Distinguishing geographical range shifts from artefacts of detectability and sampling effort

Bates, Amanda E., Bird, Tomas J., Stuart-Smith, Rick D., Wernberg, Thomas, Sunday, Jennifer M., Barrett, Neville S., Edgar, Graham J., Frusher, Stewart, Hobday, Alistair J., Pecl, Gretta T., Smale, Dan A., McCarthy, Michael and Richardson, David M. (2015) Distinguishing geographical range shifts from artefacts of detectability and sampling effort. Diversity and Distributions, 21 (1), 13-22. (doi:10.1111/ddi.12263).

Abstract

Aim:
The redistribution of species with climate change is well documented. Even so, the relative contribution of species detectability to the variation in measured range shift rates among species is poorly understood. How can true range shifts be discerned from sampling artefacts?

Location:
Australia.

Methods:
We simulate range shifts for species which differ in their abundance for comparison to patterns derived from empirical range shift data from two regional-scale (100s km) empirical studies. We demonstrate the use of spatial occupancy data in a distance-to-edge (DTE) model to assess changes in geographical range edges of fish species within a temperate reef fish community.

Results:
Simulations identified how sampling design can produce relatively larger error in range shift estimates in less abundant species, patterns that correspond with those observed in real data. Application of the DTE model allowed us to estimate the location of the true range edge with high accuracy in common species. In addition, upper confidence bounds for range edge estimates identified species with range edges that have likely shifted in location.

Conclusions:
Simulation and modelling approaches used to quantify the level of confidence that can be placed in observed range shifts are particularly valuable for studies of marine species, where observations are typically few and patchy. Given the observed variability in range shift estimates, the inclusion of confidence bounds on estimates of geographical range edges will advance our capacity to disentangle true distributional change from artefacts of sampling design.

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