Andy Royle, Ph.D.
Andy Royle is a Research Statistician at the Eastern Ecological Science Center in Laurel, MD.
Andy Royle is a Senior Scientist at USGS Eastern Ecological Science Center (Patuxent). At EESC, he is engaged in the development of statistical methods and analytic tools for animal demographic modeling, statistical inference and sampling wildlife populations and communities. His current research is focused on hierarchical models of animal abundance and occurrence, and the development of spatial capture-recapture methods and applications. He has authored or coauthored 6 books on quantitative analysis in ecology including the recent book Applied Hierarchical Models Vols. 1 and 2 (2016 and 2021, with Marc Kéry).
Professional Experience
Statistician (1998-2004) for the U.S. FWS in the Migratory Bird Management Office where he worked primarily on waterfowl surveys and monitoring projects
visiting scientist in the Geophysical Statistics Project at the National Center for Atmospheric Research, Boulder, CO.
Education and Certifications
PhD in Statistics (1996) from North Carolina State University
BS in Fisheries and Wildlife (1990) from Michigan State University
Science and Products
Filter Total Items: 198
Modeling abundance using hierarchical distance sampling
In this chapter, we provide an introduction to classical distance sampling ideas for point and line transect data, and for continuous and binned distance data. We introduce the conditional and the full likelihood, and we discuss Bayesian analysis of these models in BUGS using the idea of data augmentation, which we discussed in Chapter 7. We then extend the basic ideas to the problem of hierarchic
Authors
Andy Royle, Marc Kery
Estimating abundance
This chapter provides a non-technical overview of ‘closed population capture–recapture’ models, a class of well-established models that are widely applied in ecology, such as removal sampling, covariate models, and distance sampling. These methods are regularly adopted for studies of reptiles, in order to estimate abundance from counts of marked individuals while accounting for imperfect detection
Authors
Chris Sutherland, Andy Royle
What are hierarchical models and how do we analyze them?
In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood a
Authors
Andy Royle
Advanced hierarchical distance sampling
In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence o
Authors
Andy Royle
Spatial capture-recapture models allowing Markovian transience or dispersal
Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatial
Authors
J. Andrew Royle, Angela K. Fuller, Chris Sutherland
Comparing spatial capture–recapture modeling and nest count methods to estimate orangutan densities in the Wehea Forest, East Kalimantan, Indonesia
Accurate information on the density and abundance of animal populations is essential for understanding species' ecology and for conservation planning, but is difficult to obtain. The endangered orangutan (Pongo spp.) is an example; due to its elusive behavior and low densities, researchers have relied on methods that convert nest counts to orangutan densities and require substantial effort for re
Authors
Stephanie N. Spehar, Brent Loken, Yaya Rayadin, J. Andrew Royle
Estimating population size for Capercaillie (Tetrao urogallus L.) with spatial capture-recapture models based on genotypes from one field sample
We conducted a survey of an endangered and cryptic forest grouse, the capercaillie Tetrao urogallus, based on droppings collected on two sampling occasions in eight forest fragments in central Switzerland in early spring 2009. We used genetic analyses to sex and individually identify birds. We estimated sex-dependent detection probabilities and population size using a modern spatial capture-recapt
Authors
Pierre Mollet, Marc Kery, Beth Gardner, Gilberto Pasinelli, Andy Royle
Book review: Analysis of capture–recapture data
Analysis of Capture–Recapture Data by McCrea and Morgan is an excellent, easy to read monograph about capture–recapture models. In this book, the authors provide a concise overview of traditional closed population capture–recapture models (Models M0, Mb, Mh, etc.), individual covariate models, and open population models such as the Cormack–Jolly–Seber, Jolly–Seber models, multi-state models, and m
Authors
Andy Royle
Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks
Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A recently proposed extension of spatial capture-recapture (SCR) models resolve
Authors
Christopher Sutherland, Angela K. Fuller, J. Andrew Royle
Small mammal use of native warm-season and non-native cool-season grass forage fields
Recent emphasis has been put on establishing native warm-season grasses for forage production because it is thought native warm-season grasses provide higher quality wildlife habitat than do non-native cool-season grasses. However, it is not clear whether native warm-season grass fields provide better resources for small mammals than currently are available in non-native cool-season grass forage p
Authors
