A MODIS-based energy balance to estimate evapotranspiration for clear-sky days in Brazilian tropical savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r 2= 0.64 and r2 = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r 2 = 0.76 and r2 = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km2 (r2 = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Rn). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas

Evaluating the Potential of Commercial Forest Inventory Data to Report on Forest Carbon Stock and Forest Carbon Stock Changes for REDD+ under the UNFCCC

In the context of the adoption at the 16th Conference of the Parties in 2010 on the REDD+ mitigation mechanism, it is important to obtain reliable data on the spatiotemporal variation of forest carbon stocks and changes (called Emission Factor, EF). A re-occurring debate in estimating EF for REDD+ is the use of existing field measurement data. We provide an assessment of the use of commercial logging inventory data and ecological data to estimate a conservative EF (REDD+ phase 2) or to report on EF following IPCC Guidance and Guidelines (REDD+ phase 3). The data presented originate from five logging companies dispersed over Gabon, totalling 2,240 plots of 0.3 hectares.We distinguish three Forest Types (FTs) in the dataset based on floristic conditions. Estimated mean aboveground biomass (AGB) in the FTs ranges from 312 to 333 Mg ha-1. A 5% accuracy is reached with the number of plots put in place for the FTs and a low sampling uncertainty obtained (± 10 to 13 Mg ha-1). The data could be used to estimate a conservative EF in REDD+ phase 2 and only partially to report on EF following tier 2 requirements for a phase 3

Linking functional traits to multiscale statistics of leaf venation networks

Funding Information UK Natural Environment Research Council. Grant Number: NE/M019160/1 US National Science Foundation. Grant Number: DEB‐2025282 NERC Human‐modified Tropical Forest Programme. Grant Number: NE/M017508/1 Biodiversity And Land‐use Impacts on Tropical Ecosystem Function (BALI). Grant Numbers: NE/K016253/1, NE/K016253/1 Sime Darby Foundation Stability of Altered Forest Ecosystems (SAFE) Project Sabah Biodiversity Council Institute for Tropical Biology and Conservation (ITBC) at the University of Malaysia, Sabah (UMS) Sabah Forest Research Centre (FRC) at Sepilok Sabah Forestry Department SEARRP, Yayasan Sabah (Maliau Basin Conservation Area) Maliau Basin and Danum Valley Management Committees Acknowledgements Fieldwork was supported by Unding Jami, Matheus Henrique Nuñes, Rudi Saul Cruz Chino, Milenka Ximena Montoya, and South East Asia Rainforest Research Program (SEARRP) staff. Research was facilitated by Rob Ewers, Laura Kruitbos, Reuben Nilus, Glen Reynolds, and Charles Vairappan. Species identifications were made by Bernadus Bala Ola, Bill McDonald, Alexander Karolus, and MinSheng Khoo. This work also was supported by the UK Natural Environment Research Council (NERC; no. NE/M019160/1, to BB) and the US National Science Foundation (no. DEB‐2025282, to BB). This publication is a contribution from the NERC Human‐modified Tropical Forest Programme (no. NE/M017508/1, to YAT) and Biodiversity And Land‐use Impacts on Tropical Ecosystem Function (BALI) consortium (no. NE/K016253/1, to YM and no. NE/K016253/1, to YAT). The SAFE Project was funded by the Sime Darby Foundation and the UK NERC. The study areas are part of the Global Ecosystems Monitoring Network (GEM) via an ERC Advanced Investigator Award to YM (no. 321131). The project also was supported by the Stability of Altered Forest Ecosystems (SAFE) Project, the Sabah Biodiversity Council (SaBC, permits JKM/MBS.1000‐2/2 JLD.3‐126 and ‐154), the Institute for Tropical Biology and Conservation (ITBC) at the University of Malaysia, Sabah (UMS), the Sabah Forest Research Centre (FRC) at Sepilok, the Sabah Forestry Department, the SEARRP, Yayasan Sabah (Maliau Basin Conservation Area), and the Maliau Basin and Danum Valley Management Committees. Sean Gleason and several anonymous reviewers provided constructive feedback on the manuscript.Peer reviewedPublisher PD

