• Energy Research

Regional‐scale above‐ground biomass (AGB) estimates of tropical savannas and woodlands are highly uncertain, despite their global importance for ecosystems services and as carbon stores. In response, we collated field inventory data from 253 plots at four study sites in Cameroon, Uganda and Mozambique, and examined the relationships between field‐measured AGB and cross‐polarized radar backscatter values derived from ALOS PALSAR, an L‐band satellite sensor. The relationships were highly significant, similar among sites, and displayed high prediction accuracies up to 150 Mg ha−1 (±∼20%). AGB predictions for any given site obtained using equations derived from data from only the other three sites generated only small increases in error. The results suggest that a widely applicable general relationship exists between AGB and L‐band backscatter for lower‐biomass tropical woody vegetation. This relationship allows regional‐scale AGB estimation, required for example by planned REDD (Reducing Emissions from Deforestation and Degradation) schemes.

AbstractTropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, $$\varPsi $$ Ψ 50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3–5, little is known about how these vary across Earth’s largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters $$\varPsi $$ Ψ 50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both $$\varPsi $$ Ψ 50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth–mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink.

Summary Plant traits are increasingly being used to improve prediction of plant function, including plant demography. However, the capability of plant traits to predict demographic rates remains uncertain, particularly in the context of trees experiencing a changing climate. Here we present data combining 17 plant traits associated with plant structure, metabolism and hydraulic status, with measurements of long‐term mean, maximum and relative growth rates for 176 trees from the world’s longest running tropical forest drought experiment. We demonstrate that plant traits can predict mean annual tree growth rates with moderate explanatory power. However, only combinations of traits associated more directly with plant functional processes, rather than more commonly employed traits like wood density or leaf mass per area, yield the power to predict growth. Critically, we observe a shift from growth being controlled by traits related to carbon cycling (assimilation and respiration) in well‐watered trees, to traits relating to plant hydraulic stress in drought‐stressed trees. We also demonstrate that even with a very comprehensive set of plant traits and growth data on large numbers of tropical trees, considerable uncertainty remains in directly interpreting the mechanisms through which traits influence performance in tropical forests.

Data comprise tree trait data collected during September and October 2016 (the peak dry season), in the Caxiuanã National Forest Reserve, eastern Amazon, Brazil. 17 traits (including plot type, tree species name, diameter at breast height, tree light score, carboxylation capacity, electron transport capacity, leaf respiration in the dark, stomatal conductance, stem CO2 efflux, leaf mass per area, leaf nitrogen and phosphorus content, branch wood density, leaf water potential, xylem pressure, lumen conductance, percentage loss of conductivity, hydraulic Safety Margin and leaf area to sapwood area ratio) of 176 trees (most common genera) were sampled across two experimental plots: a one-hectare through-fall exclusion plot with a plastic panel structure that excludes 50% of the canopy through-fall and has done since 2002 and a corresponding one-hectare control plot without any drought structure. This data comes from the Caxiuanã through-fall exclusion (TFE) experiment located in the terra firma forest, on yellow oxisol soils at 15 m above sea level, with a mean annual rainfall between 2,000–2,500 mm and a pronounced dry season between June and November. To sample the traits, three branches from the same tree were gathered at three specific time periods each day in September and October 2016. Stem CO2 efflux measurements (Rstem) were made in October 2016 using a gas analyser attached in a close loop system to a 75cm2 area of each of our study trees. Growth rates were calculated for each tree using mean stem increment data measured every three months using dendrometers, as presented in Rowland et al., (https://doi.org/10.1038/nature15539). Mean growth increment was calculated by averaging three-monthly growth rate data from 2010-2016 for each tree and then log-transforming these data.

AbstractTerrestrial biogeochemical feedbacks to the climate are strongly modulated by the temperature response of soil microorganisms. Tropical forests, in particular, exert a major influence on global climate because they are the most productive terrestrial ecosystem. We used an elevation gradient across tropical forest in the Andes (a gradient of 20°C mean annual temperature, MAT), to test whether soil bacterial and fungal community growth responses are adapted to long‐term temperature differences. We evaluated the temperature dependency of soil bacterial and fungal growth using the leucine‐ and acetate‐incorporation methods, respectively, and determined indices for the temperature response of growth: Q10 (temperature sensitivity over a given 10oC range) and Tmin (the minimum temperature for growth). For both bacterial and fungal communities, increased MAT (decreased elevation) resulted in increases in Q10 and Tmin of growth. Across a MAT range from 6°C to 26°C, the Q10 and Tmin varied for bacterial growth (Q10–20 = 2.4 to 3.5; Tmin = −8°C to −1.5°C) and fungal growth (Q10–20 = 2.6 to 3.6; Tmin = −6°C to −1°C). Thus, bacteria and fungi did not differ significantly in their growth temperature responses with changes in MAT. Our findings indicate that across natural temperature gradients, each increase in MAT by 1°C results in increases in Tmin of microbial growth by approximately 0.3°C and Q10–20 by 0.05, consistent with long‐term temperature adaptation of soil microbial communities. A 2°C warming would increase microbial activity across a MAT gradient of 6°C to 26°C by 28% to 15%, respectively, and temperature adaptation of microbial communities would further increase activity by 1.2% to 0.3%. The impact of warming on microbial activity, and the related impact on soil carbon cycling, is thus greater in regions with lower MAT. These results can be used to predict future changes in the temperature response of microbial activity over different levels of warming and over large temperature ranges, extending to tropical regions.

Summary Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf‐ and ecosystem‐level observations. SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem‐level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root‐mean‐square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.