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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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’.
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Acknowledgements
This work was supported by National Natural Science Foundation of China (grant nos. U22A20449 and U23A20156) and a National Non-profit Institute Research Grant of the Chinese Academy of Forestry (grant no. CAFYBB2017ZE001). We thank all individuals, institutions and funding agencies listed in the Supplementary Information for supporting and maintaining the ForestGEO and other plots used in this study.
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Contributions
H.X., M.D., S.F. and F.H. conceived the study. H.X. and M.D. analysed data. H.X., M.D., S.F. and F.H. led the writing. J.A.H., A.A., J.D.B., P.B., C.C., S.J.D., G.A.F., B.C.H.H., D.K., B.L., J.L., M.L., W.L., Y.L., Z.L., J.A.L., H.R.M., X.M., V.N., H.R., J.S., J.T., M.U., R.V., T.L.Y., S.L.Y, Y.Z., J.K.Z., G.D.W., Y.L. provided constructive suggestions or substantively revised the paper. M.D. and F.H. derived the analytical models. H.X., M.D., J.A.H., A.A., J.D.B., P.B., C.C., S.J.D., G.A.F., B.C.H.H., D.K., B.L., J.L., M.L., W.L., Y.L., Z.L., J.A.L., H.R.M., X.M., V.N., H.R., J.S., J.T., M.U., R.V., T.L.Y., S.L.Y, Y.Z., J.K.Z., G.D.W., Y.L., S.F. and F.H. contributed to the data collection of the 17 forest plots.
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Extended data figures and tables
Extended Data Fig. 1 The proportion of facilitative species in each of the 17 forest plots decreases with latitude.
The relative facilitative effect on neighbourhood species was assessed based on abundance (a) and richness (b). The proportion of facilitative species was calculated from circular plots with r = 2 m centred on the focal tree. It is the ratio of the number of positive species over all species with at least 50 individuals. Positive species are those species with RNA(r) > 1 (a) and RNS(r) > 1 (b), regardless of their significance levels (equation (2) in Methods). Data are presented as proportion ± 1 standard error (calculated using equation (5) with sample size n = 187 (BCI), 94 (BSZ), 101 (CBL), 74 (DHS), 71 (GTS), 156 (HSD), 237 (JFL), 60 (LUQ), 143 (NAN), 166 (PAL), 494 (PAS), 101 (PUE), 216 (RAB), 84 (TPK), 8 (UTA), 325 (WAN), 512 (YAS) in each plot, respectively). The latitude was adjusted by altitude (Methods).
Extended Data Fig. 2 The proportions of significantly facilitative species across the 17 forest plots decrease with latitude, as tested by the local random labelling null model.
The proportion of facilitative species was assessed based on abundance (a) and on richness (b) and calculated from circular plots with r = 2 m centred on the focal tree, as in Fig. 2, but restricted to species with significantly facilitative effects. The significant effect was assessed based on 95% confidence intervals computed from 999 randomizations of the local random labelling null model. Data are presented as proportion ± 1 standard error (calculated using equation (5) with sample size n = 103 (BCI), 86 (BSZ), 73 (CBL), 48 (DHS), 58 (GTS), 85 (HSD), 173 (JFL), 35 (LUQ), 105 (NAN), 85 (PAL), 153 (PAS), 64 (PUE), 127 (RAB), 52 (TPK), 8 (UTA), 177 (WAN), 202 (YAS) in each plot, respectively). The latitude was adjusted by altitude (Methods).
Extended Data Fig. 3 Relationship between the proportions of facilitative species in each of the 17 forest plots and latitude after 5% and 10% largest trees excluded.
The proportions of positive species interactions were calculated for neighbourhood species abundance (a, c) and species richness (b, d), respectively. (a, b) 5% largest trees were excluded; (c, d) 10% largest trees were excluded. The proportions of facilitative species were calculated as the ratio of the number of positive species over all species with at least 50 individuals, for neighbourhood of 2 m radius. Positive species are those species with RNA(r) > 1 (a, c) and RNS(r) > 1 (b, d), regardless of their significance levels (equation (2) in Methods). Data are presented as proportion ± 1 standard error (calculated using equation (5) with sample size n = 187 (BCI), 94 (BSZ), 101 (CBL), 74 (DHS), 71 (GTS), 156 (HSD), 237 (JFL), 60 (LUQ), 143 (NAN), 166 (PAL), 494 (PAS), 101 (PUE), 216 (RAB), 84 (TPK), 8 (UTA), 325 (WAN), 512 (YAS) for 5% largest trees excluded and 510 (YAS) for 10% largest trees excluded in each plot, respectively). The latitude was adjusted by altitude (Methods).
