MSA: Quantifying the drivers of mammal food web networks over space and time in Sub-Saharan Africa

William Marsh Rice University, Houston TX

Investigators

Abstract

Biodiversity is central to human health and well-being because it influences services that make human life possible. Food webs and the predator-prey interactions that comprise them play a critical role in maintaining biodiversity. Most food webs have been studied locally, which inhibits generalizations to larger areas and hampers predictions of the impact of global environmental changes. The extent to which food webs depend on changes in primary productivity – the rate at which plants turn energy into plant material through photosynthesis – remains largely unknown. More studies have been published describing predator-prey interactions in mammals than in other animals, but we know little about what affects mammal food webs. Primary productivity predicts mammal biodiversity in Africa more than in other regions, suggesting the potential for a strong influence on African food webs. Nevertheless, as the biosphere changes rapidly, changes in climate and land use can alter predator-prey interactions, thereby altering food webs. In the coming decades, African mammal food webs may be more intensely affected by land-use change than other regions because projected human population growth rates for sub-Saharan Africa are among the highest globally. Identifying the ecological and anthropogenic drivers of food webs over space and time has never been more important. This work supports 2 Ph.D. students and 3 undergraduate students co-advised by the PI in Biosciences and the Co-PI in Electrical and Computer Engineering, thus providing opportunities for cross-disciplinary education in mathematical, computational, and environmental sciences. To amplify the broader impacts of the research in the Houston area, two local K-12 teachers are participating in Rice University's R-STEM program, which provides inquiry-based professional development for teachers. The research leverages standardized annual camera trap data from five African protected areas and community composition data from 170 mammal communities throughout sub-Saharan Africa, and the researchers are constructing an overarching food web for the mammal species from published data. To date, a key limitation of ecological network research has been the widespread application of heuristic approaches lacking strong theoretical support. The researchers are harnessing recent developments in topological data analysis to quantify similarities in food web structures. Specifically, they are developing fast algorithmic implementations to measure differences in food webs over space and time. The research objectives are to determine: 1) how climate and fragmentation influence vegetation productivity, 2) how local food web dynamics respond to changes in productivity and fragmentation over time, and 3) how food web network structure varies as a function of productivity and fragmentation at regional and continental scales. The researchers are also providing open-source implementation of the algorithms and examples and tutorials of their use. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.