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

Anticipating global terrestrial ecosystem state change using FLUXNET

Ecosystems can be characterized as complex systems that traverse a variety of functional and structural states in response to changing bioclimatic forcings. A central challenge of global change biology is the robust empirical description of these states and state transitions. An ecosystem's functional state can be empirically described using Process Networks (PN) that use timeseries observations to determine the strength of process-level functional couplings between ecosystem components. A globally extensive source of in-situ observations of terrestrial ecosystem dynamics is the FLUXNET eddy-covariance network that provides standardized observations of micrometeorology and carbon, water, and energy flux dynamics. We employ the LaThuile FLUXNET synthesis dataset to delineate each month's functional state for 204 sites, yielding the LaThuile PN version 1.0 database that describes the strength of an ecosystem's functional couplings from air temperature and precipitation to carbon fluxes during each site-month. Then we calculate the elasticity of these couplings to seasonal scale forcings: air temperature, precipitation, solar radiation, and phenophase. Finally, we train artificial neural networks to extrapolate these elasticities from 204 sites to the globe, yielding maps of the estimated functional elasticity of every terrestrial ecosystem's functional states to changing seasonal bioclimatic forcings. These maps provide theoretically novel resource that can be used to anticipate ecological state transitions in response to climate change and to validate process-based models of ecological change. These elasticity maps show that each ecosystem can be expected to respond uniquely to changing forcings. Tropical forests, hot deserts, savannas, and high elevations are most elastic to climate change, and elasticity of ecosystems to seasonal air temperature is on average an order of magnitude higher than elasticity to other bioclimatic forcings. We also observed a reasonable amount of moderate relationships between functional elasticity and structural state change across different ecosystems.

Environmental variables better explain changes in potential nitrification and denitrification activities than microbial properties in fertilized forest soils

Because of increases in atmospheric nitrogen (N) deposition worldwide, nutrient imbalances and phosphorus (P) limitations in soil are aggravated, with the result that P fertilizer applications to terrestrial ecosystems worldwide may increase. Nitrification and denitrification in soil are major sources of nitrous oxide emissions, especially in soils treated with fertilizers. However, few researchers have studied how forest soils respond to nutrient additions, so we are not sure how the potential nitrification and denitrification activities (PNA and PDA, respectively) and microbial communities involved in these processes might respond when N and P are added to temperate and subtropical forest soils. We investigated how the PNA, PDA, the abundances and community compositions of nitrifiers and denitrifiers, and environmental properties, including soil pH, soil total and dissolved organic carbon, total and available N and phosphorus P, changed when N and/or P were added to subtropical and temperate forest soils. We quantified the abundance, and analyzed the composition, of functional marker genes of nitrifiers (ammonia-oxidizing bacteria and archaea amoA) and denitrifiers (nirK and nirS) using quantitative PCR and sequencing, respectively. We found that the PNA and PDA in the subtropical soil increased when P was added and PNA in the temperate forest soil increased when either N or P was added. The PNA and PDA were positively correlated with the abundance of ammonia-oxidizing bacteria and nirK-denitrifiers, respectively, in the subtropical forest soil but were not correlated with changes in corresponding community compositions in either of the forest soils. The soil total N to total P ratio explained most of the variabilities in the PNA and PDA in the subtropical forest soils, and the soil exchangeable ammonium concentrations and pH were the main controls on the PNA and PDA, respectively, in the temperate forest soils. Our results indicate that soil environmental conditions have more influence on variations in the PNA and PDA in forest soils fertilized with N and P than the corresponding microbial properties.

Compositional response of Amazon forests to climate change

Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

Crown damage and the mortality of tropical trees

What causes individual tree death in tropical forests remains a major gap in our understanding of the biology of tropical trees and leads to significant uncertainty in predicting global carbon cycle dynamics. We measured individual characteristics (diameter at breast height, wood density, growth rate, crown illumination and crown form) and environmental conditions (soil fertility and habitat suitability) for 26 425 trees ≥ 10 cm diameter at breast height belonging to 416 species in a 52-ha plot in Lambir Hills National Park, Malaysia. We used structural equation models to investigate the relationships among the different factors and tree mortality. Crown form (a proxy for mechanical damage and other stresses) and prior growth were the two most important factors related to mortality. The effect of all variables on mortality (except habitat suitability) was substantially greater than expected by chance. Tree death is the result of interactions between factors, including direct and indirect effects. Crown form/damage and prior growth mediated most of the effect of tree size, wood density, fertility and habitat suitability on mortality. Large-scale assessment of crown form or status may result in improved prediction of individual tree death at the landscape scale.

