Home | Archived October 29, 2018 | (i) |
![]() |
projects > compilation of alligator data sets in south florida for restoration needs > 2001 Proposal
Compilation of Alligator Data Sets in South Florida for Restoration NeedsProject Proposal for 2001Continuation Research Plan [Year 2 of 3 Years] PROJECT TITLE: Compilation of alligator data sets in south Florida for restoration needs Principal Investigator: Dr. Kenneth G. Rice Co-Principal Investigator: Dr. Frank J. Mazzotti BACKGROUND: Alligators have been identified as a key component of the Everglades ecosystem. Long-term changes in alligator numbers, nesting effort, growth, condition, and survival can be used as indicators of the health of the Everglades marsh system. Due to their sensitivity to hydrologic conditions, an alligator population model is underway in the ATLSS program to evaluate restoration alternatives. Evaluating long-term trends and developing population models require a large amount of data collected over a number of years and a number of locations. Information on alligator densities, nesting and growth have been collected in south Florida since the 1950s by rangers and researchers in Everglades National Park and Big Cypress National Preserve, Florida Fish and Wildlife Conservation Commission personnel, University researchers, and private consultants. Many of the most critical data sets (those having the largest amount of data or those from particular areas or years) are not accessible for use in evaluating restoration alternatives or developing models. The data are not available in a centralized, easily accessible, well documented database. Further, the size and scope of these data sets are not fully known. Certainly, thousands of individual records need to be evaluated, compiled, and entered into an appropriate database. It is critical that these data sets are accessible to establish restoration targets for alligator populations, develop models, and design short and long-term monitoring tools for evaluating restoration success. Objectives: The main objective of the study is to compile, in a format accessible to all researchers, all data collected on alligator numbers, biology, and ecology in south Florida. The data are required to set restoration success criteria, provide input to models being developed to evaluate effects of Everglades restoration on alligators, and to develop short and long-term monitoring protocols for assessing the success of Restoration efforts. Specific objectives for the initial phase include:
INFORMATION NEEDS AND USES
KEY FINDINGS
PROJECT DESCRIPTION Purpose and Goals USGS-BRD and its cooperators are using a system of empirical data collection and simulation modeling to apply information on wildlife community patterns in guiding the restoration process. Through the development of population simulation models based on these empirical data, we can evaluate restoration alternatives and assess restoration performance measures. By applying these models to restoration alternatives and predicting population responses, we can choose the alternatives that result in biotic characteristics that approximate historical conditions and identify future research needs. The benefits to restoration of this project would arise by having more confidence in improved tools, like the ATLSS models, that are used to evaluate alternatives for ecological effects of the Central and Southern Florida Project Restudy, C-111 Project, and Modified Water Deliveries Plan to Shark Slough. Evaluating long-term trends and developing population models require a large amount of data collected over a number of years and a number of locations. Information on alligator densities, nesting and growth have been collected in south Florida since the 1950s by rangers and researchers in Everglades National Park and Big Cypress National Preserve, Florida Game and Fresh Water Fish Commission personnel, University researchers, and private consultants. Many of the most critical data sets (those having the largest amount of data or those from particular areas or years) are not accessible for use in evaluating restoration alternatives or developing models. The data are not available in a centralized, easily accessible, well documented database. Further, the size and scope of these data sets are not fully known. Certainly, thousands of individual records need to be evaluated, compiled, and entered into an appropriate database. It is critical that these data sets are accessible to establish restoration targets for alligator populations, develop models, and design short and long-term monitoring tools for evaluating restoration success. Objectives:
Urgency or Timelines This study provides access to data required for the construction of the ATLSS American alligator population model and other evaluative tools used during adaptive implementation of the Comprehensive Ecosystem Restoration Plan. We also provide other timely investigations involving comparisons of condition of alligator populations in the Everglades. The alligator is both a keystone and indicator species in the Everglades ecosystem. Therefore, it is critical to understand the effects of restoration alternatives on this species and to include the alligator in restoration alternative selection, evaluation, and monitoring. Effectiveness
