Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change

Long-term drought effects on the thermal sensitivity of Amazon forest trees

The continued functioning of tropical forests under climate change depends on their resilience to drought and heat. However, there is little understanding of how tropical forests will respond to combinations of these stresses, and no field studies to date have explicitly evaluated whether sustained drought alters sensitivity to temperature. We measured the temperature response of net photosynthesis, foliar respiration and the maximum quantum efficiency of photosystem II (F_v /F_m ) of eight hyper-dominant Amazonian tree species at the world's longest-running tropical forest drought experiment, to investigate the effect of drought on forest thermal sensitivity. Despite a 0.6°C-2°C increase in canopy air temperatures following long-term drought, no change in overall thermal sensitivity of net photosynthesis or respiration was observed. However, photosystem II tolerance to extreme-heat damage (T₅₀ ) was reduced from 50.0 ± 0.3°C to 48.5 ± 0.3°C under drought. Our results suggest that long-term reductions in precipitation, as projected across much of Amazonia by climate models, are unlikely to greatly alter the response of tropical forests to rising mean temperatures but may increase the risk of leaf thermal damage during heatwaves.

Nocturnal warming accelerates drought-induced seedling mortality of two evergreen tree species

Extreme drought is one of the key climatic drivers of tree mortality on a global scale. However, it remains unclear whether the drought-induced tree mortality will increase under nocturnal climate warming. Here we exposed seedlings of two wide-ranging subtropical tree species, Castanopsis sclerophylla and Schima superba, with contrasting stomatal regulation strategies to prolonged drought under ambient and elevated night-time temperature by 2 °C. We quantified the seedling survival time since drought treatment by measuring multiple leaf traits such as leaf gas exchange, predawn leaf water potential and water-use efficiency. The results showed that all seedlings in the ambient temperature died within 180 days and 167 days of drought for C. sclerophylla and S. superba, respectively. Night warming significantly shortened the survival time of C. sclerophylla, by 31 days, and S. superba by 28 days, under the drought treatment. A survival analysis further showed that seedlings under night warming suffered a 1.6 times greater mortality risk than those under ambient temperature. Further analyses revealed that night warming suppressed net leaf carbon gain in both species by increasing the nocturnal respiratory rate of S. superba across the first 120 days of drought and decreasing the photosynthetic rate of both species generally after 46 days of drought. These effects on net carbon gain were more pronounced in S. superba than C. sclerophylla. After 60 days of drought, night warming decreased the predawn leaf water potential and leaf water-use efficiency of C. sclerophylla but not S. superba. These contrasting responses are partially due to variations in stomatal control between the two species. These findings suggest that stomatal traits can regulate the response of leaf gas exchange and plant water-use to nocturnal warming during drought. This study indicates that nocturnal warming can accelerate tree mortality during drought. Night warming accelerates the mortality of two subtropical seedlings under drought.Night warming differently affects the drought response of leaf gas exchange and plant water-use between the two species due to species-specific stomatal morphological traits.Carbon metabolism changes and hydraulic damage play differential roles in driving night-warming impacts on the drought-induced mortality between the two species.

Response of Amazonian forests to mid-Holocene drought: A model-data comparison

There is a major concern for the fate of Amazonia over the coming century in the face of anthropogenic climate change. A key area of uncertainty is the scale of rainforest dieback to be expected under a future, drier climate. In this study, we use the middle Holocene (ca. 6000 years before present) as an approximate analogue for a drier future, given that palaeoclimate data show much of Amazonia was significantly drier than present at this time. Here, we use an ensemble of climate and vegetation models to explore the sensitivity of Amazonian biomes to mid-Holocene climate change. For this, we employ three dynamic vegetation models (JULES, IBIS, and SDGVM) forced by the bias-corrected mid-Holocene climate simulations from seven models that participated in the Palaeoclimate Modelling Intercomparison Project 3 (PMIP3). These model outputs are compared with a multi-proxy palaeoecological dataset to gain a better understanding of where in Amazonia we have most confidence in the mid-Holocene vegetation simulations. A robust feature of all simulations and palaeodata is that the central Amazonian rainforest biome is unaffected by mid-Holocene drought. Greater divergence in mid-Holocene simulations exists in ecotonal eastern and southern Amazonia. Vegetation models driven with climate models that simulate a drier mid-Holocene (100-150 mm per year decrease) better capture the observed (palaeodata) tropical forest dieback in these areas. Based on the relationship between simulated rainfall decrease and vegetation change, we find indications that in southern Amazonia the rate of tropical forest dieback was ~125,000 km² per 100 mm rainfall decrease in the mid-Holocene. This provides a baseline sensitivity of tropical forests to drought for this region (without human-driven changes to greenhouse gases, fire, and deforestation). We highlight the need for more palaeoecological and palaeoclimate data across lowland Amazonia to constrain model responses.

