Ecological research in the Large Scale Biosphere Atmosphere Experiment in Amazonia: A discussion of early results

The Large-scale Biosphere–Atmosphere Experiment in Amazonia (LBA) is a multinational, interdisciplinary research program led by Brazil. Ecological studies in LBA focus on how tropical forest conversion, regrowth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in the Amazon region. Early results from ecological studies within LBA emphasize the variability within the vast Amazon region and the profound effects that land-use and land-cover changes are having on that landscape. The predominant land cover of the Amazon region is evergreen forest; nonetheless, LBA studies have observed strong seasonal patterns in gross primary production, ecosystem respiration, and net ecosystem exchange, as well as phenology and tree growth. The seasonal patterns vary spatially and interannually and evidence suggests that these patterns are driven not only by variations in weather but also by innate biological rhythms of the forest species. Rapid rates of deforestation have marked the forests of the Amazon region over the past three decades. Evidence from ground-based surveys and remote sensing show that substantial areas of forest are being degraded by logging activities and through the collapse of forest edges. Because forest edges and logged forests are susceptible to fire, positive feedback cycles of forest degradation may be initiated by land-use-change events. LBA studies indicate that cleared lands in the Amazon, once released from cultivation or pasture usage, regenerate biomass rapidly. However, the pace of biomass accumulation is dependent upon past land use and the depletion of nutrients by unsustainable land-management practices. The challenge for ongoing research within LBA is to integrate the recognition of diverse patterns and processes into general models for prediction of regional ecosystem function

Using ICESAT\u27s geoscience laser altimeter system to assess large scale forest disturbance caused by Hurricane Katrina

We assessed the use of GLAS data as a tool to quantify large-scale forest damage. GLAS data for the year prior to and following Hurricane Katrina were compared to wind speed, forest cover, and MODIS NPV maps to analyze senor sampling, and changes in mean canopy height. We detected significant losses in mean canopy height post-Katrina that increased with wind intensity, from ∼.5m in forests hit by tropical storm winds to ∼4m in forests experiencing category two force winds. Season of data acquisition was shown to influence calculations of mean canopy height. There was insufficient sampling to adequately detect changes at one degree resolution and less. We observed a strong relationship between delta NPV and post storm mean canopy heights. Changes in structure were converted into loss of standing carbon estimates using a height structured ecosystem model, yielding above ground carbon storage losses of ∼30Tg over the domain

Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure

Abrupt forest disturbances generating gaps \u3e0.001 km2 impact roughly 0.4–0.7 million km2a−1. Fire, windstorms, logging, and shifting cultivation are dominant disturbances; minor contributors are land conversion, flooding, landslides, and avalanches. All can have substantial impacts on canopy biomass and structure. Quantifying disturbance location, extent, severity, and the fate of disturbed biomass will improve carbon budget estimates and lead to better initialization, parameterization, and/or testing of forest carbon cycle models. Spaceborne remote sensing maps large-scale forest disturbance occurrence, location, and extent, particularly with moderate- and fine-scale resolution passive optical/near-infrared (NIR) instruments. High-resolution remote sensing (e.g., ∼1 m passive optical/NIR, or small footprint lidar) can map crown geometry and gaps, but has rarely been systematically applied to study small-scale disturbance and natural mortality gap dynamics over large regions. Reducing uncertainty in disturbance and recovery impacts on global forest carbon balance requires quantification of (1) predisturbance forest biomass; (2) disturbance impact on standing biomass and its fate; and (3) rate of biomass accumulation during recovery. Active remote sensing data (e.g., lidar, radar) are more directly indicative of canopy biomass and many structural properties than passive instrument data; a new generation of instruments designed to generate global coverage/sampling of canopy biomass and structure can improve our ability to quantify the carbon balance of Earth\u27s forests. Generating a high-quality quantitative assessment of disturbance impacts on canopy biomass and structure with spaceborne remote sensing requires comprehensive, well designed, and well coordinated field programs collecting high-quality ground-based data and linkages to dynamical models that can use this information

Can Landsat-Derived Variables Related to Energy Balance Improve Understanding of Burn Severity From Current Operational Techniques?

