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Directed species loss reduces community productivity in a subtropical forest biodiversity experiment

Nature Ecology & Evolution volume 4, pages 550–559 (2020)Cite this article

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Abstract

Unprecedented species loss in diverse forests indicates the urgent need to test its consequences for ecosystem functioning. However, experimental evaluation based on realistic extinction scenarios is lacking. Using species interaction networks we introduce an approach to separate effects of node loss (reduced species number) from effects of link loss or compensation (reduced or increased interspecific interactions) on ecosystem functioning along directed extinction scenarios. By simulating random and non-random extinction scenarios in an experimental subtropical Chinese forest, we find that species loss is detrimental for stand volume in all scenarios, and that these effects strengthen with age. However, the magnitude of these effects depends on the type of attribute on which the directed species loss is based, with preferential loss of evolutionarily distinct species and those from small families having stronger effects than those that are regionally rare or have high specific leaf area. These impacts were due to both node loss and link loss or compensation. At high species richness (reductions from 16 to 8 species), strong stand-volume reduction only occurred in directed but not random extinction. Our results imply that directed species loss can severely hamper productivity in already diverse young forests.

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Fig. 1: Conceptual diagram showing the processes affecting community productivity after loss of species A and B from a community of four species A–D.
Fig. 2: Effects of species loss on stand volume across forest ages along five types of extinction scenarios.
Fig. 3: Effects of species loss on stand volume strengthen with forest age along five types of extinction scenarios.
Fig. 4: Net effects of species loss and their additive components (node-loss, link-loss and link-compensation effects) on stand volume in different extinction steps across forest ages for random and effectively non-random (directed by SLA and ED) extinction scenarios.
Fig. 5: Net effects of species loss and their additive components (node-loss, link-loss and link-compensation effects) on stand volume in different extinction steps at the latest age for random (red) and effectively non-random (blue; directed by SLA and ED) extinction scenarios.

Data availability

The data supporting the findings of this study are available in the Figshare digital repository (https://doi.org/10.6084/m9.figshare.9192629)34.

Code availability

The JAGS and Stan codes of Bayesian models are available in the Figshare digital repository (https://doi.org/10.6084/m9.figshare.9194555)45.

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Acknowledgements

This study was funded by the EU 7th FP Project IDP-BRIDGES (grant number 608422 to B.S., K.M. and P.A.N.), by the Swiss National Science Foundation (grant number 31003A_166457 to B.S.) and by the BEF-China project, which is supported by the German Science Foundation (grant DFG FOR-891/1-3) and the Institute of Botany of the Chinese Academy of Sciences. B.S. and P.A.N. were additionally funded by the University of Zürich Research Priority Program on Global Change and Biodiversity. We thank C. Lin, Y. Bo and a large number of farmers for help with maintenance of the field experiment. We thank X. Sui for providing the data of species regional rarity.

Author information

Author notes

  1. These authors contributed equally: Yuxin Chen, Yuanyuan Huang.

Authors and Affiliations

  1. Department of Evolutionary Biology and Environmental Studies, University of Zürich, Zürich, Switzerland

    Yuxin Chen, Yuanyuan Huang, Pascal A. Niklaus & Nadia Castro-Izaguirre

  2. Key Laboratory of the Coastal and Wetland Ecosystems (Ministry of Education), College of the Environment & Ecology, Xiamen University, Xiamen, China

    Yuxin Chen

  3. School of Life Sciences/State Key Laboratory of Biocontrol, Sun Yat-sen University, Guangzhou, China

    Yuxin Chen

  4. Department of Physiological Diversity, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany

    Adam Thomas Clark

  5. German Centre for Integrative Biodiversity Research (iDiv) Halle—Jena—Leipzig, Leipzig, Germany

    Adam Thomas Clark & Helge Bruelheide

  6. Martin Luther University Halle-Wittenberg, Halle (Saale), Germany

    Helge Bruelheide

  7. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China

    Keping Ma

  8. Department of Geography, University of Zürich, Zürich, Switzerland

    Bernhard Schmid

  9. Institute of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing, China

    Bernhard Schmid

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Contributions

Y.C. and B.S. conceived the study. Y.C. and A.T.C. developed the analytical procedure. Y.C. performed the analyses with contributions from Y.H. and B.S. H.B., N.C.-I., Y.C., K.M., Y.H., P.A.N. and B.S. contributed to the data collection. All authors discussed analysis results and helped write the paper.

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Correspondence to Bernhard Schmid.

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Extended data

Extended Data Fig. 1 Diagram showing the planting design of the BEF-China experiment.

Panel a shows the overall design. Panel b shows the design of random extinction scenarios. Panel c shows one of the two designed non-random extinction scenarios (rare species going extinct first). The random draws in panel c were done twice. The other designed non-random scenario (species with high SLA going extinct first) is similar. Designed non-random scenarios share the monocultures with the designed random scenarios. 1 mu equals to 0.067 ha.

