Search

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia-along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%-30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%-15% of incoming solar radiation, compared to 0.15%-0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (Rn ), the key driver of water and energy fluxes (LE ~ 0.6 Rn and H ~ 0.15 Rn ), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation-atmosphere exchange and reduce uncertainty of regional and global biogeochem

© 2016 John Wiley & Sons Ltd 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 (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re 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 cur

Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model – CLM3.5–DGVM; Ecosystem Demography model version 2 – ED2; the Joint UK Land Environment Simulator version 2.1 – JULES; Simple Biosphere model version 3 – SiB3; and the soil–plant–atmosphere model – SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model–data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest t

Evapotranspiration (E) in the Amazon connects forest function and regional climate via its role in precipitation recycling However, the mechanisms regulating water supply to vegetation and its demand for water remain poorly understood, especially during periods of seasonal water deficits In this study, we address two main questions: First, how do mechanisms of water supply (indicated by rooting depth and groundwater) and vegetation water demand (indicated by stomatal conductance and intrinsic water use efficiency) control evapotranspiration (E) along broad gradients of climate and vegetation from equatorial Amazonia to Cerrado, and second, how do these inferred mechanisms of supply and demand compare to those employed by a suite of ecosystem models? We used a network of eddy covariance towers in Brazil coupled with ancillary measurements to address these questions With respect to the magnitude and seasonality of E, models have much improved in equatorial tropical forests by eliminating most dry season water limitation, diverge in performance in transitional forests where seasonal water deficits are greater, and mostly capture the observed seasonal depressions in E at Cerrado However, many models depended universally on either deep roots or groundwater to mitigate dry season water deficits, the relative importance of which we found does not vary as a simple function of climate or vegetation In addition, canopy stomatal conductance (gs) regulates dry season vegetation demand for water at all except the wettest sites even as the seasonal cycle of E follows that of net radiation In contrast, some models simulated no seasonality in gs, even while matching the observed seasonal cycle of E. We suggest that canopy dynamics mediated by leaf phenology may play a significant role in such seasonality, a process poorly represented in models Model bias in gs and E, in turn, was related to biases arising from the simulated light response (gross primary productivity, GPP) or the in

This study analyzes the inter-annual variability (IAV) of simulations of 21 different land surface model formulations, driven by meteorological conditions measured at 8 flux towers, located in rain forest, forest-savanna ecotone and pasture sites in Amazonia, and one in savanna site in Southeastern Brazil. Annual totals of net ecosystem exchange (NEE) of carbon and evapotranspiration (ET), measured and simulated by each model for each site-year, were compared in terms of year-to-year variability and possible relation to climate drivers. Results have shown that most of models simulations for annual totals of NEE and ET, and IAV of these fluxes, are frequently different from measurements. The average of the model simulations of annual fluxes tend to respond to climatic drivers similarly to the observations, but with noticeable discrepancies. Annual measurements of NEE are negatively correlated to annual rainfall in the forest sites group. Although the ensemble of all models yields a similar result, only three model formulations reproduce a significant negative correlation of simulated NEE with rainfall. For the IAV of ET, tower measurements are controlled by annual variations of radiation and this feature is captured by the ensemble of the models, both at individual sites and when all forest sites are grouped. However, simulated ET values are also significantly correlated to the amount of precipitation in many models and in the model ensemble, while there is no significant correlation in the observations. In general, the surface models are able to reproduce the responses of fluxes to climatic drivers, but improvements are still needed to better capture their inter-annual variability. © 2013 Elsevier B.V..