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projects > across trophic level system simulation (atlss) > snail kite > work plan
Project Work Plan
Greater Everglades Science Program: Place-Based Studies
Project Work Plan FY 2003
A. GENERAL INFORMATION:
Project Title: Estimation of Critical Parameters in Conjunction with Monitoring The Florida Snail Kite Population
Project Summary: Life history traits and the population dynamics of the snail kite may vary considerably across space and over time. Understanding the influence of environmental (spatial and temporal) variation on demographic parameters is essential to understanding the population dynamics of a given species. Recognition of information needs for management decisions and conservation strategies has resulted in an increased emphasis on correlations to spatial and temporal environmental variation in relation to demographic studies. The purpose if this study is to provide valid estimates of the demographic parameters of the snail kite, including temporal and spatial variability due to environmental factors. These parameters will be used in a predictive model of the snail kite already developed under the ATLSS Program (Mooij et al. 2002).
Project Objectives and Strategy: The snail kite (Rostrhamus sociabilis) is an endangered species that resides in the highly fluctuating ecosystem in the central and southern Florida wetlands. Many demographic traits, such as stage-dependent survival, reproduction, and movement of the snail kite vary both temporally and spatially. How these demographic parameters vary as a function of environmental conditions, hydrology in particular, is crucial for understanding how the snail kite will respond to proposed changes in water regulation in South and Central Florida. In particular, these data are needed for testing and improving the existing spatially-explicit, individual-based ATLSS snail kite model, developed by Mooij and Bennetts, which has recently been delivered to Department of Interior and other agencies (Mooij et al. 2002). From these data and the model, projections can be made on snail kite response to any hydrologic scenario. Also, continued estimates will be made of the rate of population growth (). Assessing as well as the demographic parameters, is critical for identifying and evaluating the effectiveness of management actions and conservation strategies. In addition, new modeling techniques, such as structural modeling are being explored to better understand the effects of hydrology on the snail kite. The objective of this project is to do the following:
Potential Impacts and Major Products:
The most important results of this study are
This study is providing reliable estimates of critical temporal and spatial factors structuring the demographic responses of snail kites as well as to provide a sound monitoring program during implementation of restoration.
B. WORK PLAN
Title of Task 1: Estimation of Critical Parameters in Conjunction with Monitoring The Florida Snail Kite Population
Task Summary and Objectives:
Mark-resighting methods have a long and solid statistical foundation for estimating survival and population size (Lebreton et al. 1992; Nichols 1992). And more recently, mark-resighting methods have been developed to estimate recruitment and the rate of population change (Pradel 1996, Nichols et al. In press). In 1992, a mark-resighting program was initiated to estimate survival of snail kite (Bennetts and Kitchens 1997). More recently, this approach has been used to estimate the population size and rate of population change in snail kites (Dreitz 2000). Our study design would continue the use of mark-resighting techniques to monitor the snail kite population. Our approach would also attempt to incorporate spatial and temporal components of environmental variation (i.e., habitat conditions in wetland units, hydrological dynamics, apple snail densities) to assess how these factors influence the demographic parameters (i.e., survival and reproduction). The most efficacious approach, manipulative experiments (Harrison and Cappucino 1995) are impractical for threatened and endangered species. We believe that our proposed approach employing observational studies that concentrate on valid parameter estimation, model selection, exploration of process variation (i.e., understanding the components of variance estimates), and examination of different factors under varying environmental conditions is the only feasible alternative.
Mark-resighting data were collected from March 1 to June 30 of each year starting in 1997 and continuing through 2000. This sampling period was chosen because it coincides with the major period of breeding activity (Sykes et al. 1995, Bennetts and Kitchens 1997a). During the breeding season adults remain in close proximity to their nest, which increases our ability to read the band (i.e., a resighting). Sampling during this period also coincides with our banding of juveniles at the time of fledgling (24-30 d) (Sykes et al. 1995). Prior to 1997, over 1000 snail kites had been banded as either adults or juveniles (Bennetts pers.comm). Juvenile snail kites have the potential to breed at nine months (Snyder et al. 1989), thus; they advance to the adult age class the following breeding season.
During the sampling period, the entire study area was surveyed on 6 separate 2 to 3-week sampling occasions. Except for the repetitive sources, the format of the surveys was similar to the quasi-systematic transects conducted by airboat for the annual surveys (Sykes 1979, 1982; Rodgers et al. 1988, Bennetts et al. 1994). However, specific survey methodology depended on size, water levels, and vegetation structure in the individual wetland units. During each 2 to 3-week sampling occasion, we categorized and recorded an individual as 1) "marked" if the bird had a colored leg band with a distinct letter/number combination so that individuals could be identified, 2) "unmarked" if no leg bands were present or if birds were banded with only a USFWS band or color band without a letter/number combination, or 3) "unknown" if the banding status was not determined.
Initially, it was hoped that resighting data could be used with capture-recapture models for closed populations because of the ability to model sources of variation in capture probability with these models (e.g. Otis et al. 1978, White et al. 1982). Thus, the first step in the analyses was testing for demographic closure. The closure test implemented in program CAPTURE (Otis et al. 1978) and program CLOSTEST (Stanley and Burnham 1999) were used to test the assumption of demographic closure of the sampled population. The closure test in CAPTURE is unaffected by heterogeneity in resighting probabilities; however, it is insensitive to temporary violation of closure occurring during the middle of the sampling period (Otis et al. 1978). While program CLOSTEST is more robust to time-specific variation in resighting probabilities in the absence of behavioral or individual heterogeneity, its use is recommended in conjunction with the closure test in program CAPTURE in order to better detect closure violations in resighting data sets (Stanley and Burnham 1999).
Work to be undertaken during the proposal year and a description of the methods and procedures:
This task will be to continue the following:
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