Chapman, Misty A. (jsu6516k@jsu.edu) ABSTRACT Photodynamic action associated with light aetivation of photosensitive dyes has been used to control various human health disorders and agricultural pests. These dyes are eonsidered effective alternatives compared to eurrent treatments with known negative impacts on the environment. In the present study the effieacy of the following dyes for potential pest management was examined: methylene blue, eosin yellow, acridine orange, rose bengal, and phloxine B. Cultures of Tetrahynieiia pyriformis, a eommonly used protozoan model for eeotoxicological evaluation, were exposed to the photodynamic dyes at various eoncentrations, at 25°C, in light (66 pE ■ m - • s '), and in the dark (0 pE • m - • s"') for 24 h. In the dark, cell growth was inhibited by all the dyes. Only a 5% to 10% variation in growth inhibition was observed at dye eoneentrations of 100, 1000, and 10000 ppb. In the presence of light, all the photodynamie dyes tested exhibited a linear log dose response eurve of photodynamic action. The deleterious effeets of the dyes were deteeted at concentrations as low as 100 ppb. INTRODUCTION "'PhotodyLmischem (‘photodynamic action’) was coined in 1904 by von Tappeiner and Jodlbauer as the deteriorating effects of ehemieals interactingwith visible light in various biological systems (Blum, 1941 ). A variety of compounds, including synthetic dyes, drugs, antibioties, and plant secondary compounds, have been shown to exhibit this photodynamie effeet (Santamaria and Prino, 1972). Lipid peroxidation, membrane lysis, DNA base modification and strand breakage, mutagenesis, protein inactivation, and inhibition of metabolic pathways are the types of eellular photodamage that oeeur (Wallis and Melnick, 1965; Foote, 1976). These wide ranges of targets damaged by photodynamie aetion make it less likely that any organism will be able to mutate cellular eomponents and develop resistance (Jori et ak, 2006). A renewed interest in photodynamic action, accompanied by the development of new photosensitive dyes and recent advaneements in light delivery, has advaneed this technique for the inactivation and destruction of various 13 Chapman et al.— Effect of Phcto^^ei sitjve Dyes on Tetrahymena biological systems (Stapleton and Rhodes, 2003). Currently, photodynamic therapy (PDT) is one of the newest treatments of various microbial, viral, and inflammatory disorders (Badylak et al., 1983; Ali and Olivio, 20^3; PDT proved to be an effective alternative cancer treatment and is also used in experimental studies of dermatology, ophthalmology, and gastroenterology (Henderson, 1992; Meisel and Kocher, 2005). In an aim to control agricultural pests, such as insects, protozoan, bacteria, and fungi, ongoing research of alternative methods and treatments with a variety of chemical compounds has been explored (Heitz, 1997). These alternatives are replacements for current chemical structures and strategies that have been rendered ineffective by resistance and negative environmental impacts (Heitz, 1997). Effects of photosensitive dyes on insects have been studied since the early seventies. These earlier investigations have demonstrated the usefulness of phototoxic dyes as an alternative to other chemical pesticides. Research demonstrated the photodynamic effects of the following dyes on the order Diptera: rhodamine, rose bengal, erythrosin B, eosin blue, phenosafranin, methylene blue chloride, and uranine (Yoho et al., 1971 ). Dye mixtures have been formulated in baits that are attractive to the target species (fruit fly); the dye is activated to its phototoxic state only after ingestion and exposure to light through the transparent gut of the insect (Chase, 1996). This study was aimed at evaluating the photodynamic effects of selected photosensitive dyes on the protozoan T. pynformis. Tetrahymena pyriformis serve as an excellent ciliated protozoa model for the toxicological evaluations of carcinogens, insecticides, dyes, and pharmaceutical drugs due to the ease of culturing, which allows in vitro screening of multiple chemicals without expensive animal facilities (Sauvant et al., 1999). The photodynamic dyes examined are acridine (acridine orange), phenothiazinium (methylene blue), and the xanthenes (phloxine B, rose bengal, and eosin yellow). MATERIALS AND METHODS Tetrahymena pyriformis was obtained from Carolina Biological Supply Company and were maintained in standard media comprised of 5.0 g proteose peptone, 5.0 g Tryptone, and 0.2 g potassium phosphate in 1 L of spring water and adjusted to pH 7.2. All media were autoclaved at 15 psi, 121°C for 15 min. For test purposes, stock cultures were maintained in an environmental growth chamber (Conviron Inc. CMP4030) at 25°C, 50 % humidity in the dark. Cells were cultured in 100 mL of standard medium in 250 niL Erlenmeyer flasks until cell concentrations were between 25,000-35,000 cells/mL. The 24-h test protocol included two independent tests (light and dark) carried out in triplicate at each dye concentration. The effect of the dyes on population density during 24 h of growth was examined. Culture tubes (23 X 150 mm) containing 8 mL of fresh culture media and 8 mL of T pyriformis cell suspension were exposed to concentrations of 100, 1000, and 10000 ppb of the following compounds: cosin yellow, methylene blue, acridine orange, rose bengal, and phloxine B (all obtained from Sigma Chemical Supply Company). At time zero, the dyes at 100, 1000, and 10000 ppb were added to the medium 14 Journal of Alabama Academy of Science Vol. 78, No. 1, January 2007 and the tubes were swirled to evenly disperse the toxieant. All tubes were placed in the dark for 1 h in the incubator to allow absorption of the dye. Half the tubes were left in the dark (0 pE • m‘“ ■ s'), and half were removed and incubated in the light (66 pE • nr- • s') tor the remaining 23 h. Illumination of cells was carried out by using cool white fluorescent lights with a maximum spectral output around 540 nm. Light intensity (66 pE • nr- - s ') was used, as measured with a light meter (Ll-COR Inc. Ll-250). Culture tubes were inclined at a 75° angle to increase surface area. Cell density was evaluated turbidimetrically (LaMotte model 2020). Dark and light control mean cell densities ± 1 SD of T. pyrifonnis cultures were eompared using Student's t-test after 24 h in light (66 pE • nr- • s ') or in the dark (0 pE • nr- • s ' ). The least-square method was used to ealculate a regression line for eaeh dye. The light and dark data were analyzed using SYSTAT® 1 1 and an ANOVA and Tukey’s HSD were used for eomparisons. RESULTS In the dark, the effect of all the dyes was a significant (p < 0.001 ) reduction on cell density compared to the dark control. The inhibitory effects of the dyes in the dark were similar and were not dose dependent (Fig. 1 ). 40000 35000 30000 25000 _l E ■35 20000 ■5 o 15000 10000 5000 0. ppb of Dyes B Methylene Blue S Acridine Orange 0 Eosin Yellow S Rose Bengal B Phloxine B Figure 1. Effects of methylene blue, acridine orange, eosin yellow, rose bengal, and phloxine B on the mean cell number of Tetrahymena after 24 hours in the dark (0 pEm ^s '). Error bars denote ± 1 standard deviation. Methylene blue, acridine orange, and phloxine B appeared to have a dose dependent action in the dark; however, regression analyses of the dyes revealed that there w ere no significant dose dependent responses. The reduced growth associated with dye concentrations of 100, 15 Chapman et al.— Effect of Photosensitive Dyes on Tetrahymena 1000, and 10000 ppb differed only by 5% to 10%. The effect of light alone on T. pyrifonnis is illustrated in Figs.l and 2. Control cells grown in the light are significantly (p< 0.001) inhibited when compared to control cells incubated in the dark. In the presence of light, all photodynamic dyes tested exhibited a linear log dose response curve of photodynamic action (Fig. 2). Methylene blue was the least effective dye at reducing cell density. At 100 and 1000 ppb, methylene blue treated cell cultures grew to 73% and 54% of light control cell growth respectively in the 24 h period. Acridine orange at 1000 and 10000 ppb inhibited T. pyrifonnis cell growth by 81% and 99% respectively compared to light control. The xanthene dyes (eosin yellow, rose bengal, and phloxine B) reduced cell density the most. Eosin yellow at 100, 1000, and 10000 ppb decreased cell growth by 41%, 62%, and 98% respectively compared to light control. Rose bengal completely inhibited cell growth at 10000 ppb. 40000 35000 30000 o O H Methylene Blue [H Acridine Orange E2 Eosin Yellow HI Rose Bengal ■ Phloxine B ppb of Dyes Figure 2. Effects of methylene blue, acridine orange, eosin yellow, rose bengal, and phloxine B on mean cell number of Tetrahymena after the 24 hour light exposure (66 pEm ^s ')• Error bars denote ± 1 standard deviation. At 100 and 1000 ppb, rose bengal inhibited cell growth by 52% and 95% respectively compared to light control. Phloxine B at the three concentrations inhibited T. pyrifonnis cell growth by 47%, 77%, and 99% respectively compared to light control. 16 Journal of Alabama Academy of Science Vol. 78, No. I , January 2007 DISCUSSION The relative effeetiveness and environmental friendliness of photosensitive dyes have promoted investigations of their use in various fields of science (Henderson, 1992; Heitz, 1997; McBride, 2002; Jori et ah, 2006). The photodynamic action of these dyes in the management of human disorders and pests is dependent on the method of dye and light delivery (Pooler and Valenzeno, 1982; Stapelton and Rhodes, 2003; Meisel and Koeher, 2005). Photosensitive dyes are toxie to organisms that do not have strong pigmentation or greater body mass; therefore, it is unlikely that non-target organisms with the above mentioned anatomical traits would be harmed (Heitz, 1997; Thomas and Meats, 1999; MeNeill and Goldson, 2001). High toleranee to the photosensitive dye phloxine B was reported in the 2"^' instar larvae stages of two leafroller species, Epiphyas postvittania (Walker) and Planotortrix excessana (Walker), that exhibited greater body mass and darker pigmentations relative to the P' instar larvae stages of both species (MeNeill and Goldson, 2001). The potential risk effects of photodynamic dyes, partieularly the xanthenes, on reported target and non-target organisms are dependent upon faetors including: illumination, dye coneentration and availability, and the organism’s physical and structural properties (Heitz, 1997; Martin et ak, 1998; Mischke et al., 1998; Walthall and Stark, 1998). These dyes use light energy to facilitate a variety of reactions between oxygen and suseeptible molecules, which may lead to cellular inaetivation of these smaller bodied organisms including the test organism used in this study, T. pyriformis. In the dark, the effeet of the dyes was a signifieant (p< 0.001 ) reduetion on eell growth. The mean cell densities of the treated cells were reduced by 40-50% compared to dark eontrol. In the dark, the deleterious effect of all dyes at 100, 1000, and 10000 ppb differed only by 5% to 10% and have significant overlap (Fig 1). This non-specific deleterious effeet, which is not dose dependent, is not due to photodynamie action. More likely, since cultures remain in the dark, the addition of the dyes interferes with some nutrient or other essential eomponent of the culture media, thus slowing cell growth. Other studies also report similar inhibitions by the dye alone; however, in most eases the effeet was considered non-specific or not significant compared to the increased action exhibited in the light (LuksienD et ak, 2005; Dutta et ak, 2005). The effect of light alone on T. pyriformis is illustrated in Figs. 1 and 2. Control cells grown in the light are signifieantly (p< 0.001 ) inhibited when eompared to control cells incubated in the dark. Tetrahymena pyriformis is negatively phototaxie, and growth rate is naturally inhibited by light. Although light alone ean reduce the growth of T. pyriformis, the combination of dye and light further redueed growth, likely due to a photodynamie effect of the dye. In the presence of light, all photosensitive dyes tested exhibited a linear log dose response curve of photodynamie aetion (Fig. 2). Methylene blue is a producer of superoxide radieals in the presence of light (Trindale et ak, 2000). Furthermore, methylene blue is well known for its strong photodynamic activity on nucleic acids and their components in vitro. The dye causes growth inhibition of T. pyriformis in the light and dark. However, in the light at 10000 ppb, the dye was not as effective as the other dyes tested (Fig. 2). 17 Chapman et al.— Effect of Photosensitive Dyes on Tetrahyniena In light, acridine orange is very effective in suppressing the growth of the cells at all three concentrations. However, the use of acridine orange may be impractical since this dye is possibly mutagenic and/ or carcinogenic to humans. The fact that acridine binds more specifically to DNA and has photodynamic properties may explain its suppression of T. pyriformis cell growth. There are several classes of dyes that exhibit photodynamic action, but the most effective are the halogenated xanthenes (Heitz, 1997). The current investigation examined the photodynamic effect of the xanthene dyes (eosin yellow, rose bengal, and phloxine B) and found that these dyes were more effective in comparison to the other dyes tested. Eosin yellow was the least effective of the xanthene dyes, yet at 1 0000 ppb it inhibited cell growth by 98% compared to light control. Rose bengal exhibited a strong photodynamic action in light, even at 100 ppb. At 10000 ppb it completely inhibited T. pyriformis growth. Rose bengal is among the most widely used of all photodynamic sensitizers for single oxygen production (Paczkowska et al., 1985). The highly reactive singlet oxygen leads to loss of membrane integrity through lipid peroxidation and inactivation of essential enzymes (Castano et al, 2004). Tetrahymena pyriformis cell density was most likely inhibited by the oxidation of significant biomolecules (Walthall and Stark, 1999). Phloxine B also exhibited an effective photodynamic action in the growth suppression of T. pyriformis at the three concentrations tested in this study. At 100, 1000, and 10000 ppb cell growth was inhibited by 47%, 77%, and 99% respectively compared to light control cell growth. The United States Food and Drug Administration (USDA) has approved phloxine B (D&C Red 27 and 28) for human consumption at concentrations of 1 .25 mg • kg ' • day'. Phloxine B is a water-soluble xanthene dye, and has a chemical half-life of 0.5 h in water exposed to sunlight (Bergsten, 1 997). The safety of phloxine B to humans and other vertebrates makes it especially useful where non-target organisms may also be exposed to the dye. In the search for an effective and environmentally safe non¬ toxic biological control agent, the photodynamic effect and biodegradability of phloxine B are essential and practical considerations for an effective program in protozoan control. ACKNOWLEDGEMENTS The authors are grateful to Dr. Tim Yoho for his valuable assistance and comments during the preparation of the manuscript. Thanks are given to Dr. George Cline and Dr. Robert Carter assistance in statistical analyses. Thanks are given to the reviewers for their helpful comments. LITERATURE CITED Ali, S. M. and Olivo, M. 2003. Mechanisms of action of phenathroperylenequinones in photodynamic therapy (Review). International Journal of Oncology. 22: 1181-1191. 18 Journal of Alabama Academy of Science Vol. 78, No. 1, January 2007 Badylak, J. A., Scherba, G., and Gustafson, D. P. 1983. Photodynamic inactivation ot pseudorabies virus with methylene blue dye, light, and electricity. Journal of Clinical Microbiology. 17 (2): 374-376. Bergsten, D. A. 1997. Phloxine B- a photoactive insecticide. Pesticide Outlook. 8; 20-23. Blum, H. F. 1941. Photodynamic action and diseases caused by light. Reinhold Publishing Corp., New York, New York, USA (reprinted with an updated appendix, Haffner Publishing Co., New York, New York, USA, 1964). Castano, A. P., Demidova, T. N., and Hamblin, M. R. 2004. Mechanisms in photodynamictherapy: part one-photosensitizers, photochemistry, and cellular localization. Photodiagnosis and Photodynamic Therapy. 1: 279-293. Chase, V. 1996. Innovations: Waiter! There’s a dye in my soup. Environmental Health Perspectives. 104 (2): 156-158. Dutta, S., Ray, D., Kolli, B., and Chang, K.-P. 2005. Photodynamic sensitization of Leishmania amazonensis in both extracellular and intracellular stages with aluminum phthalocyanine chloride for photolysis in vitro. Antimicrobial Agents and Chemotherapy. 49 ( 1 1 ): 4474-4484. Foote, C. S. 1976. In W. Pryor [ed.]. Free radicals in biology, 2: 86-102. Academic Press, New York, New York, USA. Heitz, J. R. 1997. Pesticidal applications of halogenated xanthene dyes. Phytoparasitica. 25 (2): 93-97. Henderson, B. W. 1992. [ed.]. Photodynamic therapy: basic principles and clinical applications. Marcel Dekker Inc., New York, New York, USA. Jori, G., Fabris, C., Soncin, M., Ferro, S., Cappelloti, O., Dei, D., Fantetti, L., Chiti, G., and Roncucci, G. 2006. Photodynamic therapy in the treatment of microbial infections: basic principles and perspectives applications. Lasers in Surgery’ and Medicine. 38: 468-48 1 . Luksiene, Z., Peciulyte, D., Jurkoniene, S., and Puras, R. 2005. Inactivation of possible fungal food contaminants by photosensitization. Food Technology' and Biotechnology’. 43 (4): 335-341. Martin, P. A. W., Mischke, S., and Schroder, R. F. W. 1998. Compatibility of photoactive dyes with insect biocontrol agents. Biocontrol Science and Teehnology. 8: 501-508. McBride, G. 2002. Studies expand potential uses of photodynamic therapy. Journal of the National Cancer Institute. 94: 1740-1742. McNeill, M. R. and Goldson, S. L. 2001. Responses of two leafroller species to the photoactive dye phloxine B. New Zealand Plant Protection. 54: 27-32. Meisel, P. and Kocher, G. 2005. Photodynamic therapy for periodontal diseases: state of the art. Journal of Photochemistiy and Photobiologx^ B: Biology. 79:159-170. 19 Chapman et al.— Effect of Photosensitive Dyes on Tetrahymena Mischke, S., Martin, P. A. W., and Schroder, R. F. W. 1998. Compatibility of phloxine B, and insecticidal photoactive dye, with selected biocontrol fungi. Biocon ti'ol Science and Technology. 8: 509-5 1 5. Paczkowska, B., Paczkowski, J., and Neckers, D. 1985. Properties of rose bengal; (X) new derivatives of polymer-rose bengal. Photochemistry and Photohiology. 42 (5): 603-604. Pooler, J. P. and Valenzeno, D. P. 1982. A method to quantify the potency of photosensitizers that modify cell membranes. Journal of the National Cancer Institute. 69:211-215. Santamaria, L. and Prino, G. 1972. List of the photodynamic substances. Research progress in organic, biological and medicinal chemistry, vol. 3 (Pt 1 ): Xl-XXXV. Sauvant, M. P., Pepin, D., and Piccinni, E. 1999. Tetrahymena pyriformis'. a tool for toxicological studies. Chemosphere. 3^ {1): 1631-1669. Stapleton, M. and Rhodes, L. E. 2003. Photosensitizer for photodynamic therapy of cutaneous d\sease. Journal of Dermatological Treatment. 19: 107- 112. Thomas, B. J. and Meats, A. 1999. The effect of simulated “wash off’ from spot-sprays containing either malathion or phloxine B on ground-dwelling arthropods in an orchard. Agricultural and Forest Entomology^ 1 : 55-60. Trindale, G. S., Farias, S. L. A., Rumjanej, V. M., and Capella, M. A. M. 2000. Methylene blue reverts multidrug resistance: sensitivity of multidrug resistant cells to this dye and its photodynamic action. Caneer Letters. 151: 161-167. Wallis, C. and Melnick, H. L. 1965. Photodynamic inactivation of animal viruses: a review. Photochemistiy and Photohiology. 4: 159-170. Walthall, W. K. and Stark, J. D. 1999. The acute and chronic toxicity of xanthene dyes, fluorescein sodium salt and phloxine B, to Daphnia pule.x. Environmental Pollution. 104: 207-215. Yoho, T., Butler, L., and Weaver, J. 1971. Photodynamic effect of light on dyc-fed house flics: preliminary observations of mortality. Journal of Economic Entomology. 64: 972-973. 