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.

Variation in hydroclimate sustains tropical forest biomass and promotes functional diversity

The fate of tropical forests under climate change is unclear as a result, in part, of the uncertainty in projected changes in precipitation and in the ability of vegetation models to capture the effects of drought-induced mortality on aboveground biomass (AGB). We evaluated the ability of a terrestrial biosphere model with demography and hydrodynamics (Ecosystem Demography, ED2-hydro) to simulate AGB and mortality of four tropical tree plant functional types (PFTs) that operate along light- and water-use axes. Model predictions were compared with observations of canopy trees at Barro Colorado Island (BCI), Panama. We then assessed the implications of eight hypothetical precipitation scenarios, including increased annual precipitation, reduced inter-annual variation, El Niño-related droughts and drier wet or dry seasons, on AGB and functional diversity of the model forest. When forced with observed meteorology, ED2-hydro predictions capture multiple BCI benchmarks. ED2-hydro predicts that AGB will be sustained under lower rainfall via shifts in the functional composition of the forest, except under the drier dry-season scenario. These results support the hypothesis that inter-annual variation in mean and seasonal precipitation promotes the coexistence of functionally diverse PFTs because of the relative differences in mortality rates. If the hydroclimate becomes chronically drier or wetter, functional evenness related to drought tolerance may decline.

El Niño drought increased canopy turnover in Amazon forests

Amazon droughts, including the 2015-2016 El Niño, may reduce forest net primary productivity and increase canopy tree mortality, thereby altering both the short- and the long-term net forest carbon balance. Given the broad extent of drought impacts, inventory plots or eddy flux towers may not capture regional variability in forest response to drought. We used multi-temporal airborne Lidar data and field measurements of coarse woody debris to estimate patterns of canopy turnover and associated carbon losses in intact and fragmented forests in the central Brazilian Amazon between 2013-2014 and 2014-2016. Average annualized canopy turnover rates increased by 65% during the drought period in both intact and fragmented forests. The average size and height of turnover events was similar for both time intervals, in contrast to expectations that the 2015-2016 El Niño drought would disproportionally affect large trees. Lidar-biomass relationships between canopy turnover and field measurements of coarse woody debris were modest (R²  ≈ 0.3), given similar coarse woody debris production and Lidar-derived changes in canopy volume from single tree and multiple branch fall events. Our findings suggest that El Niño conditions accelerated canopy turnover in central Amazon forests, increasing coarse woody debris production by 62% to 1.22 Mg C ha^-1  yr^-1 in drought years .

Vegetation demographics in Earth System Models: A review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.

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.

Biogeographic distributions of neotropical trees reflect their directly measured drought tolerances

High levels of species diversity hamper current understanding of how tropical forests may respond to environmental change. In the tropics, water availability is a leading driver of the diversity and distribution of tree species, suggesting that many tropical taxa may be physiologically incapable of tolerating dry conditions, and that their distributions along moisture gradients can be used to predict their drought tolerance. While this hypothesis has been explored at local and regional scales, large continental-scale tests are lacking. We investigate whether the relationship between drought-induced mortality and distributions holds continentally by relating experimental and observational data of drought-induced mortality across the Neotropics to the large-scale bioclimatic distributions of 115 tree genera. Across the different experiments, genera affiliated to wetter climatic regimes show higher drought-induced mortality than dry-affiliated ones, even after controlling for phylogenetic relationships. This pattern is stronger for adult trees than for saplings or seedlings, suggesting that the environmental filters exerted by drought impact adult tree survival most strongly. Overall, our analysis of experimental, observational, and bioclimatic data across neotropical forests suggests that increasing moisture-stress is indeed likely to drive significant changes in floristic composition.

Long-term forest resilience to climate change indicated by mortality, regeneration, and growth in semiarid southern Siberia

Several studies have documented that regional climate warming and the resulting increase in drought stress have triggered increased tree mortality in semiarid forests with unavoidable impacts on regional and global carbon sequestration. Although climate warming is projected to continue into the future, studies examining long-term resilience of semiarid forests against climate change are limited. In this study, long-term forest resilience was defined as the capacity of forest recruitment to compensate for losses from mortality. We observed an obvious change in long-term forest resilience along a local aridity gradient by reconstructing tree growth trend and disturbance history and investigating postdisturbance regeneration in semiarid forests in southern Siberia. In our study, with increased severity of local aridity, forests became vulnerable to drought stress, and regeneration first accelerated and then ceased. Radial growth of trees during 1900-2012 was also relatively stable on the moderately arid site. Furthermore, we found that smaller forest patches always have relatively weaker resilience under the same climatic conditions. Our results imply a relatively higher resilience in arid timberline forest patches than in continuous forests; however, further climate warming and increased drought could possibly cause the disappearance of small forest patches around the arid tree line. This study sheds light on climate change adaptation and provides insight into managing vulnerable semiarid forests.

