Occupancy
Many wildlife studies seek to understand changes or differences in the proportion of sites occupied by a species of interest. These studies are hampered by imperfect detection of these species, which can result in some sites appearing to be unoccupied that are actually occupied. Occupancy models solve this problem and produce unbiased estimates of occupancy (ie, occurrence) and related parameters (eg, habitat variables) . Required data (detection/non-detection information) are relatively simple and inexpensive, requiring multiple samples and randomization of the sampling grid. Occupancy models were first developed by Patuxent scientists and they have revolutionized how biologists sample animal communities.
Hierarchical Models for Estimation of Population Parameters
Much of wildlife research consists of the description of variation in data. Some of the variation results from spatial and temporal change in populations, while some results from biologically irrelevant sampling variation induced by the process of data collection. Distinguishing relevant from irrelevant variation is the first task of statistical analysis, but the job does not end there. Even if the true values of population parameters were known, without the contamination of sampling variation, the investigation of population processes would require an evaluation of pattern among parameters.
Development of Statistical Methods for Biological Applications
Wildlife science and management are guided by data, and it is unquestionably the case that the greatest success occurs when good data are analyzed by good statistical methods.
Development of Computer Software for the Analysis of Animal Population Parameters
Biologists at USGS Patuxent, as well as cooperating agencies are constantly looking for new ways of answering questions about the status of animal populations and how animal populations change over time. To address these questions, data are collected on captures and or sightings of animals which can be used to estimate parameters which affect the population using legacy software. Over time, new questions and methods for addressing these questions arise which require new computer software.
Development of Patch Occupancy Models for Assessing the Spatial Distribution of Organisms
A variety of important questions about the conservation and management of natural resources requires information about the spatial distribution of organisms. For species of conservation concern, the size of a species’ range is a criterion used to assign species status as threatened or endangered. For invasive species and disease organisms, the dynamics of the species range expansion are relevant to efforts to both control invasions and to protect vulnerable species. In this period of rapid global change, it will be important to be able to understand and predict dynamics of species ranges as habitats change in suitability.
Statistical Research for the USGS - Amphibian Research and Monitoring Initiative
Since its inception in 2002 the USGS Amphibian Research and Monitoring Initiative (ARMI) has taken the lead in monitoring amphibian populations on Department of Interior lands. ARMI scientists work on a broad spectrum of species and management issues to address the core causes of amphibian declines. In many cases, research requires complex study designs and innovative methods. A key program need for ARMI has been to develop a robust set of quantitative methods for estimating patterns and dynamics of species presence.
Assessing Endangered Marsh Rabbit and Woodrat Habitat use and Predator Population Dynamics
Feral and free-ranging domestic cats (Felis catus) have strong negative effects on wildlife, particularly in island ecosystems such as the Florida Keys. We deployed camera traps to study free-ranging cats in National Wildlife Refuges and state parks on Big Pine Key and Key Largo and used spatial models to estimate cat population dynamics and stable isotope analyses to examine cat diets. Top models separated cats based on movements and activity patterns and represent feral, semi-feral, and indoor/outdoor house cats. We provide evidence that cat groups within a population move different distances, exhibit different activity patterns, and that individuals consume wildlife at different rates - all of which have implications for managing this invasive predator.
Hierarchical Models of Animal Abundance and Occurrence
Research goals of this project are to develop models, statistical methods, sampling strategies and tools for inference about animal population status from survey data. Survey data are always subject to a number of observation processes that induce bias and error. In particular, inferences are based on spatial sampling – we can only ever sample a subset of locations where species occur --and imperfect detection – species or individuals might go undetected in the sample. Principles of hierarchical modeling can be applied directly to accommodate both features of ecological data. Prior to the development of hierarchical models at PWRC, studies of unmarked populations focused on simplistic descriptions of distribution patterns and temporal trends. Hierarchical models have advanced the field of population ecology by enabling the estimation of demographic and movement parameters that previously could only be obtained using costly field methods. Ecologists can now make inferences about population dynamics at broad spatial and temporal scales using models designed specifically for this task.
