Vulnerability of Protected Areas to Human Encroachment, Climate Change and Fire in the Fragmented Tropical Forests of West Africa

The Upper Guinean region of West Africa is home to some of the most globally significant tropical biodiversity hotspots, providing ecosystem services that are crucial for the region’s socio-economic and environmental wellbeing. Nonetheless, following decades of human-caused destruction of natural habitats, protected areas currently remain the only significant refugia of original vegetation relics in landscapes that are highly fragmented. Aside from having strong geographic variation in land use, climate, vegetation, and human population, the region has also experienced remarkable biophysical and socio-economic changes in recent decades. All these factors influence the fire regime and the vulnerability of forests within protected areas to fire-mediated changes and forest loss, yet little is known about fire regimes and fire-vegetation interactions within the region. Therefore, the overarching goal of this dissertation was to improve our understanding of the interactions of climate, land use, and fire regimes, as well as effects of fire on forest resilience in the Upper Guinean region of West Africa. I conducted the first comprehensive regional analysis of the fire regime across the gradient from humid tropical forests to drier woodlands and woody savanna. This analysis revealed that different components of the fire regime were influenced by different environmental drivers. As a result, the various combinations of these environmental factors create distinctive fire regimes throughout the region. The results further showed increasing active fire trends in parts of the forested areas, and decreasing trend in fire activity across much of the savannas that were likely linked with land cover changes. An analysis of fire-vegetation interactions in the forest zone of Ghana provided evidence of alternative stable states involving tropical forest and a novel non-forest vegetation community maintained by fire-vegetation feedbacks. Furthermore, an analysis exploring recent drought-associated wildfires in the forest zone of Ghana revealed widespread fire encroachment into hitherto fire-resistant moist tropical forests, which were associated with forest degradation. These findings suggest that ongoing regional landscape and socio-economic changes along with climate change will lead to further changes in the fire regimes and forest vegetation of West Africa. Hence, efforts to project future fire regimes and develop regional strategies for adaptation will require an integrated approach, which encompasses multiple components of the fire regime and consider multiple drivers, including land use and climate. Furthermore, projections of future vegetation dynamics in the region will need to consider land use, vegetation, fires, and their dynamic landscape-scale interactions in the context of broader responses to climate change and human population growth. Overall, this dissertation produced novel results about the pathways and drivers of disturbance land cover change that are necessary for improving our understanding of ongoing changes in a lesser-known part of the tropics. These findings are also relevant for predicting and mitigating similar fire impacts in tropical forests worldwide

Effects of land‐cover changes on the partitioning of surface energy and water fluxes in Amazonia using high‐resolution satellite imagery

Spatial variability of surface energy and water fluxes at local scales is strongly controlled by soil and micrometeorological conditions. Thus, the accurate estimation of these fluxes from space at high spatial resolution has the potential to improve prediction of the impact of land‐use changes on the local environment. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Large‐Scale Biosphere‐Atmosphere Experiment in Amazonia (LBA) data were used to examine the partitioning of surface energy and water fluxes over different land‐cover types in one wet year (2004) and one drought year (2005) in eastern Rondonia state, Brazil. The spatial variation of albedo, net radiation (Rn), soil (G) and sensible (H) heat fluxes, evapotranspiration (ET), and evaporative fraction (EF) were primarily related to the lower presence of forest (primary [PF] or secondary [SF]) in the western side of the Ji‐Parana River in comparison with the eastern side, located within the Jaru Biological Reserve protected area. Water limitation in this part of Amazonia tends to affect anthropic (pasture [PA] and agriculture [AG]) ecosystems more than the natural land covers (PF and SF). We found statistically significant differences on the surface fluxes prior to and ~1 year after the deforestation. Rn over forested areas is ~10% greater in comparison with PA and AG. Deforestation and consequent transition to PA or AG increased the total energy (~200–400%) used to heat the soil subsurface and raise air temperatures. These differences in energy partitioning contributed to approximately three times higher ET over forested areas in comparison with nonforested areas. The conversion of PF to AG is likely to have a higher impact in the local climate in this part of Amazonia when compared with the change to PA and SF, respectively. These results illustrate the importance of conserving secondary forest areas in Amazonia.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/1/eco2126_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/2/eco2126.pd

