RESUMO
Amazonia has experienced large-scale regional droughts that affect forest productivity and biomass stocks. Space-borne remote sensing provides basin-wide data on impacts of meteorological anomalies, an important complement to relatively limited ground observations across the Amazon's vast and remote humid tropical forests. Morning overpass QuikScat Ku-band microwave backscatter from the forest canopy was anomalously low during the 2005 drought, relative to the full instrument record of 1999-2009, and low morning backscatter persisted for 2006-2009, after which the instrument failed. The persistent low backscatter has been suggested to be indicative of increased forest vulnerability to future drought. To better ascribe the cause of the low post-drought backscatter, we analyzed multiyear, gridded remote sensing data sets of precipitation, land surface temperature, forest cover and forest cover loss, and microwave backscatter over the 2005 drought region in the southwestern Amazon Basin (4°-12°S, 66°-76°W) and in adjacent 8°x10° regions to the north and east. We found moderate to weak correlations with the spatial distribution of persistent low backscatter for variables related to three groups of forest impacts: the 2005 drought itself, loss of forest cover, and warmer and drier dry seasons in the post-drought vs. the pre-drought years. However, these variables explained only about one quarter of the variability in depressed backscatter across the southwestern drought region. Our findings indicate that drought impact is a complex phenomenon and that better understanding can only come from more extensive ground data and/or analysis of frequent, spatially-comprehensive, high-resolution data or imagery before and after droughts.
Assuntos
Secas , Florestas , Micro-Ondas , Espalhamento de Radiação , Brasil , Geografia , Modelos Lineares , Modelos EstatísticosRESUMO
The British Petroleum Deepwater Horizon Oil Spill in the Gulf of Mexico was the biggest oil spill in US history. To assess the impact of the oil spill on the saltmarsh plant community, we examined Advanced Visible Infrared Imaging Spectrometer (AVIRIS) data flown over Barataria Bay, Louisiana in September 2010 and August 2011. Oil contamination was mapped using oil absorption features in pixel spectra and used to examine impact of oil along the oiled shorelines. Results showed that vegetation stress was restricted to the tidal zone extending 14 m inland from the shoreline in September 2010. Four indexes of plant stress and three indexes of canopy water content all consistently showed that stress was highest in pixels next to the shoreline and decreased with increasing distance from the shoreline. Index values along the oiled shoreline were significantly lower than those along the oil-free shoreline. Regression of index values with respect to distance from oil showed that in 2011, index values were no longer correlated with proximity to oil suggesting that the marsh was on its way to recovery. Change detection between the two dates showed that areas denuded of vegetation after the oil impact experienced varying degrees of re-vegetation in the following year. This recovery was poorest in the first three pixels adjacent to the shoreline. This study illustrates the usefulness of high spatial resolution airborne imaging spectroscopy to map actual locations where oil from the spill reached the shore and then to assess its impacts on the plant community. We demonstrate that post-oiling trends in terms of plant health and mortality could be detected and monitored, including recovery of these saltmarsh meadows one year after the oil spill.
Assuntos
Poluição por Petróleo , Fenômenos Fisiológicos Vegetais/efeitos dos fármacos , Estresse Fisiológico/fisiologia , Poluentes Químicos da Água/toxicidade , Áreas Alagadas , Adaptação Fisiológica , Baías , Ecossistema , Golfo do México , Louisiana , Petróleo/toxicidade , Plantas/efeitos dos fármacos , Plantas/metabolismo , Densidade Demográfica , Dinâmica Populacional , Salinidade , Cloreto de Sódio/química , Fatores de TempoRESUMO
Old-growth forest ecosystems comprise a mosaic of patches in different successional stages, with the fraction of the landscape in any particular state relatively constant over large temporal and spatial scales. The size distribution and return frequency of disturbance events, and subsequent recovery processes, determine to a large extent the spatial scale over which this old-growth steady state develops. Here, we characterize this mosaic for a Central Amazon forest by integrating field plot data, remote sensing disturbance probability distribution functions, and individual-based simulation modeling. Results demonstrate that a steady state of patches of varying successional age occurs over a relatively large spatial scale, with important implications for detecting temporal trends on plots that sample a small fraction of the landscape. Long highly significant stochastic runs averaging 1.0 Mg biomassâ ha(-1)â y(-1) were often punctuated by episodic disturbance events, resulting in a sawtooth time series of hectare-scale tree biomass. To maximize the detection of temporal trends for this Central Amazon site (e.g., driven by CO2 fertilization), plots larger than 10 ha would provide the greatest sensitivity. A model-based analysis of fractional mortality across all gap sizes demonstrated that 9.1-16.9% of tree mortality was missing from plot-based approaches, underscoring the need to combine plot and remote-sensing methods for estimating net landscape carbon balance. Old-growth tropical forests can exhibit complex large-scale structure driven by disturbance and recovery cycles, with ecosystem and community attributes of hectare-scale plots exhibiting continuous dynamic departures from a steady-state condition.
