Andy Royle is a Research Statistician at the Eastern Ecological Science Center in Laurel, MD.
Before that he was a statistician (1998-2004) for the U.S. FWS in the Migratory Bird Management Office where he worked primarily on waterfowl surveys and monitoring projects. Prior to that he was a visiting scientist in the Geophysical Statistics Project at the National Center for Atmospheric Reserach, Boulder, CO. He has a PhD in Statistics (1996) from North Carolina State University and a BS in Fisheries and Wildlife (1990) from Michigan State University.
Science and Products
READI-Net: A network of robotic environmental DNA samplers to enhance the early detection of aquatic biological threats
USGS researchers are working with the Monterey Bay Aquarium Research Institute to optimize autonomous, robotic samplers for detection of DNA fragments shed by biological threats (BT; invasive species, parasites, pathogens) in our nation’s waters. Finding DNA fragments (a method known as environmental DNA sampling) produced by an emerging BT in water is akin to finding a needle in a haystack—many...
Quantitative Turtle Analysis Project: Machine learning with turtles
The Quantitative Turtle Analysis Project (QTAP) was created in 2019 with the goal of investigating how machine learning can be used to study wildlife populations using capture-recapture methods. QTAP has specifically been researching how digital images of the eastern box turtle (Terrapene carolina carolina) can be used by automated programs to recognize unique individual turtles, in place of a...
Enabling AI for citizen science in fish ecology
Artificial Intelligence (AI) is revolutionizing ecology and conservation by enabling species recognition from photos and videos. Our project evaluates the capacity to expand AI for individual fish recognition for population assessment. The success of this effort would facilitate fisheries analysis at an unprecedented scale by engaging anglers and citizen scientists in imagery collection.This proje
Terrestrial wildlife and legacy oil mining on National Wildlife Refuges
Amphibian surveys are being conducted on select National Wildlife Refuges with active and/or legacy oil mining to determine species relative distribution and their risk to short- and long-term effects from exposure to crude oil and its byproducts.
Capture-recapture meets big data: integrating statistical classification with ecological models of species abundance and occurrence
Advances in new technologies such as remote cameras, noninvasive genetics and bioacoustics provide massive quantities of electronic data. Much work has been done on automated (“machine learning”) methods of classification which produce “sample class designations” (e.g., identification of species or individuals) that are regarded as observed data in ecological models. However, these “data” are actu...
Spatio-Temporal Statistical Models for Forecasting Climate Change Effects on Bird Distribution
Ecological indicators of climate change are needed to measure concurrent changes in ecological systems, inform management decisions, and forecast the consequences of climate change. We seek to develop robust bird-based, climate-change indicators using North American Breeding Bird Survey data.
Hierarchical Models of Animal Abundance and Occurrence
The Challenge: 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...
Spatial Capture-Recapture Models to Estimate Abundance and Density of Animal Populations
The Challenge: For decades, capture-recapture methods have been the cornerstone of ecological statistics as applied to population biology. While capture-recapture has become the standard sampling and analytical framework for the study of population processes (Williams, Nichols & Conroy 2002) it has advanced independent of and remained unconnected to the spatial structure of the population or the...
