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Lynn Lefebvre, Dean E. Easton, Bradley M. Stith, Susan M. Butler
Aerial surveys and telemetry data from tagged manatees provide a valuable means of documenting the response of manatees to natural and human-induced fluctuations in freshwater inflow. This information, combined with water quality data obtained from monitoring stations, will be incorporated into the manatee ATLSS model which will be used to better understand and predict manatee response to different restoration scenarios.
The major objectives of the study are to determine relative abundance, distribution, movements, and habitat use of manatees associated with coastal waters and rivers in the western everglades, and to develop an individual-based ATLSS model to predict manatee response to changes in hydrology achieved by the Southern Golden Gate Estates (SGGE) project specifically, and more broadly by the Comprehensive Everglades Restoration Plan. Work has primarily focused on the TTI/SGGE restoration area, with some data also collected from tagged manatees using the southwest portion of ENP. Data for this project is collected via: satellite telemetry and tracking of individuals using a specially designed Global Positioning System (GPS) tag. Data will be used in developing the predictive manatee model which will integrate with the TIME model.
U.S. Department of Agriculture - Natural Resources Conservation Service (NRCS) Department of the Interior - U.S. Geological Survey Department of Commerce - National Oceanic and Atmospheric Administration (NOAA) Environmental Protection Agency (EPA) Smithsonian Institution - National Museum of Natural History (NMNH)
A pilot study was conducted on the use of strip-transect aerial surveys to estimate manatee population size in the Ten Thousand Islands region of southwest Florida. Six transect surveys were conducted during July-October 2000. We determined that this approach could provide a reasonable and statistically sound estimate of manatee population trend in the region.
2201 NW 40th Terrace
Marmontel, M., Reid, J. P., Rathburn, G. B., Domning, D. P.
C. A, Woods and F. E. Sergile, editors
Butler, S. M., Easton, D. E., Deutsch, C. J.
Reid, J. P., Bonde, R. K., Easton, D. E., Kochman, H. I., O'Shea, T. J.
Bonde, R. K., Reid, J. P.
Reid, J. P.
T. J. O'Shea, B. B. Ackerman, and H. F. Percival, editors
Ackerman, B. B., Lefebvre, L. W., Clifton, K. B.
Manatee locations were plotted on topographic maps, and flight paths were recorded on a Trimble Basic Plus GPS. Surveys were conducted from a Cessna 172 at an altitude of 153 m, traveling at approximately 120-140 km per hour. Perception bias, which occurs when some of the manatees visible within a strip transect are missed by an observer, was estimated by applying a Petersen mark-recapture model to counts made by two observers (Pollock and Kendall 1987; Marsh and Sinclair 1989).
To assess the potential for detecting statistically significant trends in the Ten Thousand Islands NWR population, we used TRENDS software (Gerrodette 1993). We used CVs of 0.30 and 0.15, based on results from the surveys in 2000 and 2001, respectively.
The following parameters were also selected: = 0.05; 1-tailed test; linear model of rate of change; CV proportional to the square root of the abundance estimate; standard normal distribution.
If number of sampling periods is 6 per year, sampling is continued for a minimum of 4 years, and CV = 0.30, then power = 0.32.
If number of sampling periods is 8 per year, sampling is continued for a minimum of 4 years, and CV = 0.15, then power = 0.86.
We are likely to need a minimum of 8 surveys per year for a minimum of 4 years to detect an annual rate of change of 10% per year.
The number of sediment plumes observed during the Ten Thousand Island NWR surveys (32 in 2000 and 72 in 2001 suggests that many manatees may not be directly observable. Observations from distribution surveys suggest that approximately 0.75 of plumes represent an actual manatee group. A correction factor should be developed to incorporate the number of observed plumes in the total estimated population size.
