Grassland biodiversity can pay: Proceedings of the National Academy of Sciences

TY - JOUR

T1 - Grassland biodiversity can pay

T2 - Proceedings of the National Academy of Sciences

AU - Binder, Seth

AU - Isbell, Forest

AU - Polasky, Stephen

AU - Catford, Jane A.

AU - Tilman, David

PY - 2018/4/10

Y1 - 2018/4/10

N2 - The biodiversity-ecosystem functioning (BEF) literature provides strong evidence of the biophysical basis for the potential profitability of greater diversity but does not address questions of optimal management. BEF studies typically focus on the ecosystem outputs produced by randomly assembled communities that only differ in their biodiversity levels, measured by indices such as species richness. Landholders, however, do not randomly select species to plant; they choose particular species that collectively maximize profits. As such, their interest is not in comparing the average performance of randomly assembled communities at each level of biodiversity but rather comparing the best-performing communities at each diversity level. Assessing the best-performing mixture requires detailed accounting of species' identities and relative abundances. It also requires accounting for the financial cost of individual species' seeds, and the economic value of changes in the quality, quantity, and variability of the species' collective output-something that existing multifunctionality indices fail to do. This study presents an assessment approach that integrates the relevant factors into a single, coherent framework. It uses ecological production functions to inform an economic model consistent with the utilitymaximizing decisions of a potentially risk-averse private landowner. We demonstrate the salience and applicability of the framework using data from an experimental grassland to estimate production relationships for hay and carbon storage. For that case, our results suggest that even a risk-neutral, profit-maximizing landowner would favor a highly diverse mix of species, with optimal species richness falling between the low levels currently found in commercial grasslands and the high levels found in natural grasslands.

AB - The biodiversity-ecosystem functioning (BEF) literature provides strong evidence of the biophysical basis for the potential profitability of greater diversity but does not address questions of optimal management. BEF studies typically focus on the ecosystem outputs produced by randomly assembled communities that only differ in their biodiversity levels, measured by indices such as species richness. Landholders, however, do not randomly select species to plant; they choose particular species that collectively maximize profits. As such, their interest is not in comparing the average performance of randomly assembled communities at each level of biodiversity but rather comparing the best-performing communities at each diversity level. Assessing the best-performing mixture requires detailed accounting of species' identities and relative abundances. It also requires accounting for the financial cost of individual species' seeds, and the economic value of changes in the quality, quantity, and variability of the species' collective output-something that existing multifunctionality indices fail to do. This study presents an assessment approach that integrates the relevant factors into a single, coherent framework. It uses ecological production functions to inform an economic model consistent with the utilitymaximizing decisions of a potentially risk-averse private landowner. We demonstrate the salience and applicability of the framework using data from an experimental grassland to estimate production relationships for hay and carbon storage. For that case, our results suggest that even a risk-neutral, profit-maximizing landowner would favor a highly diverse mix of species, with optimal species richness falling between the low levels currently found in commercial grasslands and the high levels found in natural grasslands.

KW - biodiversity multifunctionality optimal management agriculture ecological production function ecosystem function statistical inevitability plant diversity services insurance stability multifunctionality benefits ecology systems

U2 - 10.1073/pnas.1712874115

DO - 10.1073/pnas.1712874115

M3 - Article

SN - 0027-8424

VL - 115

SP - 3876

EP - 3881

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

IS - 15

ER -