The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate

By Xin Jing, N. Sanders, Yu Shi, Haiyan Chu, A. Classen, Ke Zhao, Litong Chen, Youxu Jiang, Jinsheng He. Nature Communications, 2015

773 citations recorded by the source corpus.

Plant biodiversity is often correlated with ecosystem functioning in terrestrial ecosystems. However, we know little about the relative and combined effects of above- and belowground biodiversity on multiple ecosystem functions (for example, ecosystem multifunctionality, EMF) or how climate might mediate those relationships. Here we tease apart the effects of biotic and abiotic factors, both above- and belowground, on EMF on the Tibetan Plateau, China. We found that a suite of biotic and abiotic variables account for up to 86% of the variation in EMF, with the combined effects of above- and belowground biodiversity accounting for 45% of the variation in EMF. Our results have two important implications: first, including belowground biodiversity in models can improve the ability to explain and predict EMF. Second, regional-scale variation in climate, and perhaps climate change, can determine, or at least modify, the effects of biodiversity on EMF in natural ecosystems. Plant biodiversity often has a positive influence on ecosystem functioning. Here Jinget al. show that belowground diversity can also significantly impact ecosystem multifunctionality, but its relative effect varies by regional-scale climate variation.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

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Citations in the corpus

Relative importance of soil properties and microbial community for soil functionality: insights from a microbial swap experiment (2016, neutral): “…functioning (Colman & Schimel 2013; Wieder, Boehnert & Bonan 2014), including broad (e.g. microbial respiration; Strickland et al. 2009), special- ized (e.g. denitrification; Philippot et al. 2013) and multiple ecosystems functions simultaneously (Jing et al. 2015; Del- gado-Baquerizo et al. 2016).”
Deciphering the associations between soil microbial diversity and ecosystem multifunctionality driven by long‐term fertilization management (2018, methodology): “While a large body of published literature used the multiple threshold approach to calculate multifunctionality (Bradford et al., 2014; Mori et al., 2016), the result of this computation was similar to the averaging approach (Jing et al., 2015).”
Scientists’ warning to humanity: microorganisms and climate change (2019, positive): “Soil microbial diversity influences plant diversity and is important for ecosystem functions, including carbon cycling 173,174 .”
Grazing practices affect the soil microbial community composition in a Tibetan alpine meadow (2018, methodology): “The taxonomic identity of each sequence was determined using Greengene database (http://greengenes.lbl.gov/; DeSantis et al., 2006; Jing et al., 2015) and Silva database (http://www.”
A global meta-analyses of the response of multi-taxa diversity to grazing intensity in grasslands (2019, background): “Our metaanalyses is among the first to find microbial diversity significantly increased after grazing, which may closely related to the changes of plant diversity and soil properties (Fierer and Jackson 2006, Jing et al 2015).”
Biodiversity and ecosystem functioning in naturally assembled communities (2019, background): “While positive relationships (N = 34, e.g. Maestre et al., 2012; Jing et al., 2015; Ratcliffe et al., 2017) between biodiversity and ecosystem multifunctionality outnumber negative ones (N = 13, e.”
Soil microbiomes with distinct assemblies through vertical soil profiles drive the cycling of multiple nutrients in reforested ecosystems (2018, methodology): “A recent study investigating biotic and abiotic factors on the Tibetan Plateau demonstrated positive associations between aboveground and belowground biodiversity and ecosystem multifunctionality, which was mediated by climate [35].”
piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics (2015, background): “…drivers of ecosystem functioning in eelgrass beds (Duffy et al. 2015), disentangle the influence of functional diversity across trophic levels in experimental estuarine mesocosms (Lefcheck & Duffy 2015), and quantify the biotic and abiotic drivers of grassland multifunctionality (Jing et al. 2015).”