The linkages between photosynthesis, productivity, growth and biomass in lowland Amazonian forests

Hydraulic traits exert greater limitations on tree-level maximum sap flux density than photosynthetic ability: Global evidence

Transpiration is a key process that couples the land-atmosphere exchange of water and carbon, and its maximum water transport ability affects plant productivity. Functional traits significantly influence the maximum transpiration rate; however, which factor plays the dominant role remains unknown. SAPFLUXNET dataset, which includes sap flux density of diverse species worldwide, provides fundamental data to test the importance of photosynthetic and hydraulic traits on maximum tree-level sap flux density (Js_max). Here, we investigated variations in Js_max of 2194 trees across 129 species using data from the SAPFLUXNET dataset, and analysed the relationship of Js_max with photosynthetic and hydraulic traits. Our results indicated that Js_max was positively correlated with photosynthetic traits at both leaf and tree level. Regarding hydraulic traits, Js_max was positively related to xylem hydraulic conductivity (Ks), leaf-specific hydraulic conductivity (Kl), xylem pressure inducing 50 % loss of hydraulic conductivity (P50), xylem vessel diameter (Vdia), and leaf-to-sapwood area ratio (AlAs). Random forest model showed that 87 % of the variability in Js_max can be explained by functional traits, and hydraulic traits (e.g., P50 and sapwood area, As) exerted larger effects on Js_max than photosynthetic traits. Moreover, trees with a lower sapwood area or depth could increase their sap flux density to compensate for the reduced whole-tree transpiration. Js_max of the angiosperms was significantly higher than that of the gymnosperms. Mean annual total precipitation (MAP) were positively related to Js_max with a weak correlation coefficient. Furthermore, Js_max showed a significant phylogenetic signal with Blomberg's K below 0.2. Overall, tree species with acquisitive resource economics or more efficient hydraulic systems show higher water transport capacity, and the efficiency of xylem hydraulic system rather than the demand for carbon uptake predominantly determines water transport capacity.

Selective logging impacts on soil microbial communities and functioning in Bornean tropical forest

Rainforests provide vital ecosystem services that are underpinned by plant-soil interactions. The forests of Borneo are globally important reservoirs of biodiversity and carbon, but a significant proportion of the forest that remains after large-scale agricultural conversion has been extensively modified due to timber harvest. We have limited understanding of how selective logging affects ecosystem functions including biogeochemical cycles driven by soil microbes. In this study, we sampled soil from logging gaps and co-located intact lowland dipterocarp rainforest in Borneo. We characterised soil bacterial and fungal communities and physicochemical properties and determined soil functioning in terms of enzyme activity, nutrient supply rates, and microbial heterotrophic respiration. Soil microbial biomass, alpha diversity, and most soil properties and functions were resistant to logging. However, we found logging significantly shifted soil bacterial and fungal community composition, reduced the abundance of ectomycorrhizal fungi, increased the abundance of arbuscular mycorrhizal fungi, and reduced soil inorganic phosphorous concentration and nitrate supply rate, suggesting some downregulation of nutrient cycling. Within gaps, canopy openness was negatively related to ectomycorrhizal abundance and phosphomonoesterase activity and positively related to ammonium supply rate, suggesting control on soil phosphorus and nitrogen cycles via functional shifts in fungal communities. We found some evidence for reduced soil heterotrophic respiration with greater logging disturbance. Overall, our results demonstrate that while many soil microbial community attributes, soil properties, and functions may be resistant to selective logging, logging can significantly impact the composition and abundance of key soil microbial groups linked to the regulation of vital nutrient and carbon cycles in tropical forests.

Spectral ecophysiology: hyperspectral pressure-volume curves to estimate leaf turgor loss

Turgor loss point (TLP) is an important proxy for plant drought tolerance, species habitat suitability, and drought-induced plant mortality risk. Thus, TLP serves as a critical tool for evaluating climate change impacts on plants, making it imperative to develop high-throughput and in situ methods to measure TLP. We developed hyperspectral pressure-volume curves (PV curves) to estimate TLP using leaf spectral reflectance. We used partial least square regression models to estimate water potential (Ψ) and relative water content (RWC) for two species, Frangula caroliniana and Magnolia grandiflora. RWC and Ψ's model for each species had R2 ≥ 0.7 and %RMSE = 7-10. We constructed PV curves with model estimates and compared the accuracy of directly measured and spectra-predicted TLP. Our findings indicate that leaf spectral measurements are an alternative method for estimating TLP. F. caroliniana TLP's values were -1.62 ± 0.15 (means ± SD) and -1.62 ± 0.34 MPa for observed and reflectance predicted, respectively (P > 0.05), while M. grandiflora were -1.78 ± 0.34 and -1.66 ± 0.41 MPa (P > 0.05). The estimation of TLP through leaf reflectance-based PV curves opens a broad range of possibilities for future research aimed at understanding and monitoring plant water relations on a large scale with spectral ecophysiology.

Contrasting carbon cycle along tropical forest aridity gradients in West Africa and Amazonia

Tropical forests cover large areas of equatorial Africa and play a substantial role in the global carbon cycle. However, there has been a lack of biometric measurements to understand the forests' gross and net primary productivity (GPP, NPP) and their allocation. Here we present a detailed field assessment of the carbon budget of multiple forest sites in Africa, by monitoring 14 one-hectare plots along an aridity gradient in Ghana, West Africa. When compared with an equivalent aridity gradient in Amazonia, the studied West African forests generally had higher productivity and lower carbon use efficiency (CUE). The West African aridity gradient consistently shows the highest NPP, CUE, GPP, and autotrophic respiration at a medium-aridity site, Bobiri. Notably, NPP and GPP of the site are the highest yet reported anywhere for intact forests. Widely used data products substantially underestimate productivity when compared to biometric measurements in Amazonia and Africa. Our analysis suggests that the high productivity of the African forests is linked to their large GPP allocation to canopy and semi-deciduous characteristics.

Exploring carbon sequestration in broad-leaved Korean pine forests: Insights into photosynthetic and respiratory processes

A comprehensive understanding of carbon assimilation and sequestration in broad-leaved Korean pine forests is crucial for accurately estimating this significant aspect of temperate forests at a regional scale. In this study, we introduced a high-temporal resolution model designed for carbon assimilation insights at the plot scale, focusing on specific parameters such as leaf area dynamics, vertical leaf distribution, photosynthetically active radiation (PAR) fluctuations, and the photosynthetic traits of tree species. The findings reveal that most tree species in broad-leaved Korean pine forests exhibit an inverted U-shaped pattern in leaf area dynamics, with shorter leaf drop periods than leaf expansion events. Leaf distribution varies significantly among different canopy heights, with approximately 80 % of the leaves above 15 m. PAR decreases as canopy height decreases, with PAR at 25 m accounting for about 60 % of the PAR above the canopy. Our framework incorporates a leaf-scale light-response curve and empirical photosynthesis-temperature relationships to estimate forest carbon assimilation on daily and hourly scales accurately. Using the model, we assess the gross primary productivity (GPP), leaf net photosynthetic assimilation (LNPA), and carbon increment (ΔC) of broad-leaved Korean pine forests from 2017 to 2020. The results demonstrate GPP, LNPA, and ΔC values of 21.4 t·ha-1·a-1, 17.4 t·ha-1·a-1, and 4.0 t·ha-1·a-1, respectively. Regarding efficiency, GPP, LNPA, and ΔC per square meter of leaf per year are 179 g, 146 g, and 33 g, respectively. Notably, tree species in the canopy layer of the forest exhibit significantly higher efficiency than those in the understory layer. This research significantly contributes to our understanding of carbon cycling and the responses of forest ecosystems to climate change. Moreover, it provides a practical tool for forest management and the development of carbon sequestration strategies.

