Arbuscular mycorrhizal trees influence the latitudinal beta-diversity gradient of tree communities in forests worldwide

Abstract

Arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) associations are critical for host-tree performance. However, how mycorrhizal associations correlate with the latitudinal tree beta-diversity remains untested. Using a global dataset of 45 forest plots representing 2,804,270 trees across 3840 species, we test how AM and EcM trees contribute to total beta-diversity and its components (turnover and nestedness) of all trees. We find AM rather than EcM trees predominantly contribute to decreasing total beta-diversity and turnover and increasing nestedness with increasing latitude, probably because wide distributions of EcM trees do not generate strong compositional differences among localities. Environmental variables, especially temperature and precipitation, are strongly correlated with beta-diversity patterns for both AM trees and all trees rather than EcM trees. Results support our hypotheses that latitudinal beta-diversity patterns and environmental effects on these patterns are highly dependent on mycorrhizal types. Our findings highlight the importance of AM-dominated forests for conserving global forest biodiversity.

Fig. 1. Global distribution of 45 forest plots.

Plots range in size from 2.1 ha (Nanjenshan) to 60 ha (Jianfengling) and in latitude from 21.5 °S (Ilha do Cardoso, Brasil) to 61.3 °N (Scotty Creek, Canada), covering all continents with forests (i.e., Asia, Africa, Europe, South America, North America, and Oceania).

Fig. 2. Latitudinal gradients in tree beta-diversity.

Total beta-diversity, species turnover, and species nestedness of all trees, AM trees, and EcM trees across latitudes at quadrat scales of 10 m × 10 m (a–c), 20 m × 20 m (d–f), and 50 m × 50 m (g–i). Orange points represent total beta-diversity and its two components (species turnover & nestedness) of all trees and orange lines represent their latitudinal patterns. Green points represent total beta-diversity and its components of AM trees and green lines represent their latitudinal patterns. Blue points represent total beta-diversity and its components of EcM trees and blue lines represent their latitudinal patterns. Points are the mean values and the error bars are the 95% confidence intervals, estimated using the non-parametric bootstrapping method (n = 200). In total, 200 replicates of average pairwise beta-diversity and its components were calculated based on 30, 15, and 15 randomly sampled quadrats of 10 m × 10 m, 20 m × 20 m, and 50 m × 50 m from each forest plot, respectively. Solid lines indicate significant relationships with latitude whereas dashed lines indicate non-significant relationships fitted using the beta regression. The error bands (shaded areas) are the 95% confidence intervals of the fitted relationships, with sample size n = 45 for all trees, n = 44 for AM trees, and n = 43 for EcM trees at the 10 m × 10 m scale; with n = 45 for all trees, n = 44 for AM trees, and n = 44 for EcM trees at the 20 m × 20 m scale; and with n = 41 for all trees, n = 40 for AM trees, and n = 41 for EcM trees at the 50 m × 50 m scale.

Fig. 3. Variation partitioning of tree beta-diversity.

Variation of total beta-diversity, species turnover, and species nestedness of all trees, AM trees, and EcM trees at quadrats scales of 10 m × 10 m (a–c), 20 m × 20 m (d–f), and 50 m × 50 m (g–i) explained by spatial and environmental variables. Orange, green, and blue points represent total beta-diversity and its two components (species turnover & nestedness) of all trees, AM trees, and EcM trees. “Env”, “Space”, and “Env + Space” represent the effects of environmental variables, spatial variables, and both, respectively. Average total beta-diversity and its two components were calculated based on 30, 15, and 15 randomly sampled quadrats of 10 m × 10 m, 20 m × 20 m, and 50 m × 50 m from each forest plot, respectively. The calculation and variation partitioning of total beta-diversity and its components were repeated 200 times. Means and 95% confidence intervals (95% CIs) of explained variation of total beta-diversity and its components were estimated using the non-parametric bootstrapping (n = 200 replicates). The means were showed as points and 95% CIs were showed as error bars. Differences between the variation explained by spatial and environmental variables were tested for significance using two-sided Mann–Whitney U tests: n.s. P ≥ 0.05, * P < 0.05, ** P < 0.01, *** P < 0.001. W = 19225 and P = 0.5029 for species turnover, W = 21765 and P = 0.127 for species nestedness, and W = 20557 and P = 0.6303 for total beta-diversity at the scale of 10 m × 10 m, and P < 0.0001 for others.

Fig. 4. Specific effects of environmental variables on latitudinal gradients in tree beta-diversity.

Relative importance of five most important environmental factors for total beta-diversity, species turnover, and species nestedness of all trees (a–c), AM trees (d–f), and EcM trees (g–i) at the scale of 20 m × 20 m. Total beta-diversity and its components are the mean values of 200 replicates of average pairwise beta-diversity and its component metrics calculated based on 15 randomly sampled quadrats of 20 m × 20 m from each forest plot. The relative importance of variables was ranked by the increase in node purity (horizontal axis). The proportion of variance displayed was explained by all of 34 environmental variables. Circle points indicate significant importance of predictors whereas triangles indicate non-significant importance of predictors. The meanings of environmental variables are as follows: bio_01 = Annual Mean Temperature, bio_02 = Mean Diurnal Range (Mean of monthly (max temp - min temp)), bio_05 = Max Temperature of Warmest Month, bio_06 = Min Temperature of Coldest Month, bio_07 = Temperature Annual Range (BIO5-BIO6), bio_08 = Mean Temperature of Wettest Quarter, bio_10 = Mean Temperature of Warmest Quarter, bio_12 = Annual Precipitation, bio_13 = Precipitation of Wettest Month, bio_16 = Precipitation of Wettest Quarter, bio_18 = Precipitation of Warmest Quarter, srad = Solar Radiation, pet = Potential Evapotranspiration, elev = Elevation, aspect = Slope Aspect, aspect.r = Range of Aspect, convex.r = Range of Curvature, slope.cv = Coefficient of Variation of Slope, convex.cv = Coefficient of Variation of Curvature.