Modeling species response to environmental change: development of integrated, scalable Bayesian models of population persistence
Estimating species response to environmental change is a key challenge for ecologists and a core mission of the USGS. Effective forecasting of species response requires models that are detailed enough to capture critical processes and at the same time general enough to allow broad application. This tradeoff is difficult to reconcile with most existing methods. We propose to extend and combine exis
SERAP: Assessment of Climate and Land Use Change Impacts on Terrestrial Species
Researchers from North Carolina State University and the USGS integrated models of urbanization and vegetation dynamics with the regional climate models to predict vegetation dynamics and assess how landscape change could impact priority species, including North American land birds. This integrated ensemble of models can be used to predict locations where responses to climate change are most lik
Filter Total Items: 195
Drivers and facilitators of the illegal killing of elephants across 64 African sites
Ivory poaching continues to threaten African elephants. We (1) used criminology theory and literature evidence to generate hypotheses about factors that may drive, facilitate or motivate poaching, (2) identified datasets representing these factors, and (3) tested those factors with strong hypotheses and sufficient data quality for empirical associations with poaching. We advance on previous analys
Sharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations
Meeting food/wood demands with increasing human population and per-capita consumption is a pressing conservation issue, and is often framed as a choice between land sparing and land sharing. Although most empirical studies comparing the efficacy of land sparing and sharing supported land sparing, land sharing may be more efficient if its performance is tested by rigorous experimental design and ha
Know what you don't know: Embracing state uncertainty in disease-structured multistate models
Hidden Markov models (HMMs) are broadly applicable hierarchical models that derive their utility from separating state processes from observation processes yielding the data. Multistate models such as mark–recapture and dynamic multistate occupancy models are HMMs frequently used in ecology. In their early formulations, states, such as pathogen infection status, were assumed to be perfectly observ
Density estimation in terrestrial chelonian populations using spatial capture–recapture and search–encounter surveys
Having an accurate estimate of population size and density is imperative to the conservation of chelonian species and a central objective of many monitoring programs. Capture–recapture and related methods are widely used to obtain information about population size of chelonians. However, classical capture–recapture methods have strict spatial sampling requirements and do not account for lack of ge
Numbers and presence of guarding dogs affect wolf and leopard predation on livestock in northeastern Iran
Livestock predation can pose socio-economic impacts on rural livelihoods and is the main cause of retaliatory killings of carnivores in many countries. Therefore, appropriate interventions to reduce livestock predation, lower conflict and promote coexistence are needed. Livestock guarding dogs have been traditionally used to reduce predation, yet details regarding the use of dogs, especially the n
Spatial dynamic N-mixture models with interspecific interactions
Interspecific interactions and movement are key factors that drive the coexistence of metapopulations in heterogenous landscapes. Yet, it is challenging to understand these factors because separating movement from local population processes relied on capture-based data that are difficult to collect. Recent development of spatial dynamic N-mixture models (SDNMs) made it possible to draw inference o
Estimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity
1. Autonomous Recording Units (ARUs) are now widely used to survey communities of species. These surveys generate spatially and temporally replicated counts of unmarked animals, but such data typically include false negatives and misclassified detections, both of which may vary across sites in proportion to abundance. These data challenges can bias estimates of occupancy, and the typical approach
Estimating species misclassification with occupancy dynamics and encounter rates: A semi-supervised, individual-level approach
1. Large-scale, long-term biodiversity monitoring is essential to conservation, land management, and identifying threats to biodiversity. However, multispecies surveys are prone to various types of observation error, including false positive/negative detection, and misclassification, where a species is thought to have been encountered but not correctly identified. Previous methods assume an imperf
Quantifying the relationship between prey density, livestock and illegal killing of leopards
Many large mammalian carnivores are facing population declines due to illegal killing (e.g., shooting) and habitat modification (e.g., livestock farming). Illegal killing occurs cryptically and hence is difficult to detect. However, reducing illegal killing requires a solid understanding of its magnitude and underlying drivers, while accounting for the imperfect detection of illegal killing events
A novel application of hierarchical modelling to decouple sampling artifacts from socio-ecological effects on poaching intensity
Poaching is a global driver of wildlife population decline, including inside protected areas (PAs). Reducing poaching requires an understanding of its cryptic drivers and accurately quantifying poaching scales and intensity. There is little quantification of how poaching is affected by law enforcement intensity (e.g., ranger stations) versus economic factors (e.g., unemployment), while simultaneou