Design and Analysis of Surveys for Estimation of Temporal and Spatial Change in Animal Populations
Population status information is required for management of migratory bird populations, and structured decision making and adaptive Management place additional emphasis on the need for rigorous survey designs and robust estimation methods. The North American Breeding Bird Survey (BBS) and Christmas Bird Count (CBC) provide continent-scale information on breeding and wintering populations of >450 species of North American birds, and for many species these two surveys are our only data source for population status and trend information. Appropriate analyses of these important surveys require sophisticated methods to accommodate variation in survey efficiency over the large areas covered by the surveys and to control for factors that influence detection of birds. Factors such as observer quality and effort, if not appropriately controlled for in the analysis, can lead to biased estimates of population change.
Development of Methods Associated with Animal Population Dynamics
Conservation and management of natural animal populations requires knowledge of their dynamics and associated environmental and management influences. Specifically, informed management requires periodic estimates of system state (e.g., population size) and models for projecting consequences of management actions for subsequent state dynamics. However, it is very difficult to draw strong inferences about system state and dynamics for natural animal populations and communities. The primary challenges are: (1) the tendency of animal densities to vary substantially over space and (2) the likelihood that any method of sampling animals (capture, direct observation, etc.) will produce counts that represent some unknown fraction of the true number of animals in the sampled locations.
WaterSMART: Apalachicola/Chattahoochee/ Flint River (ACF) Basin
The DOI WaterSMART (Sustain and Manage America’s Resources for Tomorrow) initiative is developing data and tools to help water managers identify current and future water shortages, for humans and for freshwater ecosystems. Fishes, for example, can decline in diversity and abundance when streamflow becomes too low, for too long. However, ecologists find that effects of declining streamflow can vary depending on stream characteristics and on traits of local species, confounding predictions of ecological outcomes. Scientists thus need data on ecological responses to low streamflow in differing physical and biological contexts to better inform water management decisions.
Many wildlife studies seek to understand changes or differences in the proportion of sites occupied by a species of interest. These studies are hampered by imperfect detection of these species, which can result in some sites appearing to be unoccupied that are actually occupied. Occupancy models solve this problem and produce unbiased estimates of occupancy (ie, occurrence) and related parameters (eg, habitat variables) . Required data (detection/non-detection information) are relatively simple and inexpensive, requiring multiple samples and randomization of the sampling grid. Occupancy models were first developed by Patuxent scientists and they have revolutionized how biologists sample animal communities.
Hierarchical Models for Estimation of Population Parameters
Much of wildlife research consists of the description of variation in data. Some of the variation results from spatial and temporal change in populations, while some results from biologically irrelevant sampling variation induced by the process of data collection. Distinguishing relevant from irrelevant variation is the first task of statistical analysis, but the job does not end there. Even if the true values of population parameters were known, without the contamination of sampling variation, the investigation of population processes would require an evaluation of pattern among parameters.
Development of Statistical Methods for Biological Applications
Wildlife science and management are guided by data, and it is unquestionably the case that the greatest success occurs when good data are analyzed by good statistical methods.
Development of Computer Software for the Analysis of Animal Population Parameters
Biologists at USGS Patuxent, as well as cooperating agencies are constantly looking for new ways of answering questions about the status of animal populations and how animal populations change over time. To address these questions, data are collected on captures and or sightings of animals which can be used to estimate parameters which affect the population using legacy software. Over time, new questions and methods for addressing these questions arise which require new computer software.
Development of Patch Occupancy Models for Assessing the Spatial Distribution of Organisms
A variety of important questions about the conservation and management of natural resources requires information about the spatial distribution of organisms. For species of conservation concern, the size of a species’ range is a criterion used to assign species status as threatened or endangered. For invasive species and disease organisms, the dynamics of the species range expansion are relevant to efforts to both control invasions and to protect vulnerable species. In this period of rapid global change, it will be important to be able to understand and predict dynamics of species ranges as habitats change in suitability.
