Publicações

Este trabalho, iniciado em agosto de 2017, tem como objetivo a continuidade ao projeto de Iniciação Científica em andamento desde janeiro de 2017, para a detecção de mudanças de uso e cobertura do terra através de Processamento Digital de Imagens. Inicialmente o trabalho realizado em janeiro de 2017 tratou de analisar a dinâmica de expansão da monocultura de eucalipto no município de São Luiz do Paraitinga. Os resultados obtidos demonstraram um quadro de elevada expansão da atividade no município, bem como variações na dinâmica de crescimento das áreas cultivadas, possivelmente relacionadas a ação de órgãos de regulação. Considerando a abordagem interescalar, o trabalho atual trata da mesma análise, aumentando a escala espacial ao nível da mesorregião do Vale do Paraíba Paulista. Desse modo, através do refinamento e aplicação do método anteriormente empregado, buscou-se mapear e analisar a dinâmica da expansão da monocultura do eucalipto na região entre os anos 1986 e 2017. Para realização desse objetivo foram empregadas técnicas de Processamento Digital de Imagens que incluem o realce de informações espectrais nas imagens de satélite utilizadas, através de um índice de vegetação, uma técnica de classificação e uma técnica de detecção de mudanças. A necessidade de refinamento do método anteriormente empregado se deu em função do aumento da área de estudo e da dificuldade do algorítimo de classificação empregado na discretização das respostas espectrais em classes de uso e ocupação do terra. Novamente foram utilizadas imagens pré-processadas dos sensores Landsat Thematic Mapper (TM) e Operational Land Imager (OLI) a bordo nos satélites Landsat 5 e Landsat 8 respectivamente. As etapas de trabalho programadas seguiram a seguinte ordem: Aquisição das imagens de satélite; Geração de imagens NDVI; Classificação da imagem NDVI referência correspondente ao último ano da série temporal; Aplicação do algorítimo de detecção de mudanças sobre todas as datas da série; Cruzamento dos resultados de mudança com o resultado da classificação; Análise e quantificação da expansão da cultura de eucalipto.

Os prejuízos associados aos desastres naturais vêm aumentando a cada ano no Brasil, principalmente devido ao denso crescimento populacional, uma vez que a população urbana representa mais de 84% da população do país, e com tendência de crescimento nas próximas décadas (BRITO et al., 2016), e ao mau planejamento urbano. A variável declividade do terreno é um dos principais condicionantes à ocorrência de escorregamentos de terras (BORTOLUCCI, 2015), sendo, dessa forma, uma variável muito utilizada em estudos que envolvem esta temática ambiental.

The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services -IPBESlaunched its Fellowship Programme in 2015 to involve early-career experts in its ongoing assessments on the role of biodiversity and ecosystem services for enhancing human wellbeing. The Programme provides an opportunity for early-career individuals from a variety of backgrounds and disciplines working on biodiversity and ecosystem services to fully participate in IPBES assessments through writing and reviewing documents and attending specific workshops and author meetings. This effort fosters the development of intergenerational, interdisciplinary and transnational partnerships. Creating such an atmosphere serves the larger goal of facilitating sustainability transformations by empowering and embracing diversity in skills, leadership styles, and values. In addition to working on the assessments, fellows benefit from the mentorship programme in which they are paired with senior experts working in the assessment. The mentorship involves knowledge exchange and mutual learning through the established intergenerational partnerships between fellows and senior experts. Although the fellowship finishes once the assessment is approved, fellows can choose to continue being involved through the newly established IPBES Fellows & Alumni network run by former and current fellows. For example, fellows have published scientific articles together, and currently multiple publications are under preparation. Additionally, alumni potentially serve as a pool of experts for upcoming assessments, mentors and resource persons for new cohorts of fellows, and those involved can act as ambassadors for IPBES in their local institutions, countries and regions. Besides presenting the Fellowship Programme, the poster will highlight the main lessons learned through practice and reflection about the role and relevance of the programme.