Multi-scale actual evapotranspiration mapping in South America with remote sensing data and the geeSEBAL model

O monitoramento preciso da evapotranspiração (ET) é crucial para gerenciar os recursos hídricos, garantir a segurança alimentar e avaliar os impactos das mudanças climáticas. Modelos de Balanço de Energia da Superfície (SEB) que usam dados de sensoriamento remoto são os mais confiáveis para estimar a ET, mas muitas vezes são difíceis de aplicar em grande escala devido ao longo tempo de processamento, necessidade de calibração local, entre outros obstáculos. Esta tese tem como foco a melhoria do geeSEBAL, uma implementação do modelo Surface Energy Balance Algorithm for Land (SEBAL) na plataforma Google Earth Engine (GEE), adaptando-o para modelagem em escala continental, usando imagens do Moderate Resolution Imaging Spectroradiometer (MODIS). O novo modelo, chamado geeSEBALMODIS, foi usado para gerar uma série temporal de ET a cada 8 dias para a América do Sul com pixels de 500 m. Estudos de validação mostram que o geeSEBAL-MODIS é mais preciso do que outros produtos globais de ET, com uma redução do erro de 13% na escala de campo e 30% na escala de bacia hidrográfica. O conjunto de dados está disponível para o público e pode ser usado para monitorar tanto mudanças climáticas em grande escala quanto as variações locais de ET relacionadas às atividades humanas. A análise de tendências mostra um aumento de 8,4% na ET sobre a América do Sul, associado ao aumento da demanda atmosférica, e à redução da precipitação e disponibilidade de água. Esses resultados destacam a importância de informações precisas sobre os processos do ciclo hidrológico para auxiliar no planejamento e gerenciamento dos recursos hídricos em um cenário de maior escassez. Nesse contexto, projetos como o OpenET, que fornece dados confiáveis e de alta resolução espacial de ET nos Estados Unidos, são cruciais para monitorar o consumo de água e auxiliar no desenvolvimento sustentável. Este trabalho também apresenta uma reprodução parcial do processo do OpenET para a intercomparação de modelos de sensoriamento remoto com dados de torres de fluxo, usando torres micrometeorológicas na América do Sul. Os resultados são promissores e abrem caminho para a expansão do OpenET além dos Estados Unidos e em direção a uma aplicação global.Accurately monitoring evapotranspiration (ET) is crucial for managing water resources, ensuring food security, and assessing the impacts of climate change. Surface Energy Balance (SEB) models that use remote sensing data are the most reliable for estimating ET, but they are often challenging to apply on a large scale due to long processing times, and local calibration requirements, among other obstacles. This dissertation focuses on improving geeSEBAL, an implementation of the Surface Energy Balance Algorithm for Land (SEBAL) model on the Google Earth Engine (GEE) platform, by adapting it for continental-scale modeling using Moderate Resolution Imaging Spectroradiometer (MODIS) images. The new model, called geeSEBAL-MODIS, was used to generate a temporal series of ET every 8 days for South America with pixels of 500 m. Validation studies show that geeSEBAL-MODIS is more accurate than other global ET products, with a reduction in error of 13% at the field scale and 30% at the basin scale. The dataset is publicly available and can be used to monitor both largescale climate change and local ET variations related to human activities. Trend analysis shows an 8.4% increase in ET over South America, associated with increased atmospheric demand, and reductions in precipitation and water availability. These findings underscore the importance of accurate information on hydrological cycle processes to assist in planning and managing water resources in a scenario of greater scarcity. In this context, projects like OpenET, which provides reliable and high spatial-resolution ET data in the United States, are crucial for monitoring water consumption and aiding in sustainable development. This work also presents a partial reproduction of the OpenET process for intercomparing remote sensing models with flux tower data, using micrometeorological towers in South America. The results are promising and pave the way for expanding OpenET beyond the United States and toward global application

