Novel indicators of biodiversity status based on financial portfolio metrics

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Mei-Ling E. Feng and Judy Che-Castaldo, Conservation and Science, Lincoln Park Zoo, Chicago, IL, Toryn L.J. Schafer and David S. Matteson, Department of Statistics and Data Science, Cornell University, Ithica, NY, Christian Che-Castaldo, Biology, University of Maryland, College Park, MD, Mila Getmansky Sherman, Finance Department, Isenberg School of Management, UMASS Amherst

Background/Question/Methods
Biodiversity loss is a global risk threatening the stability of human-natural systems, highlighting the need to monitor biodiversity status over time. Existing indicators of biodiversity status are based on the extent of population decline at the species level (e.g., IUCN Red List), or they integrate population sizes across species to derive community-level composition and abundance (e.g., Living Planet Index, Simpson’s diversity index). However, by focusing on directional changes in abundance and diversity, these metrics can miss important aspects of community stability, such as the magnitude of fluctuations in abundance and whether species respond to environmental changes synchronously or independently. Here we demonstrate the utility of two financial risk measures, portfolio volatility (PV) and marginal contribution to risk (MCTR), for assessing the stability of ecological systems and identifying species that disproportionately affect stability. We apply these metrics to the 1970-2017 North American Breeding Bird Survey data, focusing on the eastern forest and grassland breeding biomes as case study communities. Considering each bird community to be a biodiversity portfolio consisting of species as assets, we calculated PV and MCTR using the time series of “returns,” or annual changes in population size, for each species.
Results/Conclusions
We show that PV provides complementary insights with existing biodiversity indicators (geometric mean abundance and Hill-Simpson diversity), by detecting periods of instability or shifts in community dynamics. When instability is due to fluctuations in species dominance (as in the grassland community), both Hill-Simpson diversity and PV were able to detect those periods of change. However, instability due to changes in how species trends covary (as in the eastern forest community) was only detected by PV. Species with high MCTR contributed disproportionately to community volatility due to having high abundance relative to other species, large fluctuations in abundance, and/or high covariance in population trends with other species in the community. As such, these species may be vulnerable to extinction because of large population fluctuations, or they may serve as indicator species because their dynamics are representative of a group of species within the community and can be sensitive to drivers of change. These results suggest that MCTR can be used to identify focal species for monitoring and management, and can improve understanding of the drivers of community stability. Our study shows how the portfolio approach, by incorporating species volatility and covariance among species, can provide a more holistic way to monitor biodiversity status than abundance and diversity metrics alone.