Hydraulically-vulnerable trees survive on deep-water access during droughts in a tropical forest

Deep-water access is arguably the most effective, but under-studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep-water access may delay plant dehydration. Here, we tested the role of deep-water access in enabling survival within a diverse tropical forest community in Panama using a novel data-model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990-2015) to vapor pressure deficit, water potentials in the whole-soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water-access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981-2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress-related mortality risk through deep-water access. The role of deep-water access in mitigating mortality of hydraulically-vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

Resistance of African tropical forests to an extreme climate anomaly

The responses of tropical forests to environmental change are critical uncertainties in predicting the future impacts of climate change. The positive phase of the 2015-2016 El Niño Southern Oscillation resulted in unprecedented heat and low precipitation in the tropics with substantial impacts on the global carbon cycle. The role of African tropical forests is uncertain as their responses to short-term drought and temperature anomalies have yet to be determined using on-the-ground measurements. African tropical forests may be particularly sensitive because they exist in relatively dry conditions compared with Amazonian or Asian forests, or they may be more resistant because of an abundance of drought-adapted species. Here, we report responses of structurally intact old-growth lowland tropical forests inventoried within the African Tropical Rainforest Observatory Network (AfriTRON). We use 100 long-term inventory plots from six countries each measured at least twice prior to and once following the 2015-2016 El Niño event. These plots experienced the highest temperatures and driest conditions on record. The record temperature did not significantly reduce carbon gains from tree growth or significantly increase carbon losses from tree mortality, but the record drought did significantly decrease net carbon uptake. Overall, the long-term biomass increase of these forests was reduced due to the El Niño event, but these plots remained a live biomass carbon sink (0.51 ± 0.40 Mg C ha-1 y-1) despite extreme environmental conditions. Our analyses, while limited to African tropical forests, suggest they may be more resistant to climatic extremes than Amazonian and Asian forests.

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.

Empirical evidence for resilience of tropical forest photosynthesis in a warmer world

Tropical forests may be vulnerable to climate change^1-3 if photosynthetic carbon uptake currently operates near a high temperature limit^4-6. Predicting tropical forest function requires understanding the relative contributions of two mechanisms of high-temperature photosynthetic declines: stomatal limitation (H1), an indirect response due to temperature-associated changes in atmospheric vapour pressure deficit (VPD)⁷, and biochemical restrictions (H2), a direct temperature response^8,9. Their relative control predicts different outcomes-H1 is expected to diminish with stomatal responses to future co-occurring elevated atmospheric [CO₂], whereas H2 portends declining photosynthesis with increasing temperatures. Distinguishing the two mechanisms at high temperatures is therefore critical, but difficult because VPD is highly correlated with temperature in natural settings. We used a forest mesocosm to quantify the sensitivity of tropical gross ecosystem productivity (GEP) to future temperature regimes while constraining VPD by controlling humidity. We then analytically decoupled temperature and VPD effects under current climate with flux-tower-derived GEP trends in situ from four tropical forest sites. Both approaches showed consistent, negative sensitivity of GEP to VPD but little direct response to temperature. Importantly, in the mesocosm at low VPD, GEP persisted up to 38 °C, a temperature exceeding projections for tropical forests in 2100 (ref. ¹⁰). If elevated [CO₂] mitigates VPD-induced stomatal limitation through enhanced water-use efficiency as hypothesized^9,11, tropical forest photosynthesis may have a margin of resilience to future warming.

Mechanisms underlying leaf photosynthetic acclimation to warming and elevated CO2 as inferred from least-cost optimality theory

The mechanisms responsible for photosynthetic acclimation are not well understood, effectively limiting predictability under future conditions. Least-cost optimality theory can be used to predict the acclimation of photosynthetic capacity based on the assumption that plants maximize carbon uptake while minimizing the associated costs. Here, we use this theory as a null model in combination with multiple datasets of C₃ plant photosynthetic traits to elucidate the mechanisms underlying photosynthetic acclimation to elevated temperature and carbon dioxide (CO₂ ). The model-data comparison showed that leaves decrease the ratio of the maximum rate of electron transport to the maximum rate of Rubisco carboxylation (J_max /V_cmax ) under higher temperatures. The comparison also indicated that resources used for Rubisco and electron transport are reduced under both elevated temperature and CO₂ . Finally, our analysis suggested that plants underinvest in electron transport relative to carboxylation under elevated CO₂ , limiting potential leaf-level photosynthesis under future CO₂ concentrations. Altogether, our results show that acclimation to temperature and CO₂ is primarily related to resource conservation at the leaf level. Under future, warmer, high CO₂ conditions, plants are therefore likely to use less nutrients for leaf-level photosynthesis, which may impact whole-plant to ecosystem functioning.

Amazonia trees have limited capacity to acclimate plant hydraulic properties in response to long-term drought

The fate of tropical forests under future climate change is dependent on the capacity of their trees to adjust to drier conditions. The capacity of trees to withstand drought is likely to be determined by traits associated with their hydraulic systems. However, data on whether tropical trees can adjust hydraulic traits when experiencing drought remain rare. We measured plant hydraulic traits (e.g. hydraulic conductivity and embolism resistance) and plant hydraulic system status (e.g. leaf water potential, native embolism and safety margin) on >150 trees from 12 genera (36 species) and spanning a stem size range from 14 to 68 cm diameter at breast height at the world's only long-running tropical forest drought experiment. Hydraulic traits showed no adjustment following 15 years of experimentally imposed moisture deficit. This failure to adjust resulted in these drought-stressed trees experiencing significantly lower leaf water potentials, and higher, but variable, levels of native embolism in the branches. This result suggests that hydraulic damage caused by elevated levels of embolism is likely to be one of the key drivers of drought-induced mortality following long-term soil moisture deficit. We demonstrate that some hydraulic traits changed with tree size, however, the direction and magnitude of the change was controlled by taxonomic identity. Our results suggest that Amazonian trees, both small and large, have limited capacity to acclimate their hydraulic systems to future droughts, potentially making them more at risk of drought-induced mortality.