Development of the individual-based manatee model will focus on adding several new behavioral components to the model. A major new component will simulate manatee behavior within a Monte Carlo Markov Chain framework to model the transition of manatees between different behavioral states (e.g. feeding, drinking). Telemetry data and field observations provide valuable information that will be used to develop transition matrices that determine how much time animals engage in specific types of behavior, and how frequently they shift from one behavior to another. Another component will simulate different movement speeds associated with different behavioral activities, using distributions developed from the telemetry data. A third component will establish the home ranges of individual animals during the simulation. These home ranges will reflect the observed distribution of home ranges, with constraints added that each animal will inherit part of its range from itís mother, and each home range will include freshwater and seagrass areas. A fourth component will simulate adaptive learning in manatees, with emphasis on how they respond to positive or negative reinforcement when they are searching for freshwater. Initially, a variety of simple animal learning models developed for laboratory maze studies will be evaluated within the model. Telemetry and salinity data from this region and elsewhere around the state will provide some insights into this issue, but additional telemetry data (especially GPS) likely will be needed to reduce the uncertainty associated with this issue. As additional data is collected, the model can be refined to incorporate new insights provided by the survey and telemetry data and the response of manatees to natural environmental fluctuations and human-induced alterations.
Further descriptions of methods and procedures can be seen at <http://cars.er.usgs.gov/Manatees/manatees.html>
Water quality data will be obtained from the Southwest Florida Coastal and Wetland Systems Monitoring Project (E. Patino) at <https://sofia.usgs.gov/exchange/swcoast_est/index.html>
1. Radio tracking manatees to assess the impact of hydrological changes in southwest Florida
We have relied on two types of technologies to acquire geographic locations from tagged manatees. Most tagged manatees are fitted with satellite-based Argos transmitters, which provide approximately four location fixes per 24-hour period, and have a serviceable battery life of six months. Four newly developed Argos-linked GPS tags have been acquired and deployed in FY03. This tag relays GPS locations as sensor data through the Argos satellite link, enabling detailed tracking data to be acquired remotely. The GPS tag provides locations which are much more accurate than the Argos data (approx. 30 m vs. >/= 150 m) every 15-30 minutes, but the battery life expectancy is much shorter (8 weeks vs. 6 months). In combination, the Argos data provides region-wide, long-term coverage suitable for revealing general patterns of habitat use, while the GPS data shows fine details of travel pathways and time spent in specific areas. Location data are formatted in SAS for error checking, analyses, and display in ArcView. Databases are correlated with temperature, salinity, and tidal data collected throughout the region.
Field efforts planned for FY04 and FY05 include tagging additional manatees in the TTI region and, if practical, in the southern portion of ENP. Manatee movement and habitat use data collected from Whitewater Bay to Marco Island will be integrated with PBS models and associated field projects in this region. Remote and field-based tracking has enabled documentation of manatee use patterns associated with near shore habitats.
2. Development of an individual-based ATLSS model for manatees to evaluate the impact of hydrological change in estuaries of southwestern Florida
Work to be undertaken includes two major tasks: a) continued analysis of manatee telemetry data to support the development and parameterization of the individual-based model, and b) development of the model in preparation to evaluate different restoration scenarios. The data analysis task involves using GIS techniques to analyze the telemetry data and characterize manatee behavior, including habitat use, movement patterns, time budget, and home range size. Salinity, water temperature, water depth, and other environmental data obtained from water quality monitoring stations in the study area likely are important factors influencing the behavior of manatees. We will continue to incorporate water quality data into the telemetry data at the appropriate time intervals, and further analyze these data with multivariate statistics to investigate the importance of various factors to manatee behavior.