20 Journal o'" Alabama Academy of Science Vol. 78, No. I. January 2007 PTERIDOPHYTES OF SOUTHEAST ALABAMA Alvin R. Diamond, Jr. and Michael Woods Department of Biological and Environmental Sciences Troy University Troy, Alabama 36082 Correspondence: Diamond, Alvin ( adiamond@troy.edu ) ABSTRACT Pteridophytes of southeast Alabama are represented by seventeen families, twenty- nine genera, fifty-nine specific and three hybrid taxa. Dryopteridaceae is represented by seven genera and ten taxa, Thelypteridaceae by three genera and seven species, Pteridaceae by three genera and six species, Ophioglossaceae by two genera and eight species, Lyeopodiaeeae by two genera and eight taxa, and Isoetaceae by one genus and seven species. Aspleniaceae is represented by one genus and three species. The families Blechnaeeae, Osmundaceae, and Selaginellaceae are represented by one genus and two species each. The families Azollaceae, Dennstaedtiaceae, Equisetaceae, Eygodiaceae, Marsileaceae, Polypodiaceae, and Salviniaceae are represented by a single species each. The area delineated as southeast Alabama includes Barbour, Butler, Coffee, Conecuh, Covington, Crenshaw, Dale, Escambia, Geneva, Henry, Houston, and Pike counties. Dichotomous keys and descriptions are based upon material deposited in the herbarium of Troy University (TROY). Distribution reeords are based upon specimens deposited in the Troy University Herbarium (TROY), Auburn University Herbarium (AUA), and The University of Alabama Herbarium (UNA). INTRODUCTION Pteridophytes are a group of vascular plants reproducing primarily through the production of spores. Four divisions (Psilotophyta, Lycopodiophyta, Equisetophyta, and Polypodiophyta) and twenty-five families of pteridophytes are known to occur in the United States (Flora of North America, 1993a; Flora of North America, 1993b). All four of these divisions contain native taxa in Alabama, and three of the divisions (Lycopodiophyta, Equisetophyta, and Polypodiophyta) have been reported from southeast Alabama. Division Lycopodiophyta is represented by three families, thirteen species, and two hybrids in southeast Alabama. Division Equisetophyta is represented by one family and one species. Division Polypodiophyta is represented by thirteen families, forty-one species, and one hybrid in the study area. Since 1960, three studies have addressed the pteridophytes of Alabama. Ferns of Alabama and Fern Allies (Dean, 1964), and the revised edition Ferns of Alabama (Dean, 21 Diamond and Woods— Pteridophytes of Southeast Alabama 1 969) provide exeel lent illustrations and general information on the pteridophytes. However, the taxonomy, in many eases, is outdated and the distribution maps are incomplete. Short ( 1978), in his unpublished M.S. Thesis, Distribution of Alabama pteridophytes, produced the most comprehensive and detailed work on pteridophytes of the state. Although illustrations are not included, the dichotomous keys and county distribution maps are useful. In the 25 or more years since these publications, additional county records have been added, as well as several species newly reported for Alabama. Therefore this publication is needed to adequately document the diversity and distribution of pteridophytes found in southeast Alabama. Spaulding et al. (2000, 2000b, 2001, 2001b, 2001c) recognized the need for a more current pteridophyte flora and published Pteridophytes of Northeast Alabama and Adjacent Highlands. The objectives of this study were the development of dichotomous keys and county distribution maps for the pteridophytes of southeast Alabama. DESCRIPTION OF STUDY AREA The area delineated as southeast Alabama includes Barbour, Butler, Coffee, Conecuh, Covington, Crenshaw, Dale, Escambia, Geneva, Henry, Houston, and Pike counties (Fig. 1 ). Figure 1. Map of Alabama w ith study areas highlighted. 22 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 The entire study area lies within the Coastal Plain Province and has an area of 2,664,849 ha. The northeast corner of Butler County and the northern sections of Crenshaw, Pike and Barbour counties are in the Blue Marl Region. Most of the central section of the study area oecurs in the eastern and western portions of the Southern Red Hills. Houston County and parts of Geneva and Covington counties in the southeast section of the study area are in the Lime-Sink Region. The southwest section of the study area occurs primarily in the Southwestern Pine Hills. One exception is a small region of central and southeastern Conecuh County, which is located in the Lime Hills (Harper, 1943). The topography of the study area ranges from low rolling hills in the north to flat or gentle sloping ridges in the south. Three major watersheds drain the study area. From east to west they include the Chattahoochee, Pea/Choetawhatchee, and the Coneeuh (Mettee et al., 1996). The warm-temperate, moist elimate of the study area has an average growing season ranging from 240 to 250 days. The Gulf of Mexico has a regulating effect on the elimate and helps keep the temperature extremes at a minimum. The average annual temperature is approximately 20°C. Average temperatures during January, the coldest month, are 10.5°C, while July, the warmest month, averages 26°C. Precipitation ranges from 132 em to 142 cm throughout most of the study area. The exception occurs in the southwestern section of the study area (Conecuh and Escambia counties) where the average ranges from 142 cm to 162 cm (Cartographic Research Laboratory, 2004). MATERIALS AND METHODS This treatment includes all taxa of pteridophytes known to oceur naturally and those that have become established and are reproducing in southeast Alabama. The diehotomous keys and descriptions are based upon material deposited in the herbarium of Troy University (TROY). Distribution records are based upon speeimens deposited in the Troy University Herbarium (TROY), John D. Freeman Herbarium (AUA), and The University of Alabama Herbarium (UNA). Additional distribution data were obtained from Short ( 1 978). With the exeeption of Isoetaeeae and Lycopodiaceae, the nomenelature follows Flora of North America (Flora of North Ameriea Editorial Committee, 1993a). RESULTS Pteridophytes of southeast Alabama are represented by seventeen families, twenty- nine genera, fifty-nine specific and three hybrid taxa. Dryopteridaeeae is represented by seven genera and ten taxa, Thelypteridaeeae by three genera and seven speeies, Pteridaeeae by three genera and six species, Ophioglossaceae by two genera and eight species, Eycopodiaceae by two genera and eight taxa, and Isoetaeeae by one genus and seven species. Aspleniaceae is represented by one genus and three species. The families Bleehnaceae, Osmundaceae, and Selaginellaceae are represented by one genus and two speeies each. The families Azollaceae, Dennstaedtiaeeae, Equisetaceae, Eygodiaceae, 23 Diamond and Woods— Pteridophytes of Southeast Alabama Marsileaceae, Polypodiaceae, and Salviniaceae are represented by a single species each. Eight species are non-native. KEY TO PTERIDOPHYTE FAMILIES I. I. 3. 3. 5. 5. 7. 7. 9. 9. II. II. 13. 13. 15. Stem hollow, jointed . Equisetaceae Stem solid, not jointed . 2 2. Eeaves grass-like, root stock corm-like; plants of aquatic, semiaquatic, or vernally wet habitats . Isoteaceae 2. Eeaves expanded blades or reduced scale-like structures; stems a rhizome or stolon; plants variously aquatic, terrestrial, or epiphytic . 3 Plants aquatic, free floating or rooted in mud . 4 Plants terrestrial . 6 4. Photosynthetic blades 4-parted and clover-like, widely spaced on long creeping rhizome at least partly rooted in substrate . Marsileaceae 4. Photosynthetic blades round or oval, not clover-like, closely spaced on short free floating rhizome . 5 Eeaves glabrous adaxially, blades 1.5 mm long . Azollaceae Leaves conspicuous pubescent adaxially, blades >1.0 mm long . Salviniaceae 6. Plants moss-like in appearance; leaves <1.0 cm long . 7 6. Plants not moss-like; leaves >1.0 cm long . 8 Plants slender; sterile leaves dimorphic, ligulate; heterosporous . Selaginellaceae Plants coarse; sterile leaves monomorphic, aligulate; homosporous.... Lycopodiaceae 8. Plants vine-like . Lygodiaceae 8. Plants not vine-like . 9 Sporangia 0.5- 1.0 mm in diameter; roots tuber-like, thick, fleshy .... Ophioglossaceae Sporangia 0.08-0.1 mm in diameter; roots black, wiry . 10 10. Stems short, erect, stout; roots matted, wiry . Osmundaceae 1 0. Stems elongated rhizomes, creeping; roots scattered . 1 1 Sori marginal, under reflexed margins of blade; indusium absent . 12 Sori medial or submarginal but not under reflexed margins of blade; indusium present or absent . 13 12. Rachis winged; pinnules opposite; >2.5 cm long . Dennstaedtiaceae 12. Rachis not winged; pinnules alternate, <2.5 cm long . Pteridaceae Sori without indusia . 14 Sori with indusia . 1 5 14. Fronds >25.0 cm long, many stipitate hairs and/or glands present, scales absent abaxially; sori <0.5 mm in diameter . Thelypteridaceae 14. Fronds <25.0 cm long, glands and stipitate hairs absent, scales present abaxially; sori >1.0 mm in diameter . Polypodiaceae Sori elongate, in I row on each side and immediately adjacent to costae or costules . Blechnaceae 24 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 1 5. Sori elongate to round, many per pinna, if elongate and parallel to costae then not ... immediately adjacent to them . 16 16. Petioles with 1 x-shaped or 2 baek to baek c-shaped vascular bundles; sori on one side of a vein . Aspleniaceae 1 6. Petioles with 2 u-shaped or 2-many eircular vascular bundles arranged in an arch; sori at least partially on two sides of a vein . 17 1 7. Adaxial leaf surface pubescent, trichomes transparent; blade scales absent; petioles with 2 U-shaped vaseular bundles . Thelypteridaceae 1 7. Adaxial leaf surface glabrous; blade scales present or absent; petioles with 2-many eireular vaseular bundles arranged in an arch . Dryopteridaceae CHECKLIST OF PTERIDOPH YTES OF SOUTHEAST ALABAMA ASPLENIACEAE (Spleenwort Family) Aspleniuni platyneiiron (Linnaeus) Britton, Sterns & Poggenburg— Ebony Spleenwort Aspleniiini resiliens Kunze— Blaek-Stem Spleenwort Aspleniuni trichoinanes Linnaeus— Maidenhair Spleenwort AZOLLACEAE (Mosquito Fern Family) Azolla caroliniana Willdenow— Carolina Mosquito Fern BLECHNACEAE (Chain Fern Family) Woodwardia areolata (Linnaeus) T. Moore— Netted Chain Fern Woodwanlia virginica (Finnaeus) Smith— Virginia Chain Fern DENNSTAEDTIACEAE (Bracken Fern Family) Pteridium aquiliniim (Linnaeus) Kuhn— Northern Bracken Fern DRYOPTERIDACEAE (Wood Fern Family) Alhyhutn fHix-femina (Finnaeus) Roth ex Mertens— Subaretic Fady Fern Cyrtoinium falcatwn (Linnaeus f.) C. Presl— Japanese Net- Vein Holly Fern Deparia petersonii (Kunze) M. Kato— Peterson’s-Spleenwort Dn’opteris x australis (Wherry) Small— Hybrid Wood Fern [celsa x ludoviciana] Diyopteris celsa (W. Palmer) Knowlton, W. Palmer & Pollard— Fog Fern Diyopteris ludoviciana (Kunze) Small— Southern Wood Fern Onoclea sensibilis Finnaeus— Sensitive Fern 25 Diamond and Woods— Pteridophytes of Southeast Alabama Polystichiim acrostichoides (Michaux) Schott— Christmas Fern Polystichum hraunii (Spenner) Fee— Braun’s Holly Fern IVoodsia olitiisa (Sprengel) Torrey— Blunt-Lobe Cliff Fern EQUISETACEAE (Horsetail Family) Equisetum hyemale Linnaeus— Tall Scouring-Rush ISOETACEAE (Quillwort Family) Isoetes cippalachiana D. F. Brunton & D. M. Britton— Appalachian Quillwort Isoetes boomii Luebke— Boom’s Quillwort Isoetes fiaccida A. Braun— Southern Quillwort Isoetes hyemalis D. F. Brunton— Evergreen Quillwort Isoetes loiiisianensis Thieret— Louisiana Quillwort Isoetes inelanopodci Gay & Durieu— Black-Foot Quillwort Isoetes valida (Engelman) Clute— True Quillwort LYCOPODIACEAE (Club-Moss Family) Lycopodiella alopeciiroides (Linnaeus) Cranfill— Eox-Tail Club-Moss Lycopodiella appressa (Chapman) Cranfill— Southern Appressed Club-Moss Lycopodiella x briicei Cranfill— Hybrid Club-Moss [appressa x prostrata] Lycopodiella caroliniana (Linnaeus) Pichi Sermolli— Slender Club-Moss Lycopodiella cermia (Linnaeus) Pichi Sermolli— Stag-Horn Club-Moss Lycopodiella x copelandii (Eiger) Cranfill— Hybrid Club-Moss [alopecuroides x appressa] Lycopodiella prostrata (Harper) Cranfill— Feather-Stem Club-Moss Lycopodium digitatum Dillenius ev A. Braun-Fan Ground-Pine LYGODIACEAE (Climbing Fern Family) Lygodium japonicum (Thunberg ex Murray) Swartz— Japanese Climbing Fern MARSILEACEAE (Water-Clover Family) Marsilea miniita Linnaeus— Dwarf Water-Clover OPHIOGLOSSACEAE (Adder’s-Tongiie Family) Bottychiiim biternatiim (Savigny) L. Underwood— Sparse-Lobe Grape Fern Botfychiiim dissectiim Sprengel— Cut-Leaf Grape Fern Botiychium lunarioides (Michaux) Swartz— Winter Grape Fern 26 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 Botrychiiiiii virginiainini (Linnaeus) Swartz— Rattlesnake Fern Op/iioglossiini crotalophoroides Walter— Bulbous Adder’s-Tongue Ophioglossuni enge/nuinnii Prantl— Limestone Adder’s-Tongue Ophioglossiini inidicaiile Linnaeus— Least Adder’s-Tongue Ophioglossuni pefiolatuin Hooker— Long-Stem Adder’s-Tongue OSMUNDACEAE (Royal Fern Family) Osmunda cinnaniomea Linnaeus— Cinnamon Fern Osnnnida regalis Linnaeus— Royal Fern POLYPODIACEAE (Polypody Fern Family) Pleopehis polypodioides (Linnaeus) E. G. Andrews & Windham— Resurreetion Fern PTERIDACEAE (Maidenhair Fern Family) Adiantum capilliis-veneris Linnaeus— Southem Maidenhair Adiaiitiini pedatuni Linnaeus— Northern Maidenhair Cheilantlies lanosa (Miehau.x) D. C. Eaton— Hairy Lip Fern Pferis cretica Linnaeus— Cretan Brake Pferis miiltifida Poiret— Spider Brake Pferis vittata Linnaeus— Ladder Brake SALVINIACEAE (Water Fern Family) Salvinia minima Baker— Water-Spangles SELAGINELLACEAE (Spike-Moss Family) Selaginella apoda (Linnaeus) Spring— Meadow Spike-Moss Selaginella ludovicicma (A. Braun) A. Braun— Gulf Spike-Moss THELYPTERIDACEAE (Maiden Fern Family) Macrothelypteris torresiana (Gaudiehaud Beaupre) Ching— False Maiden Fern Phegopteris hexagonoptera (Miehaux) Fee— Broad Beeeh Fern Thelypteris dentata (Forsskal) E. P. St. John— Downy Maiden Pern Thelypteris hispidula (Deeaisne) C. F. Reed— Rough-Hairy Maiden Fern Thelypteris kimthii (Desvaux) C. V. Morton— Kunth’s Maiden Fern Thelypteris ovata R. P. St. John— Ovate Marsh Fern Thelypteris palustris Sehott— Eastern Marsh Pern 27 Diamond and Woods— Pteridophytes of Southeast Alabama ACKNOWLEDGEMENTS We thank the curators of herbaria at Auburn University (AUA) and The University of Alabama (UNA) for providing useful information during this study and making us welcome during our visits. LITERATURE CITED Cartographic Research Laboratory. 2004. Climate Maps of Alabama. URL: http://alabamamaps.ua.edu/alabama/climate/index.html. Dean, B. E. 1964. Ferns of Alabama and Fern Allies. Southern University Press. Birmingham, Alabama, USA. Dean, B. E. 1969. Ferns of Alabama. Southern University Press. Birmingham, Alabama, USA. Flora of North America Editorial Committee (eds.). 1993a. Flora of North America North of Mexico, vol. 2. Pteridophytes and gymnosperms. Oxford University Press. New York, New York, USA. Flora of North America Editorial Committee (eds.). 1 993b. Flora of North America North of Mexico, vol. 1 . Introduction. Oxford University Press. New York, New York, USA. Harper, R. M. 1943. Forests of Alabama. Alabama Geological Survey Monograph. 10: 1-230. Mettee, M. F., P. E. O’Neil, and J. M. Pierson. 1996. Fishes of Alabama and Mobile Basin. Oxmoor House. Birmingham, Alabama, USA. Short, J.W. 1978. Distribution of Alabama pteridophytes. M.S. Thesis. Auburn University. Auburn, Alabama. 133 p. Spaulding, D. D., R. D. Whetstone, and J. M. Ballard. 2000. Pteridophytes of northeast Alabama and adjacent highlands 1. Annotated checklist and key to families. Alabama Academy of Science Journal. 71:1 59- 1 72. Spaulding, D. D., J. M. Ballard, and R. D. Whetstone. 2000b. Pteridophytes of northeast Alabama and adjacent highlands 11. Equisetophyta and Lycopodiophyta. Alabama Academy of Science Journal. 71: 173-192. Spaulding, D. D., J. M. Ballard, and R. D. Whetstone. 2001. Pteridophytes of northeast Alabama and adjacent highlands 111. Ophioglossales and Polypodiales (Aspleniaceae to Dennstaedtiaceae. Alabama Academy of Science Journal. 72: 39-64. Spaulding, D. D., J. M. Ballard, and R. D. Whetstone. 2001b. Pteridophytes of northeast Alabama and adjacent highlands IV. Polypodiales (Dryopteridaceae to Osmundaceae). Alabama Academy of Science Journal. 72: 230-252. Spaulding, D. D., J. M. Ballard, and R. D. Whetstone. 2001c. Pteridophytes of northeast Alabama and adjacent highlands V. Polypodiales (Polypodiaceae to Vittariaceae). Alabama Academy of Science Journal. 72: 253-274. 28 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 HETEROGENOUS MODELING AND SIMULATION OF ACTIVATED SLUDGE PROCESSES Gamal M. Ibrahim', Ahmed H. El-Ahwany% Abdel K. Mazher^ and Hisham I. Ibrahim'' ' Menofta Univerisity, Faculty of Engineering. Basic Engineering Scienee Department, Egypt. 'Cairo University Faculty of Engineering, Chemical Engineering Department, Egypt ^Aerospace Scienee Engineering Department, Tuskegee University, Tuskegee, AL 36088 ''Helwan University-, Faculty of Engineering, Biomedical Engineering Department, Egypt Correspondenee: Mazher, A. K. (akmazher_l@bellsouth.net) ABSTRACT A simulation model of an activated sludge proeesses reactor was developed considering mass transfer balanee and the three growth processes: carbon oxidation, nitrification, and denitrification. Helwan wastwater treatment plant (WWTP) was used to extract the suitable stoiehiometric and kinetic parameters to be used for the simulation. Helwan WWTP was used to simulate the removal efficiency of the biochemieal oxygen demand (BOD) substrate and ammonia. The average error of the removal efficieney in Helwan WWTP reached 3.3 1 1 % for the substrate and 12.521 % for the ammonia. Zenine WWTP was used for the testing and validation of the process model through predicting the response of substrate only where the average error of the removal efficieney of substrate reaehed 4.634 %. A parametrie study of the aetivated sludge was performed taking into aeeoLint the effects of recycle ratio, flow rate, and influent substrate eoncentrations on the removal efficiency of the aeration tank. It was found that the removal effieieney of substrate and ammonia was inereased by inereasing of reeyele ratio, influent substrate concentrations and also increased by decreasing influent flow rates. It was found that the sludge age inereased by inereasing the reeyele ratio and deereased by decreasing the influent flow rates. INTRODUCTION Simulation models of the activated sludge process are believed to be a useful tool for researeh, process optimization, and troubleshooting at full-seale treatment plants. Aetivated sludge is a eomplex dynamic process; and simulation of sueh proeess must neeessarily account for a large number of reactions between a large number of eomponents. There is a need for simulation models that deseribe the dynamie behavior of the activated sludge process. However, implementing a model to simulate most treatment plants is limited due to a laek of aeeurate input parameter values required by the models. To improve the operating effieiencies of eurrent wastewater treatment plants, both municipal and industrial engineers have looked to automatie process eontrol. 29 Ibrahim et al.— Heterogenous Modeling of Aetivated Sludge Proeesses Figure 1 shows a sehematie diagram of the activated sludge process where aeration basins (reactors) are typically open tanks containing equipment to provide aeration and to provide sufficient mixing energy to keep the biomass in suspension. The depth is mainly determined by energy transfer and mixing characteristics, and usually ranges from 3 to 7.5m (Grady 1990). A single piece of equipment such as diffused air, mechanical surface aerator, or jet aerator is used in many cases to provide aeration and keep the solids in suspension. Auxiliary mechanical mixers are used when the aeration does not provide sufficient mixing energy. Figure 1. Schematic diagram of the activated sludge process. *Purge Fraction (W), liifliieiit Volumetric Flow Rate (Q), Recycled Volume Flow Rate (Ouj-Total Volume (V), Recycle Ratio Qr/Q (R)- Substrate Componet Mass (SO) Sustrate Feed Concentration (Sf), Soluable Substare, Concentrate (S* ), Substrate Output From The Reactor (Si, ),Biomass Componet Mass (\), Biomass Feed Concentration (X| ), Recycled Biomass Concentration ) Effluent Biomass Concentarion (X,. ), Biomass Rate Of Reaction (r^ ), .\mmonia Componet Mass (H), .\mmonia Feed Concentration (Hf ), .Ammonia Soluable Concentrate) Hs), Ammonia Output From The Reacto r (Hh), Nitrate Componet Mass (Z), Nitrate Feed Concentration (Zf ), Nitrate Soluable Concentrate (Z, ), Nitrate Output From The Reacto r (Zh ), Oxygen Componet Mass (C ), Oxygen Feed Concentration (Cf), Oxygen Soluable Concentrate (Cs ), Oxygen Output From The Reactor (C.'h ), Substarte Growth Rate Coefficient (Kg, ), Amomonia Growth Rate Coefficient (K.gh ), Oxygen Growth Rate C oefficient (Kg,), Nitrate C.rowth Rate Coefficient (K„, ). The secondary clarifier performs two functions in the activated sludge process. The first function, clarification, is the separation of the biomass from the treated wastewater to produce a clarified effluent that meets the effluent suspended solids goal. The other is the thickening of sludge for return to the bioreactor. Since both functions are affected by clarifier depth, the design depth must be selected to provide an adequate volume for both functions (Tchobanoglous and Burton, 1991, Jack, 2001). For instance, the volume must be sufficient to store the solids during periods of high flow. The objectives of this study thus are: 1. To build a process model considering mass transfer balance and simulates an Egyptian plant, Helwan wastewater treatment plant, that exists in the south of Cairo and has a capacity of 350000 in'* /d and average removal efficiency of 85% 30 Journal of Alabama Academy of Science Vol. 78, No. 1, January 2007 for substrate and 62% for ammonia. To assess the simulation results, the model validation was performed for Zenine wastewater treatment plant that exists in the west of Cairo and has a capacity of 330000 m^ /d and average removal effieieney of 87.6% for substrate. 2. To adjust the model kinetie parameters of the bioehemieal reaetions of the three growth processes: carbon oxidation, nitrification, and denitrification under the effect of mass transfer conditions for the simulation purpose. 3. To study the effect of the operating eonditions sueh as flow rate, recyele ratio, and feed substrate eoneentrations on the removal effieieney of both substrate and ammonia. ACTIVATED SLUDGE PROCESSES MODEL DEVELOPMENT The key to a successful modeling of the aetivated sludge proeess is the appropriate assumptions to achieve a eompromise between eomplexity and utility. In the present study we have derived the general dynamie model of the aetivated sludge process in the bioreaetor. The bioreaetor (aeration basin) model deseribes the removal of organic matter, nitrification, and denitrification. The derived bioreaetor model is an extension of the aetivated sludge model number 1 (ASM I ). It is a biofloe model, developed in Henze et al. ( 1987), eonsidering both the mass transfer and bioehemieal process reaetions. The simulation model considers the four main components: BOD (readily biodegradable substrate (S), ammonia (H), Nitrate (Z), and oxygen (C). The assumptions in the biofloe model and the proeess model are: 1 . The power input used in the bioreaetor is assumed to equal 80% of the maximum value to realize a eomplete mixing in the reaetor. 2. The effluent biomass concentration is negleeted. 3. The eonsumption of substrate, ammonia, and oxygen in the settler is negleeted. 4. The average volumetric flow rate of the influentis eonstant. 