Extended Data Fig. 2 Difference in community-weighted mean values of specific leaf area (SLA) between pre- and post-extinction communities.

Differences are shown for each extinction step (16→8, 8→4, 4→2 and 2→1 species) from designed random (black circles) and designed non-random, SLA-directed (red circles) extinction scenarios.

Extended Data Fig. 3 Filtering rule to create species richness gradients for effectively non-random extinction scenarios, with regional rarity as an example.

Mixtures at a richness level were selected by matching communities composed by the filtered species pool at the same richness level with the community composition of the 469 plots (plot source). Communities selected from this rule can be both nested and non-nested, and were used in the regression-based analysis of the relationship between species richness and productivity.

Extended Data Fig. 4 Community-weighted means (CWM) and coextinction probabilities for different extinction scenarios.

CWMs; (panels a–d) and coextinction probabilities (panels e–h) are shown across species-richness levels of the plots along five types of extinction scenarios. Black boxes represent the effectively non-random extinction scenarios, while grey boxes represent the designed random extinction scenario. We normalized each trait to have extinction probability spanning from 0.01 to 0.99. Species coextinction probability of each community was calculated as the geometric mean of extinction probability of species present in that community. A small county number indicates a high regional rarity. Horizontal lines at the centres of the boxes and the box edges show the medians and interquartile range (IQR), respectively. Vertical lines extending from the boxes are whiskers, representing values within four times of IQR. Dots are outliers.

Extended Data Fig. 5 Effects of species loss on stand-volume increment across forest ages along five types of extinction scenarios.

Species loss is random (a) or directed by specific leaf area (SLA; b), evolutionary distinctiveness (ED; c), regional rarity (d) or inverse of taxon size (e). Points and vertical lines represent means and two-times standard errors of observed stand-volume increment. Lines are fitted relationships between stand-volume increment (y axis) and species richness in the plot (x axis). Solid lines represent statistically significant declines of stand-volume increment with species loss.

Extended Data Fig. 6 Effects of species loss on stand-volume increment strengthen with forest age along five types of extinction scenarios.

Species loss is random (a) or directed by specific leaf area (SLA; b), evolutionary distinctiveness (ED; c), regional rarity (d) or inverse of taxon size (e). Points and vertical lines represent medians and 95% credible intervals (CI) of estimated net effect of species loss across richness levels. Filled points represent statistically significant effects of species loss on stand-volume increment. Blue lines are the fitted relationships between age and extinction effects. Results are considered as significant if their 95% CI excludes zero.

Extended Data Fig. 7 Relationships between species richness in the plot and average species dissimilarity within communities from the designed random (grey boxes) and effectively non-random (black boxes) extinction scenarios.

Non-random species loss is directed by specific leaf area (SLA; panel a) or evolutionary distinctiveness (ED; panel b). Species dissimilarity was calculated as functional dispersion (FDis) for SLA and mean pairwise phylogenetic distance (MPD) for ED. Horizontal lines at the centres of the boxes and the box edges show the medians and interquartile range (IQR), respectively. Vertical lines extending from the boxes are whiskers, representing values within four times of IQR. Dots are outliers.

Extended Data Fig. 8 Number of 1-mu plots used in five types of extinction scenarios.

Red bars represent the numbers of plots in the regression-based analysis of species loss effects on stand volume. Blue bars represent the numbers of plots of pre-extinction communities from extinction steps used in the analysis of decomposing the net effects of species loss on stand volume. Dashed horizontal lines indicate 10 plots.

Extended Data Fig. 9 Change of species loss effects (net effects and their additive components: node-loss, link-loss and link-compensation effects) on stand volume with forest age for different extinction steps along the designed random (red) and effectively non-random (blue; SLA and ED; abbreviations defined in Fig. 2) extinction scenarios.

Points and vertical lines represent the medians and 95% CI of estimated change of species loss effects through ages. Filled points represent statistically significant changes of species loss effect with forest age. Results are considered significant if their 95% CI excludes zero.

Extended Data Fig. 10 Effects of species loss on stand volume strengthen with forest age along five types of extinction scenarios from the models with positive constraints for the data and parameters associated with stand volume.

Species loss is random (a) or directed by specific leaf area (SLA; b), evolutionary distinctiveness (ED; c), regional rarity (d) or inverse of taxon size (e). Points and vertical lines represent medians and 95% credible intervals (CI) of estimated net effect of species loss across richness levels, respectively. Filled points represent statistically significant effects of species loss on stand volume. Blue lines are the fitted relationships between age and net effect of species loss. Results are considered as significant if their 95% CI excludes zero.

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Chen, Y., Huang, Y., Niklaus, P.A. et al. Directed species loss reduces community productivity in a subtropical forest biodiversity experiment. Nat Ecol Evol 4, 550–559 (2020). https://doi.org/10.1038/s41559-020-1127-4

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