Modeling of Aboveground Biomass with Landsat 8 OLI and Machine Learning in Temperate Forests

An accurate estimation of forests’ aboveground biomass (AGB) is required because of its relevance to the carbon cycle, and because of its economic and ecological importance. The selection of appropriate variables from satellite information and physical variables is important for precise AGB prediction mapping. Because of the complex relationships for AGB prediction, non-parametric machine-learning techniques represent potentially useful techniques for AGB estimation, but their use and comparison in forest remote-sensing applications is still relatively limited. The objective of the present study was to evaluate the performance of automatic learning techniques, support vector regression (SVR) and random forest (RF), to predict the observed AGB (from 318 permanent sampling plots) from the Landsat 8 Landsat 8 Operational Land Imager (OLI) sensor, spectral indexes, texture indexes and physical variables the Sierra Madre Occidental in Mexico. The result showed that the best SVR model explained 80% of the total variance (root mean square error (RMSE) = 8.20 Mg ha−1). The variables that best predicted AGB, in order of importance, were the bands that belong to the region of red and near and middle infrared, and the average temperature. The results show that the SVR technique has a good potential for the estimation of the AGB and that the selection of the model hyperparameters has important implications for optimizing the goodness of fit.

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.

Exploring the Sensitivity of Subtropical Stand Aboveground Productivity to Local and Regional Climate Signals in South China

Subtropical forest productivity is significantly affected by both natural disturbances (local and regional climate changes) and anthropogenic activities (harvesting and planting). Monthly measures of forest aboveground productivity from natural forests (primary and secondary forests) and plantations (mixed and single-species forests) were developed to explore the sensitivity of subtropical mountain productivity to the fluctuating characteristics of climate change in South China, spanning the 35-year period from 1981 to 2015. Statistical analysis showed that climate regulation differed across different forest types. The monthly average maximum temperature, precipitation, and streamflow were positively correlated with primary and mixed-forest aboveground net primary productivity (ANPP) and its components: Wood productivity (WP) and canopy productivity (CP). However, the monthly average maximum temperature, precipitation, and streamflow were negatively correlated with secondary and single-species forest ANPP and its components. The number of dry days and minimum temperature were positively associated with secondary and single-species forest productivity, but inversely associated with primary and mixed forest productivity. The multivariate ENSO (EI Niño-Southern Oscillation) index (MEI), computed based on sea level pressure, surface temperature, surface air temperature, and cloudiness over the tropical Pacific Ocean, was significantly correlated with local monthly maximum and minimum temperatures (Tmax and Tmin), precipitation (PRE), streamflow (FLO), and the number of dry days (DD), as well as the monthly means of primary and mixed forest aboveground productivity. In particular, the mean maximum temperature increased by 2.5, 0.9, 6.5, and 0.9 °C, and the total forest aboveground productivity decreased by an average of 5.7%, 3.0%, 2.4%, and 7.8% in response to the increased extreme high temperatures and drought events during the 1986/1988, 1997/1998, 2006/2007, and 2009/2010 EI Niño periods, respectively. Subsequently, the total aboveground productivity values increased by an average of 1.1%, 3.0%, 0.3%, and 8.6% because of lagged effects after the wet La Niña periods. The main conclusions of this study demonstrated that the influence of local and regional climatic fluctuations on subtropical forest productivity significantly differed across different forests, and community position and plant diversity differences among different forest types may prevent the uniform response of subtropical mountain aboveground productivity to regional climate anomalies. Therefore, these findings may be useful for forecasting climate-induced variation in forest aboveground productivity as well as for selecting tree species for planting in reforestation practices.

Changes in Sensitivity of Tree-Ring Widths to Climate in a Tropical Moist Forest Tree in Bangladesh

Tree growth in the tropics is strongly influenced by climate. However, reported tree growth responses to climate are largely inconsistent, varying with geographic location, forest type, and tree species. It is thus important to study the growth responses of tropical trees in sites and species that are under-represented so far. Bangladesh, a country influenced by the Asian monsoon climate, is understudied in terms of tree growth response to climate. In the present study, we developed a 121-year-long regional ring-width index chronology of Chukrasia tabularis A. Juss. sampled in two moist forest sites in Bangladesh to investigate tree growth responses to climate in monsoon South Asia. Standard dendrochronological methods were used to produce the ring-width chronologies. The climate sensitivity of C. tabularis was assessed through bootstrap correlation analysis and the stationarity and consistency of climate–growth relationships was evaluated using moving correlation functions and comparing the regression slopes of two sub-periods (1950–1985 and 1986–2015). Tree growth was negatively correlated with the mean, minimum, and maximum temperatures, particularly during the early growing season (March). Likewise, precipitation negatively influenced tree growth in the later growing season (October). Besides, radial growth of Chukrasia sharply ceased in years following strong and moderate El Niño events. In parallel with a significant positive trend in local temperatures, tree growth sensitivity to early growing season (March–April) mean temperatures and July minimum temperatures increased in recent decades. Tree growth sensitivity to October precipitation and April vapor pressure deficit also increased. Overall, climate–growth relationships were stronger during the period 1986–2015 than during 1950–1985. Changes in climate sensitivity might be linked to a warming trend that induced an increase in the dry season length during recent decades. With a further predicted temperature increase at our study sites, our results suggest that radial growth of C. tabularis will further decline in response to climate warming.

Evaluating biological plausibility in supporting evidence for action through systematic reviews in public health

OBJECTIVES

The objective of this research was to develop and test methods for accessing and evaluating information on the biological plausibility of observed associations between exposures or interventions and outcomes to generate scientific evidence for action consistent with practice in systematic reviews.

STUDY DESIGN

To undertake this research, we used the example of the observed associations between antimicrobial use in food animals and increased risks of human exposures to antimicrobial-resistant pathogens of zoonotic origin.

