10.5061/DRYAD.66KC7
Abrahms, Briana
University of California, Berkeley
Sawyer, Sarah C.
United States Department of Agriculture
Jordan, Neil R.
Taronga Conservation Society Australia
UNSW Sydney
McNutt, J. Weldon
University of California, Berkeley
Wilson, Alan M.
University of London
Brashares, Justin S.
University of California, Berkeley
Data from: Does wildlife resource selection accurately inform corridor
conservation?
Dryad
dataset
2017
Lycaon pictus
step selection
conservation planning
landscape connectivity
resource selection
corridor ecology
behavioural state
landscape resistance
2017-05-25T00:00:00Z
2017-05-25T00:00:00Z
en
https://doi.org/10.1111/1365-2664.12714
2098804 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Evaluating landscape connectivity and identifying and protecting corridors
for animal movement have become central challenges in applied ecology and
conservation. Currently, resource selection analyses are widely used to
focus corridor planning where animal movement is predicted to occur. An
animal's behavioural state (e.g. foraging, dispersing) is a
significant determinant of resource selection patterns, yet has largely
been ignored in connectivity assessments. We review 16 years of
connectivity studies employing resource selection analysis to evaluate how
researchers have incorporated animal behaviour into corridor planning, and
highlight promising new approaches for identifying wildlife corridors. To
illustrate the importance of behavioural information in such analyses, we
present an empirical case study to test behaviour-specific predictions of
connectivity with long-distance dispersal movements of African wild dogs
Lycaon pictus. We conclude by recommending strategies for developing more
realistic connectivity models for future conservation efforts. Our review
indicates that most connectivity studies conflate resource selection with
connectivity requirements, which may result in misleading estimates of
landscape resistance, and lack validation of proposed connectivity models
with movement data. Our case study shows that including only directed
movement behaviour when measuring resource selection reveals markedly
different, and more accurate, connectivity estimates than a model
measuring resource selection independent of behavioural state. Synthesis
and applications. Our results, using African wild dogs as a case study,
suggest that resource selection analyses that fail to consider an
animal's behavioural state may be insufficient in targeting movement
pathways and corridors for protection. This failure may result in
misidentification of wildlife corridors and misallocation of limited
conservation resources. Our findings underscore the need for considering
patterns of animal movement in appropriate behavioural contexts to ensure
the effective application of resource selection analyses for corridor
planning.
African wild dog GPS dataGPS data collected from collared African wild
dogs.JAEfile_Fig2_DispersalPaths.csv
Botswana