Nature-based solutions are critical for putting Brazil on track towards net-zero emissions by 2050

Most of the world's nations (around 130) have committed to reaching net-zero carbon dioxide or greenhouse gas (GHG) emissions by 2050, yet robust policies rarely underpin these ambitions. To investigate whether existing and expected national policies will allow Brazil to meet its net-zero GHG emissions pledge by 2050, we applied a detailed regional integrated assessment modelling approach. This included quantifying the role of nature-based solutions, such as the protection and restoration of ecosystems, and engineered solutions, such as bioenergy with carbon capture and storage. Our results highlight ecosystem protection as the most critical cost-effective climate mitigation measure for Brazil, whereas relying heavily on costly and not-mature-yet engineered solutions will jeopardise Brazil's chances of achieving its net-zero pledge by mid-century. We show that the full implementation of Brazil's Forest Code (FC), a key policy for emission reduction in Brazil, would be enough for the country to achieve its short-term climate targets up to 2030. However, it would reduce the gap to net-zero GHG emissions by 38% by 2050. The FC, combined with zero legal deforestation and additional large-scale ecosystem restoration, would reduce this gap by 62% by mid-century, keeping Brazil on a clear path towards net-zero GHG emissions by around 2040. While some level of deployment of negative emissions technologies will be needed for Brazil to achieve and sustain its net-zero pledge, we show that the more mitigation measures from the land-use sector, the less costly engineered solutions from the energy sector will be required. Our analysis underlines the urgent need for Brazil to go beyond existing policies to help fight climate emergency, to align its short- and long-term climate targets, and to build climate resilience while curbing biodiversity loss.

Shifting of nutrient limitation dominates the recovery of aboveground net primary productivity of mixed forests in northeastern China after selective logging

The primary productivity of temperate forests is commonly limited by nitrogen (N) supply, which may be aggravated by the removal of trees. After selective logging, whether and the mechanism by which the N limitation can be alleviated by the rapidly increasing nutrient turnover during the recovery processes, which is important for improving carbon sequestration in temperate forests, remain unclear. We investigated the effect of nutrient limitation (leaf N:Pcom: the leaf N:P ratio at the community level) on plant community productivity by selecting 28 forest plots including seven forest recovery periods (at the sites logged 6, 14, 25, 36, 45, 55, and 100 years ago) following low-intensity selective logging (13-14 m3/ha) and one unlogged treatment by measuring the soil N concentration, soil phosphorus (P) concentration, leaf N concentration, leaf P concentration, and the aboveground net primary productivity (ANPP) of 234 plant species. The plant growth in temperate forests was limited by N, but the P limitation was observed at the sites logged 36 years ago, which showed a transition pattern of plant growth from N limitation to P limitation during the forest recovery process. Meanwhile, a robust linear trend in the community ANPP was observed with the increase in the community leaf N:P ratio, which suggests the enhancement in community ANPP with the release of N limitation after selective logging. Nutrient limitation (leaf N:Pcom) had a significant direct effect (56.0 %) on the community ANPP and showed a higher independent contribution (25.6 %) to the variation in the community ANPP than the soil nutrient supply and even the changes in species richness. Our results suggested that selective logging alleviated the N limitation, but a shift toward P limitation should also be highly regarded in learning the changes in carbon sequestration during the recovery processes.

Co-developing an international TLS network for the 3D ecological understanding of global trees: System architecture, remote sensing models, and functional prospects

Trees are spread worldwide, as the watchmen that experience the intricate ecological effects caused by various environmental factors. In order to better understand such effects, it is preferential to achieve finely and fully mapped global trees and their environments. For this task, aerial and satellite-based remote sensing (RS) methods have been developed. However, a critical branch regarding the apparent forms of trees has significantly fallen behind due to the technical deficiency found within their global-scale surveying methods. Now, terrestrial laser scanning (TLS), a state-of-the-art RS technology, is useful for the in situ three-dimensional (3D) mapping of trees and their environments. Thus, we proposed co-developing an international TLS network as a macroscale ecotechnology to increase the 3D ecological understanding of global trees. First, we generated the system architecture and tested the available RS models to deepen its ground stakes. Then, we verified the ecotechnology regarding the identification of its theoretical feasibility, a review of its technical preparations, and a case testification based on a prototype we designed. Next, we conducted its functional prospects by previewing its scientific and technical potentials and its functional extensibility. Finally, we summarized its technical and scientific challenges, which can be used as the cutting points to promote the improvement of this technology in future studies. Overall, with the implication of establishing a novel cornerstone-sense ecotechnology, the co-development of an international TLS network can revolutionize the 3D ecological understanding of global trees and create new fields of research from 3D global tree structural ecology to 3D macroecology.

Laisk measurements in the nonsteady state: Tests in plants exposed to warming and variable CO2 concentrations

Light respiration (RL) is an important component of plant carbon balance and a key parameter in photosynthesis models. RL is often measured using the Laisk method, a gas exchange technique that is traditionally employed under steady-state conditions. However, a nonsteady-state dynamic assimilation technique (DAT) may allow for more rapid Laisk measurements. In 2 studies, we examined the efficacy of DAT for estimating RL and the parameter Ci* (the intercellular CO2 concentration where Rubisco's oxygenation velocity is twice its carboxylation velocity), which is also derived from the Laisk technique. In the first study, we compared DAT and steady-state RL and Ci* estimates in paper birch (Betula papyrifera) growing under control and elevated temperature and CO2 concentrations. In the second, we compared DAT-estimated RL and Ci* in hybrid poplar (Populus nigra L. × P. maximowiczii A. Henry "NM6") exposed to high or low CO2 concentration pre-treatments. The DAT and steady-state methods provided similar RL estimates in B. papyrifera, and we found little acclimation of RL to temperature or CO2; however, Ci* was higher when measured with DAT compared to steady-state methods. These Ci* differences were amplified by the high or low CO2 pre-treatments. We propose that changes in the export of glycine from photorespiration may explain these apparent differences in Ci*.

