Understanding how biodiversity and ecosystems will respond to the striking rates of climate and land-use change that characterize the Anthropocene world is one of the most important questions for contemporary science. In this endeavour, species distribution modelling (SDM) in response to anthropogenic changes have been widely applied, yet their ‘ecological realism’ is not always well considered . Practical and theoretical limitation are accountable: e.g. coarse-grain environmental data and inept downscaling methodologies, arbitrary absence estimates, processes crucial to species range shifts, notably propagule dispersal and establishment probability being disregarded .
As part of this EU funded Marie Sklodowska-Curie Fellowship, EcoFunc4Cast has specifically targeted much of these limitations extending the state of the art in view of a novel conceptual framework for mechanistic SDMs. The framework adheres to suggestions set out to improve biodiversity forecasts , namely: obtain good information and make better use of it; improve widely used modelling methods; account for multiple causes of changes in biodiversity and crucially; evaluate models before using them. Given the weight of importance of improving modelling approaches prior to applying them, EcoFunc4Cast invested vastly more resource towards framework development over application. The application of this framework is now the logical extension of this work, demonstrating the utility of improved ecological realism in biological forecasts, both taxonomic and functional.
To summarize, a conceptual paper discussing these methodological tools for facilitating SDMs in the Anthropocene is in prep. Models being only as reliable as the input data we address climate downscaling and validation through Geographical Weighted Regression, explicitly accounting for non-stationarity relationships between microclimate and geodiversity . We introduce an improved approach to pseudo absence generation, one that utilises the dark-diversity concept, and we address multiple causes of changes in biodiversity through the application of dispersal dynamics, introducing and exemplifying in itself one novel framework for estimating plant species dispersal dynamics. We discuss the utility and application of our framework within highly heterogeneous landscapes and microclimatic research. Our hope is to open a new chapter of discussion for explicitly consideration of the ecological realism of forecast modelling and see wide adoption and uptake of our developed framework for improving our understanding of anthropogenic driven environmental change at timescale immediately relevant to today societies.
This work has been presented at the BES Macroecology Special Interest Group Annual Conference, St Andrews, Uk 2018; and was invited for pre-submission to Ecography under their E4 award for excellence in Ecology in Evolution. Upon acceptance, open access this work will be guaranteed in accordance to Article 29.2 of the Grant Agreement and will acknowledge the funding received from the Marie Sklodowska-Curie programme (Article 29.4 of the grant agreement).