5. The average reeycle ratio and wastage ratio are not negleeted. The details of the proeess model developed are shown in Fig. 1 . DERIVATION OF THE PROCESS MODEL The equations of substrate is considred by applying mass balanee on the settler in order to get the biomass coneentration exiting, which is recycled to the bioreaetor. Next, the mass balance equations of the bioreaetor will be derived. The following are the variables used in the derivation ( see Fig. 1 ): 31 Ibrahim et al.— Heterogenous Modeling of Activated Sludge Proeesses W= purge fraetion Q = influent volumetrie flow rate Qi^=recyeled volume flow rate V= total volume R= recycle ratio = Q,^/Q S= substrate componet mass S = sustrate feed concentration S = soluable substare concentrate s S^= substrate output from the reactor X= biomass componet mass X = biomass feed concentration X^ = recycled biomass concentration X = effluent biomass concentarion e r = biomass rate of reaction x H= ammonia componet mass H = ammonia feed concentration Hs= ammonia soluable concentrate ammonia output from the reactor Z= nitrate componet mass nitrate feed concentration Z = nitrate soluable concentrate S Z^= nitrate output from the reactor C= oxygen componet mass C = oxygen feed concentration C^= oxygen soluable concentrate oxygen output from the reactor substarte growth rate coefficient K^i^= amomonia growth rate coefficient oxygen growth rate coefficient nitrate growth rate coefficient Applying a component mass balance on biomass for the settler gives: Q {l + r)x =Q(R+}V X,. + x^ Neglecting the effluent biomass concentration, X=().(), then. ( 1 + R \ R-hfV \ X (2) 32 Journal of Alabama Academy of Science Vol. 78, No. I , January 2007 By performing mass balance on the reactor, the following equations are obtained; I. Component Mass Balance on Substrate (S) Neglecting the substrate consumption in the settling tank and assuming a substantial decrease in the water content of the settled sludge, related to that measured, lead to ^ Applying a component mass balance on the substrate for the bioreactor gives: Inflow “ Outflow + Net growth + Accumulation Q S^- +RQ Q dt (3) (4) 2. Component Mass Balance on Ammonia (H) Ammonia nitrogen can be removed from wastewater by volatilization of ammonia. Gas stripping is most effective when contaminated wastewater is exposed tc Hence, this process is considered by adding a factor of ammonia stripping (Gf) in the f differential equation of ammonia mass balance. Applying a component mass ba ammonia for the bioreactor gives: V_c^ Q dt tf Q ) (5) 3. Component Mass Balance on Nitrate (Z) Applying a component mass balance on nitrate for the bioreactor gi\ es: Q dt ^ gz^tf Q (6) 4. Component Mass Balance on Oxygen (C) Applying a component mass balance on oxygen for the bioreactor gives: Q dt V + — K a Q I cd-Ct ^ gc^tf Q (c* - C, ) (7) 33 Ibrahim et a!.— Heterocenous Modeling of Activated Sludge Processes o c o 5. Component Mass Balance on Biomass (X) V Applying a component mass balance on biomass for the bioreactor gives; QXf + RQ ^ J + R^ ^R + W j X =Q(1 + R)X -r^V + V dX dt Hence, dX Q dt V {w + r) (8) (9) From task group (Henze et al. 1987) the rate of reaetion of heterotrophic and autotrophic biomass can be obtained as follows: r c. ( V ^oH + Q S, V K.. Y K^+S h J H b Xh + fit f C, \ K^a + c, \^cA h J -^H -^A (10) These dynamie model equations are first order differential equations. Solution Technique The initial value problem given by equations (4)-(9) are solved by any of the standard numerical methods for a system of ordinary differential equations using the finite difference teehnique. A large number of points have been taken to improve the aeeuraey of the results. RESULTS AND DISCUSSION Seleeting suitable kinetic and stoichiometric parameters is eonsidered by using Helwan WWTP data. The model is tested by earrying out the simulation on Helwan WWTP on substrate BOD and ammonia concentrations. Zenine WWTP was used for the testing and validation of the proeess model through predicting the response of substrate only as will be shown. 34 Journal of Alabama Academy of Science Vol. 78, No. 1, January 2007 Parameters Evaluation Shieh and Leo (1986) used an experimental procedure for determination of intrinsic kinetic coefficients. The experimental apparatus, rotating disk biofilm reactor, provides a relatively simple yet rigorous means for examination of both intrinsic and mass transfer limited kinetics. It allows for direct measurement of intrinsic kinetic coefficients and biological parameters relevant to a given reaction. The intrinsic kinetic coefficient of biologieal denitrification measured in their study is Kz = 2.875 mg NOB-N^/d, and nitrate- nitrogen effective diffusivity De = 0.815x10 -“^ cmVsec. Alison et al. (1993) measured the maximum specific growth rate and the half saturation coefficient (KJ. A simple respirometric technique was used where different volumes of concentrated wastewater were contacted with biomass and the response measured as a change in oxygen uptake rate AOUR. The AOUR was then related to the growth rate, and a series of substrate concentrations and growth rate relationships were determined, and from which u and K were calculated. Typical u and K values published for municipal sewage are in the range =1-5 d ', with a typieal value of 2. 5 d ' (Metcalf and Eddy, 1990). The range is 6-19 mg f with a typical value of 12 mgl ' Yerachmiel et al. (1990) carried out bench-scale experiments using domestic wastewater under a constant flow rate. They obtained a set of kinetic and stoichiometric coefficients with BOD removal and nitrification only. The denitrification process was not tested. The set of measured coefficients falls within the range reported in the literature for domestic wastewater. Differences in some of the values may be attributed to the selection of decreased diffusional mass transfer kinetics in systems. The component mass balance equations on the substrate, ammonia, nitrate, oxygen, autotrophic and hetrotrophic biomass derived above are considered to extract the best values of parameters to simulate Helwan plant performance. Many points were taken from Helwan wastewater treatment plant data to obtain the optimum result at which the theoretical predictions (the output of the simulation model program) are very close to the measured results (the output from Helwan WWTP). The data shown in Table 1 are used as input for the model program. The suitable parameters in turn will be used for the validation and simulation of Zenine WWTP. Table 1 shows the average measured values of process parameters for Helwan WWTP. Selecting kinetic and stoichiometric parameters using the literature data, depending on ASM 1 at first, can validate the model. However, in order to achieve acceptable agreement between the real and theoretical concentrations, numerical estimation of some parameters is necessary. To simplify this procedure, the relations between the effluent concentrations of the components and the kinetic and stoichiometric coefficients used in the model should be known. It was found that the effluent concentration of substrate, ammonia are directly proportional to the values of the saturation coefficients Ks, K^, and yield coefficients and Y^. Also, it was found that they are inversely proportional to growth rates and p^. These relations are very useful to reach the best values of kinetic and soichiometric coefficients that make the theoretical results comparatively much closer to that of the actual results. 35 Ibrahim et al.— Heterogenous Modeling of Aetivated Sludge Proeesses Table 1. Average values of process parameters for Helwan plant Parameter Value Qo (m3/day) (inlet flow) 43750 %R 60 %W 3.5 Sf (mg/1) (BOD ) 83 Hf (mg/I) (ammonia) 1 .03 Zf (mg/1) (nitrate) 11 SVI (ml/gm) 57 (P/V) (W/m3 ) 109.7 V (m3) ( reactor volume) 3000 Xf (mg/1) (biomass) 50 R= recycle ratio, W= purge fraction, S= substrate component mass, Sf= sustrate feed concentration, Hf= ammonia feed concentration, Zf= nitrate feed concentration, SVI= substarte concentarion, and PA^= power input per liquid volume. The values given in Table 2 are considered typical for neutral pH and domestic wastewater. The selected values of the kinetic and stoichiometric coefficients shown in Table 2 represent a set of values that result in a good fit of the experimental data and the model prediction. The following are some observations on the values shown in Table 2: 1 . Some parameters such as 9.8 mg/1, density, diffusivities, viscosity, are adopted from the literature. 2. Diffusivity inside floes is assumed to be 80% of that in pure water. 3. Some parameter values such as and are within the same range of the AMSl model adopted by Henze et al.l987. 4. Some parameter values such as K ,,, K and K are out of the range of ASM 1 model ( Henze et al., 1987) due to considering the mass transfer limitations. 5. The study of parametric sensitivity of the model has shown that the influence of the parameters and K .^ is not large on the effluent concentration of ammonia. It can be explained that the fraction of the autotrophs that oxidize ammonia in aerobic growth process to the heterotrophs is very small, so the effluent ammonia is more sensitive to p,. and b,, than p , and b, for the same reason. 6. The assumed value for ammonia stripping factor G^, = 0.075 is very small and suitable because of simultaneous loss of ammonia due to practical conditions 36 Journal of Alabama Academy of Science Vol. 78. No. 1, January 2007 such as agitation, temperature, and exposed surface area in addition to non-adding any chemicals such as lime inside the aeration basin. 7. The assumed value for n is taken from the literature. 8. The range of experimental values for the ratio of active biomass in floes is nearly 0.8. 9. This makes the effluent of biomass 2.2 - 3 gm / 1. Table 2. The parameter values extracted from the floe model Symbol Value Explanation y. 0.55 Yh 0.7 |iA 0.42 day ' Ah 4.35 day ' Ks 220 mg r' Kc, 0.05 mg 02 f ' K. 0, 15 mg NO3-N f' K. 250 g NH 3-N r 1 K,2 2 mg 02 1 ' Aa 0.08 day ' bn 0.62 day ' 0.8 K,a c* 9.8 mg/1 Yield for autotrophic biomass Yield for heterotrophic biomass Maximum specific growth rate for autotrophic biomass Maximum specific growth rate for heterotrophic biomass half saturation coefficient for heterotrophic biomass Oxygen half saturation coefficient for heterotrophic biomass Nitrate half saturation coefficient for denitrifying heterotrophic biomass Ammonium half saturation coefficient for autotrophic biomass Oxygen half saturation coefficient for autotrophic biomass Decay rate coefficient for autotrophic biomass Decay rate coefficient for heterotrophic biomass Correction factor for [in under anoxic conditions Volumetric oxygen transfer coefficient see Chapter 2 Saturated oxygen concentration MODEL TESTING Min et al. (1997) performed some trials for a coke wastewater treatment plant by fixed biofilm system for COD and NH^-N removal. The experimental results showed that this system was efficient and stable in COD and NH3-N, reductions. The effluent COD and NH3-N, were 1 14 and 3.1 mg/I with removal efficiency of 92.4 and 98.8 % respectively. In order to test the accuracy of the values obtained for the parameters, numerical runs of the model have been carried out for the simulation model using the parameters obtained for the model and the constants that define the characteristics of the system. The model proposed in this work was tested. Helwan WWTP data, which were used for the extraction of kinetic and stoichiometric coefficient, shown in Table 2, are also used in order to test the model. The theoretical results (or the model predictions) in terms of the effluent concentrations were compared against the field results of Helwan plant . 37 Ibrahim et al.— Heterogenous Modeling of Aetivated Sludge Proeesses Hehvan WWTP Aeration Basin The operating data for Helwan aeration basin are; 1 . The aeration basin volume =3200 m\ 2. Cross seetional area =806.88 m^ 3. Volumetric Flow rate=43,750 mVday. 4. Average recycle ratio =30-120% of the feed. 5. Average wastage ratio = 0. 1 -5.% of the feed. 6. The power input in (W/nV) for the aeration basin = 200 kW on the basis of 80% of the available maximum power input. 7. The technique of the aeration used in the plant is mechanical surface aeration whereby the wastewater is agitated at the surface to promote the transfer of oxygen to the water from the atmosphere above the liquid . The surface aerators also throw water into the air to increase contact area. The agitator type used is a cone turbine with 16 blades. 8. Available volumetric flow rate of air =1246.36 m Vhr. 9. is a function of power input per m^ of liquid volume (P/V) in the aeration basin: (P/V) + k (11) Where V=occupied reactor volume=l 822.91 m^ and P=200 kW. Hence, P/V=109.71 W/nP and by fitting = 500 day', K=450 , and =98.01 day. ' Simulation Results for Helwan WWTP Because the effluent BOD and ammonia field data is noisy, it can only serve as a rough guide for evaluating the model behavior (Lessard and Beck, 1993)._Considering the previous operating data for the northern aeration basin for Helwan WWTP in the simulation model, for readily biodegradable substrate BOD (S) and ammonia (H), the results shown in Tables 3 and 4 were obtained. Where the average removal efficiency error equals the real removal efficiency, and the theoretical removal efficiecy is defind as: (12) 38 Journal of Alabama Academy of Science Vol. 78. No. 1 , January 2007 Table 3. Simulation results for Helwan plant in Feb 1996 Feed Soul H DUl %Average Removal Error Date Sf (mg/1) Hf (mg/1) SVI (ml/g) Real Thco. Real Theo. %s %H 3/2/9 6 83 1 1 57 12 1 2.075 5.3 5.593 0.01 2.67 10/2 83 12.5 56 14 1 2.076 3 6.3 2.32 26.4 13/2 90 13.1 56 20 12.7 11 6.67 8.1 1 33.1 16/2 88 12.3 57 14 12.526 4.5 6.25 1.7 14.23 21/2 69 12 47 17 1 1 5.3 6.8 8.75 12.5 26/2 69 11.3 53 10 10,68 3 5.8 1 24.78 Average error 3.65 18.95 Sf= sustrate feed concentration, Hf= ammonia feed concentration, SVI= substarte concentarion, S= substrate component mass, and H= ammonia component mass Table 4. Simulation results for Helwan plant in March 1996. Feed Soul H, out %Average Removal Error Date s, (mg/1) Hf (mg/I) SVI (ml/g) Real Theo. Real Theo. %S %H 2/3 221 18.8 57 31 20.46 10.6 11.15 4 77 4.7 6/3 427 20.6 54 39 47 11.9 13.47 2 82 7.62 1 1/3 266 20.3 56 34 41.9 15.6 13.23 2.97 1 1.4 23/3 280 15.4 57 48 54.33 10.2 10.1 2.3 .0.65 30/3 248 23.3 47 28 23.348 12.5 13.9 2 6 Average error 2.972 6.074 Sf= sustrate feed concentration, Hf= ammonia feed concentration, SVI = substarte concentarion, S= substrate component mass, and H= ammonia component mass. It is noted from Tables 3 and 4 that the theoretical and real values of readily biodegradable substrate BOD (S) are in close agreement. This result gives a good indication for model capability to simulate BOD effluent and suggests that the inclusion of mass transfer effects in the floe model will be useful in better describing real dynamic behavior of the removal efficiency or the effluent quality. The theoretical and real effluent ammonia concentration (H ) values as shown in Tables 3 and 4 are not in close agreement. The average removal error of both the substrate (BOD) and ammonia are 3.31 1 and 12.521% respectively. The difference between the real and theoretical results may be due to the finite accuracy of the numerical method used. 39 Ibrahim et al.— Heterogenous Modeling of Activated Sludge Processes The average removal error between the theoretical and real values of ammonia (H) comes from the air stripping operation, where the assumed value of the air stripping factor may not be accurate enough to express the real amount which was lost when exposed to free air. In fact, for a real plant the stripping factor is not constant but depends on the practical situations. The average removal error between the theoretical and real values is as shown in the range of 6-19%. MODEL VALIDATION Helwan WWTP was used for extraction of kinetic and stoichiometric coefficient as shown in Table 2 and used also for testing the model. However, Zenine WWTP is used for validation of the model using the same kinetic and stoichiometric coefficient as shown in Table 9. Zenine WWTP is located in the west of Cairo. It treats wastewater at a capacity of 330,000 mV day. It consists of 3 modules, each one containing 22 aeration basins. They have the same total volume, method of aeration and working conditions. It is noted that the volumes of the aeration basins in Zenine WWTP are smaller than that of Helwan WWTP but their numbers in Zenine WWTP are greater. ZenineWWTP Aeration Basin The operating data for ZenineWWTP aeration basin are: 1 . The aeration basin volume =537 mk 2. Cross sectional area =50 m^ 3. Volumetric flow rate=5,000 mVday. 4. Average recycle ratio =90% of the feed. 5. Average wastage ratio = 0.5 -5.0% of the feed. 6. The power input in ( W/mV for the aeration basin = 40.33 kW on the basis of 75 % of the available maximum power input. 7. The technique of aeration method used in the plant is the diffused air technique, whereby the air is introduced below the surface through diffusers or nozzles. The rise velocity of the bubbles creates a circulating mixing pattern in the liquid. 8. Available volumetric flow rate of air =1227.3 mVh. 9. Evaluation of in the same as above , using the same correlation (11), where V =208.33 m-^ and P=40.33 kW, hence, P/V= 193.6 W/mk By fitting it is found that K, = 500 day-', K=450 and K, =150.41 day' Simulation Results for Zenine WWTP The previous operating data of the aeration basin in module 3 for Zenine WWTP and stoichiometric and kinetic parameters shown in Table 2 are used to validate the simulation model. Readily biodegradable substrate BOD (S) only is used for the purpose of validation because of unavailable data for other components such as ammonia. The simulation model was applied for 12 months in 1994 for BOD. Tables 5-10 show some 40 Journal of Alabama Academy of Science Vol. 7K, No. 1 . January 2007 simulation results for Zenine WWTP. From these tables it can be shown that the percentage average removal error of the removal efficieney of substrate (BOD) between the real and theoretical results oi Zenine WWTP equals 4.634%. Also, the results show that the theoretieal and the real values of substrate (BOD) are in elose agreement. The differenee between the real and theoretieal results is due to the finite aeeuraey of the numerieal method used. These results give a good impression that the model is able to predict the output ot the aeration tank in a wastewater treatment plant. This emphasis the validation of the model and also the aeeuraey of the kinetie parameters. Table 5. Simulation results for Zenine plant in January 1994 Date Sr SVl Soul Real Thco. %Average Removal Eff. Error (%S ) I/l 119 130 16 17.4 1.2 5/1 146 129 15 19.4 3.01 9/1 133 141 16 18.5 1.9 15/1 124 152 16 17.8 1.45 21/1 138 132 16 18.9 2.2 26/1 132 120 17 18.4 1 Average error 2.152 Sf= sustrate feed concentration, SVI= substarte concentarion, and S= substrate component mass. Table 6. Simulation results for Zenine plant in March 1994 Soul %Average Date Sf svi ■ Real Theo. Removal Error (%S) 1/3 127 128 20 17.72 1.8 5/3 160 144 23 1S.9 2.5 13/3 174 164 24 20.6 2 17/3 166 144 22 20.2 1.1 22/3 110 101 14 16.3 2.1 ' 31/3 135 122 30 18.3 8.67 Average error 3.03 Sf= sustrate feed concentration, SVI= substarte concentarion, and S= substrate component mass. 41 Ibrahim et al.— Heterogenous Modeling of Aetivated Sludge Processes Table 7. Simulation results for Zenine plant in May 1994 Sf SVI - Sput Real %Average Removal Theo. Eff. Error (%S) 2/5 130 91 15 18.3 2.54 4/5 137 95 20 18.8 1 6/5 111 96 13 16.7 3.33 10/5 1 12 111 18 16.89 1 15/5 117 119 18 17.3 1.5 141 143 29 19.1 7.02 26/5 160 119 27 20.31 4.2 31/5 103 150 1 1 16.1 4.95 Average error 3.2 Sf= sustrate feed concentration, SVI= substarte concentarion, and S= substrate component mass Table 8. Simulation results for Zenine plant in July 1994 Sput _ %Average Date Sf SVI Real Theo. Removal Eff. Error (%S) 1/7 147 141 44 18.2 17.55 4/7 95 133 1 1 14.8 4 7/7 121 116 5 16.5 9.5 10/7 101 106 10 14.5 4.45 13/7 93 91 35 14.9 21.6 19/7 127 142 20 16.94 2.9 25/7 109 175 16 15.6 0.36 31/7 140 231 8 17.8 7 _ Average error _ 8.42 Sf= sustrate feed concentration, SVI= substarte concentarion, and S= substrate component mass. Table 9. Simulation results for Zenine plant in September 1994 Sput _ "^Average Date Sf SVI Real Theo. Removal Elf. Erroi' (%S) 1/9 131 98 20 18.1 1.53 5/9 109 122 19 16.3 2.5 8/9 no 133 14 16.64 2.4 15/9 119 138 1 1 17.2 5.21 22/9 99 193 9 15.5 5.57 25/9 102 217 10 15.5 5.24 30/9 133 203 10 18.2 6.2 Average error 4.05 St= sustrate feed concentration, SVI= substarte concentarion, and S = substrate component mass 42 Journal of Alabama Academy of Science Vol. 78, No. I , January 2007 Table 10. Simulation results for Zenine plant in December 1994 Sout % Average Date Sf SVI Real Then. Removal Eff. Error (%S) 1/12 144 95 24 15.8 5.7 5/12 1 19 98 13 15.4 9 1 1/12 105 97 1 1 14.8 3.62 17/12 121.7 89 28 21 5.75 25/12 104 122 29 14.7 13.75 31/12 130 190 10 15 3.85 Average error 5.78 Sf= sustrate feed concentration, SV1= substarte concentarion, and S= substrate component mass. Parametric Study of Activated Sludge Process The parametric study is conducted to evaluate the performanee of the aeration basin in the activated sludge plants. This is performed by studying the effect of the following operating parameters; influent flow rate, recyele ratio, wastage ratio, power input and influent eomposition of substrate and biomass on removal effieiency of the substrate (BOD) and ammonia. Yuiehi et al. ( 1992) studied the effeet of the operational performanee on percentage nitrogen removal efficieney by a single-stage, single-sludge activated sludge proeess. They found that more than 97% of the organ ie earbon was removed and only small concentrations of the NH_|-N2 were found in the effluent. The data shown in Table 1 and the kinetie and stoichiometric coefficients shown in Table 2 will be eonsidered. When the effeet of one parameter is studied the other parameters are kept eonstant. In our study we defined: Removal effieiency of substrate * 100 (13) Removal efficiency of ammonia * 100 (14) Sludge age, 0^., is defined as the ratio of biomass in the reaetor to the net rate of biomass. It is often ealled solids retention time in the reaeting system. It has a prineipal effect on the performanee and the capabilities of an activated sludge system. It is important in aetivated sludge systems beeause it is an operational parameter that can be physically controlled to maintain treatment performance. Lawrenee and McCarty’s ( 1970) landmark paper linked the sludge age to the treatment efficieney thereby providing means of maintaining treatment 43 Ibrahim ct al.