Elucidating climatic drivers of photosynthesis by tropical forests

Tropical forests play a pivotal role in regulating the global carbon cycle. However, the response of these forests to changes in absorbed solar energy and water supply under the changing climate is highly uncertain. Three-year (2018-2021) spaceborne high-resolution measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) provide a new opportunity to study the response of gross primary production (GPP) and more broadly tropical forest carbon dynamics to differences in climate. SIF has been shown to be a good proxy for GPP on monthly and regional scales. Combining tropical climate reanalysis records and other contemporary satellite products, we find that on the seasonal timescale, the dependence of GPP on climate variables is highly heterogeneous. Following the principal component analyses and correlation comparisons, two regimes are identified: water limited and energy limited. GPP variations over tropical Africa are more correlated with water-related factors such as vapor pressure deficit (VPD) and soil moisture, while in tropical Southeast Asia, GPP is more correlated with energy-related factors such as photosynthetically active radiation (PAR) and surface temperature. Amazonia is itself heterogeneous: with an energy-limited regime in the north and water-limited regime in the south. The correlations of GPP with climate variables are supported by other observation-based products, such as Orbiting Carbon Observatory-2 (OCO2) SIF and FluxSat GPP. In each tropical continent, the coupling between SIF and VPD increases with the mean VPD. Even on the interannual timescale, the correlation of GPP with VPD is still discernable, but the sensitivity is smaller than the intra-annual correlation. By and large, the dynamic global vegetation models in the TRENDY v8 project do not capture the high GPP seasonal sensitivity to VPD in dry tropics. The complex interactions between carbon and water cycles in the tropics illustrated in this study and the poor representation of this coupling in the current suite of vegetation models suggest that projections of future changes in carbon dynamics based on these models may not be robust.

Optical Remote Sensing in Provisioning of Ecosystem-Functions Analysis-Review

Keeping natural ecosystems and their functions in the proper condition is necessary. One of the best contactless monitoring methods is remote sensing, especially optical remote sensing, which is used for vegetation applications. In addition to satellite data, data from ground sensors are necessary for validation or training in ecosystem-function quantification. This article focuses on the ecosystem functions associated with aboveground-biomass production and storage. The study contains an overview of the remote-sensing methods used for ecosystem-function monitoring, especially methods for detecting primary variables linked to ecosystem functions. The related studies are summarized in multiple tables. Most studies use freely available Sentinel-2 or Landsat imagery, with Sentinel-2 mostly producing better results at larger scales and in areas with vegetation. The spatial resolution is a key factor that plays a significant role in the accuracy with which ecosystem functions are quantified. However, factors such as spectral bands, algorithm selection, and validation data are also important. In general, optical data are usable even without supplementary data.

Forest disturbances and climate constrain carbon allocation dynamics in trees

Forest disturbances such as drought, fire, and logging affect the forest carbon dynamics and the terrestrial carbon sink. Forest mortality after disturbances creates uncertainties that need to be accounted for to understand forest dynamics and their associated C-sink. We combined data from permanent resampling plots and biomass oriented dendroecological plots to estimate time series of annual woody biomass growth (ABI) in several forests. ABI time series were used to benchmark a vegetation model to analyze dynamics in forest productivity and carbon allocation forced by environmental variability. The model implements source and sink limitations explicitly by dynamically constraining carbon allocation of assimilated photosynthates as a function of temperature and moisture. Bias in tree-ring reconstructed ABI increased back in time from data collection and with increasing disturbance intensity. ABI bias ranged from zero, in open stands without recorded mortality, to over 100% in stands with major disturbances such as thinning or snowstorms. Stand leaf area was still lower than in control plots decades after heavy thinning. Disturbances, species life-history strategy and climatic variability affected carbon-partitioning patterns in trees. Resprouting broadleaves reached maximum biomass growth at earlier ages than nonresprouting conifers. Environmental variability and leaf area explained much variability in woody biomass allocation. Effects of stand competition on C-allocation were mediated by changes in stand leaf area except after major disturbances. Divergence between tree-ring estimated and simulated ABI were caused by unaccounted changes in allocation or misrepresentation of some functional process independently of the model calibration approach. Higher disturbance intensity produced greater modifications of the C-allocation pattern, increasing error in reconstructed biomass dynamics. Legacy effects from disturbances decreased model performance and reduce the potential use of ABI as a proxy to net primary productivity. Trait-based dynamics of C-allocation in response to environmental variability need to be refined in vegetation models.

Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño

The 2015/16 El Niño brought severe drought and record-breaking temperatures in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of [Formula: see text]. [Formula: see text] is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data-RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high [Formula: see text] may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high [Formula: see text] ([Formula: see text] ≥ 0.3) appear to have a stronger capacity to recover than low-[Formula: see text] ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics.

Tropical tree mortality has increased with rising atmospheric water stress

Evidence exists that tree mortality is accelerating in some regions of the tropics^1,2, with profound consequences for the future of the tropical carbon sink and the global anthropogenic carbon budget left to limit peak global warming below 2 °C. However, the mechanisms that may be driving such mortality changes and whether particular species are especially vulnerable remain unclear^3-8. Here we analyse a 49-year record of tree dynamics from 24 old-growth forest plots encompassing a broad climatic gradient across the Australian moist tropics and find that annual tree mortality risk has, on average, doubled across all plots and species over the last 35 years, indicating a potential halving in life expectancy and carbon residence time. Associated losses in biomass were not offset by gains from growth and recruitment. Plots in less moist local climates presented higher average mortality risk, but local mean climate did not predict the pace of temporal increase in mortality risk. Species varied in the trajectories of their mortality risk, with the highest average risk found nearer to the upper end of the atmospheric vapour pressure deficit niches of species. A long-term increase in vapour pressure deficit was evident across the region, suggesting that thresholds involving atmospheric water stress, driven by global warming, may be a primary cause of increasing tree mortality in moist tropical forests.

Tropical tree growth sensitivity to climate is driven by species intrinsic growth rate and leaf traits

A better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) drive spatial variations in species' baseline growth rates, whereas deviations from these averages over time (anomalies) can create growth variation around the local baseline. However, the rarity of long-term tree census data spanning climatic gradients has so far limited our understanding of their respective role, especially in tropical systems. Furthermore, tree growth sensitivity to climate is likely to vary widely among species, and the ecological strategies underlying these differences remain poorly understood. Here, we utilize an exceptional dataset of 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how multiannual tree growth responds to both climate means and anomalies, and how species' functional traits mediate these growth responses to climate. We show that anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both climate means and anomalies. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests and that species traits can provide insights into understanding these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.