Methods to Evaluate Land-Atmosphere Exchanges in Amazonia Based on Satellite Imagery and Ground Measurements

During the last three decades, intensive campaigns and experiments have been conducted for acquiring micrometeorological data in the Amazonian ecosystems, which has increased our understanding of the variation, especially seasonally, of the total energy available for the atmospheric heating process by the surface, evapotranspiration and carbon exchanges. However, the measurements obtained by such experiments generally cover small areas and are not representative of the spatial variability of these processes. This chapter aims to discuss several algorithms developed to estimate surface energy and carbon fluxes combining satellite data and micrometeorological observations, highlighting the potentialities and limitations of such models for applications in the Amazon region. We show that the use of these models presents an important role in understanding the spatial and temporal patterns of biophysical surface parameters in a region where most of the information is local. Data generated may be used as inputs in earth system surface models allowing the evaluation of the impact, both in regional as well as global scales, caused by land-use and land-cover changes

Drought impacts assessment in Brazil - a remote sensing approach

Climate extremes are becoming more frequent in Brazil; studies project an increase in drought occurrences in many regions of the country. In the south, drought events lead to crop yield losses affecting the value chain and, therefore, the local economy. In the northeast, extended periods of drought lead to potential land degradation, affecting the livelihood and hindering local development. In the southern Amazon, an area that experienced intense land use change (LUC) in the last, the impacts are even more complex, ranging from crop yield loss and forest resilience loss, affecting ecosystem health and putting a threat on the native population traditional way of living. In the studies here we analyzed the drought impacts in these regions during the 2000s, which vary in nature and outcomes. We addressed some of the key problems in each of the three regions: i) for the southern agriculture, we tackled the problem of predicting soybean yield based on within-season remote sensing (RS) data, ii) in the northeast we mapped areas presenting trends of land degradation in the wake of an extended drought and, iii) in southern Amazon, we characterized a complex degradation cycle encompassing LUC, fire occurrence, forest resilience loss, carbon balance, and the interconnectedness of these factors impacting the local climate. Advisor: Brian D. Wardlo

Amazon hydrology from space : scientific advances and future challenges

As the largest river basin on Earth, the Amazon is of major importance to the world's climate and water resources. Over the past decades, advances in satellite-based remote sensing (RS) have brought our understanding of its terrestrial water cycle and the associated hydrological processes to a new era. Here, we review major studies and the various techniques using satellite RS in the Amazon. We show how RS played a major role in supporting new research and key findings regarding the Amazon water cycle, and how the region became a laboratory for groundbreaking investigations of new satellite retrievals and analyses. At the basin-scale, the understanding of several hydrological processes was only possible with the advent of RS observations, such as the characterization of "rainfall hotspots" in the Andes-Amazon transition, evapotranspiration rates, and variations of surface waters and groundwater storage. These results strongly contribute to the recent advances of hydrological models and to our new understanding of the Amazon water budget and aquatic environments. In the context of upcoming hydrology-oriented satellite missions, which will offer the opportunity for new synergies and new observations with finer space-time resolution, this review aims to guide future research agenda toward integrated monitoring and understanding of the Amazon water from space. Integrated multidisciplinary studies, fostered by international collaborations, set up future directions to tackle the great challenges the Amazon is currently facing, from climate change to increased anthropogenic pressure

Surface water and energy fluxes in South America : an integrated approach based on remote sensing and flux measurements