— Heterogenous Modeling of Aetivated Sludge Proeesses performanee by manipulating physieal attributes sueh as wastage rate. At steady state conditions, the net rate of biomass generation is equal to the rate at which biomass flows out of the system. If biomass is removed by wasting from the recycle line and by losses in the clarifier overflow, the sludge age, as shown in Fig. I, is given by: 0c (d) = QWX y X ^ v{r + w) QW {] + r) (15) where A' =0.d. Through experience, operators of conventional activated sludge reactors have found that 0, usually lie between 3-14 days in order to produce a biological floe which can be handled easily. For 0^, less than 3 days, the biomass is not dense enough to settle easily, producing “bulking sludge.” For 0^ greater than 14 days, the floe particles are too small to settle rapidly and the fraction of living cells in the biomass is low. Good sludge settling properties are essential for an efficient gravity settler operation and a stable activated sludge process. Since the sludge age largely governs how well a floe will settle, an age value is chosen based upon experience and the type of sludge generated in the process. The sludge age can be controlled by the wastage rate from the bottom of the settler or by the rate of sludge recycle. By decreasing the sludge wastage rate, the sludge age is increased. The same result can be obtained when the rate of recycle ratio (R) is increased. (Donald and Herbert, 1979 ). Perdrieux et al. (1980) showed that higher sludge age results in better assimilation of the substrate by the cell and increases the rate of utilization of the stored carbon for energetic requirements. Effect of Recycle Ratio The purpose of the recycle of sludge is to maintain a sufficient concentration of activated sludge and to increase the concentration of the biomass in the aeration basin. The addition of a recycle stream dilutes the concentration of entering substrate and decreases the residence time of fluid elements in the aeration basin. So the required degree of treatment can be obtained in the time interval desired. The return of activated sludge from the clarifier to the inlet of the aeration tank is the essential feature of the process. Recycle ratio (R) is defined as the ratio between the recycle flow rate to the aeration tank and influent flow rate. Figure 2 shows the effect of change of recycle ratio on the percentage removal efficiency of the substrate and ammonia at certain conditions of Hp C|. and (P/V). As R increases removal efficiency of substrate increases till it reaches 84% at R = 40%, then it reaches 86% at R = 80 %. Finally, it becomes almost constant with further increase of R where it appears that substrate removal efficiency is not enhanced by a recycle ratio larger than 80%. 44 Journal of Alabama Academy of Science Vol. 78. No. 1, January 2007 With respeet to the ammonia, the pereentage removal effieiency increases from 33.991 at a very small value of R till it reaches 52% at R equals 80 %, then beeomes constant as R increases. It appears that ammonia removal efficiency was not enhanced by a recycle ratio larger than 80%. In the first stage, when R increases in the range 0- 80% the removal efficiency of substrate and ammonia inereases continuously. The rate of biomass produetion inereases dependently, and the produced biomass degrades the organie substrate (BOD) and ammonia efficiently. This explains why pereentage removal efficieney increases till it reaehes nearly 80%. However, in the seeond stage, the pereentage removal effieiency becomes constant because the aeration is unable to supply the excess biomass to the neeessary oxygen in addition to the rate of inereasing biomass eoncentration will be reduced as R inereases as shown in Fig. 3. When the operating eonditions ehange, the eurves in Fig. 2 will have the same shape, but they are shifted to the right or the left aecording to the available conditions. Fieure 3 shows that the effluent biomass eoncentration (X ) will always inerease as R inereases due to the biomass resulting from the degradation of the substrate and ammonia. Yuichi et al. ( 1992) showed that the higher the eoneentration of sludge biomass in an aeration basin, the larger the number of mieroorganisms and the number of floes that possess aerobie and anoxie micro-sites inside the floes. Thus the oxidation and denitrifieation rate in the aeration basin will be enhaneed by higher volumetrie BOD loading. Sinee organie matter is essential for oxidation and denitrification, Tashiro et al. ( 1990) showed that it might be difficult to carry out simultaneous earbon-nitrogen removal when the influent is applied to this process. Since the sludge age largely governs how well a floe will settle, it is important to study the effect of recycle ratio on sludge age. Figure 4 shows the effect of change of R on the sludge age, 0^, in the aeration tank. It is shown that 0^ increases continuously as R increases. It is noted that the inereasing of R will increase the biomass eoneentration, and eonsequently a better assimilation of the substrate by the cell ean be obtained and the rate of utilization of the substrate for energetie requirements ean be inereased (Perdrieux et al., 1980). Henee, the sludge age can be eontrolled by the sludge reeycle from the bottom of the clarifier. Effect of Influent Flow Rate It is important to study the effect of influent flow rate, as an external faetor, on the pereentage removal effieieney beeause it is very diffieult to eontrol. Logically, the inereasing of flow rate will eause high loading on the performanee of the plant. Figure 5 shows the effect of increasing the flow rate on the removal effieiency of substrate and ammonia. It is shown that the removal effieiency of substrate decreased from 100% at very small values of the flow' rate to 36.5% at 0=100,000 m Vd. The same is true for ammonia, but the removal effieieney of ammonia is less than that of substrate. Figure 6 shows that inereases from 25mg/l till the highest value of 4577 mg/1 at 50,000 mVd then deereases as the flow rate inereases till reaches the eonstant value. The highest value of ean be eonsidered the optimum value, and the flow rate then is ealled the eritical flow rate. The microorganisms after the critieal flow rate are washed out of the reactor faster than they are generated by the reaetion under washout conditions. 45 Ibrahim et al.— Heterogenous V ' )0 '!ing of Activated Sludge Processes The concentration of biomass in th,- reactor decreases and the conversion of substrate decreases. In fact, optimizing the differen ilow rates in the plant is an interesting area of research. Real wastewater treatment plants should work in a range of flow rate close to the critical to fulfill the highest effluent biomass such as Helwan WWTP which has a flow rate of 43750 mVd. Maintaining a high concentration of biomass is a tempting strategy to improve plant performance since a large biomass can degrade more organic material. However, other forms of microorganisms may adapt to the high concentration of biomass, which in turn makes the activated sludge process less efficient. These results agree with Muller et al. (1995) who showed that a very low biomass production could be achieved when a very high influent flow rate is applied. Figure 7 shows that the increasing of flow rate will decrease the sludge age in the reactor; hence the removal efficiency of the aeration basin decreases. The microorganisms will not have enough time to oxidize the substrates and ammonia and it is required to control the influent flow rate to maintain a high conversion. The sludge age can be calculated at the critical flow rate according to Eq. (14), and equals 8.6 days. This is an optimum value for the sludge age that allows sufficient time to perform different biodegradations Effect of Influent Substrate Concentration The influent composition is important for the design and control of a WWTP. The concentration of influent substrate determines the performance of the plant. Benefield and Randall (1985) showed that although substrate treatment would not likely be affected until a very low concentration was reached, a distinction between excess and low concentartion was made since nitrification is limited at concentration less than 2 mg/I. In Fig. 8, the behavior of percentage removal efficiency can be classified into two stages. In the first, the conversion of substrate increases with increasing from 77.7 % at small values of S|. to reach 96.5% at = 700 mg/I; then it becomes constant as S|. increases. This means that the output substrate concentration remains constant, but in the second stage the effluent substrate concentration remains constant and does not depend upon the entering substrate concentration. It appears that the removal efficiency was not enhanced by S,, larger than 700 mg/1. This response represents an inherent “self control” by the reactor since changes in feed concentration do not affect the output substrate concentration (Donald et al., 1979). This can be understood by Fig. 9 where the effluent biomass (biological solids) concentration is increasing linearly as S^. increases sufficiently to handle the higher loading of the substrate. The percentage removal efficiency of ammonia increases from 44.3% at a very small value of S^. then increases continuously till it reaches 86.6% at S^. = 1409mg/l. 46 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 on removal efficiency. biomass effluent Figure 4. Effect of recycle ratio on sludge age. 47 % Efficiency removal Ibrahim et ah— Heterogenous Modeling of Activated Sludge Processes Flow rate (m3/d) Figure 5. Effect of flow rate on removal efficiency. Flow rate (m3/d) Figure 6. Effect of flow rate on effluent biomass. Flow rate (m3/d) Figure 7. Effect of flow rate on sludge age. 48 Journal of Alabama Academy of Science Vol. 78, No. 1 . January 2007 Figure 8. Effect of feed substrate concentrations on % removal efficiency. Figure 9. Effect of feed substrate concentrations on effluent biomass (Xout). 49 Ibrahim et al. -Heterogenous Modeling of Aetivated Sludge Processes Figure 2. Effect of recycle ratio on removal efficiency. Figure 3. Effect of recycle ratio on biomass effluent. Figure 4. F^ect of recycle ratio on sludge age. 50 Jt^urnal of Alabama Academy of Science Vol. 78, No. I , January 2007 CONCLUSION A mathematical process model was developed for the aeration tank of the aetivated sludge plant. Identifieation of kinetie and stoichiometrie parameters was studied in order to obtain the suitable values of parameters as shown in Table (2) to prepare the model for the simulation purpose and to obtain results eompatible with true activated sludge plants. It was found that some parameter values such as half saturation coefficients were found out of the range of ASM 1 (Henze et al. 1987) due to the mass transfer limitations in the floe model. Some other parameter values sueh as the ammonia stripping factor were assumed. The other parameters sueh as saturated concentration of oxygen were taken from ranges given in the literature. In this study, two Egyptian wastewater treatment plants were used: Helwan WWTP and Zenine WWTP. The two plants are different in some eonditions such as aeration tank volume, flow rates, and the aeration teehnique. Helwan WWTP uses the surfaee aeration with meehanieal agitation technique while Zenine WWTP uses the diffused air technique. Helwan WWTP data were used through the simulation of the response of different eomponents of substrate (BOD) and ammonia. Zenine WWTP was used for testing and validation of the proeess model through the predietion of the substrate only. The average errors of the removal effieiency of the actual results of the plant and the theoretical results of the process model were measured. The average error of the removal efficieney in Helwan WWTP reaehed 3.3 1 1 % for the substrate and 12.521 % for the ammonia. However, in Zenine WWTP it reaehed 4.634 % for the substrate. These results emphasize the model validation and the kinetic parameter accuracy. A parametric study of the aetivated sludge was performed. The effects of recycle ratio, flow rate, and influent substrate eoneentrations on the removal efficiency of the aeration tank were studied. It has been found that the removal efficiency of substrate and ammonia was inereased by inereasing the reeyele ratio and influent substrate eoneentrations and also increased by decreasing the influent flow rates. It has found that the sludge age inereased by inereasing the reeyele ratio and decreased by decreasing the influent flow rates. The highest value of can be eonsidered the optimum value, and the flow rate then is ealled the eritieal flow rate. After the eritieal flow rate is reached, the mieroorganisms are washed out of the reaetor faster than they are generated by the reaetion, so the concentration of biomass in the reaetor deereases and the conversion of substrate also deereases. The sludge age is ealculated at the eritieal flow rate aceording to Eq. (15) and equals 8.6 days; this value allows suffieient time to perfomi different biodegradations. Maintaining a high coneentration of biomass is a tempting strategy to improve plant performanee since a large biomass ean degrade more organie material. However, other forms of mieroorganisms may adapt to the high concentration of biomass, which in turn makes the aetivated sludge process less effieient. 51 Ibrahim et al.— Heterogenous Modeling of Activated Sludge Processes LITERATURE CITED Alison, H. Slade and D. H. Peter. 1993. Measuring maximum specific growth rate and half saturation coefficient for activated sludge systems using a freeze concentration technique. Wat. Res., 27( 1 2): 1 793- 1 795. Benefield, L. and C. Randall. 1985. Biological process design for wastewater treatment. Larry, D. Benefield and Clifford, W. Randall (editors), Charlottesville, VA, USA. Donald, W. S and E. K. Herbert. 1979. Wastewater Treatment. Prentice- Hall, Inc., Englewood Cliffs, USA. Grady, N.F 1990. Activated sludge theoiy and practice. Oxford University Press, USA. Henze, M., L. Grady, W. M. Gujer, G.V.R. and T. Matsou.. 1987. A general model for single sludge wastewater treatment systems. Wat. Res. 21(5): 505-515. Jack, J. P. 2001. The effects of dissolved oxygen and biological solids retention time on activated sludge treatment performance. The University of Tennessee, Knoxville Lawrence, A. and P. McCarty.. 1970. Unified basis for biological treatment design and operation. Journal of the American Society of Civil Engineers, 96; 757-778. Lessard, P. and Beck, M. B. 1993. Dynamic modeling of the activated sludge process: a case study. Wat.. Res. 27 (6); 963-978. Metcalf & Eddy. Inc. 1990. Wastewater engineering: treatment, disposal, and reuse. Tenth reprint, McGraw- Hill Inc. , NY, USA. Min, Z. J., H. T. Qian and S. G. Xia. 1998. Coke plant wastewater treatment by fixed biofilm system for COD and NH3-N removal. Wat. Res. 32 (2): 519-527. Muller, E. B., A. H.Stouthamer,.H. W. Van Verseveld, and D.H. Eikelboom. 1 995. Aerobic domestic wastewater treatment in a pilot plant with complete sludge retention by cross flow filtration. Wat. Res. 29 (4): 1 179-1 189. Perdrieux, S. and N.Therien.. 1980. Modeling the dynamics of the activated sludge wastewater treatment process in terms of the carbon variable. Wat. Res. 14, 1333- 1344. Shieh, Wen K. andT. M. Leo. 1986. Experimental determination of intrinsic kinetic coefficients for biological wastewater treatment systems. Wat. Sci. Tech 18: 1-10. Tashiro, T., Y. Suwa, T. Yamagishi. and M. Hirai. 1990. Ammonium oxidation by an activated sludge process with cross-flow filtration. Hakkokogaku 68: 31-34 (in Japanese). Tchobanoglous, G. and F.L. Burton. 1991. Wastewater Engineering: Treatment, Disposal and Reuse. Third edition, McGraw-Hill, USA. Yerachmiel, A and P. Gregory. 1990. A steady-state model for the single sludge activated sludge system-II. model application. Wat. Res. 29(1): 147-153. Yuichi, S., S. Tsuneo, T. Hiroki, Y. Takao. and U.Yoshikuni.. 1992. Single-stage single¬ sludge nitrogen removal by an activated sludge process with cross-flow filtration. Wat. Res. 26(9): 1149-1157. 52 .U)urnal ('1'.'- 1 ibama Academy of Science Vol. 78, No. 1, January 2007 SCIENCE AND THE UNDERSTANDING OF CONSCIOUSNESS Gerard Elfstrom Department of Philosophy, 6080 Haley Center Auburn University Auburn, AL, 36849-5210 Correspondence; elfstga@auburn.edu The study of consciousness has come alive in the past several decades. Researchers are drawn to the area and energized by the belief that they now have the skills and technology to address a problem that has bedeviled humanity for centuries (Koch, 2004, p. 314). Christof Koch formulates the hope nicely. He says, “Science seeks a causal chain of events that leads from neural activity to subjective percept; a theory that accounts for what organisms under what conditions generate subjective feelings, what purposes they serve, and how they came about” (Koch, 2004, p. 326). Despite this optimism, several eommentators assert Koch’s goal can never be achieved. One of them, Stevan Harnad, makes the skepties’ case vividly. He employs an example of free floating anxiety, a conscious state that has arisen without any discernable cause and serves no apparent purpose. He then notes the relations between brain states and the state of anxiety that science can trace: So suppose we find its correlates, the pattern of brain activity that occurs whenever we feel anxious. And suppose we go on to confirm that that brain activity is not only correlated with anxiety, but it causes it in that ( 1 ) it comes before the feeling, (2) if it is present we feel anxiety, (3) if it is absent we do not, and (4) there is no other correlate or cause that we have missed, and (5) we can explain what causes that pattern of brain activity. (Harnad, 2005, p. 56) Harnad is convinced that these correlations, though they indisputably reveal causal relations, will never yield a complete understanding of the relation between brain states and states of consciousness. He asks, “Now, what about the ‘how’? How does a pattern of brain activity generate feeling?. . . It is a question about how feeling itself is generated” (Harnad, 2005, p. 56; see also, Chalmers, 1995, p. 201 and p. 207). Harnad appears to agree that science can achieve Koch’s goal of tracing a causal chain of events leading from brain states to states of consciousness. However, he denies this success will open the way to Koch’s goal of constructing a theory competent to explain this relationship. In the brief letter quoted above, Harnad provides no evidence for his assertion, nor does he explain why he is convinced that science can never devise a theory to fully explain the relation between brain states and states of mind. The difficulty he finds can be characterized in at least three ways. Each will be examined in turn. 53 Elfstom-Science and the Understandinc of Consciousness CAUSAL INCOMPLETENESS Though he seems to agree that science will eventually trace a causal chain which connects brain events to states of mind, it is possible Harnad believes that science will never uncover the complete array of causal steps that connect brain states to states of consciousness. Perhaps he is convinced that the causal chain unearthed by scientific investigation can never be sufficiently detailed to allow a satisfactory theory of the relation between brain states and states of mind. Or, Harnad may believe that some essential links in the causal chain must always lie beyond the reach of science. These are important concerns. If the causal chain available to science must necessarily remain overly coarse or incomplete, researchers will not be able to devise a theory competent to explain the relation between brain states and states of mind. However, it appears that lack of sufficient causal detail poses no difficulty for science. For decades researchers have been able to record the activity of individual neurons (Kandel, 2000, et al., pp. 176—86; Koch, 2004, pp. 28—33; For an intriguing examination of the role of individual neurons in memory, see Quiroga, et al., 2005). There is no reason to believe that science requires finer resolution than is provided by the ability to monitor single neurons. In addition, recent technological advances, including positron emission tomography (PET) and Functional Magnetic Resonance Imaging (fMRl), allow researchers to examine the function of whole living brains (Blackmore, 2004, pp. 228—9). Christof Koch does not yearn for technology with higher resolution than is presently available. Rather, Koch believes that the challenge for research resides in a domain intermediate between single neuron firing and whole brain activity. He hopes for technology to observe tens or hundreds of thousands of neurons at work (Koch, 2004, p. 3 12 and p. 323). Perhaps such technology will always lie outside the reach of science, but there is presently no reason to believe this must be the case. As a result, there is little reason to accept the conclusion that the causal chain accessible to science must remain too coarse to allow complete understanding of the relation between brain states and states of mind. Nonetheless, it remains possible that critically important links in the causal chain must always lurk beyond human reach. The difficulty can be stated as follows: Science can observe chains of physical events in the brain. Under proper conditions, these chains of physical events will result in states of mind. States of mind are presumed to be nonphysical. But, nonphysical states cannot be directly observed by science. Their existence can only be inferred from external observation. Hence, there must be a point at which direct observation halts and the inference of mental activity begins. Since the point at which brain states activate states of mind can never be observed, it may seem reasonable to infer that science can never construct a successful theory to explain the relation between the physical and the mental. However, if lack of direct observation of mental phenomena is the difficulty, it hardly seems insurmountable. In fact, it is no difficulty at all. Much of the fundamental science of the 20"' Century is built on inferences from what can be directly observed to that which cannot be. Subatomic physics is an instructive example. Neutrinos, quarks. 