
Using species co‐occurrence networks to assess the impacts of climate change
Author(s) -
Araújo Miguel B.,
Rozenfeld Alejandro,
Rahbek Carsten,
Marquet Pablo A.
Publication year - 2011
Publication title -
ecography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.973
H-Index - 128
eISSN - 1600-0587
pISSN - 0906-7590
DOI - 10.1111/j.1600-0587.2011.06919.x
Subject(s) - climate change , ecological network , co occurrence , ecology , robustness (evolution) , biodiversity , global biodiversity , complex network , biology , computer science , ecosystem , biochemistry , artificial intelligence , world wide web , gene
Viable populations of species occur in a given place if three conditions are met: the environment at the place is suitable; the species is able to colonize it; co‐occurrence is possible despite or because of interactions with other species. Studies investigating the effects of climate change on species have mainly focused on measuring changes in climate suitability. Complex interactions among species have rarely been explored in such studies. We extend network theory to the analysis of complex patterns of co‐occurrence among species. The framework is used to explore the robustness of networks under climate change. With our data, we show that networks describing the geographic pattern of co‐occurrence among species display properties shared by other complex networks, namely that most species are poorly connected to other species in the network and only a few are highly connected. In our example, species more exposed to climate change tended to be poorly connected to other species within the network, while species more connected tended to be less exposed. Such high connectance would make the co‐occurrence networks more robust to climate change. The proposed framework illustrates how network analysis could be used, together with co‐occurrence data, to help addressing the potential consequences of species interactions in studies of climate change and biodiversity. However, more research is needed to test for links between co‐occurrence and network interactions.