Leveraging community science data for population assessments during a pandemic
The COVID-19 pandemic has disrupted field research programs, making conservation and management decision-making more challenging. However, it may be possible to conduct population assessments using integrated models that combine community science data with existing data from structured surveys. We developed a space-time integrated model to characterize spatial and temporal variability in populatio
Evaluation of a two-season banding program to estimate and model migratory bird survival
The management of North American waterfowl is predicated on long-term, continental scale banding implemented prior to the hunting season (i.e., July–September) and subsequent reporting of bands recovered by hunters. However, single-season banding and encounter operations have a number of characteristics that limit their application to estimating demographic rates and evaluating hypothesized limiti
PROGRAM SPACECAP
A Program to Estimate Animal Abundance and Density using Spatially-Explicit Capture-Recapture
Science and Products
- Science
READI-Net: A network of robotic environmental DNA samplers to enhance the early detection of aquatic biological threats
USGS researchers are working with the Monterey Bay Aquarium Research Institute to optimize autonomous, robotic samplers for detection of DNA fragments shed by biological threats (BT; invasive species, parasites, pathogens) in our nation’s waters. Finding DNA fragments (a method known as environmental DNA sampling) produced by an emerging BT in water is akin to finding a needle in a haystack—many...Quantitative Turtle Analysis Project: Machine learning with turtles
The Quantitative Turtle Analysis Project (QTAP) was created in 2019 with the goal of investigating how machine learning can be used to study wildlife populations using capture-recapture methods. QTAP has specifically been researching how digital images of the eastern box turtle (Terrapene carolina carolina) can be used by automated programs to recognize unique individual turtles, in place of a...Enabling AI for citizen science in fish ecology
Artificial Intelligence (AI) is revolutionizing ecology and conservation by enabling species recognition from photos and videos. Our project evaluates the capacity to expand AI for individual fish recognition for population assessment. The success of this effort would facilitate fisheries analysis at an unprecedented scale by engaging anglers and citizen scientists in imagery collection.This projeTerrestrial wildlife and legacy oil mining on National Wildlife Refuges
Amphibian surveys are being conducted on select National Wildlife Refuges with active and/or legacy oil mining to determine species relative distribution and their risk to short- and long-term effects from exposure to crude oil and its byproducts.Capture-recapture meets big data: integrating statistical classification with ecological models of species abundance and occurrence
Advances in new technologies such as remote cameras, noninvasive genetics and bioacoustics provide massive quantities of electronic data. Much work has been done on automated (“machine learning”) methods of classification which produce “sample class designations” (e.g., identification of species or individuals) that are regarded as observed data in ecological models. However, these “data” are actu...Spatio-Temporal Statistical Models for Forecasting Climate Change Effects on Bird Distribution
Ecological indicators of climate change are needed to measure concurrent changes in ecological systems, inform management decisions, and forecast the consequences of climate change. We seek to develop robust bird-based, climate-change indicators using North American Breeding Bird Survey data.Hierarchical Models of Animal Abundance and Occurrence
The Challenge: 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...Spatial Capture-Recapture Models to Estimate Abundance and Density of Animal Populations
The Challenge: For decades, capture-recapture methods have been the cornerstone of ecological statistics as applied to population biology. While capture-recapture has become the standard sampling and analytical framework for the study of population processes (Williams, Nichols & Conroy 2002) it has advanced independent of and remained unconnected to the spatial structure of the population or the...Modeling species response to environmental change: development of integrated, scalable Bayesian models of population persistence
Estimating species response to environmental change is a key challenge for ecologists and a core mission of the USGS. Effective forecasting of species response requires models that are detailed enough to capture critical processes and at the same time general enough to allow broad application. This tradeoff is difficult to reconcile with most existing methods. We propose to extend and combine exisSERAP: Assessment of Climate and Land Use Change Impacts on Terrestrial Species
Researchers from North Carolina State University and the USGS integrated models of urbanization and vegetation dynamics with the regional climate models to predict vegetation dynamics and assess how landscape change could impact priority species, including North American land birds. This integrated ensemble of models can be used to predict locations where responses to climate change are most lik - Multimedia
- Publications
Filter Total Items: 195
Drivers and facilitators of the illegal killing of elephants across 64 African sites
