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利用纵向数据和因果推理方法阐明生物多样性对自然生态系统生产力的影响。

Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference.

机构信息

Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA.

Department of Environmental Health and Engineering, Bloomberg School of Public Health & Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.

出版信息

Nat Commun. 2023 May 5;14(1):2607. doi: 10.1038/s41467-023-37194-5.

DOI:10.1038/s41467-023-37194-5
PMID:37147282
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10163230/
Abstract

Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs - designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [-4.1, -0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones.

摘要

生物多样性对生态系统功能的因果效应可以通过实验或观测设计来估计 - 这些设计在从相关性中得出可信的因果推断和得出可推广的推断之间存在权衡。在这里,我们开发了一种设计,可以减少这种权衡,并重新探讨植物物种多样性如何影响生产力的问题。我们的设计利用了来自 11 个国家的 43 个草地的纵向数据,并借鉴了生态学以外的领域的方法,从观测数据中得出因果推断。与许多先前的研究相反,我们估计,样地水平物种丰富度的增加导致生产力下降:丰富度增加 10%会使生产力降低 2.4%,95%置信区间[-4.1,-0.74]。这种矛盾源于两个来源。首先,先前的观测研究不能完全控制混杂因素。其次,大多数实验种植的稀有和非本地物种比自然界中存在的要少。尽管本地优势物种的增加提高了生产力,但稀有和非本地物种的增加降低了生产力,使得我们的研究中的平均效应为负。通过减少实验和观测设计之间的权衡,我们的研究表明了观测研究如何补充先前的生态实验,并为未来的实验提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/94c4f7d3eaf5/41467_2023_37194_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/6361837bb894/41467_2023_37194_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/f6c1e6fd2b3a/41467_2023_37194_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/f4fb0579a785/41467_2023_37194_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/ff49abcbfa3b/41467_2023_37194_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/94c4f7d3eaf5/41467_2023_37194_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/6361837bb894/41467_2023_37194_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/f6c1e6fd2b3a/41467_2023_37194_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/f4fb0579a785/41467_2023_37194_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/ff49abcbfa3b/41467_2023_37194_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f9c/10163230/94c4f7d3eaf5/41467_2023_37194_Fig5_HTML.jpg

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