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Integrative modelling reveals mechanisms linking productivity and plant species richness



How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology1. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns2,3. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models4,5,6,7. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis8, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.

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Figure 1: Comparison between low-dimension (top panel) and high-dimension (bottom panel) examinations of data.
Figure 2: Structural equation model representing connections between productivity and richness supported by the data.

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J.B.G. was supported by the US Geological Survey Ecosystems and Climate and Land use Change Programs. This work uses data from the Nutrient Network ( experiment, funded at the site scale by individual researchers. Coordination and data management were supported by funding to E.T.B. and E.W.S. from the National Science Foundation (NSF) Research Coordination Network (NSF-DEB-1042132) and Long Term Ecological Research (NSF-DEB-1234162 to Cedar Creek LTER) programs and the UMN Institute on the Environment (DG-0001-13). The Minnesota Supercomputer Institute hosts project data. The use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. Support for site-level activities is acknowledged in the Supplementary Information. We thank D. Laughlin for comments on the manuscript.

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Authors and Affiliations



E.W.S., E.T.B., W.S.H. and E.M.L. are Nutrient Network coordinators. J.B.G. and T.M.A. developed and framed the research questions. T.M.A., E.W.S., E.T.B., P.B.A., W.S.H., Y.H., H.H., J.D.B., Y.M.B., M.J.C., E.I.D., K.F.D., P.A.F., J.F., D.S.G., A.H., J.M.H.K., A.S.M., B.A.M., J.W.M., J.L.O., S.M.P. and M.D.S. collected data used in this analysis. T.M.A. assembled the data and performed initial analyses. J.B.G. analysed the data and wrote the paper with contributions and input from all authors.

Corresponding author

Correspondence to James B. Grace.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Structural equation meta-model showing hypothesized probabilistic expectations based on literature related to the productivity–diversity debate.

Solid lines represent expected positive effects, dashed lines represent expected negative effects. Literature and meta-model development are discussed in the Supplementary Information. Specific implementations of this generalized model for particular cases will probably differ in detail as appropriate for the situation and available data.

Extended Data Table 1 Model variables and their indicators*
Extended Data Table 2 Results of model dimensionality evaluations
Extended Data Table 3 Basic information on the study sites included in the final analyses

Supplementary information

Supplementary Information

This file contains Supplementary Materials and Methods, Supplementary Tables 1-2, Supplementary References and Supplementary Acknowledgements. (PDF 740 kb)

Supplementary Data 1

This file contains the computer code that accompanies the paper. (TXT 29 kb)

Supplementary Data 2

This file contains the plot-level data set. (CSV 222 kb)

Supplementary Data 3

This file contains the site-level dataset. (CSV 9 kb)

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Grace, J., Anderson, T., Seabloom, E. et al. Integrative modelling reveals mechanisms linking productivity and plant species richness. Nature 529, 390–393 (2016).

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