Ivory poaching continues to threaten African elephants. We (1) used criminology theory and literature evidence to generate hypotheses about factors that may drive, facilitate or motivate poaching, (2) identified datasets representing these factors, and (3) tested those factors with strong hypotheses and sufficient data quality for empirical associations with poaching. We advance on previous analysSharing land via keystone structure: Retaining naturally regenerated trees may efficiently benefit birds in plantations
Meeting food/wood demands with increasing human population and per-capita consumption is a pressing conservation issue, and is often framed as a choice between land sparing and land sharing. Although most empirical studies comparing the efficacy of land sparing and sharing supported land sparing, land sharing may be more efficient if its performance is tested by rigorous experimental design and haKnow what you don't know: Embracing state uncertainty in disease-structured multistate models
Hidden Markov models (HMMs) are broadly applicable hierarchical models that derive their utility from separating state processes from observation processes yielding the data. Multistate models such as mark–recapture and dynamic multistate occupancy models are HMMs frequently used in ecology. In their early formulations, states, such as pathogen infection status, were assumed to be perfectly observDensity estimation in terrestrial chelonian populations using spatial capture–recapture and search–encounter surveys
Having an accurate estimate of population size and density is imperative to the conservation of chelonian species and a central objective of many monitoring programs. Capture–recapture and related methods are widely used to obtain information about population size of chelonians. However, classical capture–recapture methods have strict spatial sampling requirements and do not account for lack of geNumbers and presence of guarding dogs affect wolf and leopard predation on livestock in northeastern Iran
Livestock predation can pose socio-economic impacts on rural livelihoods and is the main cause of retaliatory killings of carnivores in many countries. Therefore, appropriate interventions to reduce livestock predation, lower conflict and promote coexistence are needed. Livestock guarding dogs have been traditionally used to reduce predation, yet details regarding the use of dogs, especially the nSpatial dynamic N-mixture models with interspecific interactions
Interspecific interactions and movement are key factors that drive the coexistence of metapopulations in heterogenous landscapes. Yet, it is challenging to understand these factors because separating movement from local population processes relied on capture-based data that are difficult to collect. Recent development of spatial dynamic N-mixture models (SDNMs) made it possible to draw inference oEstimating occupancy from autonomous recording unit data in the presence of misclassifications and detection heterogeneity
1. Autonomous Recording Units (ARUs) are now widely used to survey communities of species. These surveys generate spatially and temporally replicated counts of unmarked animals, but such data typically include false negatives and misclassified detections, both of which may vary across sites in proportion to abundance. These data challenges can bias estimates of occupancy, and the typical approachEstimating species misclassification with occupancy dynamics and encounter rates: A semi-supervised, individual-level approach
1. Large-scale, long-term biodiversity monitoring is essential to conservation, land management, and identifying threats to biodiversity. However, multispecies surveys are prone to various types of observation error, including false positive/negative detection, and misclassification, where a species is thought to have been encountered but not correctly identified. Previous methods assume an imperfQuantifying the relationship between prey density, livestock and illegal killing of leopards
Many large mammalian carnivores are facing population declines due to illegal killing (e.g., shooting) and habitat modification (e.g., livestock farming). Illegal killing occurs cryptically and hence is difficult to detect. However, reducing illegal killing requires a solid understanding of its magnitude and underlying drivers, while accounting for the imperfect detection of illegal killing eventsA novel application of hierarchical modelling to decouple sampling artifacts from socio-ecological effects on poaching intensity
Poaching is a global driver of wildlife population decline, including inside protected areas (PAs). Reducing poaching requires an understanding of its cryptic drivers and accurately quantifying poaching scales and intensity. There is little quantification of how poaching is affected by law enforcement intensity (e.g., ranger stations) versus economic factors (e.g., unemployment), while simultaneouLeveraging community science data for population assessments during a pandemic
The COVID-19 pandemic has disrupted field research programs, making conservation and management decision-making more challenging. However, it may be possible to conduct population assessments using integrated models that combine community science data with existing data from structured surveys. We developed a space-time integrated model to characterize spatial and temporal variability in populatioEvaluation of a two-season banding program to estimate and model migratory bird survival
The management of North American waterfowl is predicated on long-term, continental scale banding implemented prior to the hunting season (i.e., July–September) and subsequent reporting of bands recovered by hunters. However, single-season banding and encounter operations have a number of characteristics that limit their application to estimating demographic rates and evaluating hypothesized limiti - Software
PROGRAM SPACECAP
A Program to Estimate Animal Abundance and Density using Spatially-Explicit Capture-Recapture