Development of the individual-based manatee model will continue focusing on behavioral components within the model. This ongoing effort includes simulating manatee behavior within a Monte Carlo Markov Chain framework to model the transition of manatees between different behavioral states (e.g. feeding, drinking). We expect to improve our analysis of the telemetry data and transition matrices by utilizing multi-state mark-recapture models that are able to handle gaps in the telemetry data, to provide a robust means of evaluating factors affecting shifts in behavior. Modeling of individual home ranges will incorporate new telemetry data to better reflect observed variation in home range within the model. Further evaluation of reinforcement learning models will be conducted to simulate adaptive learning in manatees, with emphasis on how they respond to positive or negative reinforcement when they are searching for freshwater. We will continue to work to link the manatee model to a hydrology model (ultimately the TIME model). In the interim, we plan to simulate salinities along the network of creeks, rivers, and canals used by manatees using a technique demonstrated by Doering, Chamberlain et al. (SFWMD) to relate freshwater discharge to salinity gradients at varying distances from point of discharge. As additional data is collected, the model will be refined to incorporate new insights provided by the survey and telemetry data and the response of manatees to natural environmental fluctuations and human-induced alterations.
Radio tracking manatees to assess the impact of hydrological changes in southwest Florida
Field efforts planned for FY 2005 are minimal. Tagged manatees will be tracked through the end of the 2004 wet season. These individuals will then be utilized in the second year of a companion study of the winter-use patterns of manatees in the TenThousand Islands (TTI) region. Tagged manatee movement and environmental data collected between 2002 and 2004 from the study area will be error-checked and formatted for analysis. Distribution and movement data on manatees, combined with water quality data obtained from monitoring stations, will provide a basis for comparative studies in other areas of the region. Sharing of tracking and model data, such as manatee high use areas and travel patterns, are planned with TTI, ENP, and other agencies to address resource management needs.
Development of an individual-based ATLSS model for manatees to evaluate the impact of hydrological changes in esturaries of Southwestern Florida:
Work to be undertaken includes four major tasks: 1) finalize the analysis of manatee telemetry data obtained from Task 2 to support the development and parameterization of the individual-based model, 2) develop empirically-based surrogates for hydrology model output simulating the relationship between salinity and freshwater inflow for major rivers, 3) finalize and validate the individual-based manatee model, 4) devise and conduct a set of simulation runs to evaluate different restoration scenarios.
The telemetry data analysis task involves using GIS techniques to analyze the telemetry data and characterize manatee behavior, including habitat use, movement patterns, time budget, and home range size. We are using the telemetry data to delineate a comprehensive network of sites used by manatees which will provide the landscape used in all simulations. The fine-scale GPS data is being used to develop detailed travel corridors between offshore and inshore areas, as well as movement speeds for incorporation into the model. The coarse-scale Argos data is being used in a robust, multi-state mark-recapture model to analyze the movement of manatees between different habitat zones (e.g. riverine and offshore). This analysis provides transition probabilities as input into the individual-based model in a Monte Carlo Markov Chain framework to model the transition of manatees between different habitat zones, and to provide a measure of individual heterogeneity in transition probabilities. We will complete the analysis of manatee home ranges using a fixed kernal approach with least square cross validation smoothing to identify overall home range, and core areas of utilization. Patterns of individual heterogeneity in home range size and location will be incorporated into the model. We are using a simple reinforcement model (Rescorla-Wagner) to model shifts in manatee home ranges in response to changes in availability of freshwater. A sensitivity analysis will be conducted to evaluate the parameters with the strongest influence on the model. We will devise a set of simple restoration scenarios that vary the influx of freshwater within the network of river systems used by manatees. The "status quo" scenario will be used to output data from the model to compare to the telemetry data (task 1) and to several years of aerial survey data (completed for a previous task). The response of simulated manatees to several different scenarios representing alternative restoration scenarios will be compared and evaluated.
Because no hydrology model is available for the estuarine or marine portions of this study area, we will analyze data from monitoring stations within the study area to develop empirical relationships between freshwater discharge and salinity gradients at varying distances from point of discharge. We will vary these empirical relationships to simulate output from a hydrology model under alternative restoration scenarios. Water quality data will be obtained from several sources, including the USGS PBS project "Southwest Florida Coastal and Wetland Systems Monitoring Project"
2201 NW 40th Terrace
2201 NW 40th Terrace
U.S. Department of the Interior, U.S. Geological Survey, Center for
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