Projecting the impacts of climate change on biodiversity is a major goal in macroecology and biogeography. The failure of commonly used methodologies to produce accurate forecasts has led to increasing interest among researchers in adopting more mechanistic or process-based approaches. Yet, the transition away from traditional correlational studies is proving slow, partly due to data limitations. Until the outcomes of experimental macroecology become more common, forest and agricultural species offer conspicuous study cases to investigate species responses to climate. Data availability on long temporal series of phenological observations for crops allows—for example—the calibration of phenological and demographic models that can accurately predict species responses to varying temperature regimes. Similarly, process-based forestry approaches allow determining how forest dynamics will be altered by climate change. The availability of high-resolution spatial and temporal data on agricultural and forestry species has the potential to deepen our understanding of how biodiversity responds to climate. Even so, biogeographers still seem reluctant to employing data and practices from sister disciplines.
On the other hand, modelling strategies in agronomy or forestry have developed highly detailed, process-based approaches able to make accurate predictions, but strongly limited in their geographic scope. Merging techniques commonly used in biogeography with process-based approaches from agronomy or forestry can be mutually beneficial. First, by increasing the accuracy of wild species distribution forecasts across scales. Second, by expanding biogeography towards a more applied paradigm, where the typically large-scale focus of its forecasts would be useful to compare agricultural and forestry practices and predictions across regions. These predictions are particularly welcome in a context where assessment of threats on ecosystem services such as food and wood supply, and carbon sequestration, is of critical concern to human livelihoods.
The topic of this symposium will bring together world experts who have combined crop or inventory data (from both agricultural or forest species) and/or, high temporal-resolution climate data with process-based models based on phenology, demography or physiology, to predict the future impacts of climate change on targeted species. Besides sharing advances in fields that usually fall outside biogeography but whose findings would be relevant in the attempt to move the field towards using process- based approaches, this symposium aims to foster discussion on three topics.
- On the utility and feasibility of importing process-based approaches used in agronomy and forestry to biogeography.
- On identifying data gaps and needs, if such implementation were to be applied to wild species.
- On how the large spatial focus of biogeography may allow upscaling process-based models, by e.g. combining them with niche models, to produce outcomes relevant to inform decisions of farmers, forest managers and policy makers.