Regionally strong feedbacks between the atmosphere and terrestrial biosphere

The terrestrial biosphere and atmosphere interact through a series of feedback loops. Variability in terrestrial vegetation growth and phenology can modulate fluxes of water and energy to the atmosphere, and thus affect the climatic conditions that in turn regulate vegetation dynamics. Here we analyze satellite observations of solar-induced fluorescence, precipitation, and radiation using a multivariate statistical technique. We find that biosphere-atmosphere feedbacks are globally widespread and regionally strong: they explain up to 30% of precipitation and surface radiation variance. Substantial biosphere-precipitation feedbacks are often found in regions that are transitional between energy and water limitation, such as semi-arid or monsoonal regions. Substantial biosphere-radiation feedbacks are often present in several moderately wet regions and in the Mediterranean, where precipitation and radiation increase vegetation growth. Enhancement of latent and sensible heat transfer from vegetation accompanies this growth, which increases boundary layer height and convection, affecting cloudiness, and consequently incident surface radiation. Enhanced evapotranspiration can increase moist convection, leading to increased precipitation. Earth system models underestimate these precipitation and radiation feedbacks mainly because they underestimate the biosphere response to radiation and water availability. We conclude that biosphere-atmosphere feedbacks cluster in specific climatic regions that help determine the net CO₂ balance of the biosphere.

Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks

Reduced rainfall increases the risk of forest dieback, while in return forest loss might intensify regional droughts. The consequences of this vegetation–atmosphere feedback for the stability of the Amazon forest are still unclear. Here we show that the risk of self-amplified Amazon forest loss increases nonlinearly with dry-season intensification. We apply a novel complex-network approach, in which Amazon forest patches are linked by observation-based atmospheric water fluxes. Our results suggest that the risk of self-amplified forest loss is reduced with increasing heterogeneity in the response of forest patches to reduced rainfall. Under dry-season Amazonian rainfall reductions, comparable to Last Glacial Maximum conditions, additional forest loss due to self-amplified effects occurs in 10–13% of the Amazon basin. Although our findings do not indicate that the projected rainfall changes for the end of the twenty-first century will lead to complete Amazon dieback, they suggest that frequent extreme drought events have the potential to destabilize large parts of the Amazon forest.

Relatively little is understood about seasonal effect of climate change on the Amazon rainforest. Here, the authors show that Amazon forest loss in response to dry-season intensification during the last glacial period was likely self-amplified by regional vegetation-rainfall feedbacks.

Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison

To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, 'soil water stress' and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (R_e ) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and R_e consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. Correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.

SAPFLUXNET: towards a global database of sap flow measurements

Plant transpiration is the main evaporative flux from terrestrial ecosystems; it controls land surface energy balance, determines catchment hydrological responses and influences regional and global climate. Transpiration regulation by plants is a key (and still not completely understood) process that underlies vegetation drought responses and land evaporative fluxes under global change scenarios. Thermometric methods of sap flow measurement have now been widely used to quantify whole-plant and stand transpiration in forests, shrublands and orchards around the world. A large body of research has applied sap flow methods to analyse seasonal and diurnal patterns of transpiration and to quantify their responses to hydroclimatic variability, but syntheses of sap flow data at regional to global scales are extremely rare. Here we present the SAPFLUXNET initiative, aimed at building the first global database of plant-level sap flow measurements. A preliminary metadata survey launched in December 2015 showed an encouraging response by the sap flow community, with sap flow data sets from field studies representing >160 species and >120 globally distributed sites. The main goal of SAPFLUXNET is to analyse the ecological factors driving plant- and stand-level transpiration. SAPFLUXNET will open promising research avenues at an unprecedented global scope, namely: (i) exploring the spatio-temporal variability of plant transpiration and its relationship with plant and stand attributes, (ii) summarizing physiological regulation of transpiration by means of few water-use traits, usable for land surface models, (iii) improving our understanding of the coordination between gas exchange and plant-level traits (e.g., hydraulics) and (iv) analysing the ecological factors controlling stand transpiration and evapotranspiration partitioning. Finally, SAPFLUXNET can provide a benchmark to test models of physiological controls of transpiration, contributing to improve the accuracy of individual water stress responses, a key element to obtain robust predictions of vegetation responses to climate change.