Biomass burning is a significant source of trace gases and aerosols to the atmosphere, and the evolution of these species depends acutely on where they are injected into the atmosphere. GEOS-Chem is a chemical transport model driven by assimilated meteorological data that is used to probe a variety of scientific questions related to atmospheric composition, including the role of biomass burning. This paper presents the development and implementation of a new global biomass burning emissions injection scheme in the GEOS-Chem model. The new injection scheme is based on monthly gridded Multi-angle Imaging SpectroRadiometer (MISR) global plume-height stereoscopic observations in 2008. To provide specific examples of the impact of the model updates, we compare the output from simulations with and without the new MISR-based injection height scheme to several sets of observations from regions with active fires. Our comparisons with Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) aircraft observations show that the updated injection height scheme can improve the ability of the model to simulate the vertical distribution of peroxyacetyl nitrate (PAN) and carbon monoxide (CO) over North American boreal regions in summer. We also compare a simulation for October 2010 and 2011 to vertical profiles of CO over the Amazon Basin. When coupled with larger emission factors for CO, a simulation that includes the new injection scheme also better matches selected observations in this region. Finally, the improved injection height improves the simulation of monthly mean surface CO over California during July 2008, a period with large fires.

Southeastern Brazil is characterized by seasonal rainfall variability. This can have a great social, economic, and environmental impact due to both excessive and deficient water availability. During 2014 and 2015, the region experienced one of the most severe droughts since 1960. The resulting water crisis has seriously affected water supply to the metropolitan region of São Paulo and hydroelectric power generation throughout the entire country. This research considered the upstream basins of the southeastern Brazilian reservoirs Cantareira (2,279 km2; water supply) and Emborcação (29,076 km2), Três Marias (51,576 km2), Furnas (52,197 km2), and Mascarenhas (71,649 km2; hydropower) for hydrological modelling. It made the first attempt at configuring a season-based probability-distributed model (PDM-CEMADEN) for simulating different hydrological processes during wet and dry seasons. The model successfully reproduced the intra-annual and interannual variability of the upstream inflows during 19852015. The performance of the model was very satisfactory not only during the wet, dry, and transitional seasons separately but also during the whole period. The best performance was obtained for the upstream basin of Furnas, as it had the highest quality daily precipitation and potential evapotranspiration data. The NashSutcliffe efficiency and logarithmic NashSutcliffe efficiency were 0.92 and 0.93 for the calibration period 19842001, 0.87 and 0.88 for the validation period 20012010, and 0.93 and 0.90 for the validation period 20102015, respectively. Results indicated that during the wet season, the upstream basins have a larger capacity and variation of soil water storage, a larger soil water conductivity, and quicker surface water flow than during the dry season. The added complexity of configuring a season-based PDM-CEMADEN relative to the traditional model is well justified by its capacity to better reproduce initial conditions for hydrological forecasting and prediction. The PDM-CEMADEN is a simple, efficient, and easy-to-use model, and it will facilitate early decision making and implement adaptation measures relating to disaster prevention for reservoirs with large-sized upstream basins.

Soil moisture over the Brazilian semiarid region is presented in different visualizations that highlight spatial, temporal and short-term agricultural risk. The analysis used the Soil Moisture Index (SMI), which is based on a normalization of soil moisture by field capacity and wilting point. The index was used to characterize the actual soil moisture conditions into categories from severe drought to very wet. In addition, the temporal evolution of SMI was implemented to visualize recent trends in short-term drought and response to rainfall events at daily time steps, as new data are available. Finally, a visualization of drought risk was developed by considering a critical value of SMI (assumed as 0.4), below which water stress is expected to be triggered in plants. A novel index based on continuous exposure to critical SMI was developed to help bring awareness of real time risk of water stress over the region: the Index of Stress in Agriculture (ISA). The index was tested during a drought over the region and successfully identified locations under water stress for periods of three days or more. The monitoring tools presented here help to describe the real time conditions of drought over the region using daily observations. The information from those tools support decisions on agricultural management such as planting dates, triggering of irrigation, or harvesting.

