OOS 52-4
Dynamic species distribution models for global change: Processes and resolution through the lenses of different approaches
Global change poses many challenges to ecologists seeking to provide a good estimation of changes in species distributions in the Anthropocene era. Through the combination of different modeling approaches, ecologists seek to address how the changing climate and atmosphere affect processes directly linked to species range changes.
One of the key challenges is how to integrate over different life stages when ecological processes and environmental controls operate at different spatial and temporal resolutions.
Here, we present three modeling frameworks that aim to unveil microenvironmental controls in macrosystems: a metapopulation model, a demographic-landscape model and a landscape model. We apply these models to 4 abundant tree species that characterize foothills and montane forests in the California Floristic Province making use of very high resolution climate data and common garden experiments.
Results/Conclusions
Some processes are modeled with a fair amount of detail (e.g. vital rates, interactions, phenology, etc.), but much less attention has been directed towards extreme events in each of these modeling approaches. Extreme events and disturbances are projected to change in their frequency and magnitude (e.g. droughts, fire), and may affect species persistence and range changes in the future. These events will likely preclude or favor some species over others depending on their autoecology and on the new conditions in which they may have to survive or regenerate.
We conclude that it is desirable to include key processes as well as disturbances affecting species regeneration and colonization capacities both at the population and landscape level and to control the spatial resolution of the work under study, so that the modeling approaches effectively capture survival of critical life stages that may act as bottlenecks to population persistence. Future directions will better relate experiments with models to more tightly link models to the mechanisms governing persistence or vulnerability under global change.