METHODS

We conducted a scoping search using terms related to biological plausibility or mechanism to identify key references. As recommended by these references, we also used expert consultation with researchers and a public health informationist. We used their recommendations, which included expert consultation, to identify mechanisms relevant to biological plausibility of the association we selected to test. We used the reviews conducted by the World Health Organization (WHO) Guidelines Development Group in support of reducing antimicrobial use in food animal production to populate our model for assessing biological plausibility.

RESULTS

We were able to develop a transparent model for biological plausibility based on the adverse outcome pathway used in toxicology and ecology. We were also able to populate this model using the WHO reviews.

CONCLUSIONS

This analysis of biological plausibility used transparent and validated methods to assess the evidence used in systematic reviews based on the observational studies accessed through searches of the scientific literature. Given the importance of this topic in systematic reviews and evidence-based decision-making, further research is needed to define and test the methodological approaches to access and properly evaluate information from the scientific literature.

Limiting the high impacts of Amazon forest dieback with no-regrets science and policy action

Large uncertainties still dominate the hypothesis of an abrupt large-scale shift of the Amazon forest caused by climate change [Amazonian forest dieback (AFD)] even though observational evidence shows the forest and regional climate changing. Here, we assess whether mitigation or adaptation action should be taken now, later, or not at all in light of such uncertainties. No action/later action would result in major social impacts that may influence migration to large Amazonian cities through a causal chain of climate change and forest degradation leading to lower river-water levels that affect transportation, food security, and health. Net-present value socioeconomic damage over a 30-year period after AFD is estimated between US dollar (USD) $957 billion (×10⁹) and $3,589 billion (compared with Gross Brazilian Amazon Product of USD $150 billion per year), arising primarily from changes in the provision of ecosystem services. Costs of acting now would be one to two orders of magnitude lower than economic damages. However, while AFD mitigation alternatives-e.g., curbing deforestation-are attainable (USD $64 billion), their efficacy in achieving a forest resilience that prevents AFD is uncertain. Concurrently, a proposed set of 20 adaptation measures is also attainable (USD $122 billion) and could bring benefits even if AFD never occurs. An interdisciplinary research agenda to fill lingering knowledge gaps and constrain the risk of AFD should focus on developing sound experimental and modeling evidence regarding its likelihood, integrated with socioeconomic assessments to anticipate its impacts and evaluate the feasibility and efficacy of mitigation/adaptation options.

Short-term effects of drought on tropical forest do not fully predict impacts of repeated or long-term drought: gas exchange versus growth

Are short-term responses by tropical rainforest to drought (e.g. during El Niño) sufficient to predict changes over the long-term, or from repeated drought? Using the world's only long-term (16-year) drought experiment in tropical forest we examine predictability from short-term measurements (1-2 years). Transpiration was maximized in droughted forest: it consumed all available throughfall throughout the 16 years of study. Leaf photosynthetic capacity [Formula: see text] was maintained, but only when averaged across tree size groups. Annual transpiration in droughted forest was less than in control, with initial reductions (at high biomass) imposed by foliar stomatal control. Tree mortality increased after year three, leading to an overall biomass loss of 40%; over the long-term, the main constraint on transpiration was thus imposed by the associated reduction in sapwood area. Altered tree mortality risk may prove predictable from soil and plant hydraulics, but additional monitoring is needed to test whether future biomass will stabilize or collapse. Allocation of assimilate differed over time: stem growth and reproductive output declined in the short-term, but following mortality-related changes in resource availability, both showed long-term resilience, with partial or full recovery. Understanding and simulation of these phenomena and related trade-offs in allocation will advance more effectively through greater use of optimization and probabilistic modelling approaches.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'.

Drivers and mechanisms of tree mortality in moist tropical forests

Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO₂ fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change.

Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km² ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100.

Differences in leaf thermoregulation and water use strategies between three co-occurring Atlantic forest tree species

Given anticipated climate changes, it is crucial to understand controls on leaf temperatures including variation between species in diverse ecosystems. In the first study of leaf energy balance in tropical montane forests, we observed current leaf temperature patterns on 3 tree species in the Atlantic forest, Brazil, over a 10-day period and assessed whether and why patterns may vary among species. We found large leaf-to-air temperature differences (maximum 18.3 °C) and high leaf temperatures (over 35 °C) despite much lower air temperatures (maximum 22 °C). Leaf-to-air temperature differences were influenced strongly by radiation, whereas leaf temperatures were also influenced by air temperature. Leaf energy balance modelling informed by our measurements showed that observed differences in leaf temperature between 2 species were due to variation in leaf width and stomatal conductance. The results suggest a trade-off between water use and leaf thermoregulation; Miconia cabussu has more conservative water use compared with Alchornea triplinervia due to lower transpiration under high vapour pressure deficit, with the consequence of higher leaf temperatures under thermal stress conditions. We highlight the importance of leaf functional traits for leaf thermoregulation and also note that the high radiation levels that occur in montane forests may exacerbate the threat from increasing air temperatures.

Exploring uncertainty of Amazon dieback in a perturbed parameter Earth system ensemble

The future of the Amazon rainforest is unknown due to uncertainties in projected climate change and the response of the forest to this change (forest resiliency). Here, we explore the effect of some uncertainties in climate and land surface processes on the future of the forest, using a perturbed physics ensemble of HadCM3C. This is the first time Amazon forest changes are presented using an ensemble exploring both land vegetation processes and physical climate feedbacks in a fully coupled modelling framework. Under three different emissions scenarios, we measure the change in the forest coverage by the end of the 21st century (the transient response) and make a novel adaptation to a previously used method known as "dry-season resilience" to predict the long-term committed response of the forest, should the state of the climate remain constant past 2100. Our analysis of this ensemble suggests that there will be a high chance of greater forest loss on longer timescales than is realized by 2100, especially for mid-range and low emissions scenarios. In both the transient and predicted committed responses, there is an increasing uncertainty in the outcome of the forest as the strength of the emissions scenarios increases. It is important to note however, that very few of the simulations produce future forest loss of the magnitude previously shown under the standard model configuration. We find that low optimum temperatures for photosynthesis and a high minimum leaf area index needed for the forest to compete for space appear to be precursors for dieback. We then decompose the uncertainty into that associated with future climate change and that associated with forest resiliency, finding that it is important to reduce the uncertainty in both of these if we are to better determine the Amazon's outcome.