Assuntos
Árvores/crescimento & desenvolvimento , Biomassa , Brasil , Ciclo do Carbono , Simulação por Computador , Ecossistema , Modelos Biológicos , Rios , Árvores/metabolismo , Clima TropicalRESUMO
The rate and extent of deforestation determine the timing and magnitude of disturbance to both terrestrial and aquatic ecosystems. Rapid change can lead to transient impacts to hydrology and biogeochemistry, while complete and permanent conversion to other land uses can lead to chronic changes. A large population of watershed boundaries (N=4788) and a time series of Landsat TM imagery (1975-1999) in the southwestern Amazon Basin showed that even small watersheds (2.5-15 km2) were deforested relatively slowly over 7-21 years. Less than 1% of all small watersheds were more than 50% cleared in a single year, and clearing rates averaged 5.6%/yr during active clearing. A large proportion (26%) of the small watersheds had a cumulative deforestation extent of more than 75%. The cumulative deforestation extent was highly spatially autocorrelated up to a 100-150 km lag due to the geometry of the agricultural zone and road network, so watersheds as large as approximately 40000 km2 were more than 50% deforested by 1999. The rate of deforestation had minimal spatial autocorrelation beyond a lag of approximately 30 km, and the mean rate decreased rapidly with increasing area. Approximately 85% of the cleared area remained in pasture, so deforestation in watersheds of Rondônia was a relatively slow, permanent, and complete transition to pasture, rather than a rapid, transient, and partial cutting with regrowth. Given the observed landcover transitions, the regional stream biogeochemical response is likely to resemble the chronic changes observed in streams draining established pastures, rather than a temporary pulse from slash-and-burn.
Assuntos
Ecologia , Árvores , BrasilRESUMO
Este artigo se propõe a apresentar exemplos de questões científicas que puderam ser respondidas no contexto do Projeto LBA (Large Sale Biosphere-Atmosphere Experiment in Amazonia) graças à contribuição de informações derivadas de sensoriamento remoto. Os métodos de sensoriamento remoto permitem integrar informações sobre os vários processos físicos e biológicos em diferentes escalas de tempo e espaço. Nesse artigo, são enfatizados aqueles avanços de conhecimento que jamais seriam alcançados sem a concorrência da informação derivada de sensoriamento.
Assuntos
Reconhecimento Automatizado de Padrão , Processos Estocásticos , Tecnologia de Sensoriamento RemotoRESUMO
This paper aims to assess the contribution of remote sensing technology in addressing key questions raised by the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). The answers to these questions foster the knowledge on the climatic, biogechemical and hydrologic functioning of the Amazon, as well as on the impact of human activities at regional and global scales. Remote sensing methods allow integrating information on several processes at different temporal and spatial scales. By doing so, it is possible to perceive hidden relations among processes and structures, enhancing their teleconnections. Key advances in the remote sensing science are summarized in this article, which is particularly focused on information that would not be possible to be retrieved without the concurrence of this technology.
Este artigo se propõe a apresentar exemplos de questões científicas que puderam ser respondidas no contexto do Projeto LBA (Large Sale Biosphere-Atmosphere Experiment in Amazonia) graças à contribuição de informações derivadas de sensoriamento remoto. Os métodos de sensoriamento remoto permitem integrar informações sobre os vários processos físicos e biológicos em diferentes escalas de tempo e espaço. Nesse artigo, são enfatizados aqueles avanços de conhecimento que jamais seriam alcançados sem a concorrência da informação derivada de sensoriamento.