54 Journal of Alabama Academy of Science Vol. 78, No. I, January 2007 pi mesons, and the like will perhaps never be monitored directly. The link between the observable and the unobservable is provided by theories that allow researehers to infer the relations between direetly observed phenomena and unobservable partieles. Henee, in the domain of subatomic physics, the link between the directly and indirectly observable is provided by theory. Obviously, successful theories of subatomie physies have been formulated even though they connect the observable to the unobservable Of course, there may be other reasons why it may be impossible to devise a satisfactory theory of the emergenee of states of eonseiousness from brain states. This possibility opens the way to a second difficulty Harnad may have in mind. It is a problem whieh has been vigorously formulated by the philosopher David Chalmers. CONSCIOUS STATES ARE SIMPLE Chalmers has devoted eonsiderable energy to developing the position that studying brain states can never yield the understanding neeessary to explain the existenee of states of eonseiousness. He insists, “The structure and dynamies of physical processes yield only more structure and dynamies, so structures and funetions are all we ean expeet these processes to explain. The facts about experience eannot be an automatie eonsequence of any physieal aceount, as it is eoneeptually coherent that any given proeess could exist without experienee. Experience may arise from the physical, but it is not entailed by the physieal” (Chalmers, 1995, p. 208). There is a quick and easy response to Chalmers’ elaims, and a longer, more complex rejoinder. Koeh has the quiek and easy response (Koch, 2004, p. 6). He agrees that we presently have no eoncepts able to link physical states to mental experienees. Therefore, Chalmers and others are quite right to insist that eoneeptual analysis will not reveal a connection between brain states and states of consciousness. But Koeh is convineed that this does not mean we can never devise such theories. Doing so is the goal of his research. He forthrightly aeknowledges that his efforts may fail, but he finds no reason to believe they must fail (Koch, 2004, p. 6 and p. 326). For much of human history, we have understood that adding suffieient heat to liquid water will produce steam. However, we had no proven theory able explain this relationship. Our diseovery of the molecular composition of water and the effeets of adding energy to that moleeular strueture allowed eomplete understanding of the process that leads from liquid water to steam*. In similar fashion, the recognition that changes in brain states may eause ehanges of eonseiousness is eomparatively reeent. Nonetheless, we presently have no reason to conelude that a theory that will explain the connection must remain permanently beyond our reaeh. Chalmers, however, believes his argument should be viewed in a different way, and that version requires a more eomplex response. He asserts that the relationship of liquid water to steam is not analogous to that of the relationship of brain states to states of eonseiousness beeause water and steam are both physieal. Brain states and states of consciousness differ beeause states of eonseiousness are not physical (Chalmers, 1995, pp. 8—9). At first glanee, it is not obvious that this distinetion should matter. Though 55 Elfstom-Science and the Understanding of Conseiousness both physical, liquid water and steam have distinct properties. Also, though living and nonliving beings are quite different, educated people are at ease with the train of steps which lead from nonliving matter to life fonns (Fi-y, 2000, pp. 1—8 and pp. 65—78). Chalmers nonetheless insists there is a critically important difference between the cases. Physical things can be analyzed into their elemental constituents, and we can understand how these physical constituents are reconfigured when physical stuff changes from one state to another. For example, we are aware that both liquid water and steam are composed of water molecules, but the molecules have different energy levels in the two states. In the case of nonliving matter and live organisms, Chalmers points out that we have determined that life consists of a series of functions, i.e., metabolism, reproduction, etc., and we can understand how the assemblage of these functions can be performed by nonliving matter (Chalmers, 1995, p. 204 and p. 208). In contrast, our ordinary experience of conscious states prompts us to believe they are not functions and have no structure. They are completely simple, in other words. Hence, they cannot be analyzed into more elemental states. Even if they could be thus dissected, it is possible that any simpler constituents will also be immaterial entities. Furthermore, as the example of free floating anxiety illustrates, it appears that states of consciousness cannot be resolved into an array of functions. Apparently, Chalmers believes we give complete explanations of states of consciousness in terms of physical brain states only by analyzing them into simpler constituents and observing their interaction or by dividing them into an array of functions. In consequence, he believes we will never be able to fully explain the relation between physical states and states of consciousness (Chalmers, 1995, pp. 8-9). If the above reading is correct, Chalmers’ position has shifted. The sticking point is no longer the perceived difference between states of matter and states of mind. Rather, the difficulty is that we experience states of consciousness as simple. Though they may have functions, they are not functions. They appear to have no structure which could be analyzed. Consequently, we will never understand states of consciousness completely in terms of physical constituents. But, if that is the sticking point, the situation is not as hopeless as Chalmers believes. As always, researchers remind us that introspection has often proven an unreliable guide to neurological research (Koch, 2004, p. 316). It is entirely possible that our conception of states of consciousness will change as neurological research progresses. After all, advances in other areas, such as physics, have been accompanied by significant changes in conceptions of space, time, mass, motion, etc. Thomas Nagel believes that the ultimate solution to the problem of the relations between minds and brains must await a revised and deepened conception of consciousness (Nagel, 1998, pp. 337—8). Recent neurological research offers a hint of how this revision may occur. It reveals that even the simplest visual experience is the product of an astonishing array of different neural processes that are parceled out to distinct parts of the brain and occur at varying speeds (Kandel, et al, 2000, pp. 496—500). Hence, one sector of the brain responds to edges, another to colors, another to shape, yet another to contrasts of light and dark. Somehow, 56 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 these strands of neural processing are then united to produce our (apparently) unitary visual experience. The question of how these strands merge into unified experience remains unanswered and is termed the “binding problem” (Kandel, et al, 2000, p. 502; Koch, 2004, p. 43, pp. 167--70 and Blackmore, 2004, pp, 244-8). Hence, contemporary research reveals that our conscious states are not simple even though we experience them as such'. It is entirely possible, though in no way assured, that scientific research will at some point determine how to divide experience into its constituents. These constituents may or may not display consciousness awareness. If they do, it is possible researchers will determine how they arise from nonconscious states. If they do not, researchers may determine how consciousness arises from their combination. At present, we are unable to deny that these are possible outcomes. Nonetheless, Chalmers could well remain unmoved by such advances. He might claim that we are either conscious or not. It doesn’t matter that experience is formed from a variety of constituents, and it doesn't matter that these constituents are somehow bound together. The point is that, once conscious awareness is achieved, it is achieved wholly. Even if the experienced content of consciousness is formed from an array of elements, our conscious awareness either exists or does not. When it exists, it experienced as simple. This is a significant point. But, again, the matter is not as simple as everyday experience seems to indicate. Hospital emergency room workers and anesthesiologists are well aware that there are different types of consciousness and that each is present to varying degrees. Conscious awareness is not simply present or absent. Further, no sharp boundary separates conscious from unconscious states. In some cases, there is no clear agreement on whether a state should be considered conscious or not (Nikolinakos, 1994, pp. 93-100). It is possible Chalmers will be undeterred by this complexity as well. He may well insist that, when consciousness is clearly present, it is simple. It doesn’t matter that we on occasion have difficulty determining whether a particular state is a state of consciousness, and it doesn’t matter that consciousness is present in degrees. The important point is that conscious states are simple and unanalyzable when present. But, once again, Chalmers’ argument butts up against researchers’ observations that introspection has proven a poor guide to the understanding of consciousness. Though our states of consciousness appear simple, it remains possible that they are not. Chalmers may respond that by definition consciousness is what we experience. Hence, it is impossible for us to be mistaken about it. This is a compelling argument. Unfortunately, it is mistaken. As noted earlier, research demonstrates that though experience appears to us to be unitary, it is in fact not so. The very simple visual perception of a coffee cup requires the processing of information about color, boundary, shape, texture, and location. Information about these matters is processed in different domains of the brain, and the processing occurs at different rates. Researchers are presently at a loss to explain how we experience these things as unitary. Another line of research has shown that blind people commonly use echolocation to navigate. However, they describe the experience as feeling pressure on their faces rather than as an auditory response (Schwitzgebel and Gordon, 2000). 57 Elfstom-Science and the Understanding of Consciousness Nonetheless, let us suppose Chalmers’ claim that experience is simple and unitary is correct. Would this demonstrate that no theory can be devised to explain how states of mind arise from states of matter? This is a plausible claim, but is it correct? Given his remarks, it appears that Chalmers is most concerned to refute reductionism, the view that mental states can be analyzed into physical brain processes. However, if this is Chalmers’ concern, there is little reason to believe that researchers in the area, such as Koch, would disagree. The question, then, is, “If conscious states are unanalyzable, is it impossible to explain them in terms of the activity of brain states?” Apparently, Chalmers believes this to be the case. He is convinced that researchers can, at best, concoct “bridge principles” which will correlate states of consciousness to brain states (Chalmers, 1995, p. 10). However, the ultimate constituents of the universe such as electrons, photons, quarks, etc. are also simple in the way Chalmers believes consciousness to be. That is, they are without internal structure and are not functions (Greene, 1999, p. 124)-. Nonetheless, under proper circumstances, photons, the elemental units of electromagnetic force, can become electrons, elemental units of matter, and electrons may become photons (Greene, 1999, pp. 158—60). What is more, science has an elegant and profound explanation of these transformations, Einstein’s formulation of the equivalence of matter and energy (Greene, 1999, pp. 51—2 and p. 120). Thus, in the physical sciences it is possible to provide explanations of the ways in which simple entities can be created, transformed, and destroyed. As a result, it is apparent that the simplicity of states of consciousness does not debar a convincing explanation of their relationship to brain states. At this point, scientists such as Koch seek only to trace out the complete story of the causal connections between states of consciousness and brain states. Harnad is entirely correct to insist that examining this causal chain will not automatically yield a theory of the relation between brain states and states of consciousness. But, as in all other fundamental theories, from Copernicus’ theory of planetary motion to Bohr’s quantum mechanics, successful theory is not simply read from the data. Rather, it must result from human thought and insight. These tasks may prove simpler if, as Nagel believes, future research prompts us to revise our conception of consciousness. As always, there is no guarantee that examination of the causal chain will yield a viable theory, but the possibility cannot be ruled out simply by claiming that states of consciousness are completely simple. THIRD PERSON ACCOUNTS OF FIRST PERSON EXPERIENCE A third possibility is that Harnad is convinced science will never be able to devise a successful third-person account of our first-hand experience of conscious awareness? In an earlier exchange, Harnad comments, “In the special case of mind we are instead trying to replace SUBJECTIVITY ITSELF by something OTHER than subjectivity, appearances by something other than appearances” (Harnad, 1993, p. 15). It appears that Harnad believes that a successful theory of consciousness must somehow capture the essence of subjectivity. However, according to one philosopher consciousness is completely transparent (Moore, 1 903, p. 450)^. The state of consciousness is invisible even to the conscious subject. Thus, 58 Journal of Alabama Academy of Science Vol. 78, No. I , January 2007 to grasp a conscious subject’s experience, researchers must aim to fathom the contents of conscious states. That is, they, as external observers, must understand exactly what a conscious experimental subjeet feels. Of eourse, it is unclear how this might be achieved. As it happens, several authors have formulated this challenge to scientific inquiry in detail. Thomas Nagel has recently asserted that the ultimate goal of a scientific theory of eonsciousness is to give genuine eontent to the statement, “That’s what the experience of tasting ehoeolate looks like from the outside” (Nagel, 1998, p. 337). This opens the possibility that seience will allow us to determine the precise array of sensations a research subject is experiencing simply by scanning monitors of physical brain activity^ It appears that scienee ean meet Nagel’s challenge without particular difficulty. It seems likely that scienee will at some point be able to precisely determine which arrays of neurons become active whenever we have a particular sensation, and it will also be able to precisely eorrelate that neural aetivity with the different elements of an experienee that we perceive as unitary. In addition, scienee may aequire the ability to aecLirately predict the exaet eonstituents of our sensations when particular neural networks beeome aetive. At that point, scienee would indeed have the means to reveal to Professor Nagel exaetly how ehoeolate tastes from the outside. It could, in other words, present him with the entire array of sensations he would have were he tasting chocolate. As it happens, a beautiful bit of science gives an example of how this effort might proceed. “What the frog’s eye tells the frog’s brain,” first published in 1959, records the types of information a frog’s retinal neurons eonvey to its brain. The researchers conclude, “The output from the retina of the frog is a set of four distributed operations of the visual image. These operations are independent of the level of general illumination and express the image in terms of 1 ) local sharp edges and contrast, 2) the eurvature of edge of a dark objeet, 3) the movement of edges, and 4) the local dimmings produced by movement or rapid general darkening” (Lettvin, et al., 1959, p. 1950). The authors are pleased to label this array a “bug deteetor” (Lettvin, et al., 1959, p. 1951). It is reasonable to believe that seientists may eventually be able to map the output of each type of frog neuron, determine what each registers, and diseover the ways in which these signals eombine in the frog’s experience. Should that be aehieved, it seems entirely sensible to claim we would be able to fathom the entire content of a frog’s consciousness at any instant*’. In that event, scientists would have met Nagel’s ehallenge of grasping the contents of a particular conscious state from the outside, as least with regard to the frog, if not with the taste of chocolate. It is probable that Harnad will be dissatisfied with this idea and may express his dissatisfaetion in two ways. First, he is likely to note that these studies will be based on eorrelations only, so they eannot meet the challenge he posed initially. However, if the challenge is understood as the ehallenge of describing the essence of subjectivity, and if that is understood in turn as understanding the eontents of someone’s consciousness from the outside, then Hamad’s dissatisfaction is beside the point. If his challenge has been correctly formulated above, then it has been met. However, Hamad’s dissatisfaction may take a different and more probing form. 59 Elfstom-Science and the Understanding of Consciousness He may well note that, when Lettvin, et al., 1959, move convex shapes across a screen and record that certain frog neurons fire, the human researchers are recording what they experience. Human eyes perceive the movement of convex shapes, but the frog may experience something entirely different. The researchers have no way to determine exactly what the frog experiences. That is a limitation of relying on causal correlations only. This difficulty is important, but it is not insurmountable. Scientists have long understood that analogy is a powerful instrument for extending human knowledge. After all, the foundation of any individual’s belief that his or her fellow human beings possess conscious experience is the conviction that they are relevantly like him or her. Hence, to determine whether the frog’s experience is similar to ours, researchers would have to determine whether frog neurons devoted to visual perception and their neural circuits resemble ours. If they differ, researchers could examine the ways in which they differ, attempt to determine whether they are likely to alter the frog’s perceptual experience, and, if so, what the difference is likely to be. On the assumption that similar structures retain similar functions across evolution, researchers would have considerable justification for presuming the resulting experience was similar. Certainly, there would be little evidence to support a conclusion that the frog’s experience differed. A different line of argument yields a similar conclusion. It is reasonable to presume that there is a significant evolutionary advantage in perceiving the world as it genuinely is. There are objective measures for shape, contrast of light and dark, etc, so it is likely these are aspects of the world as it is. Hence, there is support for the conclusion that both humans and frogs experience the world as it is. However, Lettvin, et al., 1959, also have good reason to believe that the frog’s experience is quite distinct from our own in certain ways. The evidence of their research supports the view that the frog experiences only several abstracted features of moving insects and not the complete array of features we are able to experience. So, neural research is able to reveal the ways in which our experience and that of frogs are alike and ways in which they differ. But, frogs are not human beings, and human conscious states are vastly more complex than those of frogs^ We can ask whether it may be possible to canvass the conscious states of human beings. There is evidence to support the hope that such a prospect exists. At present, researchers can determine whieh single neurons hold the memory of a particular face (Quiroga, et al., 2005). At some point, they may very possibly be able to determine exactly how individual memories are encoded in single neurons and how networks of neurons work to retain the memory. Once this information is in hand, not merely for individual faces but for all memories and the entire array of sensations an individual is experiencing from instant to instant, researchers should be well equipped to determine the contents of an individual’s thoughts from the outside — assuming appropriate detection apparatus is available. It will obviously be extremely diffieult