Effects of Different Soils on the Biomass and Photosynthesis of Rumex nepalensis in Subalpine Region of Southwestern China

The performance of Rumex nepalensis, an important medicinal herb, varies significantly among subalpine grasslands, shrublands and forest ecosystems in southwestern China. Plant–soil feedback is receiving increasing interest as an important driver influencing plant growth and population dynamics. However, the feedback effects of soils from different ecosystems on R. nepalensis remain poorly understood. A greenhouse experiment was carried out to identify the effects of different soil sources on the photosynthesis and biomass of R. nepalensis. R. nepalensis was grown in soils collected from the rooting zones of R. nepalensis (a grassland soil, RS treatment), Hippophae rhamnoides (a shrub soil, HS treatment), and Picea asperata (a forest soil, PS treatment). The chlorophyll contents, net photosynthetic rates, and biomasses of R. nepalensis differed significantly among the three soils and followed the order of RS > HS > PS. After soil sterilization, these plant parameters followed the order of RS > PS > HS. The total biomass was 16.5 times higher in sterilized PS than in unsterilized PS, indicating that the existence of soil microbes in P. asperata forest ecosystems could strongly inhibit R. nepalensis growth. The root to shoot biomass ratio of R. nepalensis was the highest in the sterilized PS but the lowest in the unsterilized PS, which showed that soil microbes in PS could change the biomass allocation. Constrained redundancy analysis and path analysis suggested that soil microbes could impact the growth of R. nepalensis via the activities of soil extracellular enzymes (e.g., β-1,4-N-acetylglucosaminidase (NAG)) in live soils. The soil total soluble nitrogen concentration might be the main soil factor regulating R. nepalensis performance in sterilized soils. Our findings underline the importance of the soil microbes and nitrogen to R. nepalensis performance in natural ecosystems and will help to better predict plant population dynamics.

The CO2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales

High-quality atmospheric CO₂  measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO₂ . In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO₂ at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO₂ regional signal ( ΔCO2obs ) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between ΔCO2obs and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of ΔCO2obs . In addition, we present how the 2015-2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of ΔCO2obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO₂ exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO₂ from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.

Altered growth conditions more than reforestation counteracted forest biomass carbon emissions 1990-2020

Understanding the carbon (C) balance in global forest is key for climate-change mitigation. However, land use and environmental drivers affecting global forest C fluxes remain poorly quantified. Here we show, following a counterfactual modelling approach based on global Forest Resource Assessments, that in 1990-2020 deforestation is the main driver of forest C emissions, partly counteracted by increased forest growth rates under altered conditions: In the hypothetical absence of changes in forest (i) area, (ii) harvest or (iii) burnt area, global forest biomass would reverse from an actual cumulative net C source of c. 0.74 GtC to a net C sink of 26.9, 4.9 and 0.63 GtC, respectively. In contrast, (iv) without growth rate changes, cumulative emissions would be 7.4 GtC, i.e., 10 times higher. Because this sink function may be discontinued in the future due to climate-change, ending deforestation and lowering wood harvest emerge here as key climate-change mitigation strategies.

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade-off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade-off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers.

Genome-wide association studies reveal the coordinated regulatory networks underlying photosynthesis and wood formation in Populus

Photosynthesis and wood formation underlie the ability of trees to provide renewable resources and perform ecological functions; however, the genetic basis and regulatory pathways coordinating these two linked processes remain unclear. Here, we used a systems genetics strategy, integrating genome-wide association studies, transcriptomic analyses, and transgenic experiments, to investigate the genetic architecture of photosynthesis and wood properties among 435 unrelated individuals of Populus tomentosa, and unravel the coordinated regulatory networks resulting in two trait categories. We detected 222 significant single-nucleotide polymorphisms, annotated to 177 candidate genes, for 10 traits of photosynthesis and wood properties. Epistasis uncovered 74 epistatic interactions for phenotypes. Strikingly, we deciphered the coordinated regulation patterns of pleiotropic genes underlying phenotypic variations for two trait categories. Furthermore, expression quantitative trait nucleotide mapping and coexpression analysis were integrated to unravel the potential transcriptional regulatory networks of candidate genes coordinating photosynthesis and wood properties. Finally, heterologous expression of two pleiotropic genes, PtoMYB62 and PtoMYB80, in Arabidopsis thaliana demonstrated that they control regulatory networks balancing photosynthesis and stem secondary cell wall components, respectively. Our study provides insights into the regulatory mechanisms coordinating photosynthesis and wood formation in poplar, and should facilitate genetic breeding in trees via molecular design.

Tackling unresolved questions in forest ecology: The past and future role of simulation models

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass

Tropical forests vary widely in biomass carbon (C) stocks and fluxes even after controlling for forest age. A mechanistic understanding of this variation is critical to accurately predicting responses to global change. We review empirical studies of spatial variation in tropical forest biomass, productivity and woody residence time, focusing on mature forests. Woody productivity and biomass decrease from wet to dry forests and with elevation. Within lowland forests, productivity and biomass increase with temperature in wet forests, but decrease with temperature where water becomes limiting. Woody productivity increases with soil fertility, whereas residence time decreases, and biomass responses are variable, consistent with an overall unimodal relationship. Areas with higher disturbance rates and intensities have lower woody residence time and biomass. These environmental gradients all involve both direct effects of changing environments on forest C fluxes and shifts in functional composition - including changing abundances of lianas - that substantially mitigate or exacerbate direct effects. Biogeographic realms differ significantly and importantly in productivity and biomass, even after controlling for climate and biogeochemistry, further demonstrating the importance of plant species composition. Capturing these patterns in global vegetation models requires better mechanistic representation of water and nutrient limitation, plant compositional shifts and tree mortality.

Does economic optimisation explain LAI and leaf trait distributions across an Amazon soil moisture gradient?

Leaf area index (LAI) underpins terrestrial ecosystem functioning, yet our ability to predict LAI remains limited. Across Amazon forests, mean LAI, LAI seasonal dynamics and leaf traits vary with soil moisture stress. We hypothesise that LAI variation can be predicted via an optimality-based approach, using net canopy C export (NCE, photosynthesis minus the C cost of leaf growth and maintenance) as a fitness proxy. We applied a process-based terrestrial ecosystem model to seven plots across a moisture stress gradient with detailed in situ measurements, to determine nominal plant C budgets. For each plot, we then compared observations and simulations of the nominal (i.e. observed) C budget to simulations of alternative, experimental budgets. Experimental budgets were generated by forcing the model with synthetic LAI timeseries (across a range of mean LAI and LAI seasonality) and different leaf trait combinations (leaf mass per unit area, lifespan, photosynthetic capacity and respiration rate) operating along the leaf economic spectrum. Observed mean LAI and LAI seasonality across the soil moisture stress gradient maximised NCE, and were therefore consistent with optimality-based predictions. Yet, the predictive power of an optimality-based approach was limited due to the asymptotic response of simulated NCE to mean LAI and LAI seasonality. Leaf traits fundamentally shaped the C budget, determining simulated optimal LAI and total NCE. Long-lived leaves with lower maximum photosynthetic capacity maximised simulated NCE under aseasonal high mean LAI, with the reverse found for short-lived leaves and higher maximum photosynthetic capacity. The simulated leaf trait LAI trade-offs were consistent with observed distributions. We suggest that a range of LAI strategies could be equally economically viable at local level, though we note several ecological limitations to this interpretation (e.g. between-plant competition). In addition, we show how leaf trait trade-offs enable divergence in canopy strategies. Our results also allow an assessment of the usefulness of optimality-based approaches in simulating primary tropical forest functioning, evaluated against in situ data.

