Predicting impacts of climate change on biodiversity: a role for semi-mechanistic community-level modelling


Karel Mokany, CSIRO Ecosystem Sciences, PO Box 1700, Canberra, ACT 2601, Australia.


Aim  Robust and reliable predictions of the effects of climate change on biodiversity are required in formulating conservation and management strategies that best retain biodiversity into the future. Significant challenges in modelling climate change impacts arise from limitations in our current knowledge of biodiversity. Community-level modelling can complement species-level approaches in overcoming these limitations and predicting climate change impacts on biodiversity as a whole. However, the community-level approaches applied to date have been largely correlative, ignoring the key processes that influence change in biodiversity over space and time. Here, we suggest that the development of new ‘semi-mechanistic’ community-level models would substantially increase our capacity to predict climate change impacts on biodiversity.

Location  Global.

Methods  Drawing on an expansive review of biodiversity modelling approaches and recent advances in semi-mechanistic modelling at the species level, we outline the main elements of a new semi-mechanistic community-level modelling approach.

Results  Our quantitative review revealed a sharp divide between mechanistic and non-mechanistic biodiversity modelling approaches, with very few semi-mechanistic models developed to date.

Main conclusions  We suggest that the conceptual framework presented here for combining mechanistic and non-mechanistic community-level approaches offers a promising means of incorporating key processes into predictions of climate change impacts on biodiversity whilst working within the limits of our current knowledge.