to gain all this information, and the effort may require many decades, but there is presently no reason to believe it will never be achieved. In consequence, it appears that there are ample resources for assuaging Hamad’s dissatisfaction. This is not the end of the difficulty posed by subjectivity. Some years ago, Nagel 60 Journal of Alabama Academy of Science Vol. 78, No. 1, January 2007 issued a more probing challenge. In his famous artiele “What Is It Like to Be A Bat?,” Nagel argued that no matter how much knowledge of a bat’s brain we amass, we will never be able to understand the kinds of experienees the bat has in the way it has them — assuming it has phenomenal consciousness rather than bare aceess eonsciousness. “I have said that the essence of the belief that bats have experienee is that there is something that it is like to be a bat.... But bat sonar, though clearly a form of perception, is not similar in its operation to any sense that we possess, and there is no reason to suppose that it is subjectively like anything we can experience or imagine” [emphasis added] (Nagel, 1979, p. 168). In this formulation, Nagel's concern is that we can never come to scientific terms with conscious states that we have reason to believe are highly dissimilar to any we personally have experienced. The critically important point is that he believes that the experience of the bat is so radically different from ours that we are unable employ the tool of analogy to examine it. Philosopher Frank Jackson in “What Mary Didn’t Know” concocts an argument akin to Nagel’s early challenge. Jackson is not immediately concerned with the relation of brain states to conscious states. Rather, he is eager to demonstrate that the universe is not eomposed of physical stuff only. Fie constructs a science fietion scenario in which a scientist, Mary, matures and is edueated in an enclosed space without experience of colors other than black and white^ Jackson postulates that she could master all available scientific information regarding the nature of color and color vision. However, he is convinced that, if she were then exposed to a color, such as red, she would agree that she had learned something novel, namely, what the sensation of redness is like. Jackson asserts she eould never have learned this from studying the scientific literature of the physical nature of colors and the processes of color vision. He is satisfied this demonstrates that the examination of physieal stuff eannot reveal the entirety of what exists — assuming that seienee ean examine physical stuff only (Jackson, 1982). Jackson’s position is obviously relevant to the endeavors of consciousness researchers. No matter how thoroughly scientists delineate the structure and funetion of neural cells, Jackson believes their studies will never reveal what experience is genuinely like. For the sake of clarity, it is worth pausing to note that Nagel and Jackson do not claim that a successful theory of consciousness must give us the sensations associated with the experience of the eolor red. This ean be ruled out quickly, since no theory could achieve that. Jackson does not wish his claims to be eonstrued in this way, since he allows that Mary, on being exposed to the eolor red, may respond, “Aha, that’s what I thought it would be like” — apparently based on her scientific studies (Jackson, 1986, p 291 ). Jackson believes she will not give this report but instead will say, “So, that’s what red is like.” So, he is claiming that a successful theory must allow us to determine exactly what Mary’s sensation of red would be like, though it would not create that sensation in us. And, of eourse, it is difficult to imagine how a theory could accomplish this. Taken together, Nagel and Jackson are asserting there are at least two domains of eonsciousness that lie beyond the reach of analogy — and therefore of scientifie understanding. The first ineludes creatures whose sensory apparatus seems vastly different 61 Elfstom-Science and the Understanding of Conseiousness from ours. The second is the realm of sensations which we have not experienced — such as the case of the scientist Mary or creatures whose range of vision, hearing, smell, or touch extends far beyond ours. Dogs, for an obvious instance, experience sounds and smells that are far beyond the sensitivity of human sensory apparatus. Also, some insects are capable of experiencing light which is far outside the frequencies available to human vision. But, it is appropriate to ask whether these sensations are genuinely beyond the reach of analogy. It is possible, for example, that the machinery of bat sonar is closely akin to the sensory apparatus of quite different creatures, and this similarity may suffice to allow us to grasp their experience. As it happens, there is evidence that whales and dolphins also employ echolocation. More to the point, there is considerable evidence that blind human beings employ echolocation. Furthermore, studies demonstrate that humans with normal vision can be trained to employ echolocation (Schwitzgebel and Gordon, 2000). In retrospect, this should not surprise. Evolution is conservative. Abilities that prove useful to one species are likely to appear in other species as well. Of course, Nagel may be undeterred by this result. He may assert that, though humans can also employ echolocation, it is quite possible that the human experience of echolocation is quite different from that of the bat. However, it is probable that the bat's sensory machinery emerged as a version of that employed by other creatures. Certainly, neither Nagel nor we can rule this out of the realm of possibility. Further, by noticing the precise ways in which a bat’s brain processes this information, which areas of the brain are employed and which neural connections are present, we may well gain additional insight into the bat’s sonar experience. But, Nagel may be quick to note that the above claims can prove only that his example of echolocation was unfortunate. It remains possible that other modes of sensation or other sensations lurk beyond the reach of human experience and therefore of scientific understanding via analogy. That is the point of Frank Jackson’s example of the scientist Mary. Jackson’s example is particularly difficult for consciousness researchers because it appears that human beings have no way to understand what simple sensations are like without experiencing them. Complex sensations, like the taste of chocolate or of wine, can be analyzed into their constituent sensations. If those simple constituent sensations are similar to those the researcher has experienced, the scientist will understand the nature of the complex sensation. This would be similar to an account provided by a wine reviewer. A wine reviewer will seek to give readers a sense of how a particular wine will taste by giving an account of the various flavors that a particular wine offers. In the case of simple sensations, however, no such analysis is possible. So, if the researcher has not experienced it. he or she has no way to determine what a particular simple sensation is like. Thus, Frank Jackson claimed the color red would be unfathomable for Mary prior to her experience of it. But, we can nonetheless ask whether such alien, but simple, sensations are genuinely beyond the reach of analogy. To focus our reflection, we can employ the example of canine hearing, since no human being is able to experience the high pitched sounds that 62 Journal of Alabama Academy of Science Vol. 78, No. 1 , January 2007 dogs can hear. Researchers know that dogs are able to sense extremely high pitehed sounds because dogs react to these sounds, but human beings do not. There are at least four strategies researchers might employ to gain a sense of the canine experience of high pitched sounds. For one thing, it is possible scientists will discover that differing species will have similar experiences at common points in their range of hearing, so that sounds near the upper limit of human hearing will be experienced in the same way as sounds near the upper limit of canine hearing. In addition, it is possible that careful analysis of the mechanics of processing sound waves will yield insight into the way in which particular sounds are experienced. Additional insight may be gained from the fact that the range of human hearing contracts with age. Young people are able to hear sounds of far higher pitches than older people (For an amusing example of one eonsequence of this difference, see Vitello, 2006.). This would allow researchers to compare the descriptions young people offer of high pitched sounds with the descriptions older people provide of sounds near the upper limit of what they are able to hear. Researchers who compare and contrast these reports and correlate them with the physiology of hearing of people who possess differing ranges of hearing may then be able to devise theories that will enable them to determine the sensations of other species and correlate them with the sensations of human beings. Lastly, based on their studies of the physiology of hearing and eomparative analysis of the hearing ranges of human beings of differing ages, researchers may be able to construct devices able to produce sounds analogous to those experienced by other species. It is entirely true that none of these techniques will yield certain knowledge of the experience of other species or of individuals with different ranges of sensation than our own. Nonetheless, a reasonable degree of probability is commonly sufficient for the needs of science. Also, eaeh of us has no more than reasonable probability of understanding what other human beings are experiencing, yet we are often confident that we know their moods and sensations. Any conscientious researcher will hasten to note that the approaehes listed above may fail or prove inadequate. Nonetheless, there is presently little reason to believe they must in principle fail, and there is little reason to believe it will never be possible to devise other methods as our understanding inereases. This conclusion applies to the present time. It is possible that in the future researchers will uneover significant reasons to conclude we can never become aware of the sensory experience of other creatures, but we have no such information at present. In sum, there are reasons to remain confident that science will continue to successfully employ analogy and a more sophisticated understanding of the function of neural machinery to further our grasp of the conseious experience of other beings. The preeeding does not demonstrate that seience will overcome the ehallenges of discerning the complete chain of causal connections that lead from brain states to states of awareness or of devising an adequate theory of the relation between brain states and states of awareness. This essay only supports the conclusion that there is presently no reason to believe that science is doomed to fail in this endeavor. 63 Elfstom-Science and the Understanding of Consciousness LITERATURE CITED Blackmore, S. 2004. Consciousness; An Introduction. Oxford University, New York, New York, USA. Block, N. 1995. On a Confusion about a Function of Consciousness. Behavioral and Brain Sciences. 18; 227—87. Chalmers, D. 1995. Facing Up to the Problem of Consciousness. Journal of Consciousness Studies. 3; 200-219. Fry, 1. 2000. The Emergence of Life on Earth. Rutgers University Press, New Brunswick, New Jersey, USA. Greene, B. 1999. The Elegant Universe. Vintage Books, New York, New York, USA. Harnad, S. 1993. Discussion (passim) In; Bock, Gram & Marsh, J. (Eds.) Experimental and Theoretical Studies of Consciousness. 15. CIBA Foundation Symposium 1 74. Wiley. Chichester, UK. 2005. Letter to the editor. The New York Review of Books. 1 1 ; 56. Jackson, F. 1982. Epiphenomenal Qualia. Philosophical Quarterly. 32. 127—136 1986. What Mary Didn’t Know. Journal of Philosophy. 83; 291—95. Koch, C. 2004. The Quest for Consciousness. Roberts and Company, Englewood. Colorado, USA. Kandel, E. R., J. H. Schwartz, and T. M. Jessell. 2000. Principles of Neural Science. McGraw-Hill, New York, New York, USA. Lettvin, J.Y., H. R. Maturana, W. S. McCulloch, and W. H. Pitts. 1959. What the Frog’s Eye Tells the Frog’s Brain. Proceedings of the Institute of Radio Engineering. 47; 1940-1951. Moore, G.E. 1903. The Refutation of Idealism. Mind. 12; 433—53. Nagel, T. 1979. What is it like to be a bat? In T. Nagel, Mortal Questions. 165—80. Cambridge University Press, Cambridge, UK.. 1998. Conceiving the Impossible and the Mind-Body Problem. Philosophy. 285; 337-352. Nikolinakos, D. 1994. General Anesthesia, Consciousness, and the Skeptical Challenge. The Journal of Philosophy. 91; 88—104. Quiroga, R. Quian, L. Reddy, G. Krieman, C. Koch, and I. Fried. 2005. Invariant visual representation by single neurons in the human brain. Nature. 435; 1 102—07. Schwitzgebel, E. and M. Gordon. 2000. How Well Do We Know Our Own Conscious Experience? The Case of Human Echolocation. Philosophical Topics. 28; 235— 246. Vitello, P. 2006 (Published June 10, 2006). A Ring Tone Meant to Fall on Deaf Ears. The New York Times. A 1 . 64 Journal of Alabama Academy of Science Vol. 78, No. I , January 2007 ' Though Chalmers explicitly states that states of consciousness are complex, he does not reveal the way in which he believes they are complex (Chalmers, 1995. p. 21 1). If he means only that the contents of our conscious states are complex, the point has no relevance to the present discussion. If, however, he means to assert that conscious states are complex, then his claim that states of consciousness have no structure becomes mysterious. ' Of course, if string theory is correct, these entities are actually minute strings, existing at the Plank Length, vibrating in distinctive ways (Greene, 1999. pp. 13—4). If this view is correct, subatomic particles, though scientists presently believe they are simple, are not what they appear to be. Nonetheless, string theory remains hotly contested, and the final story of the ultimate nature of fundamental entities may be quite different. Ned Block points out the difference between ‘access consciousness’ and ‘phenomenal consciousness’ (Block, 1995). Our senses continually provide us with a stream of data necessary for ordinary function. For example, to stand erect we need a vast array of information about the configuration of our body and the relative position of our limbs. Without this information, we cannot maintain a standing posture. However, we are generally unaware of this information unless something goes awry. Also, when driving, we contrive to remain in the center of the right lane, maintain constant speed, and negotiate curves in the road while being engrossed in other matters. So, we must employ visual and tactile information to stay on course and avoid mishap, but we are typically unaware of it. These sensations are part of ‘access consciousness’. They are available to us, but we are generally unaware of them. But, if we step into a rut or notice brake lights flashing in front of us, we immediately focus our attention on these data streams, and they enter into ‘phenomenal consciousness’. The difficulties that concern Harnad are those of ‘phenomenal consciousness’, the sensory data that enters into our awareness. ■^As Moore says, “When we try to introspect the sensation of blue, all we can see is the blue: the other element is as if it were diaphanous” (Moore, 1 903, p. 450). Researchers would not be able to observe these conscious states directly. Rather, directly observed data, coupled with a theory of the sort Nagel envisages, would allow inferences about the experimental subject’s conscious experience. ^This presumes that the frog has experience in Block’s sense of phenomenal consciousness. It is entirely possible the frog does not have experience of this sort, but has access consciousness only. A number of studies have shown that experimental subjects must receive a stimulus for about lA second to have phenomenal consciousness (Koch, 2004, 205—16). They nonetheless have access consciousness because they are able to react to the stimulus even though they have no experience consciousness of it. Koch believes there is a simple explanation for the difference. Actions that require an exceedingly quick response would not enter phenomenal consciousness and need not do so. Responses that benefit from greater flexibility or a time lapse between stimulus and response enter phenomenal consciousness, Koch speculates. Hence, as a practical matter, Koch presumes that responses that occur only after some delay require phenomenal consciousness (Koch, 2004, 1 1—2). Since the frog must react very quickly to make its 65 Elfstom-Science and the Understanding of Consciousness living catching flies, it is likely it lacks conscious awareness of its actions. The research of Lettvin, et ah, 1959, demonstrates that frogs’ neurons respond to sharp edges and contrast, the curvature of an edge, the movement of an edge, and local dimmings. Taken together, these do not construct an image of a fly. This latter point is driven home by the additional observation that it is easy to fool frogs by dangling small objects in their field of vision. (Lettvin, et al., p. 1941 ). Humans, on the other hand, have a far richer experience of flies. We are able to distinguish flies from other insects and from small objects. We think of them as having segmented bodies, and we are aware of the distinctive motions of their various body parts. To be sure, processing all this information requires considerable time, and that is part of the explanation of why we are unable to catch flies with our tongues. ** This example requires suspension of disbelief, since Mary’s body would not be black and white, and it would be exceedingly difficult to contrive black and white food only. Nonetheless, this difficulty does not undermine the force of the example, since it is designed only to make vivid the claim that Maiy could not genuinely comprehend a sensation which she had not experienced. 66 Reports from the October 2006 Executive Committee Meeting Samford University Birmingham Alabama By James R. Rayburn, Secretary Call to Order Officer Reports (B) 1 . Board of Trustees, Eugene Omasta Members of the Board of Trustees of the Academy remain active in the affairs of the Academy including participation at the spring and fall Executive Committee meetings and serving on committees of the Academy. The trustees meet annually with the elected officers of the Academy and members of the Budget and finance Committee at a luncheon during the annual meeting. 2. President, David Nelson 1. Committee Structure: Since the AAS Constitution specifies that the First Vice-President (President elect) will appoint chairs and members to all committees, 1 first became familiar with the entire committee structure of AAS just last year. The appointment task is a significant one that necessitates effective participation of many other members of the academy. Nobody is aware of the diverse abilities of all academy members, or even knows the entire membership. Doubtlessly, many willing and interested people within the academy are never approached. 1 would encourage the AAS officers and membership routinely to refer the names of potential nominees to the first Vice-President, so that he / she can appoint members who are interested and enthusiastic. There are some committees that never meet or do anything. These committees probably need new members to be appointed. 1 have frequently contacted sectional chairmen to solicit the names of potential committee members. For the AAS to remain a strong, effective, and viable organization, we need to have broad representation of competent scientists from a diversity of institutions and geographic regions. In the future, let us all contribute the names of nominees whom we would like to recommend to the First Vice-President. 2. Although the Auditing Committees have not been functional for several years, I filled the positions for these two committees. 67 Senior Academy: Sergey Belyi (2007) Mathematics, Troy Robert Angus (2007) Biology, UAB Junior Academy: Henry Barwood (2007) Mathematics and Physics, Troy Govind Menon (2007) Mathematics and Physics, Troy Hopefully they can review the financial records of the AAS and AJAS sometime during the spring meeting at Tuskegee. The schedule will need to be coordinated with the respective treasurers (AAS and AJAS). 3. Present vacancies on AAS Committees for which we need members: Committee on Research ( 1 vacancy) Committee on Place and Date of Meeting (3 vacancies) Committee on Public Relations (staggered 4-year terms) ( 1 vacancy- must be past president) Resolutions Committee ( 1 vacancy) Mason Scholarship Committee ( 1 vacancy) Committee on Development (not active, reactivate?) Presently there is no Committee Description for the Resolutions Committee in the AAS Constitution and By-laws. Should we authorize such a description to be formulated and considered in the future? 4. During the AAS Executive Committee Meeting on 1 5 March 2006 at Troy University, Larry Davenport (in the Presidential Report) proposed that the academy solicit patrons for the Journal of the Alabama Academy of Science, at a cost of $500 per 'A page space in the journal. Members were encouraged to pursue potential patrons: Alabama Power Co, Thompson/Cole, etc. . .We need to continue to pursue potentially interested organizations. 5. Kenneth R. Sundberg from Troy University submitted a refund check payable to the AAS for $ 5,758. 1 9. It represents a refund of the account for local arrangements from last year’s spring meeting at Troy University. Receipts there totaled $ 12,588.00; expenses were $ 6,829.8 1 . The balance was refunded to AAS in the check, which has been given to our treasurer, Taba Hammisou (JSU). 