Pattern and control of biomass allocation across global forest ecosystems

Climate factors affect forest biomass allocation by altering soil nutrient availability and leaf traits

Biomass in forests sequesters substantial amounts of carbon; although the contribution of aboveground biomass has been extensively studied, the contribution of belowground biomass remains understudied. Investigating the forest biomass allocation is crucial for understanding the impacts of global change on carbon allocation and cycling. Moreover, the question of how climate factors affect biomass allocation in natural and planted forests remains unresolved. Here, we addressed this question by collecting data from 384 planted forests and 541 natural forests in China. We evaluated the direct and indirect effects of climate factors on the belowground biomass proportion (BGBP). The average BGBP was 31.09% in natural forests and was significantly higher (38.75%) in planted forests. Furthermore, we observed a significant decrease in BGBP with increasing temperature and precipitation. Climate factors, particularly those affecting soil factors, such as pH, strongly affected the BGBP in natural and planted forests. Based on our results, we propose that future studies should consider the effects of forest type (natural or planted) and soil factors on BGBP.

Tree biomass allocation differs by mycorrhizal association

Tree biomass allocation to leaves, roots, and wood affects the residence time of carbon in forests, with potentially dramatic implications for ecosystem carbon storage. However, drivers of tree biomass allocation remain poorly quantified. Using a combination of global datasets, we tested the relative importance of climate, leaf habit, and tree mycorrhizal associations on biomass allocation. We show that trees that associate with arbuscular mycorrhizal fungi allocate roughly 4% more of their biomass to root tissue than trees that associate with ectomycorrhizal fungi. Further, the effect of mycorrhizal association on root biomass allocation was greater than that of climate and similar in magnitude to that of leaf habit (evergreen vs. deciduous). These patterns in whole-plant biomass allocation are likely due to differences in carbon investment toward root vs fungal tissues, where trees with arbuscular mycorrhizal fungi favor root production while trees with ectomycorrhizal fungi favor fungal tissue production. These results suggest that considering tree mycorrhizal associations could improve our understanding of ecosystem carbon storage in terrestrial biosphere models: specifically, that greater within-tree allocation to root biomass in AM-associated tree species may contribute to stable soil carbon pools in forests dominated by arbuscular mycorrhizal fungi.

Spatial patterns of global-scale forest root-shoot ratio and their controlling factors

The forest root-shoot ratio (R/S), i.e., the ratio of belowground to aboveground biomass at the stand level, is widely used in global and regional forest carbon stock estimation and in modeling of the forest carbon cycle. Despite recent advances in understanding forest R/S variations at the individual-tree level, spatial patterns of stand-level forest R/S ratio across the globe and their driving factors remain relatively unknown. Here, we compiled and analyzed an extensive dataset from 873 forest sites worldwide, analyzed and quantified the effects of major environmental and forest growth-related variables on the stand-level R/S ratio. Based on this analysis, we further mapped the spatial pattern of the global forest R/S ratio. Our results show that, globally, variations on the stand-level forest R/S ratio are largely affected by canopy height, latitude, climatic water deficit, forest type and regeneration method, which collectively explain 37% of the variations in R/S ratio. In addition, our results suggest significant intercontinental and national variations in forest R/S ratio. At the continental scale, forest R/S ratio is highest in Oceania and lowest in South America. At the national scale, Australia has the highest forest R/S ratio while Russia has the lowest values. The forest R/S ratio is generally lower in moist tropical regions, but increases when moving to the extra-tropics when seasonality in precipitation increases. The R/S ratio in temperate and boreal regions shows prominent spatial features regulated by forest species composition and regeneration method. We conclude that future changes in environmental, biotic and anthropogenic factors, such as increased climatic water deficit and forest management, might influence the forest R/S ratio, with implications for the global and regional land carbon cycle.

Pattern and control of biomass allocation across global forest ecosystems

The underground part of a tree is an important carbon sink in forest ecosystems. Understanding biomass allocation between the below- and aboveground parts (root:shoot ratios) is necessary for estimation of the underground biomass and carbon pool. Nevertheless, large-scale biomass allocation patterns and their control mechanisms are not well identified. In this study, a large database of global forests at the community level was compiled to investigate the root:shoot ratios and their responses to environmental factors. The results indicated that both the aboveground biomass (AGB) and belowground biomass (BGB) of the forests in China (medians 73.0 Mg/ha and 17.0 Mg/ha, respectively) were lower than those worldwide (medians 120.3 Mg/ha and 27.7 Mg/ha, respectively). The root:shoot ratios of the forests in China (median = 0.23), however, were not significantly different from other forests worldwide (median = 0.24). In general, the allocation of biomass between the belowground and aboveground parts was determined mainly by the inherent allometry of the plant but also by environmental factors. In this study, most correlations between root:shoot ratios and environmental factors (development parameter, climate, altitude, and soil) were weak but significant (p < .01). The allometric model agreed with the trends observed in this study and effectively estimated BGB based on AGB across the entire database.