Statistical Research for the USGS - Amphibian Research and Monitoring Initiative
Since its inception in 2002 the USGS Amphibian Research and Monitoring Initiative (ARMI) has taken the lead in monitoring amphibian populations on Department of Interior lands. ARMI scientists work on a broad spectrum of species and management issues to address the core causes of amphibian declines. In many cases, research requires complex study designs and innovative methods. A key program need for ARMI has been to develop a robust set of quantitative methods for estimating patterns and dynamics of species presence.
Assessing Endangered Marsh Rabbit and Woodrat Habitat use and Predator Population Dynamics
Feral and free-ranging domestic cats (Felis catus) have strong negative effects on wildlife, particularly in island ecosystems such as the Florida Keys. We deployed camera traps to study free-ranging cats in National Wildlife Refuges and state parks on Big Pine Key and Key Largo and used spatial models to estimate cat population dynamics and stable isotope analyses to examine cat diets. Top models separated cats based on movements and activity patterns and represent feral, semi-feral, and indoor/outdoor house cats. We provide evidence that cat groups within a population move different distances, exhibit different activity patterns, and that individuals consume wildlife at different rates - all of which have implications for managing this invasive predator.
Hierarchical Models of Animal Abundance and Occurrence
Research goals of this project are to develop models, statistical methods, sampling strategies and tools for inference about animal population status from survey data. Survey data are always subject to a number of observation processes that induce bias and error. In particular, inferences are based on spatial sampling – we can only ever sample a subset of locations where species occur --and imperfect detection – species or individuals might go undetected in the sample. Principles of hierarchical modeling can be applied directly to accommodate both features of ecological data. Prior to the development of hierarchical models at PWRC, studies of unmarked populations focused on simplistic descriptions of distribution patterns and temporal trends. Hierarchical models have advanced the field of population ecology by enabling the estimation of demographic and movement parameters that previously could only be obtained using costly field methods. Ecologists can now make inferences about population dynamics at broad spatial and temporal scales using models designed specifically for this task.
Design and Analysis of Surveys for Estimation of Temporal and Spatial Change in Animal Populations
Population status information is required for management of migratory bird populations, and structured decision making and adaptive Management place additional emphasis on the need for rigorous survey designs and robust estimation methods. The North American Breeding Bird Survey (BBS) and Christmas Bird Count (CBC) provide continent-scale information on breeding and wintering populations of >450 species of North American birds, and for many species these two surveys are our only data source for population status and trend information. Appropriate analyses of these important surveys require sophisticated methods to accommodate variation in survey efficiency over the large areas covered by the surveys and to control for factors that influence detection of birds. Factors such as observer quality and effort, if not appropriately controlled for in the analysis, can lead to biased estimates of population change.
Development of Methods Associated with Animal Population Dynamics
Conservation and management of natural animal populations requires knowledge of their dynamics and associated environmental and management influences. Specifically, informed management requires periodic estimates of system state (e.g., population size) and models for projecting consequences of management actions for subsequent state dynamics. However, it is very difficult to draw strong inferences about system state and dynamics for natural animal populations and communities. The primary challenges are: (1) the tendency of animal densities to vary substantially over space and (2) the likelihood that any method of sampling animals (capture, direct observation, etc.) will produce counts that represent some unknown fraction of the true number of animals in the sampled locations.
WaterSMART: Apalachicola/Chattahoochee/ Flint River (ACF) Basin
The DOI WaterSMART (Sustain and Manage America’s Resources for Tomorrow) initiative is developing data and tools to help water managers identify current and future water shortages, for humans and for freshwater ecosystems. Fishes, for example, can decline in diversity and abundance when streamflow becomes too low, for too long. However, ecologists find that effects of declining streamflow can vary depending on stream characteristics and on traits of local species, confounding predictions of ecological outcomes. Scientists thus need data on ecological responses to low streamflow in differing physical and biological contexts to better inform water management decisions.