Consensus forecasting of species distributions: the effects of niche model performance and niche properties

PloS One
Lei ZhangLinlin Wang

Abstract

Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species' geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species' ranges. Multiple stepwise regression models showed the three factors (niche mar...Continue Reading

References

Oct 3, 2006·Trends in Ecology & Evolution·Miguel B Araújo, Mark New
Mar 13, 2014·Global Change Biology·Gaël Grenouillet, Lise Comte

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Methods Mentioned

BETA
PCA
MDA

Software Mentioned

ClimateBC
ClimateChina
R
ENFA
ArcGIS9
MDA
R package “ adehabitatHS ”
BIOMOD

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