Water table depth modulates productivity and biomass across Amazonian forests - Thaiane R. Sousa; Juliana Schietti; Igor O. Ribeiro; Thaise Emílio; Rafael Herrera Fernández; Hans ter Steege; Carolina V. Castilho; Adriane Esquivel‐Muelbert; Timothy Baker; Aline Pontes‐Lopes; Camila V. J. Silva; Juliana M. Silveira; et al. (Global Ecology and Biogeography, 2022)
Aim Water availability is the major driver of tropical forest structure and dynamics. Most research has focused on the impacts of climatic water availability, whereas remarkably little is known about the influence of water table depth and excess soil water on forest processes. Nevertheless, given that plants take up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water conditions. Location Lowland Amazonian forests. Time period 1971–2019. Methods We used 344 long‐term inventory plots distributed across Amazonia to analyse the effects of long‐term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil‐water and edaphic properties. Results Water supplied by both precipitation and groundwater affects forest structure and dynamics, but in different ways. Forests with a shallow water table (depth Main conclusions We show that the two extremes of water availability (excess and deficit) both reduce productivity in Amazon upland ( terra‐firme ) forests. Biomass and productivity across Amazonia respond not simply to regional climate, but rather to its interaction with water table conditions, exhibiting high local differentiation. Our study disentangles the relative contribution of those factors, helping to improve understanding of the functioning of tropical ecosystems and how they are likely to respond to climate change.

Compositional response of Amazon forests to climate change - Adriane Esquivel‐Muelbert; Timothy R. Baker; Kyle G. Dexter; Simon L. Lewis; Roel J. W. Brienen; Ted R. Feldpausch; Jon Lloyd; Abel Monteagudo‐Mendoza; Luzmila Arroyo; Esteban Álvarez-Dávila; Niro Higuchi; Beatriz S. Marimon; et al. (Global Change Biology, 2019)
Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate‐induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long‐term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO 2 concentrations): maximum tree size, biogeographic water‐deficit affiliation and wood density. Tree communities have become increasingly dominated by large‐statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry‐affiliated genera have become more abundant, while the mortality of wet‐affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry‐affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate‐change drivers, but yet to significantly impact whole‐community composition. The Amazon observational record suggests that the increase in atmospheric CO 2 is driving a shift within tree communities to large‐statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

Variation in stem mortality rates determines patterns of above‐ground biomass in A mazonian forests: implications for dynamic global vegetation models - Michelle O. Johnson; David Galbraith; Manuel Gloor; Hannes De Deurwaerder; Matthieu Guimberteau; Anja Rammig; Kirsten Thonicke; Hans Verbeeck; Celso von Randow; Abel Monteagudo; Oliver L. Phillips; Roel J. W. Brienen; et al. (Global Change Biology, 2016)
Understanding the processes that determine above‐ground biomass ( AGB ) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models ( DGVM s). AGB is determined by inputs from woody productivity [woody net primary productivity ( NPP )] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP , control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVM s. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB , which is consistent with the importance of stand size structure for determining spatial variation in AGB . The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB . In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB . Across the four models, basin‐wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVM s typically show strong positive relationships between woody NPP and AGB . Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVM s.