Ryan L Klimstra, Christopher E. Moorman, Sarah J. Converse, J. Andrew Royle, Craig A Harper
Likelihood analysis of spatial capture-recapture models for stratified or class structured populations
We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which fre
Authors
J. Andrew Royle, Christopher S. Sutherland, Angela K. Fuller, Catherine C. Sun
An open-population hierarchical distance sampling model
Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estima
Authors
Rachel Sollmann, Beth Gardner, Richard B Chandler, J. Andrew Royle, T Scott Sillett
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- Publications
Filter Total Items: 198
Modeling abundance using hierarchical distance sampling
In this chapter, we provide an introduction to classical distance sampling ideas for point and line transect data, and for continuous and binned distance data. We introduce the conditional and the full likelihood, and we discuss Bayesian analysis of these models in BUGS using the idea of data augmentation, which we discussed in Chapter 7. We then extend the basic ideas to the problem of hierarchicAuthorsAndy Royle, Marc KeryEstimating abundance
This chapter provides a non-technical overview of ‘closed population capture–recapture’ models, a class of well-established models that are widely applied in ecology, such as removal sampling, covariate models, and distance sampling. These methods are regularly adopted for studies of reptiles, in order to estimate abundance from counts of marked individuals while accounting for imperfect detectionAuthorsChris Sutherland, Andy RoyleWhat are hierarchical models and how do we analyze them?
In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood aAuthorsAndy RoyleAdvanced hierarchical distance sampling
In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence oAuthorsAndy RoyleSpatial capture-recapture models allowing Markovian transience or dispersal
Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatialAuthorsJ. Andrew Royle, Angela K. Fuller, Chris SutherlandComparing spatial capture–recapture modeling and nest count methods to estimate orangutan densities in the Wehea Forest, East Kalimantan, Indonesia
Accurate information on the density and abundance of animal populations is essential for understanding species' ecology and for conservation planning, but is difficult to obtain. The endangered orangutan (Pongo spp.) is an example; due to its elusive behavior and low densities, researchers have relied on methods that convert nest counts to orangutan densities and require substantial effort for reAuthorsStephanie N. Spehar, Brent Loken, Yaya Rayadin, J. Andrew RoyleEstimating population size for Capercaillie (Tetrao urogallus L.) with spatial capture-recapture models based on genotypes from one field sample
We conducted a survey of an endangered and cryptic forest grouse, the capercaillie Tetrao urogallus, based on droppings collected on two sampling occasions in eight forest fragments in central Switzerland in early spring 2009. We used genetic analyses to sex and individually identify birds. We estimated sex-dependent detection probabilities and population size using a modern spatial capture-recaptAuthorsPierre Mollet, Marc Kery, Beth Gardner, Gilberto Pasinelli, Andy RoyleBook review: Analysis of capture–recapture data
Analysis of Capture–Recapture Data by McCrea and Morgan is an excellent, easy to read monograph about capture–recapture models. In this book, the authors provide a concise overview of traditional closed population capture–recapture models (Models M0, Mb, Mh, etc.), individual covariate models, and open population models such as the Cormack–Jolly–Seber, Jolly–Seber models, multi-state models, and mAuthorsAndy RoyleModelling non-Euclidean movement and landscape connectivity in highly structured ecological networks
Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A recently proposed extension of spatial capture-recapture (SCR) models resolveAuthorsChristopher Sutherland, Angela K. Fuller, J. Andrew RoyleSmall mammal use of native warm-season and non-native cool-season grass forage fields
Recent emphasis has been put on establishing native warm-season grasses for forage production because it is thought native warm-season grasses provide higher quality wildlife habitat than do non-native cool-season grasses. However, it is not clear whether native warm-season grass fields provide better resources for small mammals than currently are available in non-native cool-season grass forage pAuthorsRyan L Klimstra, Christopher E. Moorman, Sarah J. Converse, J. Andrew Royle, Craig A HarperLikelihood analysis of spatial capture-recapture models for stratified or class structured populations
We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which freAuthorsJ. Andrew Royle, Christopher S. Sutherland, Angela K. Fuller, Catherine C. SunAn open-population hierarchical distance sampling model
Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimaAuthorsRachel Sollmann, Beth Gardner, Richard B Chandler, J. Andrew Royle, T Scott Sillett - Software
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