The importance of competition and facilitation for global tree diversity | Nature

Subjects

- Biodiversity

- Climate-change ecology

- Community ecology

Abstract

Although competition and facilitation both influence tree diversity1,2,3,4,5, their relative importance and variation with latitude remain poorly understood. Using data from 17 large forest plots, including around 2.7 million trees and over 5,400 species spanning 5° S to 47° N, we quantified the latitudinal trends of the relative importance of negative (competitive) and positive (facilitative) interactions among neighbouring tree species, accounting for three biotic and eight environmental factors. We examined whether the average neighbourhood species diversity around individuals of each focal species was larger or smaller than expected under null models. The results show that negative interspecific interactions prevailed across most plots. Near the equator, the relative proportions of species surrounded by a lower or higher than expected number of neighbours were roughly equal, but at higher latitudes, the proportions of species with a relatively higher number of neighbours declined, and those with fewer neighbours increased significantly. This latitudinal pattern can be attributed in part to reduced abundance of legumes, non-arbuscular mycorrhizal associations, and the weaker canopy nursing effect towards higher latitudes, but it was mediated by mean annual temperature. These findings reveal a previously unrecognized relative decline in facilitative interactions and increase in competitive interactions with latitude and suggest that rising temperatures could enhance facilitative effects and promote tree community diversity at higher latitudes.

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Fig. 1: Locations of the 17 permanent forest plots.

Fig. 2: The proportion of facilitative species in each of the 17 forest plots decreases with latitude.

Fig. 3: Slopes between relative neighbourhood interactions and latitude across the 17 forest plots after excluding leguminous or non-AM tree species.

Fig. 4: Relationships between species abundance versus relative neighbourhood abundance or richness for four forest plots.

Fig. 5: Proportions of species with positive neighbourhood species abundance or richness change with MAT for the 17 forest plots.

Data availability

Data from 17 plots can be requested from the ForestGEO plot network via https://www.forestgeo.si.edu/. Chebaling plot data can be requested from the principal investigators of Heishiding plot in the ForestGEO plot network; Nanling and Puer plots’ data can be requested from the principal investigators of Jianfengling plot in the ForestGEO plot network. Plot elevation range, MAT, January temperature, July temperature and mean annual precipitation, were obtained from a past work59. Soil total nitrogen density (g m−3) was compiled from the IGBP-DIS database at a resolution of 5 × 5 arc-minutes, and in a soil depth interval 0–100 cm from Oak Ridge National Laboratory Distributed Active Archive Center (https://daac.ornl.gov)60. Soil temperature was obtained from https://zenodo.org/record/4558663#.ZFRV46BBztU (ref. 61) and soil wetness was obtained from https://climate.esa.int/en/projects/soil-moisture/ (ref. 62). We also stored the running results of 17 plots to Github via https://github.com/mdetto/Positive-Interactions (ref. 68).

Code availability

Extended Data 1–4 are stored on Github at https://github.com/mdetto/Positive-Interactions (ref. 68), whereas Extended Data 5 was uploaded to Code Ocean at https://codeocean.com/capsule/4844196/tree (ref. 69). Extended Data 1: R script for computing the number of individuals (N) and number of species richness (S) around all stems, ‘ISAR’. Extended Data 2: R script for calculating the relative neighbourhood abundance and richness for trees within 60 m circular neighbourhood of focal species and falling within the same DBH class as the focal tree, ‘RNA.RNS’. Extended Data 3: R script for local random labelling null model test, ‘LocalRLNullModel’. Extended Data 4: R script for large tree exclusion analysis, ‘LargeTreeExclusion’. Extended Data 5: Matlab script for running spatial model simulation to assess the potential biases for the latitudinal neighbourhood interaction pattern, ‘SpatialBirthDeathSim’.

References

- Michalet, R. et al. Competition, facilitation and environmental severity shape the relationship between local and regional species richness in plan