Scaling up biodiversity–ecosystem function relationships across space and over time

Jiangxiao Qiu, Bradley J. Cardinale

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Understanding how to scale up effects of biological diversity on ecosystem functioning and services remains challenging. There is a general consensus that biodiversity loss alters ecosystem processes underpinning the goods and services upon which humanity depends. Yet most of that consensus stems from experiments performed at small spatial scales for short time frames, which limits transferability of conclusions to longer-term, landscape-scale conservation policies and management. Here we develop quantitative scaling relationships linking 374 experiments that tested plant diversity effects on biomass production across a range of scales. We show that biodiversity effects increase by factors of 1.68 and 1.10 for each 10-fold increase in experiment temporal and spatial scales, respectively. Contrary to prior studies, our analyses suggest that the time scale of experiments, rather than their spatial scale, is the primary source of variation in biodiversity effects. But consistent with earlier research, our analyses reveal that complementarity effects, rather than selection effects, drive the positive space–time interactions for plant diversity effects. Importantly, we also demonstrate complex space–time interactions and nonlinear responses that emphasize how simple extrapolations from small-scale experiments are likely to underestimate biodiversity effects in real-world ecosystems. Quantitative scaling relationships from this research are a crucial step towards bridging controlled experiments that identify biological mechanisms across a range of scales. Predictions from scaling relationships like these could then be compared with observations for fine-tuning the relationships and ultimately improving their capacities to predict consequences of biodiversity loss for ecosystem functioning and services over longer time frames across real-world landscapes.

Original languageEnglish (US)
Article numbere03166
JournalEcology
Volume101
Issue number11
DOIs
StatePublished - Nov 1 2020

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics

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