Habitat connectivity is the milestone towards species’ long-term persistence, especially considering impacts of climate change and human activities. Here, we examined the potential implications of climate change and human pressure on connectivity among habitat patches, aiming to identify priority areas and potential corridors for elephant conservation. We used an ensemble modelling approach to evaluate the potential climatic distribution of the savannah elephants Loxodonta fricana through time. We considered different climatic scenarios and used current potential climatic suitability and human pressure to evaluate habitat quality for the species. In addition, we used habitat quality and the centroids of elephant patches to evaluate habitat connectivity considering four progressive dispersal distances (100 km, 200 km, 300 km, 400 km). Elephant response to climate change has been conservative through time with overall slight improvement in climatic suitability in southern and eastern Africa and reduction in western Africa and northern portions of central Africa. Habitat quality followed the distribution of currently suitable areas for the species. We found three major areas with high density of least-cost paths in southern, eastern and western Africa, identifying them as potential areas for increasing the connectivity of elephant populations.

The Amazon rain forest is a major global isoprene source, but little is known about its seasonal ambient concentration patterns. To investigate the environmental and phenological controls over isoprene seasonality, we measured isoprene mixing ratios, concurrent meteorological data, and leaf area indices from April 2014 to January 2015 above a rain forest in the central Amazon, Brazil. Daytime median isoprene mixing ratios varied throughout the year by a factor of two. The isoprene seasonal pattern was not solely driven by sunlight and temperature. Leaf age and quantity also contributed to the seasonal variations of isoprene concentrations, suggesting leaf phenology was a crucial variable needed to correctly estimate isoprene emissions. A zero-dimensional model incorporating the estimated emissions, atmospheric boundary layer dynamics, and air chemistry was used to assess the contributions of each process on the variability of isoprene. Surface deposition was an important sink mechanism and accounted for 78% of the nighttime loss of isoprene. Also, chemical reactions destroyed isoprene and during 6:00 to 18:00 h local time 56, 77, 69, and 69% of the emitted isoprene was chemically consumed in June, September, December, and January, respectively. Entrainment fluxes from the residual layer contributed 34% to the early-morning above-canopy isoprene mixing ratios. Sensitivity analysis showed that hydroxyl radical (HO) recycling and segregation of isoprene HO played relatively lesser roles (up to 16%) in regulating ambient isoprene levels. Nitric oxide (NO) levels dominated isoprene chemical reaction pathways associated with consumption and production of HO under low-NO and high volatile organic compound (VOC) conditions. While surface deposition and oxidative processes altered isoprene levels, the relative importance of these factors varied seasonally with leaf phenology playing a more important role.

Mapping tropical tree species at landscape scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. For this purpose, detection and delineation of individual tree crowns (ITCs) is a prerequisite. Here, we present a new method of automatic tree crown delineation based only on very high resolution images from WorldView-2 satellite and apply it to a region of the Atlantic rain forest with highly heterogeneous tropical canopy cover the Santa Genebra forest reserve in Brazil. The method works in successive steps that involve pre-processing, selection of forested pixels, enhancement of borders, detection of pixels in the crown borders, correction of shade in large trees and, finally, segmentation of the tree crowns. Principally, the method uses four techniques: rolling ball algorithm and mathematical morphological operations to enhance the crown borders and ease the extraction of tree crowns; bimodal distribution parameters estimations to identify the shaded pixels in the gaps, borders, and crowns; and focal statistics for the analysis of neighbouring pixels. Crown detection is validated by comparing the delineated ITCs with a sample of ITCs delineated manually by visual interpretation. In addition, to test if the spectra of individual species are conserved in the automatic delineated crowns, we compare the accuracy of species prediction with automatic and manual delineated crowns with known species. We find that our method permits detection of up to 80% of ITCs. The seven species with over 10 crowns identified in the field were mapped with reasonable accuracy (30.596%) given that only WorldView-2 bands and texture features were used. Similar classification accuracies were obtained using both automatic and manual delineation, thereby confirming that species spectral responses are preserved in the automatic method and thus permitting the recognition of species at the landscape scale. Our method might support tropical forest applications, such as mapping species and canopy characteristics at the landscape scale.