Phenology and Seasonal Ecosystem Productivity in an Amazonian Floodplain Forest

everal studies have explored the linkages between phenology and ecosystem productivity across the Amazon basin. However, few studies have focused on flooded forests, which correspond to c.a. 14% of the basin. In this study, we assessed the seasonality of ecosystem productivity (gross primary productivity, GPP) from eddy covariance measurements, environmental drivers and phenological patterns obtained from the field (leaf litter mass) and satellite measurements (enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer/multi-angle implementation correction (MODIS/MAIAC)) in an Amazonian floodplain forest. We found that ecosystem productivity is limited by soil moisture in two different ways. During the flooded period, the excess of water limits GPP (Spearman’s correlation; rho = −0.22), while during non-flooded months, GPP is positively associated with soil moisture (rho = 0.34). However, GPP is maximized when cumulative water deficit (CWD) increases (rho = 0.81), indicating that GPP is dependent on the amount of water available. EVI was positively associated with leaf litter mass (Pearson’s correlation; r = 0.55) and with GPP (r = 0.50), suggesting a coupling between new leaf production and the phenology of photosynthetic capacity, decreasing both at the peak of the flooded period and at the end of the dry season. EVI was able to describe the inter-annual variations on forest responses to environmental drivers, which have changed during an observed El Niño-Southern Oscillation (ENSO) year (2015/2016)

Grass Species Flammability, Not Biomass, Drives Changes in Fire Behavior at Tropical Forest-Savanna Transitions

Forest-savanna mosaics are maintained by fire-mediated positive feedbacks; whereby forest is fire suppressive and savanna is fire promoting. Forest-savanna transitions therefore represent the interface of opposing fire regimes. Within the transition there is a threshold point at which tree canopy cover becomes sufficiently dense to shade out grasses and thus suppress fire. Prior to reaching this threshold, changes in fire behavior may already be occurring within the savanna. Such changes are neither empirically described nor their drivers understood. Fire behavior is largely driven by fuel flammability. Flammability can vary significantly between grass species and grass species composition can change near forest-savanna transitions. This study measured fire behavior changes at eighteen forest-savanna transition sites in a vegetation mosaic in Lopé National Park in Gabon, central Africa. The extent to which these changes could be attributed to changes in grass flammability was determined using species-specific flammability traits. Results showed simultaneous suppression of fire and grass biomass when tree canopy leaf area index (LAI) reached a value of 3, indicating that a fire suppression threshold existed within the forest-savanna transition. Fires became less intense and less hot prior to reaching this fire suppression threshold. These changes were associated with higher LAI values, which induced a change in the grass community, from one dominated by the highly flammable Anadelphia afzeliana to one dominated by the less flammable Hyparrhenia diplandra. Changes in fire behavior were not associated with changes in total grass biomass. This study demonstrated not only the presence of a fire suppression threshold but the mechanism of its action. Grass composition mediated fire-behavior within the savanna prior to reaching the suppression threshold, and grass species composition was mediated by tree canopy cover which was in turn mediated by fire-behavior. These findings highlight how biotic and abiotic controls interact and amplify each other in this mosaicked landscape to facilitate forest and savanna co-existence

The structures underpinning vulnerability: examining landscape-society interactions in a smallholder coffee agroforestry system