6. Proposed Symposium 2007 (Friday morning at the Tuskegee Meeting): ‘‘HURRICANE IMPACTS ALONG THE GULF COAST” (Tentative) Meteorology - Keith Blackwell (USA)? Engineering - Scott Douglass (USA) CANCELLED Sociology - Steve Picon (USA) CANCELLED 68 Biology - John Dindo(DlSL) Biology- John Valentine (DISL) Nursing - Eriea Prior & Pam Autrey (UAB) Environmental Policy & Int'ormation Center Pete Conroy (JSU)? (Other Potential Speakers Pending) 3. President Eleet, George Cline 1 have been working with the President to find people to fill committees. We also have discussed the process of filling the various committees. Assisted in discussions regarding the Symposium and the Banquet Speaker. Ellen Buckner and I did the site visit to Tuskegee University in preparation for the Spring Meetings. We examined the facilities, and we discussed the location for the Junior Academy meetings. Everything appears to be on track for the meetings 28 Eeb- 2 March. One source of concern is the availability of laptops and projectors. Spoke with Ken Roblee about 2"'' VP duties and discussed nominations for the Board of Trustees. Will continue these discussions through the year. 4. Second Vice-President, Kenneth Roblee No Written report submitted. 5. Secretary, James Rayburn 1 . 1 formatted the reports and minutes from the March meetings as requested by the Editor to be published in the Journal in June. I was concerned about publishing the minutes before we met in October to review them. (The reason this happened is that the journal is catching up in its publication date). 1 sent an email requesting approval as Earry Krannich suggested. Is this how we are going to approve minutes from now on? 2. I provided 3 sets labels including 2005 (not paid 2006) and 2006 memberships to Sue Bradley for mailing the Journal. 3. 1 provided Excel worksheets of not paid members to Mark Meade in June 2006. 4. In October 1 sent reminders to current members reminding them to pay dues for next year. I am preparing two more mailing one for November and January 07. 5. One of our members recently died, Shawn B. Allin of Spring Hill. 6. Our current membership is 276 members including Eibraries and others. 7. We have 1 17 Active members (30% paid for 2007), 13 Emeritus (60% paid for 2007), 65 Lifetime, 44 Student (16% paid for 2007) and 37 other members. 8. If current membership stays stable we can expect $3,065.00 more in dues. We have already received $1,025.00 in dues for 2007. Last year dues for 2006 totaled $5,290.00 69 Membership Breakdown AAS October 22, 2006 Paid membef^ through 2007 as of October 22 2006 ' # of members « paid 2007 1.. 1 1.1 : Active 1 1 7 I Emeritus 13 Lifetime 65 i ' ■' Student 44 Other 37 1 - Active Emeiitus Lifetime Student Other Type of member 6, Treasurer, Mijitaba Hamissou: Beginning Balance (03-14-2006) $ 1,780.31 A. Income April Membership 2,110.00 Science Fair 5,736.25 Mason 5.00 May Membership 415.00 Journal support 128.70 AAS Journal (pub. Income) 200.00 Membership/interest/others 282.17 June 2006 Science Fair 8,502.00 July Money transfer to Compass 4,523.20 August 2006 Science Fair 916.00 Membership Journal support 100.00 September/October Membership 340.00 Royalty 83.91 Journal Other Total Income $24,815.25 B. Expenses March 15/ApriI Partial 2006 meeting expenses 612.00 Gorgas/Mason scholarships/travel grants 1375.00 70 Bank charges .IASS expenses Honoraria May Honorarium Scienee fair June Science Fair July JAS Honorarium Honorarium Mason Scholarship Gorgas travel August Honorarium .lournal Sept. / October Honorarium Scholarship JAS supplement Mailing Total expenses this quarter 1 13.00 1,275.00 350.00 350.00 5,012.50 9,000.00 1,250.00 700.00 1,000.00 1,823.20 350.00 114.00 350.00 750.00 30.38 78.00 $24,533.08 The Academy Financial trend March 15, 2006 - October 15, 2006 March 15, 2006 cd ( 1 ) + cd(2) +cd(3) $56,051.17 Saving account $1,258.60 Money Market Cheeking aceount (per statement) Total assets all accounts (03/06) $2,072.04 $1,780.31 $61,162.12 October 20, 2006 cd( 1 ) + cd(2) +cd(3) + cd(4)* $56,560.38 Saving account Money Market $1,259.50 $2,833.36 Cheeking aceount (as of Oct. 20) Current assets all accounts (010/20/06) (*) New cd purchased $791.05 $61,444.29 71 7. Journal Editor, Safaa Al-Hamdani • April issue of the volume 77 has been released successfully. • July and October issue of volume 77 is in the process of completion. • 1 would like to suggest that the abstract should be submitted electronically to one location. The abstract should be written following specific criteria to standardize for publication. • Miss Sue Bradley has resigned from her responsibilities. I have selected a local replacement. • The journal style and manuscript organization has improved • following specific standardized criteria. • Instructions to the author have been revised. 8. Counselor to AJAS, B.J. Bateman 2006 Annual Report of the Alabama Junior Academy of Science and the Junior Science and Humanities Symposium State Officers/Counselors Meeting The State Officers and the State Counselors met at the Birmingham Southern College to discuss the State Officer’s roles for the upcoming year (2005-2006). Fall AAS Executive Meeting The State Counselor (B. J. Bateman) was unable to attend the Fall Executive Meeting. Annual Meeting: The 2006 Annual Meeting, like all previous meetings of AJAS, was shared jointly with the Alabama Academy of Science. The host institution was Troy University. Ken Sundburg was the local arrangements for the AJAS, B. J. Bateman, Counselor to the AJAS, and Wanda PhiHips and Henry Barwood, Associate Counselors, planned registration procedures, space needs, and arrangements for the AJAS-JSHS social and banquet. Registration was held at the Hampton Inn. Highlights of the program were: (1) Paper Competition - The paper competition was conducted on Friday morning in McCall Hall. Rahul Goli was chosen to be the overall winner and would therefore represent Alabama in national competition held at Albekerque NM. The other four state winners (Omar Ahmed, Eacy Casteel, Marshal Everett, and Paige Poole) and Einda Kanipe. (2) Banquet - More than One hundred students, teachers, university professors, and members of business, industry and government shared the Friday night banquet. A major part of the after-dinner program was the recognition of the first and second- place winners of the paper competition, and other competitions 72 (3) Business Meeting - The customary AJAS business meeting was held on Saturday morning. This provided a time for awarding a plaque to the outstanding region, a certificate and a check to the outstanding teacher(s), and other awards. Winners and Awards 2006 ‘‘‘'Best with the Least” Biological Sciences Eibby Swift The Altamont School Engineering Christina Carroll Brooks High School Humanities Diana Patterson JC IB Physical Science Meridith Daniels Brooks High School Second Place Biological Sciences Einnea Pepper JCIB Engineering Brandon Kirkland JCIB Humanities Diana Patterson JCIB Physical Science Ray Smith JCIB First Place Biological Sciences Rahut Go 11 The Altamont School Engineering Omar Ahmed Elorence High School Humanities Marshal Everett Shoals Christian School Mathematics Paige Poote JCIB Physical Science Eacy Casteel Brooks High School Research Grant Award Meredith Daniels $109.00 AAAS Award Outstanding Teacher Award Vlckf Farina Outstanding Region Northwest Newly elected officers for 2006-2007: President Meredith Daniels Brooks High School Vice-President Brittney Daniels Brooks High School Treasurer Omar Ahmed Florence High School Secretary Eiz Raballais Florence High School Event Coordinator Chris Pjare JCIB School 73 JSHS Participants Attending the Annual Meeting 46 students, sponsors, and counselors attended the annual meeting as JSHS participants. Students Brandon Kirkland Diana Patterson Paige Poole Chris Phare Ray Smith Linn Trann Emily Smith Ashley Cockrell Sarah Erling Linnea Pepper Melisa Smith JCIB Will Me Wane Eibby Swift Rahul Goti The Altamont School Meredith Daniels Brittney Bradford Christina Carroll Eacy Casteel Jessica Swinea Brooks High School Eiz Raballais Florence High School Lauern Bradfod Lacy Casteel Marshall Everett Omar Ahmed Jennifer Taylor President Seeretary Shoals Christian Sehool Treasurer Vice President 74 Adults Billy Sanders Assistant to the Counselor Gene Omasta Assistant to the Counselor Wanda Phillips Associate Counselor B. J. Bateman Counselor Linda Kanipe Northwest Regional Counselor Henry Barwood Associate Counselor Vicki Farina Brooks Catherine Shields Central Region Counselor Conrad Smith JCIB Thersa Smith JCIB Rita Phare JCIB Robert Phare JCIB JacqJen Poole JCIB Bobby Patterson JCIB Randy Kirkland JCIB Doreen Pepper JCIB Susie Bradford Brooks Donna Casteel Brooks High School Joan Lee Florence High School PamTaylor Florence High School _ Rafeeq Ahmed _ _ Florence High School _ 9. Science Fair Coordinator, Virginia Valardi No Written report submitted. 10. Science Olympiad Coordinator, Jane Nall Perhaps still the best kept secret in the State, many volunteers of Alabama Science Olympiad provide students the opportunity to participate and compete in Science Olympiad. Teachers, parents, coaches, bus drivers, university professors, university work study students, and other volunteers work to provide the students of Alabama the joys of “doing science” in an arena resembling athletic tournaments. Herculean efforts are made each year by staff and volunteers on several university campuses, and teachers, parents, and students of over 200 public and private schools, so they might experience the Joys and thrills of doing lab hands-on science. Placing 10"’ in the nation for membership, Alabama Science Olympiad continues to grow in numbers of teams and participation at all levels. For several years now, because of the number of teams registering in Alabama, two teams in both Division B (grades 6-9) and Division C (grades 9-12) have advanced to the national competition following successfully winning at regional and the state tournaments. Only the top ten states in membership receive the second invitation at the secondary level to compete at the national tournament. The elementary levels compete at various local and regional tournaments. 75 The University of West Alabama, Jacksonville High School and Auburn University host an A2 tournament (grades 4-6) and report they have a great time, and they are already planning this year’s tournaments. There will be five regional C tournaments and four regional B tournaments. We really need at least one more B host! State Alabama B will be held at Huntingdon College and Alabama C will be on the campus of Samford University in April. Science Olympiad events address the National Standards for Science Education and comprise all areas of science including astronomy, meteorology, experimental design, genetics, anatomy, process skills for life science and biology, chemistry and polymers, physics, earth science and fossils, and water quality and the environment, map skills, CIS and remote sensing as well as building events such as a Rube Golberg-like device, robot, bottle rocket, plane, bridge and tower building, musical instruments. Alternating events in taxonomy include topics of trees, amphibians and reptiles, birds, insects. Director Nall is in search of more universities willing to host tournaments! Consider showcasing your campus and join us in the fun! The State Director is appointed by the Alabama Academy of Science. To date Alabama has been lead by two directors - 1985- 1996 Mr. Steven Carey, University of Mobile and 1997-present Ms. Jane Nall, Spanish Fort High School and the University of Mobile. 11. Counselor to AAAS, Steve Watts The annual meeting for the AAAS affiliates convened on February 15-19, 2007 in San Francisco, California.. All state Academies maintain an association with the American Association for the Advancement of Science. We are members of the Section on Agriculture, Food and Renewable Resources and the Section on General Interest in Science and Engineering. The theme of this years meeting “Science and Technology for Sustainable Well-Being” brings together provocative thinkers and decision-makers for a wide range of symposia, plenary lectures, topical lectures, seminars, presidential tracks, and other sessions that address global and national issues in health, energy, the environment, economic development, education, terrorism, science frontiers, and more. We welcome the opportunity for any AAS member to attend the AAAS meeting on our behalf Information about the AAAS can be obtained at www.aaasmeeting.org. 12. Section Officers I. Biological Sciences, Brian Burnes No Written report submitted. II. Chemistry, Houston Byrd No written report submitted 76 III. Geology & Earth Sciences, Mark Puckett No written report submitted IV. Geography, Forestry, Conservation & Planning, Greg Gaston No written report submitted V. Physics & Mathematics, Nirmol Fodder (by Kenneth Roblee) In the 2006 annual meeting of the AAS at Troy University, our section hosted a total of 19 presentations, which is an increase over the previous few years. Two of these were given by students. We also had an invited lecture this year, given by Dr. A. Kumar of Tuskegee University. During the business meeting the seetion members elected Dr. A. Kumar of Tuskegee University as section vice-chair for the 2006-07 academic year. For the 2006-07 aeademic year. Dr. Brian Thompson of the University of North Alabama will be the section chair. We plan to keep building this section by using the list of math and physics department contacts in the state compiled by Dr. Krannich to recruit speakers for the spring 2007 meeting. VI. Industry & Economics, Marsha Griffin No written report submitted VII. Science Education, Lori Cormier No written report submitted VIII. Behavior & Social Sciences, Cheryl Bullard No written report submitted IX. Health Sciences, Virginia Hughes I. Recruited judges for the annual meeting II. Contact the following clinical laboratory science program directors to inform them of the spring annual meeting in Tuskegee: Dr. Janelle Chiasera - UAB School of Health Professions Dr. George Harwell - University of South Alabama Dr. Cheryl Davis - Tuskegee University III. Contacted the Cytotechnology program directors: Sonya Griffin - Auburn University Montgomery Dr. Vivian Pijuan-Thompson - UAB X. Engineering & Computer Sciences, Marietta Cameron No written report submitted XI. Anthropology, Phillip Koerper No written report submitted 77 XII. Bioethics & History/Philosophy of Science, Keith Gibson No written report submitted 13. Executive Officer, Larry Krannich Since March, 2006, 1 have been involved in the following activities associated with the Executive Director of the Alabama Academy of Science position: 1 . Discussed with Prakash Shanna materials needed concerning amangements, program booklet needs, and deadlines associated with the annual meeting of the Academy to be held on the Tuskegee University campus, Febmai-y 28 - March 3, 2007. 2. Prepared letters to Alabama colleges and univereities to solicit financial support for the Journal for distribution after November 1 . 3. Prepared the Call for Papers for the 84* meeting of the Academy that will be distributed to all Section Chairs in hard and electronic copy after November 15^'\ 4. Prepared the Annual Meeting Announcement and 2007 Dues mail-out and sent these to the Secretary for mailing. 5. Designed bookmarks advertising the Academy and participation in the annual meeting. These will be distributed statewide in mid-November. 6. Requested fi'om the American Chemical Society approval for co-sponsorship of the annual state¬ wide Undeigraduate Chemistry Research Symposium. 7. Updated the fliere and letters being sent to all Alabama chemistry faculty to solicit the participation of undergraduates and Alabama college and univereity Chemistry faculty in the 3“* annual Undergi:aduate Chemistry Research symposium to be held in conjunction with the annual meeting of the Academy. The local sections of the American Chemical Society in the State are being contacted to assess their willingness to again co-sponsor this state-wide undergi'aduate research symposium with the Academy 8. Represented the Academy and the Gorgas Scholarship Committee at the joint booth at the annual ASTA meeting. Committee Reports (C) 1. Local Arrangements, Prakash Sharma No written report submitted 2. Finance, Eugene Omasta The Alabama Academy of Science continues to be in excellent financial condition with total assets of $61,444 as of October 20, 2006. In addition, this figure does not include a return of $5,758 received from Troy University which hosted last year’s annual meeting. The assets since 2001 as reported at the Fall Executive Committee meetings and the year end assets are listed on following page: 78 Period Assets Change Period Assets Change I/I - 10/12/2001 $7 1 ,763 1/1-12/31/2001 $75,813 I/I-I0/12/2002 $72,197 $434 1/1-12/31/2002 $72,813 -$3,000 I/I-I0/I2/2003 $71,403 -$794 1/1-12/31/2003 $74,800 $1,987 I/I - 10/26/2004 $74,265 $2,862 1/1-12/31/2004 $74,610* -$190 1 /I -10/26/2005 $63,895 -$10,370 1/1-12/31/2005 $65,561* -$9,049 1 /I -10/20/2006 $61,444 -$2,45 1 The large decrease in assets during 2005 was a result of declining membership and an increase in Journal expenses due to printing back issues of the Journal that year. In an effort to increase membership. Dr. Krannich sent post card reminders, in December, 2005, to all persons who were either currently members or have been members of the Academy at some time during the past 5 years. Dr. Rayburn sent postcard reminders to current members this fall. The results of these efforts should be reflected in the year end assets. The Academy should continue to explore ways of increasing revenues including seeking the best investment rates for our assets and ways to increase membership. 3. Membership, Mark Meade With Dr. Rayburn’s help (AAS secretary) I mailed out nearly 100 reminders to recent members who have not paid annual dues. I also e-mailed all academy section chairs reminding them to contact persons within their section and remind them of dues. 4. Research, Steve Watts This year 19 students (the same as last year) applied for travel awards to the Troy University meeting. All were presenting papers or posters. All students were from out of town and were each awarded $35 Budgeted amount for travel is $750 and we encumbered $665. In addition, 5 students (down from d last year) applied for research grants. The committee is evaluating the grants and ail of these will be awarded in full ($1,250 of the budgeted amount of $2,400). Support for book purchases are no longer allowed this year, nor is travel to other conferences (decided at last fall meeting). Twenty-three students (down from 40) have applied for the Research Paper/Poster Competition in several sections. New (slightly modified) evaluation forms and suggested cruc-na were sent to all section chairs and are now on the web. All categories of awards and activities were handled electronically for the third year. .Several minor modifications may be needed for next year, but in general electronic submissions greatly improved the process and eliminated a gruesome paper trail. Richard Hudiburg has done an outstanding job in fine-tuning the process of submission. This year the paper/poster competition will be held on Thursday only, with the banquet on Thursday night where winners will be announced. 79 5. Long-Range Planning, — No written report submitted 6. Auditing, Senior Academy, Sergey Belyi No written report submitted 7. Auditing, Junior Academy, Henry Barwood By Dr. Govind Menon, Auditor Alabama Junior Academy of Science July 2005- July 2006 Audit of Alabama Junior Academy of Science Financial Records This is a report of the Alabama Junior Academy of Science Auditing Committee for the July 2005-July 2006 financial year. 1 have examined the books provided by the Alabama Junior Academy of Science Treasurer, Dr. B.J. Bateman. We are satisfied ourselves that the receipts and expenditures, as presented to us, are correct and that all expenditures are legitimate expenses. The net worth as of June 30, 2006 is $ 1 1 ,808.50 8. Editorial Board & Associate Journal Editors, Thane Wibbels No written report submitted 9. Place and Date of meeting, Mark Meade No written report submitted 10. News Letter, ~ No written report submitted 11. Public Relations, Larry Davenport No written report submitted 12. Archives, Troy Best No written report submitted 13. Science and Public Policy, Scott Brande My Favorite Web Resources on the Evolution/Creationism controversy By: Scott Brande, Ph.D. CHM-289, UAB Birmingham, AL 35294 sbrande@uab.edu The National Center for Science Education www.ncseweb.org My number one stop for information with current news and extensive resources and links. Categories include teacher resources on creationism and evolution, extensive coverage of recent court cases (Dover, Cobb County,...), references and reading lists, book reviews, and much, much more. National Science Teachers Association http://www.nsta.org/ The professional organization for science teachers, with a website that provides a modest set of links to evolution resources for teachers at http://www. nsta.org/220/ 80 including a Q&A for teachers links to current news, the NSTA position statement on teaching evolution, and web links. Understanding Evolution is a “non-commercial, education website, teaching the science and history of evolutionary biology. This site is here to help you understand what evolution is, how it works, how it factors into your life, how research in evolutionary biology is performed, and how ideas in this area have changed over time. The site is collaboration between the University of California Museum of Paleontology and the National Center for Science Education. http;//evolution. berkeley.edu/ The site includes evolution in the news, profiles of scientists, an extensive collection of searchable lesson plans from Kto 12, self¬ teaching modules on Evolution 101, and original content about interesting organisms in action from bacteria to bugs. American Association for the Advancement of Science http://www.aaas.org/news/ press room/evolution/ The front page to extensive resources, including coverage of educational issues in the news, resources for teachers (including a talking points Q&A). http;//www.aaas.org/spp/dser/ At the Programs/Science and Policy tab, you'll find a special section, the AAAS Dialogue on Science, Ethics, and Religion. Especially interesting is the availability on the web of audio files of most of the public lectures sponsored by AAAS since 2002. http:// www.aaas. org/spp/dser/02_Events/Lectures/02_Lecture Archive.shtml AAAS has just published a new book. The Evolution Dialogues: Science, Christianity, and the Quest for Understanding, “his unique and extraordinary resource presents in plain language and in fewer than 200 pages a new conversation on evolution and Christianity.” Highly recommended National Academies of Science http://nationalacademies.org/evolution/ The National Academies of Science is the nation's advisor on issues of science, engineering and medicine. It publishes books and reports, including those on evolution research and education. Important issues include “Teaching About Evolution and the Nature of Science” and “Science and Creationism: A View from the National Academy of Sciences”. TalkOrigins.org http://talkorigins.org/ One of the largest archives of information about the evolution/creation ism controversy on the web. Here you will find a “collection of articles and essays... The primary reason for this archive's existence is to provide mainstream scientific responses to the many frequently asked questions (FAQs) that appear in the talk. origins newsgroup and the frequently rebutted assertions of those advocating intelligent design or other creation creationist pseudosciences”. The Pandas Thumb http://www. pandasthumb.org/ A “virtual” (web) publication in which people gather to discuss evolutionary theory, critique the claims of the antievolution movement, defend the integrity of both science and science education, and share good conversation. Although not a tightly organized and arranged as other websites. The Pandas Thumb includes a wealth of information along with casual banter. Individual posts can be amusing and fun to read. 81 Dr. Kenneth Miller’s annotated bibliography http://www-personal.k-state.edu/~kbmill/ scifaith.html Dr. Miller is a practicing Catholic and the co-author of the biology textbook recommended by teachers at the Dover Area School District, Pennsylvania and in Cobb County, Georgia, and opposed by Intelligent Design advocates. Legal actions in both locations lead to important trials that revealed much about the nature of the evolution/creationism controversy in public schools. See Dr. Miller's bibliography his extensive reading list on science and theology, theology of creation, and Christian environmentalism. 