Intensification of terrestrial carbon cycle related to El Niño-Southern Oscillation under greenhouse warming

The El Niño/Southern Oscillation (ENSO) drives interannual variation in the global carbon cycle. However, the relationship between ENSO and the carbon cycle can be modulated by climate change due to anthropogenic forcing. We show herein that the sensitivity of the terrestrial carbon flux to ENSO will be enhanced under greenhouse warming by 44% ( ± 15%), indicating a future amplification of carbon–climate interactions. Separating the contributions of the changes in carbon sensitivity reveals that the response of land surface temperature to ENSO and the sensitivity of gross primary production to local temperature are significantly enhanced under greenhouse warming, thereby amplifying the ENSO–carbon-cycle coupling. In a warm climate, depletion of soil moisture increases temperature response in a given ENSO event. These findings suggest that the ENSO-related carbon cycle will be enhanced by hydroclimate changes caused by anthropogenic forcing.

The terrestrial carbon cycle is strongly influenced by El Niño/Southern Oscillation (ENSO), but how this relationship will change in future is not clear. Here the authors use state-of-the-art models to show that the sensitivity of the carbon cycle to ENSO will increase under future climate change.

Differences in xylem and leaf hydraulic traits explain differences in drought tolerance among mature Amazon rainforest trees

Considerable uncertainty surrounds the impacts of anthropogenic climate change on the composition and structure of Amazon forests. Building upon results from two large-scale ecosystem drought experiments in the eastern Brazilian Amazon that observed increases in mortality rates among some tree species but not others, in this study we investigate the physiological traits underpinning these differential demographic responses. Xylem pressure at 50% conductivity (xylem-P₅₀ ), leaf turgor loss point (TLP), cellular osmotic potential (π_o ), and cellular bulk modulus of elasticity (ε), all traits mechanistically linked to drought tolerance, were measured on upper canopy branches and leaves of mature trees from selected species growing at the two drought experiment sites. Each species was placed a priori into one of four plant functional type (PFT) categories: drought-tolerant versus drought-intolerant based on observed mortality rates, and subdivided into early- versus late-successional based on wood density. We tested the hypotheses that the measured traits would be significantly different between the four PFTs and that they would be spatially conserved across the two experimental sites. Xylem-P₅₀ , TLP, and π_o , but not ε, occurred at significantly higher water potentials for the drought-intolerant PFT compared to the drought-tolerant PFT; however, there were no significant differences between the early- and late-successional PFTs. These results suggest that these three traits are important for determining drought tolerance, and are largely independent of wood density-a trait commonly associated with successional status. Differences in these physiological traits that occurred between the drought-tolerant and drought-intolerant PFTs were conserved between the two research sites, even though they had different soil types and dry-season lengths. This more detailed understanding of how xylem and leaf hydraulic traits vary between co-occuring drought-tolerant and drought-intolerant tropical tree species promises to facilitate a much-needed improvement in the representation of plant hydraulics within terrestrial ecosystem and biosphere models, which will enhance our ability to make robust predictions of how future changes in climate will affect tropical forests.

Reconciling seasonal hydraulic risk and plant water use through probabilistic soil-plant dynamics

Current models used for predicting vegetation responses to climate change are often guided by the dichotomous needs to resolve either (i) internal plant water status as a proxy for physiological vulnerability or (ii) external water and carbon fluxes and atmospheric feedbacks. Yet, accurate representation of fluxes does not always equate to accurate predictions of vulnerability. We resolve this discrepancy using a hydrodynamic framework that simultaneously tracks plant water status and water uptake. We couple a minimalist plant hydraulics model with a soil moisture model and, for the first time, translate rainfall variability at multiple timescales - with explicit descriptions at daily, seasonal, and interannual timescales - into a physiologically meaningful metric for the risk of hydraulic failure. The model, parameterized with measured traits from chaparral species native to Southern California, shows that apparently similar transpiration patterns throughout the dry season can emerge from disparate plant water potential trajectories, and vice versa. The parsimonious set of parameters that captures the role of many traits across the soil-plant-atmosphere continuum is then used to establish differences in species sensitivities to shifts in seasonal rainfall statistics, showing that co-occurring species may diverge in their risk of hydraulic failure despite minimal changes to their seasonal water use. The results suggest potential shifts in species composition in this region due to species-specific changes in hydraulic risk. Our process-based approach offers a quantitative framework for understanding species sensitivity across multiple timescales of rainfall variability and provides a promising avenue toward incorporating interactions of temporal variability and physiological mechanisms into drought response models.

Hydrologic resilience and Amazon productivity

The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. The system couples the atmosphere and land, with moist forest that depends on convection to sustain gross primary productivity and growth. Earth system models that estimate future climate and vegetation show little agreement in Amazon simulations. Here we show that biases in internally generated climate, primarily precipitation, explain most of the uncertainty in Earth system model results; models, empirical data and theory converge when precipitation biases are accounted for. Gross primary productivity, above-ground biomass and tree cover align on a hydrological relationship with a breakpoint at ~2000 mm annual precipitation, where the system transitions between water and radiation limitation of evapotranspiration. The breakpoint appears to be fairly stable in the future, suggesting resilience of the Amazon to climate change. Changes in precipitation and land use are therefore more likely to govern biomass and vegetation structure in Amazonia.