Smallholder farmers dependent on rain-fed agriculture are particularly vulnerable to extreme climate events and, therefore, it is necessary to identify adaptive measures that would increase farmer resilience to these shocks. The management options in a low-input system, like forest coffee (Coffea arabica), are limited and there are several factors out of farmers' control driving their vulnerability to changing climatic conditions. These can relate to social structures and landscape factors, which can interact to reduce farmers' adaptive capacity, creating a state of contextual vulnerability. We explored the potential synergies of this interaction across elevation, patch area and shade management gradients for smallholder coffee farms around the UNESCO Yayu Coffee Forest Biosphere Reserve in Ethiopia before, during and immediately following the 2015/16 El Niño. We documented a dramatic collapse in coffee yields across all farms, resulting in coffee incomes 29.5 ± 18.0 % and 19.5 ± 10.0 % of 2014 incomes in 2015 and 2016, respectively. We identified farms at elevations between 1500-1600 m with canopy openness between 40-45 % as being consistently low yielding over our study period. We found these farmers had the highest rates of income diversification and, therefore, were already exhibiting adaptive capacity. Farmers with the largest income losses were spatially concentrated between 1600-1700 m, located in larger patch areas with lower canopy openness. Farmers at this elevation have access to poor infrastructure, restrictions on shade management and reported higher dependence on income from coffee, indicating an interaction of biotic and social factors exacerbating their vulnerability. Unfortunately, due to a nationally declared state of emergency, we were unable to survey farmers on the adaptive measures they undertook; therefore, we are limited in assessing their resilience. However, we do show the importance of considering both biotically and socially-mediated influences for assessing smallholder vulnerability, particularly barriers to diversifying incomes

Size and frequency of natural forest disturbances and Amazon carbon balance

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of B1.28 Pg C y 1 over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of B0.01 Pg C y 1 , and that the largest-scale disturbances as a result of blow-downs only account for losses of B0.003 Pg C y 1 . Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink

Increasing dominance of large lianas in Amazonian forests

Ecological orthodoxy suggests that old-growth forests should be close to dynamic equilibrium, but this view has been challenged by recent findings that neotropical forests are accumulating carbon and biomass, possibly in response to the increasing atmospheric concentrations of carbon dioxide. However, it is unclear whether the recent increase in tree biomass has been accompanied by a shift in community composition. Such changes could reduce or enhance the carbon storage potential of old-growth forests in the long term. Here we show that non-fragmented Amazon forests are experiencing a concerted increase in the density, basal area and mean size of woody climbing plants (lianas). Over the last two decades of the twentieth century the dominance of large lianas relative to trees has increased by 1.7–4.6% a year. Lianas enhance tree mortality and suppress tree growth, so their rapid increase implies that the tropical terrestrial carbon sink may shut down sooner than current models suggest. Predictions of future tropical carbon fluxes will need to account for the changing composition and dynamics of supposedly undisturbed forests

Análise sazonal dos fluxos de CO2 e respiraçao em área de floresta alagada na costa norte do Brasil

Ponencia presentada en: XXX Jornadas Científicas de la AME y el IX Encuentro Hispano Luso de Meteorología celebrado en Zaragoza, del 5 al 7 de mayo de 2008

Informing trait-based ecology by assessing remotely sensed functional diversity across a broad tropical temperature gradient

Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotelysensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivitycould be predicted by remotely sensed functional diversity. Functional richness of the community decreased withincreasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play animportant role in explaining the range of trait variation within each site and along elevation. Single- and multitraitremotely sensed measures of functional diversity were important predictors of variation in rates of net and grossprimary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.Fil: Durán, Sandra M.. University of Arizona; Estados UnidosFil: Martin, Roberta E.. Arizona State University; Estados UnidosFil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Maitner, Brian S.. Arizona State University; Estados UnidosFil: Malhi, Yadvinder. University of Oxford; Reino UnidoFil: Salinas, Norma. University of Oxford; Reino Unido. Pontificia Universidad Católica de Perú; PerúFil: Shenkin, Alexander. University of Oxford; Reino UnidoFil: Silman, Miles R.. Wake Forest University; Estados UnidosFil: Wieczynski, Daniel J.. University of Oxford; Reino UnidoFil: Asner, Gregory P.. Arizona State University; Estados UnidosFil: Bentley, Lisa Patrick. Sonoma State University; Estados UnidosFil: Savage, Van M.. University of California; Estados UnidosFil: Enquist, Brian J.. Arizona State University; Estados Unido