Unifying population and landscape ecology with spatial capture-recapture

By: , and 



Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio‐temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population state and structure. Spatial capture–recapture (SCR) represents an individual‐based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and they have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g. camera trapping, non‐invasive DNA sampling). We describe ways in which SCR methods stand to advance the study of animal population ecology.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Unifying population and landscape ecology with spatial capture-recapture
Series title Ecography
DOI 10.1111/ecog.03170
Volume 41
Issue 3
Year Published 2017
Language English
Publisher Nordic Society Oikos
Contributing office(s) Patuxent Wildlife Research Center
Description 13 p.
First page 444
Last page 456
Google Analytic Metrics Metrics page
Additional metadata about this publication, not found in other parts of the page is in this table