Earth system model simulations of future climate in the Amazon show little agreement. Here, the authors show that biases in internally generated climate explain most of this uncertainty and that the balance between water-saturated and water-limited evapotranspiration controls the Amazon resilience to climate change.

In situ temperature response of photosynthesis of 42 tree and liana species in the canopy of two Panamanian lowland tropical forests with contrasting rainfall regimes

Tropical forests contribute significantly to the global carbon cycle, but little is known about the temperature response of photosynthetic carbon uptake in tropical species, and how this varies within and across forests. We determined in situ photosynthetic temperature-response curves for upper canopy leaves of 42 tree and liana species from two tropical forests in Panama with contrasting rainfall regimes. On the basis of seedling studies, we hypothesized that species with high photosynthetic capacity - light-demanding, fast-growing species - would have a higher temperature optimum of photosynthesis (T_Opt ) than species with low photosynthetic capacity - shade-tolerant, slow-growing species - and that, therefore, T_Opt would scale with the position of a species on the slow-fast continuum of plant functional traits. T_Opt was remarkably similar across species, regardless of their photosynthetic capacity and other plant functional traits. Community-average T_Opt was almost identical to mean maximum daytime temperature, which was higher in the dry forest. Photosynthesis above T_Opt appeared to be more strongly limited by stomatal conductance in the dry forest than in the wet forest. The observation that all species in a community shared similar T_Opt values suggests that photosynthetic performance is optimized under current temperature regimes. These results should facilitate the scaling up of photosynthesis in relation to temperature from leaf to stand level in species-rich tropical forests.

The variation of productivity and its allocation along a tropical elevation gradient: a whole carbon budget perspective

Why do forest productivity and biomass decline with elevation? To address this question, research to date generally has focused on correlative approaches describing changes in woody growth and biomass with elevation. We present a novel, mechanistic approach to this question by quantifying the autotrophic carbon budget in 16 forest plots along a 3300 m elevation transect in Peru. Low growth rates at high elevations appear primarily driven by low gross primary productivity (GPP), with little shift in either carbon use efficiency (CUE) or allocation of net primary productivity (NPP) between wood, fine roots and canopy. The lack of trend in CUE implies that the proportion of photosynthate allocated to autotrophic respiration is not sensitive to temperature. Rather than a gradual linear decline in productivity, there is some limited but nonconclusive evidence of a sharp transition in NPP between submontane and montane forests, which may be caused by cloud immersion effects within the cloud forest zone. Leaf-level photosynthetic parameters do not decline with elevation, implying that nutrient limitation does not restrict photosynthesis at high elevations. Our data demonstrate the potential of whole carbon budget perspectives to provide a deeper understanding of controls on ecosystem functioning and carbon cycling.

Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO ₂, and few studies have considered how and to what extent climate change and CO ₂ influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP-DGVM coupled with CLM3 and CLM4-CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO ₂ concentration. In the temperature sensitivity tests, warming reduced the global area-averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (ΔF_tree; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether ΔF_tree was positive or negative, while the tree fractional coverage (F_tree; %) played a decisive role in the amplitude of ΔF_tree around the globe, and the dependence was more remarkable in IAP-DGVM. In cases with precipitation change, F_tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% < F_tree < 60%) for IAP-DGVM and in semiarid and arid regions for CLM4-CNDV. Moreover, ΔF_tree had a stronger dependence on F_tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO ₂ concentration.

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

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 (DGVMs). 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 DGVMs. 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, DGVMs 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 DGVMs.

Record-breaking warming and extreme drought in the Amazon rainforest during the course of El Niño 2015-2016

The El Niño-Southern Oscillation (ENSO) is the main driver of interannual climate extremes in Amazonia and other tropical regions. The current 2015/2016 EN event was expected to be as strong as the EN of the century in 1997/98, with extreme heat and drought over most of Amazonian rainforests. Here we show that this protracted EN event, combined with the regional warming trend, was associated with unprecedented warming and a larger extent of extreme drought in Amazonia compared to the earlier strong EN events in 1982/83 and 1997/98. Typical EN-like drought conditions were observed only in eastern Amazonia, whilst in western Amazonia there was an unusual wetting. We attribute this wet-dry dipole to the location of the maximum sea surface warming on the Central equatorial Pacific. The impacts of this climate extreme on the rainforest ecosystems remain to be documented and are likely to be different to previous strong EN events.

Trait Acclimation Mitigates Mortality Risks of Tropical Canopy Trees under Global Warming

There is a heated debate about the effect of global change on tropical forests. Many scientists predict large-scale tree mortality while others point to mitigating roles of CO2 fertilization and - the notoriously unknown - physiological trait acclimation of trees. In this opinion article we provided a first quantification of the potential of trait acclimation to mitigate the negative effects of warming on tropical canopy tree growth and survival. We applied a physiological tree growth model that incorporates trait acclimation through an optimization approach. Our model estimated the maximum effect of acclimation when trees optimize traits that are strongly plastic on a week to annual time scale (leaf photosynthetic capacity, total leaf area, stem sapwood area) to maximize carbon gain. We simulated tree carbon gain for temperatures (25-35°C) and ambient CO2 concentrations (390-800 ppm) predicted for the 21st century. Full trait acclimation increased simulated carbon gain by up to 10-20% and the maximum tolerated temperature by up to 2°C, thus reducing risks of tree death under predicted warming. Functional trait acclimation may thus increase the resilience of tropical trees to warming, but cannot prevent tree death during extremely hot and dry years at current CO2 levels. We call for incorporating trait acclimation in field and experimental studies of plant functional traits, and in models that predict responses of tropical forests to climate change.

Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change

Amazon forests, which store ∼ 50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.

After more than a decade of soil moisture deficit, tropical rainforest trees maintain photosynthetic capacity, despite increased leaf respiration

Determining climate change feedbacks from tropical rainforests requires an understanding of how carbon gain through photosynthesis and loss through respiration will be altered. One of the key changes that tropical rainforests may experience under future climate change scenarios is reduced soil moisture availability. In this study we examine if and how both leaf photosynthesis and leaf dark respiration acclimate following more than 12 years of experimental soil moisture deficit, via a through-fall exclusion experiment (TFE) in an eastern Amazonian rainforest. We find that experimentally drought-stressed trees and taxa maintain the same maximum leaf photosynthetic capacity as trees in corresponding control forest, independent of their susceptibility to drought-induced mortality. We hypothesize that photosynthetic capacity is maintained across all treatments and taxa to take advantage of short-lived periods of high moisture availability, when stomatal conductance (gs ) and photosynthesis can increase rapidly, potentially compensating for reduced assimilate supply at other times. Average leaf dark respiration (Rd ) was elevated in the TFE-treated forest trees relative to the control by 28.2 ± 2.8% (mean ± one standard error). This mean Rd value was dominated by a 48.5 ± 3.6% increase in the Rd of drought-sensitive taxa, and likely reflects the need for additional metabolic support required for stress-related repair, and hydraulic or osmotic maintenance processes. Following soil moisture deficit that is maintained for several years, our data suggest that changes in respiration drive greater shifts in the canopy carbon balance, than changes in photosynthetic capacity.

Vegetation Greening and Climate Change Promote Multidecadal Rises of Global Land Evapotranspiration

Recent studies showed that anomalous dry conditions and limited moisture supply roughly between 1998 and 2008, especially in the Southern Hemisphere, led to reduced vegetation productivity and ceased growth in land evapotranspiration (ET). However, natural variability of Earth’s climate system can degrade capabilities for identifying climate trends. Here we produced a long-term (1982–2013) remote sensing based land ET record and investigated multidecadal changes in global ET and underlying causes. The ET record shows a significant upward global trend of 0.88 mm yr⁻² (P < 0.001) over the 32-year period, mainly driven by vegetation greening (0.018% per year; P < 0.001) and rising atmosphere moisture demand (0.75 mm yr⁻²; P = 0.016). Our results indicate that reduced ET growth between 1998 and 2008 was an episodic phenomenon, with subsequent recovery of the ET growth rate after 2008. Terrestrial precipitation also shows a positive trend of 0.66 mm yr⁻² (P = 0.08) over the same period consistent with expected water cycle intensification, but this trend is lower than coincident increases in evaporative demand and ET, implying a possibility of cumulative water supply constraint to ET. Continuation of these trends will likely exacerbate regional drought-induced disturbances, especially during regional dry climate phases associated with strong El Niño events.

Increasing human dominance of tropical forests

Tropical forests house over half of Earth's biodiversity and are an important influence on the climate system. These forests are experiencing escalating human influence, altering their health and the provision of important ecosystem functions and services. Impacts started with hunting and millennia-old megafaunal extinctions (phase I), continuing via low-intensity shifting cultivation (phase II), to today's global integration, dominated by intensive permanent agriculture, industrial logging, and attendant fires and fragmentation (phase III). Such ongoing pressures, together with an intensification of global environmental change, may severely degrade forests in the future (phase IV, global simplification) unless new "development without destruction" pathways are established alongside climate change-resilient landscape designs.

Threshold Responses to Soil Moisture Deficit by Trees and Soil in Tropical Rain Forests: Insights from Field Experiments

Many tropical rain forest regions are at risk of increased future drought. The net effects of drought on forest ecosystem functioning will be substantial if important ecological thresholds are passed. However, understanding and predicting these effects is challenging using observational studies alone. Field-based rainfall exclusion (canopy throughfall exclusion; TFE) experiments can offer mechanistic insight into the response to extended or severe drought and can be used to help improve model-based simulations, which are currently inadequate. Only eight TFE experiments have been reported for tropical rain forests. We examine them, synthesizing key results and focusing on two processes that have shown threshold behavior in response to drought: (1) tree mortality and (2) the efflux of carbon dioxdie from soil, soil respiration. We show that: (a) where tested using large-scale field experiments, tropical rain forest tree mortality is resistant to long-term soil moisture deficit up to a threshold of 50% of the water that is extractable by vegetation from the soil, but high mortality occurs beyond this value, with evidence from one site of increased autotrophic respiration, and (b) soil respiration reaches its peak value in response to soil moisture at significantly higher soil moisture content for clay-rich soils than for clay-poor soils. This first synthesis of tropical TFE experiments offers the hypothesis that low soil moisture–related thresholds for key stress responses in soil and vegetation may prove to be widely applicable across tropical rain forests despite the diversity of these forests.

Drought-related tree mortality: addressing the gaps in understanding and prediction

Increased tree mortality during and after drought has become a research focus in recent years. This focus has been driven by: the realisation that drought-related tree mortality is more widespread than previously thought; the predicted increase in the frequency of climate extremes this century; and the recognition that current vegetation models do not predict drought-related tree mortality and forest dieback well despite the large potential effects of these processes on species composition and biogeochemical cycling. To date, the emphasis has been on understanding the causal mechanisms of drought-related tree mortality, and on mechanistic models of plant function and vegetation dynamics, but a consensus on those mechanisms has yet to emerge. In order to generate new hypotheses and to help advance the modelling of vegetation dynamics in the face of incomplete mechanistic understanding, we suggest that general patterns should be distilled from the diverse and as-yet inconclusive results of existing studies, and more use should be made of optimisation and probabilistic modelling approaches that have been successfully applied elsewhere in plant ecology. The outcome should inform new empirical studies of tree mortality, help improve its prediction and reduce model complexity.

