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

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.


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Data of 45 large forest plots across the globe were compiled. Trees were classified into AM-associated trees, EcM-associated trees, and other trees according to published database and literature. Beta regressions were used to detect the latitudinal patterns of beta diversity of different mycorrhizal-associated trees. Variation partitioning was conducted to test the relative importance of environmental and spatial variables, while random forest was used to test the relative importance of every single environmental variable.
Tree census data are compiled from the ForestGEO (https://www.forestgeo.si.edu/). In each forest plot, all free-standing woody stems with a diameter at breast (DBH) ! 1 cm were identified to species, tagged, measured, and mapped. The Uholka plot in Ukraine was an exception as woody stems were censused from a DBH ! 6 cm. Tree census data comprise tree ID, latin name, diameter at breast height (DBH) in cm, growth form, growth status, and coordinates in the plot based on tree stem. There is also a dataset of elevation at the 10-m or 20-m resolution and the Universal Transverse Mercator (UTM) or WGS84 plot coordinates.
To account for the scale-dependency of beta-diversity patterns, plot-level data were divided into 10 m × 10 m, 20 m × 20 m, and 50 m × 50 m quadrat-level data. To control for the sampling effort and to facilitate comparison across plots, we randomly sampled 30 quadrats of 10 m × 10 m, 15 quadrats of 20 m × 20 m, and 15 quadrats of 50 m × 50 m in each plot, as plot size varied across forest plots which may influence beta-diversity. This sampling procedure was repeated 200 times for each quadrat size and the results were averaged for each plot with the 95% confidence interval (95% CI). As beta-diversity measure used in this study was calculated as the averaging value of pairwise distance between sampled quadrats for each plot, 15 quadrats generated 15*14/2=105 pairs of quadrats and consequent 105 distance values, a large sample size.
Forest plot data were collected from the CTFS-ForestGEO network where forest plots were established and censused by different research teams but according to the same standard protocol which could be found in "Condit, R. 1998. Tropical forest census plots: methods and results from Barro Colorado Island, Panama and a comparison with other plots. Springer-Verlag andRG. Landes Company, Berlin andGeorgetown, TX".
Plot size ranges from 2.1 ha (Nanjenshan) to 60 ha (Jianfengling) and plot latitude ranges from 25.1°S (Ilha do Cardoso, Brazil) to 61.3°N (Scotty Creek, Canada), covering all continents with forests (i.e., Asia, Africa, Europe, South America, North America, and Oceania). Most plots especially those in China were established and censused near 2010 and they were re-censused every 5 years.
At the 50 m × 50 m scale, plots smaller than 8 ha (Cocoli, Sherman, Nanjenshan, Ngardok) were excluded from the analyses to ensure adequate sample size and statistical power. This study focused only on trees. Data of other growth forms (such as shrubs and liana) were excluded because we wanted to test the latitudinal beta-diversity patterns of trees rather than all woody plants.
We randomly sampled the same number of quadrats in each forest plot and repeated 200 times to ensure the robustness of our results. All attempts at replication were successful.
Detailed forest plot data collection were conducted according to a standard protocol and could be found in "Condit, R. 1998. Tropical forest census plots: methods and results from Barro Colorado Island, Panama and a comparison with other plots. Springer-Verlag andRG. Landes Company, Berlin andGeorgetown, TX". We randomly sampled the same number of quadrats in each forest plot and repeated 200 times to ensure the robustness of our results. These sampling procedures are random.
Blinding was not possible in this study because data were compiled from previously established and censused forest plots.