The other side of droughts: wet extremes and topography as buffers of negative drought effects in an Amazonian forest

There is a consensus about negative impacts of droughts in Amazonia. Yet, extreme wet episodes, which are becoming as severe and frequent as droughts, are overlooked and their impacts remain poorly understood. Moreover, drought reports are mostly based on forests over a deep water table (DWT), which may be particularly sensitive to dry conditions. Based on demographic responses of 30 abundant tree species over the past two decades, in this study we analyzed the impacts of severe droughts but also of concurrent extreme wet periods, and how topographic affiliation (to shallow - SWTs - or deep - DWTs - water tables), together with species functional traits, mediated climate effects on trees. Dry and wet extremes decreased growth and increased tree mortality, but interactions of these climatic anomalies had the highest and most positive impact, mitigating the simple negative effects. Despite being more drought-tolerant, species in DWT forests were more negatively affected than hydraulically vulnerable species in SWT forests. Interaction of wet-dry extremes and SWT depth modulated tree responses to climate, providing buffers to droughts in Amazonia. As extreme wet periods are projected to increase and at least 36% of the Amazon comprises SWT forests, our results highlight the importance of considering these factors in order to improve our knowledge about forest resilience to climate change.

Model-Based Estimation of Amazonian Forests Recovery Time after Drought and Fire Events

In recent decades, droughts, deforestation and wildfires have become recurring phenomena that have heavily affected both human activities and natural ecosystems in Amazonia. The time needed for an ecosystem to recover from carbon losses is a crucial metric to evaluate disturbance impacts on forests. However, little is known about the impacts of these disturbances, alone and synergistically, on forest recovery time and the resulting spatiotemporal patterns at the regional scale. In this study, we combined the 3-PG forest growth model, remote sensing and field derived equations, to map the Amazonia-wide (3 km of spatial resolution) impact and recovery time of aboveground biomass (AGB) after drought, fire and a combination of logging and fire. Our results indicate that AGB decreases by 4%, 19% and 46% in forests affected by drought, fire and logging + fire, respectively, with an average AGB recovery time of 27 years for drought, 44 years for burned and 63 years for logged + burned areas and with maximum values reaching 184 years in areas of high fire intensity. Our findings provide two major insights in the spatial and temporal patterns of drought and wildfire in the Amazon: (1) the recovery time of the forests takes longer in the southeastern part of the basin, and, (2) as droughts and wildfires become more frequent—since the intervals between the disturbances are getting shorter than the rate of forest regeneration—the long lasting damage they cause potentially results in a permanent and increasing carbon losses from these fragile ecosystems.

Response of Medical Cannabis (Cannabis sativa L.) to Nitrogen Supply Under Long Photoperiod

The development progression of medical cannabis plants includes a vegetative growth phase under long photoperiod, followed by a reproductive phase under short photoperiod. Establishment of plant architecture at the vegetative phase affects its reproduction potential under short photoperiod. Nitrogen (N) is a main component of many metabolites that are involved in central processes in plants, and is therefore a major factor governing plant development and structure. We lack information about the influence of N nutrition on medical cannabis functional-physiology and development, and plant N requirements are yet unknown. The present study therefore investigated the developmental, physiological, and chemical responses of medical cannabis plants to N supply (30, 80, 160, 240, and 320 mgL^-1 N) under long photoperiod. The plants were cultivated in an environmentally controlled growing room, in pots filled with soilless media. We report that the morpho-physiological function under long photoperiod in medical cannabis is optimal at 160 mgL^-1 N supply, and significantly lower under 30 mgL^-1 N, with visual deficiency symptoms, and 75 and 25% reduction in plant biomass and photosynthesis rate, respectively. Nitrogen use efficiency (NUE) decreased with increasing N supply, while osmotic potential, water use efficiency, photosynthetic pigments, and total N and N-NO₃ concentrations in plant tissues increased with N supply. The plant ionome was considerably affected by N supply. Concentrations of K, P, Ca, Mg, and Fe in the plant were highest under the optimal N level of 160 mgL^-1 N, with differences between organs in the extent of nutrient accumulation. The majority of the nutrients tested, including P, Zn, Mn, Fe, and Cu, tended to accumulate in the roots > leaves > stem, while K and Na tended to accumulate in the stem > leaves > roots, and total N, Ca, and Mg accumulated in leaves > roots > stem. Taken together, the results demonstrate that the optimal N level for plant development and function at the vegetative growth phase is 160 mgL^-1 N. Growth retardation under lower N supply (30-80 mgL^-1) results from restricted availability of photosynthetic pigments, carbon fixation, and impaired water relations. Excess uptake of N under supply higher than 160 mgL^-1 N, promoted physiological and developmental restrictions, by ion-specific toxicity or indirect induced restrictions of carbon fixation and energy availability.

The legacy of biogeographic history on the composition and structure of Andean forests

The biogeographic origin of species may help to explain differences in average tree height and aboveground biomass (AGB) of tropical mountain forests. After the Andean uplift, small-statured trees should have been among the initial colonizers of the highlands (new cold environment) from the lowland tropics, since these species are pre-adapted to cold conditions with narrow vessels that are relatively resistant to freezing. If the descendants of these small-statured clades continue to dominate tropical highland forests, there will be a high co-occurrence of close relatives at high elevations. In other words, this scenario predicts a systematic decline in tree size, AGB, and phylogenetic diversity with elevation. In contrast, the colonization of Andean forests by some large-statured clades that originated in temperate regions may modify this expectation and promote a mixing of tropical and temperate clades, thereby increasing the phylogenetic diversity in tropical highland forests. This latter scenario predicts an increase or no change of tree size, AGB, and phylogenetic diversity with elevation. We assessed how the historical immigration of large-statured temperate-affiliated tree lineages adapted to cold conditions may have influenced the composition and structure of Andean forests. Specifically, we used 92 0.25-ha forest inventory plots distributed in the tropical Andes Mountains of Colombia to assess the relationship between the phylogenetic diversity and AGB along elevational gradients. We classified tree species as being either "tropical affiliated" or "temperate affiliated" and estimated their independent contribution to forest AGB. We used structural equation modeling to separate the direct and indirect effect of elevation on AGB. We found a hump-shaped relationship of phylogenetic diversity, AGB, and tree size with elevation. The high phylogenetic diversity found between 1,800-2,200 m above sea level (asl) was due to the mixing of highland floras containing many temperate-affiliated species, and lowland floras containing mostly tropical-affiliated species. The high AGB in highland forests, which contrasted with the expected decline of AGB with elevation, was likely due to the significant contribution of temperate-affiliated species. Our findings highlight the lasting importance of biogeographic history on the composition and structure of Andean mountain forests.

Plant respiration: Controlled by photosynthesis or biomass?