Extended Data Fig. 4 Relationship between relative neighbourhood abundance and relative neighbourhood richness and species abundance in all 17 forest plots.
Relative neighbourhood abundance or richness below 1 suggests that species has negative (competitive) interaction with neighbours, and vice versa. Red circles indicate species has either significantly negative or positive neighbourhood interactions (P < 0.05; computed from 999 independent randomizations of the local random labelling null model). The relative neighbourhood abundance or richness were calculated from circular plots with r = 2 m.
Extended Data Fig. 5 Proportions of positive species interactions versus species richness for the 17 plots simulated from a spatially explicit neutral model.
A birth-death point process with limited dispersal and immigration, allows individuals to interact locally through either (a, c) negative interactions or (b, d) positive interactions. The results show that, contrary to what was observed in the 17 plots in Fig. 2, the proportion of species with higher neighbourhood abundance or richness decreases as overall plot richness shows no change (a, b) or increases (c, d), suggesting that the higher neighbourhood diversity in species-rich plots is not driven by a simple sampling effect.
Extended Data Fig. 6 Absolute proportions of significant facilitative (a, b) and competitive (c, d) species as a function of the absolute adjusted latitude in all 17 forest plots using the local random labelling null model.
The absolute proportion (significantly positive or significantly negative species over all species) was calculated from circular plots with r = 2 m centred on the focal tree. Significance was estimated from the local random labelling null model. Data are presented as proportion ± 1 standard error (calculated using equation (5) with sample size n = 282 (BCI), 167 (BSZ), 183 (CBL), 170 (DHS), 125 (GTS), 205 (HSD), 279 (JFL), 118 (LUQ), 215 (NAN), 303 (PAL), 825 (PAS), 227 (PUE), 314 (RAB), 155 (TPK), 14 (UTA), 526 (WAN), 1029 (YAS) in each plot, respectively). The latitude was adjusted by altitude (Methods).
Extended Data Fig. 7 Absolute proportions of significant facilitative (a, b) and competitive (c, d) species standardized at reference abundance N = 1000 as a function of the absolute adjusted latitude in all 17 forest plots.
The absolute proportion (significantly positive or significantly negative species over all species) was calculated for circular plots with r = 2 m. Significance was estimated from the local random labelling null model. Standardization at N = 1000 was estimated by generalized linear regression (Methods). The latitude was adjusted by altitude (Methods).
Extended Data Fig. 8 Relationship between relative neighbourhood abundance and relative neighbourhood richness standardized by z-scores and species abundance in all 17 forest plots.
Red circles indicate species with either significantly negative or positive neighbourhood interactions (P < 0.05; computed from 999 independent randomizations of the local random labelling null model). The relative neighbourhood abundance or richness were calculated from circular plots with r = 2 m. Vertical lines at ±1.96 are shown for reference.
Supplementary information
Supplementary Information (download PDF )
Supplementary Notes containing further acknowledgements.
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Supplementary Table 1 (download XLSX )
Relative neighbourhood diversity varied with DBH threshold (DBHs ≥ 1, 5, 10 and 20 cm) and within the circular area described by radius (r = 2, 4, 6, 8, 10, 12, 14, 16 m) to the focal species.
Supplementary Table 2 (download XLSX )
Absolute neighbourhood diversity within the circular area described by radius (r = 2 m) for DBH ≥ 1 cm individuals to the focal species.
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Xu, H., Detto, M., Hogan, J.A. et al. The importance of competition and facilitation for global tree diversity.
Nature (2026). https://doi.org/10.1038/s41586-026-10349-2
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DOI: https://doi.org/10.1038/s41586-026-10349-2
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