14. Gardner Award, Prakash Sharma Fellow - Alabama Academy of Science (FAAS) Alabama Academy of Science October 28, 2006 This is to request each and every member of this academy to publicize to individuals, heads of departments, deans and provosts of colleges and universities about this prestigious award. Please solicit nominations from individuals and difllerent academic and industrial organizations for this award. The nomination shotild be forwarded to: Dr. P. C. Sharma, Chair Head of Physics Department, Tuskegee University, Tuskegee, AL 36088. Phone: (334) 727-8998; Fax: (334) 724-3917 e-mail: pcshanna(q),tuskegee.edu You are welcome to nominate by either e-mail or by mailing a hai'd copy. The nominations should consist of the following documents: (i) Formal Nomination Letter, (ii) vitae and at least two letters of references from peers, administrators and one by an expert in area of his/her research, and (iii) one page citation that will be used for presentation of the award. Anything missing from items (i, ii, iii) will result in rejection of the nomination. The closing date for nominations is December 20, 2006. The award will be presented in the “Annual Meeting of Alabama Academy of Science-Banquef’, on Thursday, March 1, 2007. Wright Gardner Award Committee Report Alabama Academy of Science October 28, 2006 The first meeting of the Alabama Academy of Science was held at Sidney Lanier High School, Montgomery, Alabama, April 4, 1924, in conjunction with the Alabama Educational Association Meeting. Wright Gardner was elected as an office bearer of the academy in this meeting. Through his early studies he became determined to make teaching and research his two goals for his life. The Wright Gardner Award was established, after the name of this great future looking scientist and educator, by the Alabama Academy of Science in 1984 to honor individuals whose work during residence in Alabama had been 82 outstanding. Persons nominated for this award have included researchers, teachers, industrialists, clinicians, scholars and active members and office bearers of the Alabama Academy of Science. This is to request each and every member of this academy to publicize to individuals, heads of departments, deans and provosts of colleges and universities about this prestigious award. Please solicit nominations from individuals and different academic and industrial organizations for this award. The nomination should be forwarded to: Dr. P. C. Sharma, Chair, Wright Gardner Award Committee, Head of Physics Department, Tuskegee University, Tuskegee, AL 36088. Phone: (334) 727-8998; Fa.\: (334) 724-3917 e-mail: pcsharmafffituskegee.edu You are welcome to nominate by eitlier e-mail or by mailing a hard copy. The nominations should consist of the following documents: (i) Formal Nomination Letter, (ii) vitae and at least two letters of references from peers, administrators and one by an expert in area of his/her research, and (iii) one page citation that will be used for presentation of the award. Anything missing from items (i, ii, iii) will result in rejection of the nomination. The closing date for nominations is December 20, 2006. The award will be presented in the “Annual Meeting of Alabama Academy of Science-Banquef', on Thursday, March 1, 2007. 15. Carmichael Award, Richard Hudiburg The committee looks forward to reviewing research articles published in Volume 78 of the Joz//77<:// of the Alabama Academy of Science in 2006. The Emmett B. Carmichael Award will be announced during the 84"’ annual meeting in Mareh 2006. 16. Resolutions,—. No written report submitted 17. Nominating committee, Kenneth Roblee No written report submitted 18. Mason Scholarship, Mike Moeller Last spring we had six completed applieations for the William H. Mason Scholarship. After reviewing all application materials the Scholarship Committee offered the $1000 scholarship to Ms. Kelly Harbin. Ms. Harbin aceepted the award. 83 The previous recipients of the William H. Mason Scholarship are: 1990-1991 Amy Fivengood Sumner 1991-1992 Feella Shook Holt 1992-1993 Joni Justice Shankles 1993-1994 Jeffrey Baumbach 1994-1995 (Not awarded) 1995-1996 Faura W. Cochran 1996-1997 Tina Anne Beams 1997-1998 Carole Collins Clegg 1998-1999 Cynthia Ann Phillips 1999-2000 Ruth Borden 2000-2001 Karen Celestine, Amy Murphy 2001-2002 Jeannine Ott 2002-2003 (Not awarded) 2003-2004 Kanessa Miller 2004-2005 (Not awarded) 2005-2006 Mary Busbee, Bethany Knox 2006-2007 Kelly Harbin Attached to this report is a copy of an announcement that the committee plans to be sending soon to deans in schools of science and education within Alabama. Members of the AAS Executive Committee are encouraged to copy and disseminate this information. 19, Gorgas Scholarship Program, Ellen Buckner Effective 2006, the Gorgas Competition began accepting applications directly. A website was set up by Dr. Richard Hudiburg at www.GorgasScholar.org. The Competition has been renamed the Gorgas Scholarship Competition and Alabama Science Scholar Search. In 2006 eighteen applications from 1 0 schools were received and all met the minimum criteria for consideration. Twelve finalists competed in the final competition at Troy University. Thirty-nine scientists from across the state gave of their time and expertise as judges for the competition, either as paper readers or judge of the final competition. Winners were announced and pictured on the website. Congratulations to Ms. Jennifer Taylor of Florence High School who was the winner in 2006 as well as a Finalist in the national Intel Science Talent Search. The Competition was highly successful in this, the first year of direct submission. The AAS and Gorgas Competition were featured in an article published in the Alabama Association of School Boards magazine Alabama School Boards in June. The 2007 competition planning has been done. The website has been updated with the submission date of Januai-y 8, 2007. Note that the AAS meeting is veiy early this year making the need for speedy review of the papers an imperative! We plan to have the final judging completed by the first of February to announce finalists. AAS-Gorgas representatives were present at the fall meeting of the Alabama Science Teachers Association ( ASTA). Fliers were sent statewide to all chaiipersons 84 of high school science departments — both public and private. Numerous letters will be sent in the next month to students who have done internships, science fair projects or papers at the State level, and other groups (e.g. IB Schools, Governor’s School, CORD summer science graduates). AAS members are welcomed to submit names for individual letters (to teachers or students) inviting application. Send complete contact infonnation to Dr. Buckner at bucknere(ai, uab.edu. Applications to the Gorgas competition are limited to High School seniors. The Gorgas Committee met this morning and welcomed Dr. Shane Shaipe to the committee. The committee reviewed infonnation on the cuiTent status of the Legacy account. In addition, the committee has set up a checking account this year for the Gorgas funds. The account has Drs. Krannich and Buckner as signatory. It will be used for expenses of the competition. A teacher award for 2007 is under consideration to recognize those teachers who consistently encourage student’s participation. Changes for the 2007 meeting with the banquet on Thursday night will require some changes in the Gorgas Competition schedule. Members of the AAS Executive Committee are asked to talk to teachers and encourage them to visit the website and invite their top science students to apply. To realize the potential that exists, teachers throughout the state must be aware of the Gorgas competition. AAS members are asked to assist by passing along the attached flier. Please visit the website at :www. Goipas S cholar.org Fall 2006 Report of the Gorgas Scholarship Committee Finances October 28, 2006 In Fall 2006 a checking account ( Regions, Birmingham) was opened to handle expenses and publicity of the competition. The account is listed as Alabama Academy of Science- Gorgas Scholarship Program and Drs. Krannich and Buckner are signatory. Activity on the account to date is listed below: Initial deposit form APF (expenses): $5728.00 Expenses: Mailing $618.22 ASTA Booth & Ad $300.00 Total remaining: $4809.78 20. Electronic Media, Richard Hudiburg — 1 report the following activities: 1 . Updated the main webpage for the AAS website and provided links to materials based on requests from the AAS president and Executive Director of AAS. 2. Complete the transmittal of the paper abstracts from the 83rd annual meeting of AAS to the Editor of the Journal of the Alabama Academy of Science. This process was completed in a timely manner. 3. Provided preliminary information and links for the 84th annual meeting. 4. Responded to various requests from the President of AAS, Executive Director of AAS and other members concerning changes to the AAS website. 85 5. The AAS website was migrated successfully to a new platform during June and July 2006 by the web hosting company, PowWeb.com. 6. There will be a specific proposal by the associate editors for electronic media. Marietta Cameron and Brian Toone, to redesign the AAS website. Discussion During President Election Report the following took place: The following were nominated to fill vacancy in board. Gene Omasta made the motion to vote these in. Ken Marion Jim Bradley Ron Jenkins Prakarsh Sharma A vote taken and it was unanimous to accept these to fill in the vacancies. 86 Members of Alabama Academy of Sciences (2007) Kassidy, Alexander, Student Safaa, Al-Hamdani, Active Muhammad, Ali, Active Sherita, Andrews, Student Robert, Angus, Active Arthur G., Appel, Lifetime David, Arrington, Active Sonja, Artis, Student Jacary, Atkinson, Student Shaina, Attoh, Student Mark, Bailey, Lifetime Basil, Bakir, Student Laszlo, Baksay, Lifetime Ronald, Baiczon, Active Michael, Barbour, Active Wayne T. , Barger, Active Amy Marie, Barr, Student William J, Barrett, Emeritus John, Barrett, Active Brittani, Batts, Student Robert P, Bauman, Emeritus TE, Bearden, Lifetime Daley T., Beasley, Student John M, Beaton, Emeritus Eee R, Beck, Eifetime Peter, Beiersdorfer, Active Sergey, Belyi, Active Helen H., Benford, Active Neil, Billington, Lifetime Benjie, Blair, Lifetime John, Boncek, Active Larry R, Boots, Lifetime Coartney, Boyd, Student James T., Bradley, Lifetime Malcom, Braid, Lifetime Scott, Brande, Active Andre , Braxton, Student Lakisha, Brown, Student David C, Brown, Lifetime Lisa, Buchanan, Student LW, Buckalew, Lifetime Ellen, Buckner, Eifetime Charles E, Bugg, Lifetime Brian S, Bums, Active Shuntele N., Burns, Active Gayle L., Bush, Active Houston, Byrd, Active Malori, Callender, Student Leslie, Calloway, Student Sherell, Carey, Student Marcqueia L., Carson, Student Jan, Case, Active Ashley Kay, Casey, Student Gail H, Cassell, Lifetime Tanushree, Chakravarty, Student Misty, Chapman, Student Kristen, Chappell, Student Melissa, Charles, Student Kimberly, Childs, Student Janese D., Christian, Student Cleary, Clark, Student Ben A, Clements , Emeritus George, Cline, Active Andrew, Coleman, Student Eoretta A., Cormier, Lifetime Megan, Cox, Student Lonnie, Craft IV, Student Thomas F, Craig, Lifetime Johnathan, Crayton, Student Amy, Crews-Oyen, Anne, Cusic, Lifetime J William, Dapper , Active Larry, Davenport, Active Henry W., Davis, Student Richard, Davis, Active WR, Davis, Lifetime Floyd, Davis , Student Lewis S, Dean, Active Alvin R, Diamond, Jr, Active Austin, Dixon, Student Adriane, Dobson, Student Keela, Dodd, Student 87 Steve, Donaldson, Lifetime Lydia, Dorgan, Student Tracy W., Duckworth, Active Julian L, Dusi, Lifetime Rosemary D, Dusi, Lifetime Roland R, Dute, Lifetime Hussain, Elalaoui-Talibi, Active Geraldine M, Emerson, Eifetime Matthew, English, Student Oskar M, Essenwanger, Lifetime Jenny, Estes, Student Jeremy, Evans, Student Whiney, Evans, Student R Taylor, Ezell, Student Christine, Feeley, Student Joe M, Finkel, Active Sara, Finley, emeritus Wayne H, Finley, emeritus James H, French, Eifetime Michael, Froning, Active Teshome, Gabre, Active Edward B., Garner, Student Carolyn, Gathright, Active Brittany, Gay, Student Victoria K., Gibbs, Student Keith, Gibson, Active Kenneth R, Gilbert, Student Fred, Gilbert, MD, Lifetime Cameron W., Gill, Student Leslie R., GoeUzen, Active Narendra Kumar, Govil, Active Lamesha D., Greene, Student Wendy, Gregory, Student Marsha D, Griffin, Active Jan , Gryko, Active Robert T, Gudauskas, emeritus Pryce “Pete”, Haddix, Active James H, Haggard, Active Rosine W, Hall, Lifetime Mijitaba, Hamissou, Active Shana, Hardy, Student Victor, Harris, Student Joseph G., Harrison, Active Antonio, HayeO/s, Student Level! S, Hazlegrove, Lifetime Qinghua, He, Active Paul Andrew, Helminger, Active Justin, Hendricks, Student B Bart, Henson, Active Donald, Herbert, Active Miriam Helen, Hill, Lifetime Thandiwe, Hlatywayo, Student Emily, Holden, Student A Priscilla, Holland, Eifetime Richard D, Holland, Active Dan C, Holliman, emeritus Harry O, Holstein , Active Irina, Howard , Student Candice, Howard-Shaughnessy, Active Xing, Hu, Lifetime Richard A, Hudiburg, Lifetime Kelli, Hudson, Student Virginia, Hughes, Active Brenda W, Iddins, Active Issac E., Igbonagwam, Student Thomas S, Jandebeur, Lifetime Brandon P, Jarman, Student Li , Jiang, Active Adriel D, Johnson, Lifetime Ivy Krystal, Jones, Student Ruth W, Kastenmayer, Active Ellene, Kebede, Active William E., Kelly, Ashley D., Kennedy, Student Jong Hwa, Kim, Active Duk Kyung (Daniel), Kim, Active Steve, Kimble, Student Natalie, King, Student Christopher , King, Active Martha V, Knight, Active Eawrence F., Koons, emeritus Earry K, Krannich, Eifetime Srinivasarao, Krishnaprasad, Active Jeanne E., Kuhler, Active 88 Akshaya, Kumar, Active Anne Marie, LeBlane, Student Cherline, Lee, Student Aleek W., Leedy, Active Pamela M., Leggett-Robinson, Active Carol, Leitner, MD, Lifetime Michel G, LeLong, Lifetime Miehael S, Loop, Lifetime William K, Love, Active James R, Lowery, emeritus Adriane, Ludwiek, Aetive Christy, Magrath, Active Ken Roy, Marion, Aetive Julia E, Massey, Aetive Juan Luis, Mata, Active William K, McAllister, Lifetime J Wayne, MeCain, Lifetime Amanda, MeCall, Student Jim, Mcelintock, Active Vann, McCloud, Student Stuart W, MeGregor, Aetive Teena M., McGuinness, Active Matthew, MeGuire, Student Ellen W, McEaughlin, Active Bonnie , Mcquitter-Banks, Active Mark, Meade, Aetive Vietoria, Mechtly, Student Joseph, Menefee, Student Joe , Mills, Student Deanna, Minisee, Student Eeana, Mitchell, Active Staey Tyrone, Mixon, Eifetime Miehael B., Moeller, Aetive David, Mohammad, Student Jack H, Moore, emeritus Teresa Kelley, Moore, Active Anthony G, Moss, Active Christopher, Murdock, Active Gerald, Murray, Lifetime Henry David, Muse, Active Gwen, Nance, student Marione E, Nance, Active Juan M, Navia, emeritus David H, Nelson, Aetive Bradley R., Neweomer, Eifetime Ray, Neyland, Aetive Alfred, Niehols, Active Moniea, Norton, Student Samuel C., Nwosu, Student Eumumba, Obika, Student Benedict, Okeke, Active Eugene, Omasta, Aetive Albert, Osei, Active William F, Osterhoff, Active Janna, Owens, Student Donald L, Parker, Eifetime Seott C, Parrish, Lifetime Glenn D., Person, Student Mikel D., Petty, Aetive Robert E, Pieroni, Aetive James A, Pittman, Jr, Lifetime Marshall, Pitts, Lifetime Morgan S, Ponder, Aetive Duane, Pontius, Aetive Niehole L., Powell, Active Mohammed A., Qazi, Active Samiksha, Rant, Student James, Rayburn, Aetive Jarrod, Rayford, Student Gerald T, Regan, emeritus Philip D., Reynolds, Active Velma, Richardson, Active Alexander, Roberts, Student Janet, Roberts, Student Robin, Roberts, Lifetime B.K., Robetson, Aetive Edward E, Robinson, Lifetime George H, Robinson, Lifetime Kenneth, Roblee, Active Shirley, Rohrer, Aetive Frank, Romano, Aetive Donald, Roush, Lifetime Robert, Rowe, Student Bobby, Rowe, Lifetime 89 Jane, Roy, Active Albert E., Russell, Active Gullo, Safawo, Active Kristina, Schneider, Student Lacoya Tyne, Seltzer, Student PC, Sharma, Lifetime David L, Shealy, Lifetime Richard C, Sheridan, emeritus RL, Shoemaker, emeritus Michelle, Sidler, Aetive Shiva P, Singh, Lifetime Kenneth R, Sloan, Lifetime Akeem, Smith, Student Lynessa V., Smith, Student Anita, Smith, Active Micky, Smith, Lifetime Bruce L, Smith, Aetive Angela M., Spano, Student Sheldon, Spencer, Student Clyde T, Stanton, Aetive Ariel D., Stark, Student James L., Stewart, Student Samuel J, Strada, Aetive Chrystal, Sullivan, Student Kenneth, Sundberg, Active Arjun, Tan, Active Robert W, Thacker, Active Shamira, Theodore, Student Robert E, Thomas, Active D Brian, Thompson, Active Jerry N, Thompson, Active Sue, Thomson, Active Tiygve, Tollefsbol, Active Perry, Tompkins, Lifetime Diane, Tucker, Active Charmaine, Tutson, Student Katherine, Vandeven, Student SL, Varghese, Active Nagiarajan, Vasumathi, Aetive John B, Vincent, Active Kris, Walker, Student JH, Walker, Lifetime Natalie, Warren, Student Stephen A, Watts, Lifetime Clifford, Webb, Student BC, Weber, Lifetime Laura, Weinkauf, Aetive Glynn P, Wheeler, emeritus Thane, Wibbels, Active WH, Wilborn, Lifetime James C, Wilkes, Lifetime Brandon, Williams, Student Shammah O.N., Williams, Student Robert J, Williams, Lifetime Edward L, Wills, Active Katie, Wilson, Student Herman, Windham, Active Patriek L., Witmer, Student Michael, Woods, Active Emily, Wright, Student Douglas A., Wymer, Aetive Lin, Yang, Student 90 « TWI] f V •«<- ji. •S' ■■•Yy > Alabama Academy of Science Journal Scope of the Journal: The Alabama Academy of Science publishes significant, innovative research of interest to a wide audience of scientists in all areas. Papers should have a broad appeal, and particularly welcome will be studies that break new ground or advance our scientific understanding. Information for the Authors: • Manuscript layout should follow the specific guidelines of the journal. • The authors are encouraged to contact the editor (E-mail: sah@jsu.edu) prior to paper submission to obtain the guidelines for the author. • At least one author must be a member of the Alabama Academy of Science (except for Special Papers). • The author(s) should provide the names and addresses of at least two potential reviewers. • Assemble the manuscript in the following order: Title Page, Abstract Page, Text, Brief acknowledgments (if needed). Literature Cited, Figure Legends, Tables, Figures. What and Where to Submit: The original and two copies of the manuscript and a cover letter should be submitted to the following. Dr. Safaa Al-Hamdani Editor-Alabama Academy of Science Journal Biology Department Jacksonville State University 700 Pelham Road North Jacksonville, AL 36265-1602 Review Procedure and Policy: Manuscripts will be reviewed by experts in the research area. Manuscripts receiving favorable reviews will be tentatively accepted. Copies of the reviewers’ comments (and reviewer-annotated files of the manuscript, if any) will be returned to the correspondent author for any necessary revisions. The final revision and electronic copy are then submitted to the Alabama Academy of Science Journal Editor. The author is required to pay $100 for partial coverage of printing costs of the article. The Journal of the Alabama Academy of Science. 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