Two simplifying hypotheses have been proposed for whole-plant respiration. One links respiration to photosynthesis; the other to biomass. Using a first-principles carbon balance model with a prescribed live woody biomass turnover, applied at a forest research site where multidecadal measurements are available for comparison, we show that if turnover is fast the accumulation of respiring biomass is low and respiration depends primarily on photosynthesis; while if turnover is slow the accumulation of respiring biomass is high and respiration depends primarily on biomass. But the first scenario is inconsistent with evidence for substantial carry-over of fixed carbon between years, while the second implies far too great an increase in respiration during stand development-leading to depleted carbohydrate reserves and an unrealistically high mortality risk. These two mutually incompatible hypotheses are thus both incorrect. Respiration is not linearly related either to photosynthesis or to biomass, but it is more strongly controlled by recent photosynthates (and reserve availability) than by total biomass.

Carbon dynamics, net primary productivity and human-appropriated net primary productivity across a forest-cocoa farm landscape in West Africa

Terrestrial net primary productivity (NPP) is an important metric of ecosystem functioning; however, there are little empirical data on the NPP of human-modified ecosystems, particularly smallholder, perennial crops like cocoa (Theobroma cacao), which are extensive across the tropics. Human-appropriated NPP (HANPP) is a measure of the proportion of a natural system's NPP that has either been reduced through land-use change or harvested directly and, previously, has been calculated to estimate the scale of the human impact on the biosphere. Additionally, human modification can create shifts in NPP allocation and decomposition, with concomitant impacts on the carbon cycle. This study presents the results of 3 years of intensive monitoring of forest and smallholder cocoa farms across disturbance, management intensity, distance from forest and farm age gradients. We measured among the highest reported NPP values in tropical forest, 17.57 ± 2.1 and 17.7 ± 1.6 Mg C ha^-1  year^-1 for intact and logged forest, respectively; however, the average NPP of cocoa farms was still higher, 18.8 ± 2.5 Mg C ha^-1  year^-1 , which we found was driven by cocoa pod production. We found a dramatic shift in litterfall residence times, where cocoa leaves decomposed more slowly than forest leaves and shade tree litterfall decomposed considerably faster, indicating significant changes in rates of nutrient cycling. The average HANPP value for all cocoa farms was 2.1 ± 1.1 Mg C ha^-1  year^-1 ; however, depending on the density of shade trees, it ranged from -4.6 to 5.2 Mg C ha^-1  year^-1 . Therefore, rather than being related to cocoa yield, HANPP was reduced by maintaining higher shade levels. Across our monitored farms, 18.9% of farm NPP was harvested (i.e., whole cocoa pods) and only 1.1% (i.e., cocoa beans) was removed from the system, suggesting that the scale of HANPP in smallholder cocoa agroforestry systems is relatively small.

Is NPP proportional to GPP? Waring's hypothesis 20 years on

Gross primary production (GPP) is partitioned to autotrophic respiration (Ra) and net primary production (NPP), the latter being used to build plant tissues and synthesize non-structural and secondary compounds. Waring et al. (1998; Net primary production of forests: a constant fraction of gross primary production? Tree Physiol 18:129-134) suggested that a NPP:GPP ratio of 0.47 ± 0.04 (SD) is universal across biomes, tree species and stand ages. Representing NPP in models as a fixed fraction of GPP, they argued, would be both simpler and more accurate than trying to simulate Ra mechanistically. This paper reviews progress in understanding the NPP:GPP ratio in forests during the 20 years since the Waring et al. paper. Research has confirmed the existence of pervasive acclimation mechanisms that tend to stabilize the NPP:GPP ratio and indicates that Ra should not be modelled independently of GPP. Nonetheless, studies indicate that the value of this ratio is influenced by environmental factors, stand age and management. The average NPP:GPP ratio in over 200 studies, representing different biomes, species and forest stand ages, was found to be 0.46, consistent with the central value that Waring et al. proposed but with a much larger standard deviation (±0.12) and a total range (0.22-0.79) that is too large to be disregarded.

Eco-physiological performance may contribute to differential success of two forms of an invasive vine, Dolichandra unguis-cati, in Australia

Invasive plant species are hypothesized as being more efficient at resource acquisition and use, resulting in faster growth than co-occurring non-invasive plant species. Nonetheless, some findings suggest that trait differences between invasive and non-invasive species are context dependent. In this study, two forms of an invasive vine species,Dolichandraunguis-cati, were used to test the context-dependent hypothesis.Dolichandraunguis-catiis a weed of national significance in Australia with two different forms: the ‘long pod’ (LP) and ‘short pod’ (SP). The two forms have different levels of distribution on the eastern Seaboard of the continent, with the SP form occurring extensively in both States of Queensland and New South Wales while the LP form is found only in isolated sites in South-East Queensland. This study examines whether differences in eco-physiological performance could be responsible for differential success of the two forms. A partially factorial experiment was set up in controlled conditions where potted plants of both forms were grown under two levels of light, water and nutrient resources (high and low) for 15 months. We measured several traits that are known to correlate with plant performance and resource use efficiency (RUE). The SP form exhibited higher values of carbon assimilation, RUE, number of subterranean tubers and leaf nitrogen than the LP form. However, the LP form produced greater biomass than the SP form, with the difference driven mainly by high resource conditions. The LP form displayed significantly higher phenotypic integration (number of traits significantly correlated) than the SP form in response to all treatments while the SP form exhibited higher phenotypic integration than the LP form in response to high resource conditions only. The SP form displayed traits that are well suited for successful colonization, possibly explaining its increased success in Australia, while the LP form possessed traits of opportunistic plants. Overall, we find that the two forms of the weedy vine deploy different carbon economies in response to resource conditions, which is evidence of the context-dependent trait hypothesis.

Logging and soil nutrients independently explain plant trait expression in tropical forests

Plant functional traits regulate ecosystem functions but little is known about how co-occurring gradients of land use and edaphic conditions influence their expression. We test how gradients of logging disturbance and soil properties relate to community-weighted mean traits in logged and old-growth tropical forests in Borneo. We studied 32 physical, chemical and physiological traits from 284 tree species in eight 1 ha plots and measured long-term soil nutrient supplies and plant-available nutrients. Logged plots had greater values for traits that drive carbon capture and growth, whilst old-growth forests had greater values for structural and persistence traits. Although disturbance was the primary driver of trait expression, soil nutrients explained a statistically independent axis of variation linked to leaf size and nutrient concentration. Soil characteristics influenced trait expression via nutrient availability, nutrient pools, and pH. Our finding, that traits have dissimilar responses to land use and soil resource availability, provides robust evidence for the need to consider the abiotic context of logging when predicting plant functional diversity across human-modified tropical forests. The detection of two independent axes was facilitated by the measurement of many more functional traits than have been examined in previous studies.

