Collaborative Research: ABI Development: Creating a generic workflow for scaling up the production of species ranges

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The science of forecasting where a species can live and how it responds to climate change is still in its infancy. A species' geographic range is the map of where a species can be found. It is fundamental to understanding species' ecology and evolution and increasingly plays a vital role in conservation. Collections of species ranges covering most of the 30,000 terrestrial vertebrate species are already available for scientific analysis. However, collections of species ranges from the other ~95% of species on the planet are rare. The time is ripe to change this. New access to vast quantities of data from biological inventories, museums, citizen science, and previously funded studies mean that adequate data are available to estimate the ranges of many more species. However, we are currently missing robust forecasting methods and the computational tools to produce large numbers of ranges. This project will develop the novel computational methods and algorithms needed to forecast the current state and future fate of the many thousands of poorly studied species ranges. These methods will be applied to forecast how 100,000+ plant species in the New World will respond to climate change. The researchers will test key assumptions in conservation biology about how species respond to changing climate and the geographic constancy of diversity hotspots across North and South America have/will change over time. The end result of their work will be a novel tool for the ecological community that has tremendous potential to guide biological sampling strategies, particularly in conservation and citizen science applications. The proposed research will examine whether biodiversity hotspots are constant through time and whether species climatic niches are phylogenetically conserved, two implicit assumptions with wide-reaching implications in conservation biology and basic ecology. This research will develop a workflow to predict species ranges for any taxonomic group using by combining occurrence data with GIS data. This workflow will be applied to all New World plants to study basic questions, such as how species richness varies across space and time (a topic studied almost exclusively in vertebrates and trees). Computationally, the project will address core challenges in data scrubbing, niche modeling practices, novel niche modeling methods, and mega-phylogeny analysis methods. A freely available generic pipeline will be capable of linking biodiversity occurrence data to species ranges and scaling these computations to 1000s or 100,000s of species. This integrated pipeline will be implemented by: 1) appropriately scrubbing data to remove taxonomic and geographic errors, 2) identifying clear best practice methods for range modeling applicable across diverse species, 3) innovating range modeling methods that integrate diverse data such as presence only museum collections and abundance-based plot data 4) scaling computationally-intensive range modeling in an HPC environment, and 5) placing the outputs of the products in a phylogenetic context. This project will develop such a pipeline using a novel database of 20,000,000 observations of 100,000+ species of plants in the New World. The range forecasts produced will be used to test key assumptions in conservation biology about the phylogenetic conservatism of species climatic niches and the geographic constancy of diversity hotspots over time. This research will make substantial contributions to scientific infrastructure through the development of a scientific codebase for the production of high-quality species ranges from primary biodiversity data. The results of the project can be found via the following websites (http://bien.nceas.ucsb.edu/bien/ and bien3.org).