Genes to the Niche! Five reasons why genetic information can improve predictive niche models and their underlying theory

Jan O. Engler (1), Niko Balkenhol (2), Catherine H. Graham (3)

1 Zoological Research Museum Koenig, Adenauerallee 160, D‐53113 Bonn, Germany, j.engler.zfmk@uni‐, @engler_j

2 Department of Wildlife Sciences, University of Göttingen, Büsgenweg 3, D‐37077 Göttingen, Germany, niko.balkenhol@forst.uni‐

3 Department of Ecology and Evolution, Stony Brook University, NY 11789, USA,

The technological revolution in the past 25 years now allows the analysis of species occurrence information in completely novel ways. Correlative environmental niche models (ENM) that link occurrence information to a set of environmental variables appeared as a central tool in this regard, and they are frequently used to address questions related to global change. Despite their popularity, ENMs often suffer from a lack of biological realism and other methodological challenges. To this end, researchers have begun to integrate genetic  information into  ENMs.  However,  there  is  currently  no  conceptual framework that  integrates population genetic information into the theoretical assumptions made for ENMs. Here, we highlight five major  reasons  why  the  conceptual  integration  of  genetic  information  in  ENMs  can  improve  model predictions and refine underlying theory. Specifically, genetic data can elucidate how environmental change alters functional connectivity, spatial genetic structure, hybridization, density-dependent priority effects, and source-sink dynamics. Thus, linking genetic and distribution data can lead to a better understanding why species respond to  environmental change in  a  certain  way,  and  improve our  ability  to  forecast these responses. We discuss these points in the context of modeling challenges in the era of the Anthropocene, where habitat fragmentation, biotic invasions, and climate change are major human-driven threads to global biodiversity. Our overview shows that integrating different kind of genetic information into ENMs permits a more holistic view of niche theory and points to shortcomings associated with how niche theory is currently being implemented in ENMs.