Estimating Fine Root Production from Ingrowth Cores and Decomposed Roots in a Bornean Tropical Rainforest

Research highlights: Estimates of fine root production using ingrowth cores are strongly influenced by decomposed roots in the cores during the incubation period and should be accounted for when calculating fine root production (FRP). Background and Objectives: The ingrowth core method is often used to estimate fine root production; however, decomposed roots are often overlooked in estimates of FRP. Uncertainty remains on how long ingrowth cores should be installed and how FRP should be calculated in tropical forests. Here, we aimed to estimate FRP by taking decomposed fine roots into consideration. Specifically, we compared FRP estimates at different sampling intervals and using different calculation methods in a tropical rainforest in Borneo. Materials and Methods: Ingrowth cores were installed with root litter bags and collected after 3, 6, 12 and 24 months. FRP was estimated based on (1) the difference in biomass at different sampling times (differential method) and (2) sampled biomass at just one sampling time (simple method). Results: Using the differential method, FRP was estimated at 447.4 ± 67.4 g m−2 year−1 after 12 months, with decomposed fine roots accounting for 25% of FRP. Using the simple method, FRP was slightly higher than that in the differential method after 12 months (516.3 ± 45.0 g m−2 year−1). FRP estimates for both calculation methods using data obtained in the first half of the year were much higher than those using data after 12-months of installation, because of the rapid increase in fine root biomass and necromass after installation. Conclusions: Therefore, FRP estimates vary with the timing of sampling, calculation method and presence of decomposed roots. Overall, the ratio of net primary production (NPP) of fine roots to total NPP in this study was higher than that previously reported in the Neotropics, indicating high belowground carbon allocation in this forest.

ENSO Drives interannual variation of forest woody growth across the tropics

Meteorological extreme events such as El Niño events are expected to affect tropical forest net primary production (NPP) and woody growth, but there has been no large-scale empirical validation of this expectation. We collected a large high-temporal resolution dataset (for 1-13 years depending upon location) of more than 172 000 stem growth measurements using dendrometer bands from across 14 regions spanning Amazonia, Africa and Borneo in order to test how much month-to-month variation in stand-level woody growth of adult tree stems (NPP_stem) can be explained by seasonal variation and interannual meteorological anomalies. A key finding is that woody growth responds differently to meteorological variation between tropical forests with a dry season (where monthly rainfall is less than 100 mm), and aseasonal wet forests lacking a consistent dry season. In seasonal tropical forests, a high degree of variation in woody growth can be predicted from seasonal variation in temperature, vapour pressure deficit, in addition to anomalies of soil water deficit and shortwave radiation. The variation of aseasonal wet forest woody growth is best predicted by the anomalies of vapour pressure deficit, water deficit and shortwave radiation. In total, we predict the total live woody production of the global tropical forest biome to be 2.16 Pg C yr^-1, with an interannual range 1.96-2.26 Pg C yr^-1 between 1996-2016, and with the sharpest declines during the strong El Niño events of 1997/8 and 2015/6. There is high geographical variation in hotspots of El Niño-associated impacts, with weak impacts in Africa, and strongly negative impacts in parts of Southeast Asia and extensive regions across central and eastern Amazonia. Overall, there is high correlation (r = -0.75) between the annual anomaly of tropical forest woody growth and the annual mean of the El Niño 3.4 index, driven mainly by strong correlations with anomalies of soil water deficit, vapour pressure deficit and shortwave radiation.This article is part of the discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

The role of satellite observations in understanding the impact of El Niño on the carbon cycle: current capabilities and future opportunities

The 2015/2016 El Niño was the first major climate variation when there were a range of satellite observations that simultaneously observed land, ocean and atmospheric properties associated with the carbon cycle. These data are beginning to provide new insights into the varied responses of land ecosystems to El Niño, but we are far from fully exploiting the information embodied by these data. Here, we briefly review the atmospheric and terrestrial satellite data that are available to study the carbon cycle. We also outline recommendations for future research, particularly the closer integration of satellite data with forest biometric datasets that provide detailed information about carbon dynamics on a range of timescales.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Mapping the Leaf Economic Spectrum across West African Tropical Forests Using UAV-Acquired Hyperspectral Imagery

The leaf economic spectrum (LES) describes a set of universal trade-offs between leaf mass per area (LMA), leaf nitrogen (N), leaf phosphorus (P) and leaf photosynthesis that influence patterns of primary productivity and nutrient cycling. Many questions regarding vegetation-climate feedbacks can be addressed with a better understanding of LES traits and their controls. Remote sensing offers enormous potential for generating large-scale LES trait data. Yet so far, canopy studies have been limited to imaging spectrometers onboard aircraft, which are rare, expensive to deploy and lack fine-scale resolution. In this study, we measured VNIR (visible-near infrared (400–1050 nm)) reflectance of individual sun and shade leaves in 7 one-ha tropical forest plots located along a 1200–2000 mm precipitation gradient in West Africa. We collected hyperspectral imaging data from 3 of the 7 plots, using an octocopter-based unmanned aerial vehicle (UAV), mounted with a hyperspectral mapping system (450–950 nm, 9 nm FWHM). Using partial least squares regression (PLSR), we found that the spectra of individual sun leaves demonstrated significant (p < 0.01) correlations with LMA and leaf chemical traits: r2 = 0.42 (LMA), r2 = 0.43 (N), r2 = 0.21 (P), r2 = 0.20 (leaf potassium (K)), r2 = 0.23 (leaf calcium (Ca)) and r2 = 0.14 (leaf magnesium (Mg)). Shade leaf spectra displayed stronger relationships with all leaf traits. At the airborne level, four of the six leaf traits demonstrated weak (p < 0.10) correlations with the UAV-collected spectra of 58 tree crowns: r2 = 0.25 (LMA), r2 = 0.22 (N), r2 = 0.22 (P), and r2 = 0.25 (Ca). From the airborne imaging data, we used LMA, N and P values to map the LES across the three plots, revealing precipitation and substrate as co-dominant drivers of trait distributions and relationships. Positive N-P correlations and LMA-P anticorrelations followed typical LES theory, but we found no classic trade-offs between LMA and N. Overall, this study demonstrates the application of UAVs to generating LES information and advancing the study and monitoring tropical forest functional diversity.

Impacts of fire on sources of soil CO2 efflux in a dry Amazon rain forest

Fire at the dry southern margin of the Amazon rainforest could have major consequences for regional soil carbon (C) storage and ecosystem carbon dioxide (CO₂ ) emissions, but relatively little information exists about impacts of fire on soil C cycling within this sensitive ecotone. We measured CO₂ effluxes from different soil components (ground surface litter, roots, mycorrhizae, soil organic matter) at a large-scale burn experiment designed to simulate a severe but realistic potential future scenario for the region (Fire plot) in Mato Grosso, Brazil, over 1 year, and compared these measurements to replicated data from a nearby, unmodified Control plot. After four burns over 5 years, soil CO₂ efflux (R_s ) was ~5.5 t C ha^-1  year^-1 lower on the Fire plot compared to the Control. Most of the Fire plot R_s reduction was specifically due to lower ground surface litter and root respiration. Mycorrhizal respiration on both plots was around ~20% of R_s . Soil surface temperature appeared to be more important than moisture as a driver of seasonal patterns in R_s at the site. Regular fire events decreased the seasonality of R_s at the study site, due to apparent differences in environmental sensitivities among biotic and abiotic soil components. These findings may contribute toward improved predictions of the amount and temporal pattern of C emissions across the large areas of tropical forest facing increasing fire disturbances associated with climate change and human activities.

