Open AccessUsing individual tracking data to validate the predictions of species distribution models
Author(s) -
Pinto Cecilia,
Thorburn James A.,
Neat Francis,
Wright Peter J.,
Wright Serena,
Scott Beth E.,
Cornulier Thomas,
Travis Justin M. J.
Publication year - 2016
Publication title -
diversity and distributions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.918
H-Index - 118
eISSN - 1472-4642
pISSN - 1366-9516
DOI - 10.1111/ddi.12437
Subject(s) - generalized additive model , geolocation , skate , environmental data , spatial analysis , geography , species distribution , distribution (mathematics) , ecology , habitat , statistics , environmental science , computer science , mathematics , remote sensing , biology , mathematical analysis , world wide web
Aim Estimating environmental suitability from species distribution data is crucial in defining spatial conservation measures. To this end, species distribution models ( SDM s) are commonly applied, but seldom validated by completely independent data. Here, we use data on individual tracks derived from electronic tags as an alternative means of validating SDM outputs. Location West coast of Scotland, NE Atlantic. Methods We used a binomial generalized additive model ( GAM ) to predict the environmental suitability for flapper skate ( Dipturus cf. intermedia ) in Scottish waters. The GAM modelled relative habitat usage as a function of environmental variables using presence–absence data obtained from scientific trawl surveys. Additional data obtained from electronic tags attached to six individual flapper skates were used to estimate individual tracks using a tidal‐based geolocation model. Concordance between individual tracks and GAM ‐predicted maps of relative habitat usage ( RHU ) was tested by comparing predicted RHU between estimated tracks and randomly generated tracks. Results Environmental suitability for the flapper skate was driven by depth and distance from the coast in the SDM . We found high spatial concordance between the estimated tracks of the six tagged individuals and regions of high RHU predicted by the SDM . Main conclusions Integrating outputs from an independent data source allowed us to validate predictions from a species distribution model ( SDM ). The integration of individual‐ and population‐level data sources increases confidence in the outputs being used to define spatial conservation measures. The information on flapper skate distribution provided by this study provides a useful framework for considering spatial conservation measures for this species.