Stably coexisting communities deliver higher ecosystem multifunctionality
收藏DataONE2026-01-16 更新2026-01-24 收录
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Linking the processes determining species coexistence and effects of biodiversity on ecosystem functioning is important for a mechanistic understanding of how species loss impacts ecosystems. There are good theoretical reasons to expect stably coexisting communities to deliver higher ecosystem functioning, as niche differences should promote coexistence and complementarity, however, there is still little empirical evidence to demonstrate this relationship. We present a novel experimental approach to tackle this question, in which we first measured interaction coefficients and intrinsic growth rates for 12 grassland species and used population models to estimate coexistence5. We then assembled 48 three-species communities, predicted to differ in their degree of coexistence and measured seven above and belowground functions. Here we extend findings demonstrating that biodiversity increases multifunctionality to show that amongst communities with the same initial diversity, multifunctional..., , # Structural_coexistence_multifunctionality
In this folder you may find the data and code for the analysis of \"Stably coexisting communities deliver higher ecosystem multifunctionality\".
## What can you find in this project?
### a) data.zip
Please refer to the METADATA text file that regroups all information on the data folder, and contains a list of abbreviations for each variable that can be found in this folder.
#### *coexistence and experimental design*
In the data folder, you can find a subfolder called \"species alphas and lambdas\" containing all competition matrices used during the analysis, as text files which names start with \"biommatrix\", and their associated standard errors, which are named \"SE_biommatrix\". The species intrinsic growth rates are also present in this folder under the name starting with \"biomintrinsic\". These matrices are derived over the whole year 2020 (combining June and August sampling for this year), or only for June 2020 sampling, as this month was u...,
创建时间:
2026-01-17