Logging disturbance shifts net primary productivity and its allocation in Bornean tropical forests

Tropical forests play a major role in the carbon cycle of the terrestrial biosphere. Recent field studies have provided detailed descriptions of the carbon cycle of mature tropical forests, but logged or secondary forests have received much less attention. Here, we report the first measures of total net primary productivity (NPP) and its allocation along a disturbance gradient from old-growth forests to moderately and heavily logged forests in Malaysian Borneo. We measured the main NPP components (woody, fine root and canopy NPP) in old-growth (n = 6) and logged (n = 5) 1 ha forest plots. Overall, the total NPP did not differ between old-growth and logged forest (13.5 ± 0.5 and 15.7 ± 1.5 Mg C ha^-1  year^-1 respectively). However, logged forests allocated significantly higher fraction into woody NPP at the expense of the canopy NPP (42% and 48% into woody and canopy NPP, respectively, in old-growth forest vs 66% and 23% in logged forest). When controlling for local stand structure, NPP in logged forest stands was 41% higher, and woody NPP was 150% higher than in old-growth stands with similar basal area, but this was offset by structure effects (higher gap frequency and absence of large trees in logged forest). This pattern was not driven by species turnover: the average woody NPP of all species groups within logged forest (pioneers, nonpioneers, species unique to logged plots and species shared with old-growth plots) was similar. Hence, below a threshold of very heavy disturbance, logged forests can exhibit higher NPP and higher allocation to wood; such shifts in carbon cycling persist for decades after the logging event. Given that the majority of tropical forest biome has experienced some degree of logging, our results demonstrate that logging can cause substantial shifts in carbon production and allocation in tropical forests.

New perspectives on the ecology of tree structure and tree communities through terrestrial laser scanning

Terrestrial laser scanning (TLS) opens up the possibility of describing the three-dimensional structures of trees in natural environments with unprecedented detail and accuracy. It is already being extensively applied to describe how ecosystem biomass and structure vary between sites, but can also facilitate major advances in developing and testing mechanistic theories of tree form and forest structure, thereby enabling us to understand why trees and forests have the biomass and three-dimensional structure they do. Here we focus on the ecological challenges and benefits of understanding tree form, and highlight some advances related to capturing and describing tree shape that are becoming possible with the advent of TLS. We present examples of ongoing work that applies, or could potentially apply, new TLS measurements to better understand the constraints on optimization of tree form. Theories of resource distribution networks, such as metabolic scaling theory, can be tested and further refined. TLS can also provide new approaches to the scaling of woody surface area and crown area, and thereby better quantify the metabolism of trees. Finally, we demonstrate how we can develop a more mechanistic understanding of the effects of avoidance of wind risk on tree form and maximum size. Over the next few years, TLS promises to deliver both major empirical and conceptual advances in the quantitative understanding of trees and tree-dominated ecosystems, leading to advances in understanding the ecology of why trees and ecosystems look and grow the way they do.

Forest biomass, productivity and carbon cycling along a rainfall gradient in West Africa

Net Primary Productivity (NPP) is one of the most important parameters in describing the functioning of any ecosystem and yet it arguably remains a poorly quantified and understood component of carbon cycling in tropical forests, especially outside of the Americas. We provide the first comprehensive analysis of NPP and its carbon allocation to woody, canopy and root growth components at contrasting lowland West African forests spanning a rainfall gradient. Using a standardized methodology to study evergreen (EF), semi-deciduous (SDF), dry forests (DF) and woody savanna (WS), we find that (i) climate is more closely related with above and belowground C stocks than with NPP (ii) total NPP is highest in the SDF site, then the EF followed by the DF and WS and that (iii) different forest types have distinct carbon allocation patterns whereby SDF allocate in excess of 50% to canopy production and the DF and WS sites allocate 40%-50% to woody production. Furthermore, we find that (iv) compared with canopy and root growth rates the woody growth rate of these forests is a poor proxy for their overall productivity and that (v) residence time is the primary driver in the productivity-allocation-turnover chain for the observed spatial differences in woody, leaf and root biomass across the rainfall gradient. Through a systematic assessment of forest productivity we demonstrate the importance of directly measuring the main components of above and belowground NPP and encourage the establishment of more permanent carbon intensive monitoring plots across the tropics.

Ecosystem responses to elevated CO2 governed by plant-soil interactions and the cost of nitrogen acquisition

Contents Summary 507 I. Introduction 507 II. The return on investment approach 508 III. CO₂ response spectrum 510 IV. Discussion 516 Acknowledgements 518 References 518 SUMMARY: Land ecosystems sequester on average about a quarter of anthropogenic CO₂ emissions. It has been proposed that nitrogen (N) availability will exert an increasingly limiting effect on plants' ability to store additional carbon (C) under rising CO₂ , but these mechanisms are not well understood. Here, we review findings from elevated CO₂ experiments using a plant economics framework, highlighting how ecosystem responses to elevated CO₂ may depend on the costs and benefits of plant interactions with mycorrhizal fungi and symbiotic N-fixing microbes. We found that N-acquisition efficiency is positively correlated with leaf-level photosynthetic capacity and plant growth, and negatively with soil C storage. Plants that associate with ectomycorrhizal fungi and N-fixers may acquire N at a lower cost than plants associated with arbuscular mycorrhizal fungi. However, the additional growth in ectomycorrhizal plants is partly offset by decreases in soil C pools via priming. Collectively, our results indicate that predictive models aimed at quantifying C cycle feedbacks to global change may be improved by treating N as a resource that can be acquired by plants in exchange for energy, with different costs depending on plant interactions with microbial symbionts.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Unexpectedly large impact of forest management and grazing on global vegetation biomass

Carbon stocks in vegetation play a key role in the climate system1–4, but their magnitude and patterns, their uncertainties, and the impact of land use on them remain poorly quantified. Based on a consistent integration of state-of-the art datasets, we show that vegetation currently stores ~450 PgC. In the hypothetical absence of land use, potential vegetation would store ~916 PgC, under current climate. This difference singles out the massive effect land use has on biomass stocks. Deforestation and other land-cover changes are responsible for 53-58% of the difference between current and potential biomass stocks. Land management effects, i.e. land-use induced biomass stock changes within the same land cover, contribute 42-47% but are underappreciated in the current literature. Avoiding deforestation hence is necessary but not sufficient for climate-change mitigation. Our results imply that trade-offs exist between conserving carbon stocks on managed land and raising the contribution of biomass to raw material and energy supply for climate change mitigation. Efforts to raise biomass stocks are currently only verifiable in temperate forests, where potentials are limited. In contrast, large uncertainties hamper verification in the tropical forest where the largest potentials are located, pointing to challenges for the upcoming stocktaking exercises under the Paris agreement.