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Globally limited individual and combined effects of multiple global change factors on allometric biomass partitioning

机译:Globally limited individual and combined effects of multiple global change factors on allometric biomass partitioning

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Aim: Plant biomass allocation reflects the distribution of photosynthates among different organs in response to changing environmental conditions. Global change influences plant growth across terrestrial ecosystems, but impacts of individual and combined multiple global change factors (GCFs) on plant biomass allocation at the global scale are unclear. Location: Global. Time period: Contemporary. Major taxa studied: Plants in terrestrial ecosystems. Methods: We conducted a meta-analysis of data comprising 4,180 pairwise observations to assess individual and combined effects of nitrogen addition (N), warming (W), elevated CO_2 (C), irrigation (I), and drought (D) on plant biomass allocation based on the 'ratio-based optimal partitioning' and 'isometric allocation' hypotheses. Results: We found that (a) ratio-based plant biomass fractions of different organs were only minimally affected by individual and combined effects of the studied GCFs; (b) combined effects of two-factor pairs of GCFs on plant biomass allocation were commonly additive, rather than synergistic or antagonistic; (c) moderator variables influenced, but seldom changed the direction of individual and combined effects of GCFs on plant biomass allocation; and (d) neither individual nor combined effects of the studied GCFs altered allometric relationships among different organs, indicating that patterns of plant biomass allocation under the environmental stress conditions exerted by the multiple GCFs were better explained by the isometric allocation rather than the ratio-based optimal partitioning hypothesis. Main conclusions: Our results show consistent patterns of allometric plant biomass partitioning under effects of multiple GCFs and provide evidence of an isometric plant biomass allocation trajectory in response to global change perturbations. These findings improve our understanding and prediction of terrestrial vegetation responses to future global change scenarios.

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