A dynamic and hierarchical spatial occupancy model for interacting species

Occupancy models are currently being developed in two major directions: to account for spatial structure and species interactions. As interacting species (e.g., predators and prey) often operate at different spatial scales, including nested spatial structure might be especially relevant in models for interacting species. Here we bridge these two model frameworks by developing a spatially hierarchical two-species occupancy model. The model is dynamic, i.e. it estimates initial occupancy, colonization and extinction probabilities - including probabilities conditional to the other species’ presence. With a simulation study, we demonstrate that the model is able to estimate parameters without bias under low, medium and high average occupancy probabilities, as well as low, medium and high detection probabilities. We further show the model’s ability to deal with sparse field data by applying it to a spatially hierarchical camera trapping dataset on a mustelid-rodent predator-prey system. The field study illustrates that the model allows estimation of species interaction effects on colonization and extinction probabilities at two spatial scales. This creates opportunities to explicitly account for the spatial structure found in many spatially nested study designs, and to study interacting species that have contrasted movement ranges with camera traps.

[1]  Kiva L. Oken,et al.  A Bayesian hierarchical occupancy model for track surveys conducted in a series of linear, spatially correlated, sites , 2011 .

[2]  J. Andrew Royle,et al.  ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE , 2002, Ecology.

[3]  W. Wilson,et al.  Pattern Formation and the Spatial Scale of Interaction between Predators and Their Prey. , 1998, Theoretical population biology.

[4]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[5]  A. F. O'connell,et al.  Multi-scale occupancy estimation and modelling using multiple detection methods , 2008 .

[6]  Ilkka Hanski,et al.  Cyclic Dynamics in a Simple Vertebrate Predator-Prey Community , 2003, Science.

[7]  J. Nichols,et al.  Testing metapopulation concepts: effects of patch characteristics and neighborhood occupancy on the dynamics of an endangered lagomorph , 2014 .

[8]  Mevin B Hooten,et al.  Dynamic occupancy models for explicit colonization processes. , 2016, Ecology.

[9]  Kjell Einar Erikstad,et al.  SCALE‐DEPENDENT PREDATOR–PREY INTERACTIONS: THE HIERARCHICAL SPATIAL DISTRIBUTION OF SEABIRDS AND PREY , 2000 .

[10]  Juniper L. Simonis,et al.  A multistate dynamic occupancy model to estimate local colonization–extinction rates and patterns of co‐occurrence between two or more interacting species , 2018, Methods in Ecology and Evolution.

[11]  J Andrew Royle,et al.  Hierarchical modeling of an invasive spread: the Eurasian Collared-Dove Streptopelia decaocto in the United States. , 2011, Ecological applications : a publication of the Ecological Society of America.

[12]  John K Kruschke,et al.  Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.

[13]  Joshua J. Millspaugh,et al.  A multispecies occupancy model for two or more interacting species , 2016 .

[14]  D. MacKenzie.  Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence , 2005 .

[15]  Eeva M. Soininen,et al.  Under the snow: a new camera trap opens the white box of subnivean ecology , 2015 .

[16]  Chris Sutherland,et al.  A demographic, spatially explicit patch occupancy model of metapopulation dynamics and persistence , 2014 .

[17]  Erkki Korpimäki,et al.  Population oscillations of boreal rodents: regulation by mustelid predators leads to chaos , 1993, Nature.

[18]  J. Andrew Royle,et al.  Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS , 2015 .

[19]  G. Guillera‐Arroita.  Modelling of species distributions, range dynamics and communities under imperfect detection: advances, challenges and opportunities , 2017 .

[20]  Mevin B. Hooten,et al.  Spatial occupancy models for large data sets , 2013 .

[21]  E. Korpimäki,et al.  The impact of predation risk from small mustelids on prey populations , 2000 .

[22]  Marc Kéry,et al.  Effects of spatial autocorrelation and imperfect detection on species distribution models , 2018 .

[23]  Martyn Plummer,et al.  JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling , 2003 .

[24]  Jeremy A. Baumgardt,et al.  Developing Rigorous Monitoring Programs: Power and Sample Size Evaluations of a Robust Method for Monitoring Bird Assemblages , 2019, Journal of Fish and Wildlife Management.

[25]  Nathaniel P. Robinson,et al.  Assessing global patterns in mammalian carnivore occupancy and richness by integrating local camera trap surveys , 2017 .

[26]  James D Nichols,et al.  Joint estimation of habitat dynamics and species interactions: disturbance reduces co-occurrence of non-native predators with an endangered toad. , 2012, The Journal of animal ecology.

[27]  James D Nichols,et al.  The roles of competition and habitat in the dynamics of populations and species distributions. , 2014, Ecology.

[28]  Claudia Wultsch,et al.  Ecological correlates of the spatial co-occurrence of sympatric mammalian carnivores worldwide. , 2018, Ecology letters.

[29]  B. Mattsson,et al.  Addressing challenges when studying mobile or episodic species: hierarchical Bayes estimation of occupancy and use , 2011 .

[30]  Lucile Marescot,et al.  Inferring wildlife poaching in Southeast Asia with multispecies dynamic occupancy models , 2019, bioRxiv.

[31]  C. Goldberg,et al.  Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring , 2020, Ecography.

[32]  José J. Lahoz-Monfort,et al.  Ignoring Imperfect Detection in Biological Surveys Is Dangerous: A Response to ‘Fitting and Interpreting Occupancy Models' , 2014, PloS one.

[33]  J. Nichols,et al.  Advances and applications of occupancy models , 2014 .

[34]  Andrew N. Stillman,et al.  Cross‐scale occupancy dynamics of a postfire specialist in response to variation across a fire regime , 2018, The Journal of animal ecology.

[35]  E. Koskela,et al.  Predator–vole interactions in northern Europe: the role of small mustelids revised , 2014, Proceedings of the Royal Society B: Biological Sciences.

[36]  Michael A. Tabak,et al.  Machine learning to classify animal species in camera trap images: applications in ecology , 2018, bioRxiv.