Producción CientíficaForest managers rely on accurate burn severity estimates to evaluate post-fire damage and to establish revegetation policies. Burn severity estimates based on reflective data acquired from sensors onboard satellites are increasingly complementing field-based ones. However, fire not only induces changes in reflected and emitted radiation measured by the sensor, but also on energy balance. Evapotranspiration (ET), land surface temperature (LST) and land surface albedo (LSA) are greatly affected by wildfires. In this study, we examine the usefulness of these elements of energy balance as indicators of burn severity and compare the accuracy of burn severity estimates based on them to the accuracy of widely used approaches based on spectral indexes. We studied a mega-fire (more than 450 km2 burned) in Central Portugal, which occurred from 17 to 24 June 2017. The official burn severity map acted as a ground reference. Variations induced by fire during the first year following the fire event were evaluated through changes in ET, LST and LSA derived from Landsat data and related to burn severity. Fisher’s least significant difference test (ANOVA) revealed that ET and LST images could discriminate three burn severity levels with statistical significance (uni-temporal and multi-temporal approaches). Burn severity was estimated from ET, LST and LSA using thresholding. Accuracy of ET and LST based on burn severity estimates was adequate (κ = 0.63 and 0.57, respectively), similar to the accuracy of the estimate based on dNBR (κ = 0.66). We conclude that Landsat-derived surface energy balance variables, in particular ET and LST, in addition to acting as useful indicators of burn severity for mega-fires in Mediterranean ecosystems, may provide critical information about how energy balance changes due to fireMinisterio de Economía, Industria y Competitividad (project AGL2017-86075-C2-1-R)Junta de Castilla y León (project LE001P17

Recent climate and fire disturbance impacts on boreal and arctic ecosystem productivity estimated using a satellite-based terrestrial carbon flux model

Warming and changing fire regimes in the northern (≥45°N) latitudes have consequences for land-atmosphere carbon feedbacks to climate change. A terrestrial carbon flux model integrating satellite Normalized Difference Vegetation Index and burned area records with global meteorology data was used to quantify daily vegetation gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE) over a pan-boreal/Arctic domain and their sensitivity to climate variability, drought, and fire from 2000 to 2010. Model validation against regional tower carbon flux measurements showed overall good agreement for GPP (47 sites: R = 0.83, root mean square difference (RMSD) = 1.93 g C m−2 d−1) and consistency for NEE (22 sites: R = 0.56, RMSD = 1.46 g C m−2 d−1). The model simulations also tracked post-fire NEE recovery indicated from three boreal tower fire chronosequence networks but with larger model uncertainty during early succession. Annual GPP was significantly (p \u3c 0.005) larger in warmer years than in colder years, except for Eurasian boreal forest, which showed greater drought sensitivity due to characteristic warmer, drier growing seasons relative to other areas. The NEE response to climate variability and fire was mitigated by compensating changes in GPP and respiration, though NEE carbon losses were generally observed in areas with severe drought or burning. Drought and temperature variations also had larger regional impacts on GPP and NEE than fire during the study period, though fire disturbances were heterogeneous, with larger impacts on carbon fluxes for some areas and years. These results are being used to inform development of similar operational carbon products for the NASA Soil Moisture Active Passive (SMAP) mission

Radiative forcing of natural forest disturbances

Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate-regulating properties of forests. Using both tower-based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO2 forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO2 forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane-damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models

Assessment of post-fire changes in land surface temperature and surface albedo, and their relation with fire-burn severity using multitemporal MODIS imagery

This study evaluates the effects of the large 2007 Peloponnese (Greece) wildfires on changes in broadband surface albedo (a), daytime land surface temperature (LSTd) and night-time LST (LSTn) using a 2-year post-fire time series of Moderate Resolution Imaging Spectroradiometer satellite data. In addition, it assesses the potential of remotely sensed a and LST as indicators for fire-burn severity. Immediately after the fire event, mean a dropped up to 0.039 (standard deviation = 0.012) (P < 0.001), mean LSTd increased up to 8.4 (3.0) K (P < 0.001), and mean LSTn decreased up to -1.2 (1.5) K (P < 0.001) for high-severity plots (P < 0.001). After this initial alteration, fire-induced changes become clearly smaller and seasonality starts governing the a and LST time series. Compared with the fire-induced changes in a and LST, the post-fire NDVI drop was more persistent in time. This temporal constraint restricts the utility of remotely sensed a and LST as indicators for fire-burn severity. For the times when changes in a and LST were significant, the magnitude of changes was related to fire-burn severity, revealing the importance of vegetation as a regulator of land surface energy fluxes