Synopsis of Research Methods Alligator populations have been studied in the Everglades ecosystem since the 1950s. Many aspects of alligator ecology have been linked to hydrological conditions during certain periods. However, this data is not accessible to present researchers for the comparative research and ecological modeling required during the restoration process. The following discussion is predicated on the need for comparisons to current populations. Water management practices have resulted in a high and unpredictable rate of nest flooding. Historically, maximum summer water levels were positively correlated with water levels during alligator nest construction. This natural predictability has been lost (Kushlan and Jacobsen 1990). Historically, alligators were abundant in prairie habitats of the eastern floodplain, along the edge habitats of the central sloughs. Pre-drainage occupancy of the deep water, central sloughs was relatively low. Marsh alligator densities are now highest in the central sloughs and canals (Kushlan and Jacobsen 1990) and relatively low in the edge habitats. Canal habitats contain high concentrations of adult alligators. Nest densities are also relatively high on levees and associated spoil islands. Less flooding of nests occurs on these higher elevations. However, survival of young may be very low due to a decrease in the number of alligator holes or possible brood habitat proximal to canals. Modified hydrological conditions might be expected to increase nesting effort, nesting success, and abundance of alligators in the aforementioned edge habitats. There may also be a corresponding increase in the number and occupancy of alligator holes to serve as drought refugia. Everglades alligators weigh less than alligators the same length from other parts of their range (Jacobson and Kushlan 1989, Barr 1997). Further, maximum length is decreased, and sexual maturity is delayed (Kushlan and Jacobsen 1990, Dalrymple 1996). Jacobsen and Kushlans (1989) model for growth in the Everglades of Southern Florida predicted alligators reaching a mere 1.26 meters in 10 years and requiring at least 18 years to reach sexual maturity. It is currently suspected that the reason for this poor condition is a combination of low food availability and high temperatures (Jacobson and Kushlan 1989, Dalrymple 1996, Barr 1997). Historical Data Sets. -- A list of historic and current alligator projects and data sets will be compiled by sending a questionnaire to FFWCC, NPS, USFWS, University researchers, and private consultants who are currently or who have conducted research on alligators in south Florida. The questionnaire will ask for the project title, type of data, project dates, project PIs and current addresses, location and form of data (e.g. field notes, computer file etc.), and a list of reports in which the data are used. Each project will be evaluated as to the relevance of the data to restoration success criteria, modeling, and monitoring efforts, the amount of data, and the effort needed to get the data into a usable form. Based on the above information the projects will be ranked in order of importance. The 3 highest ranking data sets will be obtained and compiled during the first year. This may involve physically retrieving field notes from locations outside of south Florida, entering data from field notes, reading data from old tapes, converting computerized data sets into a form usable by our chosen database housing software (ORACLE, ACCESS), and reviewing data sets with the PIs. Guidelines for establishing standardized databases for the types of alligator research projects identified in task 1 will be developed. This will include metadata requirements. Metadata guidelines will be consistent with Federal metadata standards. These guidelines will be distributed to all researchers working on alligators in south Florida so that data currently being collected can be easily combined with historic data sets. A project plan will be developed for obtaining and compiling the remaining data sets based on the successes and challenges experienced during the first year. In addition, a plan will be developed to collect and make available in digital form historic reports and papers on alligators in south Florida. The present proposal has been developed as a 1 year project. However, the project plan outlined above will design and discuss a more thorough and longer term project. Condition. -- The definition of a reasonable "condition factor" is not trivial. This is true in part because our informal evaluations are often normative. For example, we proclaim that one animal is in good condition; another, we say, looks terrible. Even when applied to individuals within one population these terms are not objectively informative. In crocodilians we tend to believe that fat is good. Amongst crocodilians it is probably true that fatter females do produce larger clutches in a given year; however we have no strong evidence that their lifetime productivity is higher. Furthermore, even when our condition-assessments have been value-free, they have usually been qualitative rather than quantitative. So long as our definitions of condition remain unquantified, we shall confront serious difficulties when we attempt to compare across populations. Fisheries biologists routinely face the task of evaluating various populations of a target species. Consequently they have been assiduous in their quest for appropriate measures of condition (Anderson and Gutreuter, 1983; Carlander, 1977; Gabelhouse, 1984; Wege and Anderson, 1978). Clearly this enterprise has two components. The preliminary problem is to define the condition of an individual animal. The more complex objective is to establish a protocol for comparison across populations. Study areas include sampled sites from each major compartment in the Everglades: ARM Loxahatchee NWR, Water Conservation Area 2, Water Conservation Area 3, Everglades National Park, and Big Cypress National Preserve. Animals were captured by cable nooses from airboats at night. For each animal, we measured total length (TL), snout-vent length (SVL), tailgirth, chestgirth, neckgirth (all in cm), and mass (kg). We also determined the sex of each alligator, and we noted any deformities, particularly the loss of tail tips. Because condition among small alligators appears to be unstable over time, we included only animals with SVL > 50cm. For cross-population comparisons, researchers need a set of size-specific standard masses for the species as a whole. An initially appealing strategy would be to gather length-mass data as widely as possible for estimating a and b in Equation 1: mass = a(SVL)b (Equation 1). This approach, however, is logically inconsistent. Statistically it assumes a single set of a and b parameters for the entire target species. Biologists want to make inter-population comparisons precisely because they believe that crocs in different areas or time periods may have different length-mass relationships. Fisheries biologists suggest a solution to this problem in the following way: "Because we seek a measurement standard for fish populations, we should define standard weight-length relationships from a series of population statistics rather than from individual fish data across a series of populations (Murphy et al., 1990)." The two-step process of defining and then evaluating condition could be applied to crocodilians: (1) Developing the condition standards: (a) Measure mass and SVL across samples of crocodilians captured in n different populations. (2) Evaluating condition of crocodilians in a new population: (a) Measure the mass and SVL of a crocodilian from a new population. where Ci is the condition of the ith animal, mi is the observed mass of the ith animal, and Ms is the size-specific standard mass. Use of the median is appropriate because, knowing so little about the species-wide distribution of length-mass relationships, it is safest to evaluate the spectrum of "estimated" masses (produced by our n equations) as ordinal data (Murphy et al., 1990). Roughly, this is equivalent to comparing our in-hand crocodile against a typical croc of the same SVL. We must obtain suitable length-mass samples from a reasonable number of separate populations (perhaps at least 5-10; Murphy et al. [1990] examined 16 populations of largemouth bass and 114 populations for walleye). To be of value, these samples should probably measure at least 30-50 crocs (samples for Murphy et al. [1990] ranged from 12 to 5984) and must include animals from a broad spectrum of SVLs. This same technique would be suitable for evaluating populations conditions across time rather than space. Key Results
INFORMATION PRODUCTS Technical Reports See www.fcsc.usgs.gov. (see http://cars.er.usgs.gov/) Data & Models All data will be maintained at the USGS-BRD, Florida Caribbean Science Center, Restoration Ecology Branch, Everglades National Park Field Station in Homestead, Florida and the University of Floridas Everglades Research and Education Center in Belle Glade, Florida. All data requests should be forwarded to Kenneth G. Rice (305-242-7832 or ken_g_rice@usgs.gov). Permits Permits for alligator capture were obtained in 1999 from the following agencies: 1. Loxahatchee National Wildlife Refuge. Publications and Presentations 1. Abercrombie, C., K. Rice, L.A. Brandt, P. Wilkinson, K.A. Hite, and F.J. Mazzotti. 2000. Claryfing the conundrum of crocodilian condition: telling thick from thin. 15th Working Meeting of the Crocodile Specialist Group, IUCN, Varadero, Cuba. Poster. PLANNED ACTIVITIES - 1999/2000:
SCHEDULE OF ACTIVITIES AND DELIVERABLES - 2000/2001:
Literature Cited and Related References Anderson, R.O., and S.J. Gutreuter. 1983. Length, weight, and associated structural indices. Pages 283-300 in L.A. Nielsen and D. L. Johnson, editors. Fisheries techniques. American Fisheries Society, Bethesda, Maryland. Barr, B. 1997. Food Habits of the American alligator, Alligator mississippiensis, in the southern Everglades. Unpublished Ph.D. Thesis, Univ. Miami, Florida. Carlander, K.D. 1977. Handbook of freshwater fishery biology, volume 2. Iowa State University Press, Ames. Dalrymple, G. H. 1996. Growth of American Alligators in the Shark Valley Region of Everglades National Park. Copeia. 1996(1): 212-216. Gablehouse, D.W. 1984. A length-categorization system to assess fish stocks. North American Jorunal of Fisheries Management 4:273-285. Jacobsen, T. and J. A. Kushlan. 1989. Growth dynamics in the American alligator (Alligator mississippiensis). J. Zool., Lond. 219(2): 309-328. Kushlan, J. A. and T. Jacobsen. 1990. Environmental variability and the reproductive success of Everglades alligators. J. Herpetol. 24(2):176-184. Mazzotti, F. J. and L. A. Brandt. 1994. Ecology of the American alligator in a seasonally fluctuating environment. In S. Davis and J. Ogden, (eds.), Everglades: The Ecosystem and its Restoration, pp. 485-505. St. Lucie Press, Delray Beach, Florida. Murphy, B.R., M.L. Brown, and T.A. Springer. 1990. Evaluation of the relative weight (Wr) index, with new applications to walleye. North American Journal of Fisheries Management 10:85-97. Percival, H.F., K.G. Rice, and S.R. Howarter. 2000. American alligator distribution, thermoregulation, and biotic potential relative to hydroperiod in the Everglades. Contract Final Report. USGS-BRD. Gainesville, Fl.155 pp. SAS Institute Inc. 1988. SAS/STAT users guide, release 6.03 edition. SAS Institute Inc., Cary, NC. 1028 pp. Wege, J.R. and R.O. Anderson. 1978. Relative weight (Wr): a new index of condition for largemouth bass. Pages 79-91 in G.D. Novinger and J.G. Dillard, editors. New approaches to the management of small impoundments. American Fisheries Society, North Central Division, Special Publication 5, Bethesda, Maryland. |
Home | Archived October 29, 2018 |