The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO₂ levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO₂ fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO₂ fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO₂ impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO₂ fertilization effects, fire, and land use - to the fate of the Amazon over the coming century.

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

Understanding the relationship between photosynthesis, net primary productivity and growth in forest ecosystems is key to understanding how these ecosystems will respond to global anthropogenic change, yet the linkages among these components are rarely explored in detail. We provide the first comprehensive description of the productivity, respiration and carbon allocation of contrasting lowland Amazonian forests spanning gradients in seasonal water deficit and soil fertility. Using the largest data set assembled to date, ten sites in three countries all studied with a standardized methodology, we find that (i) gross primary productivity (GPP) has a simple relationship with seasonal water deficit, but that (ii) site-to-site variations in GPP have little power in explaining site-to-site spatial variations in net primary productivity (NPP) or growth because of concomitant changes in carbon use efficiency (CUE), and conversely, the woody growth rate of a tropical forest is a very poor proxy for its productivity. Moreover, (iii) spatial patterns of biomass are much more driven by patterns of residence times (i.e. tree mortality rates) than by spatial variation in productivity or tree growth. Current theory and models of tropical forest carbon cycling under projected scenarios of global atmospheric change can benefit from advancing beyond a focus on GPP. By improving our understanding of poorly understood processes such as CUE, NPP allocation and biomass turnover times, we can provide more complete and mechanistic approaches to linking climate and tropical forest carbon cycling.

Urgent need for warming experiments in tropical forests

Although tropical forests account for only a fraction of the planet's terrestrial surface, they exchange more carbon dioxide with the atmosphere than any other biome on Earth, and thus play a disproportionate role in the global climate. In the next 20 years, the tropics will experience unprecedented warming, yet there is exceedingly high uncertainty about their potential responses to this imminent climatic change. Here, we prioritize research approaches given both funding and logistical constraints in order to resolve major uncertainties about how tropical forests function and also to improve predictive capacity of earth system models. We investigate overall model uncertainty of tropical latitudes and explore the scientific benefits and inevitable trade-offs inherent in large-scale manipulative field experiments. With a Coupled Model Intercomparison Project Phase 5 analysis, we found that model variability in projected net ecosystem production was nearly 3 times greater in the tropics than for any other latitude. Through a review of the most current literature, we concluded that manipulative warming experiments are vital to accurately predict future tropical forest carbon balance, and we further recommend the establishment of a network of comparable studies spanning gradients of precipitation, edaphic qualities, plant types, and/or land use change. We provide arguments for long-term, single-factor warming experiments that incorporate warming of the most biogeochemically active ecosystem components (i.e. leaves, roots, soil microbes). Hypothesis testing of underlying mechanisms should be a priority, along with improving model parameterization and constraints. No single tropical forest is representative of all tropical forests; therefore logistical feasibility should be the most important consideration for locating large-scale manipulative experiments. Above all, we advocate for multi-faceted research programs, and we offer arguments for what we consider the most powerful and urgent way forward in order to improve our understanding of tropical forest responses to climate change.

A database for the monitoring of thermal anomalies over the Amazon forest and adjacent intertropical oceans

Advances in information technologies and accessibility to climate and satellite data in recent years have favored the development of web-based tools with user-friendly interfaces in order to facilitate the dissemination of geo/biophysical products. These products are useful for the analysis of the impact of global warming over different biomes. In particular, the study of the Amazon forest responses to drought have recently received attention by the scientific community due to the occurrence of two extreme droughts and sustained warming over the last decade. Thermal Amazoni@ is a web-based platform for the visualization and download of surface thermal anomalies products over the Amazon forest and adjacent intertropical oceans using Google Earth as a baseline graphical interface (http://ipl.uv.es/thamazon/web). This platform is currently operational at the servers of the University of Valencia (Spain), and it includes both satellite (MODIS) and climatic (ERA-Interim) datasets. Thermal Amazoni@ is composed of the viewer system and the web and ftp sites with ancillary information and access to product download.

Observing terrestrial ecosystems and the carbon cycle from space

Terrestrial ecosystem and carbon cycle feedbacks will significantly impact future climate, but their responses are highly uncertain. Models and tipping point analyses suggest the tropics and arctic/boreal zone carbon-climate feedbacks could be disproportionately large. In situ observations in those regions are sparse, resulting in high uncertainties in carbon fluxes and fluxes. Key parameters controlling ecosystem carbon responses, such as plant traits, are also sparsely observed in the tropics, with the most diverse biome on the planet treated as a single type in models. We analyzed the spatial distribution of in situ data for carbon fluxes, stocks and plant traits globally and also evaluated the potential of remote sensing to observe these quantities. New satellite data products go beyond indices of greenness and can address spatial sampling gaps for specific ecosystem properties and parameters. Because environmental conditions and access limit in situ observations in tropical and arctic/boreal environments, use of space-based techniques can reduce sampling bias and uncertainty about tipping point feedbacks to climate. To reliably detect change and develop the understanding of ecosystems needed for prediction, significantly, more data are required in critical regions. This need can best be met with a strategic combination of remote and in situ data, with satellite observations providing the dense sampling in space and time required to characterize the heterogeneity of ecosystem structure and function.