South America is a water-abundant continent, home to the world's largest river basins and rainforest, which plays a crucial role in providing moisture to other regions of the continent through evapotranspiration (). is a crucial indicator of the earth's ecosystem functioning, linking the water, energy, and carbon cycles. Due to the great challenge of obtaining information based on in situ measurements, remote sensing data has become a great opportunity to obtain estimations. Based on measurements and estimations based on remote sensing data, this study aimed to evaluate the dynamics, patterns and controls of water and energy fluxes in South America, seeking to answer three main questions: i) can remote sensing data provide accurate information on the water balance?; ii) how do the factors controlling vary across different biomes and land use and land cover (LULC) conditions? and iii) can remote sensing models represent accurately patterns and its components under different LULC conditions? To answer the first question, we performed a water balance analysis, evaluating the uncertainties of precipitation and estimations using in situ measurements, and conducting an analysis to understand how much these uncertainties can be affected due to the basin’s scales. The results showed that due to the uncertainties related to each of the variable from remote sensing it is not yet possible to achieve the water balance closing. However, the approach proved to be a great alternative to evaluate the dynamics of water fluxes from small to large basins, especially in those where in situ measurement is still scarce. To seek to answer the second question, we evaluated the influence of biotic and abiotic factors on control processes, based on surface and aerodynamic conductances and the decoupling factor, at 20 flux measurement sites in South America. Through this analysis, different patterns of latent () and sensible () heat fluxes were verified, and different degrees of importance of biotic and abiotic controls on the process according to different LULC conditions. Finally, based on 11 flux measurement sites and four models (MOD16, GLEAM, PML and SSEBOP), we assessed the accuracy of estimates in the Amazon basin, and the representation of fluxes in forest, pasture, and soybean areas, in the Tapajós basin. The results showed that obtaining accurate estimates is still a major challenge in the Amazon basin, especially in humid and seasonally flooded sites. Significant discrepancies between the models and between measurements were found, and these discrepancies were even more significant when evaluated the individual components. However, even though each model did not perform significantly under all climatic and vegetation conditions, they present together a great opportunity to improve the accuracy of estimates, leading to an improved understanding of the impacts on water and energy fluxes due to human activities. Thus, these results demonstrate the potential and limitations of hydrological components obtained by remote sensing, especially for , and how LULC changes may modify this flux in South America.A América do Sul é um continente abundante em água, abrigando as maiores bacias hidrográficas e a maior floresta tropical do mundo, a floresta Amazônica. A Amazônia desempenha um papel crucial no fornecimento de umidade para outras regiões do continente por meio da evapotranspiração (). A é um indicador crucial do funcionamento do ecossistema terrestre, interligando os ciclos da água, energia e carbono. Devido ao grande desafio de obtenção de informações de por medições in situ, o uso de dados de sensoriamento remoto tem se mostrado uma grande alternativa para obter estimativas desta variável. Com base em dados medidos e estimados por sensoriamento remoto foi conduzido um estudo que visou analisar a dinâmica, os padrões e os controles dos fluxos de água e energia na América do Sul, buscando responder a três questões principais: i) os dados de sensoriamento remoto podem fornecer informações precisas sobre o balanço hídrico?; ii) como os fatores que controlam a variam em diferentes biomas e condições de uso e cobertura do solo (LULC)?; e iii) os modelos de sensoriamento remoto conseguem representar com acurácia os padrões de e das suas componentes em diferentes condições de LULC? Para responder a primeira pergunta realizou-se uma análise de balanço hídrico, na qual foi avaliada as incertezas das estimativas de precipitação e usando medições in situ, e uma análise do quanto essas incertezas podem ser afetadas devido ao efeito de escala das bacias analisadas. Os resultados mostraram que devido às incertezas relacionadas com cada uma das componentes estimadas por sensoriamento remoto ainda não é possível alcançar o fechamento do balanço hídrico. No entanto, a abordagem demonstrou ser uma grande alternativa para avaliar a dinâmica dos fluxos de água, de pequenas a grandes bacias, especialmente naquelas onde a medição in situ ainda é escassa. Para buscar responder a segunda pergunta analisou-se a influência dos fatores bióticos e abióticos no controle dos processos de , por meio da análise das condutâncias de superfície e aerodinâmica e do fator de desacoplamento em 20 locais de monitoramento de fluxo na América do Sul. Por meio desta análise verificou-se diferentes padrões dos fluxos de calor latente () e sensível (), além de diferentes graus de importância dos controles bióticos e abióticos sobre o processo de e de acordo com as diferentes condições de LULC. Por fim, com base em 11 locais de monitoramento de fluxo e quatro modelos de (MOD16, GLEAM, PML e SSEBOP), analisou-se a acurácia destas estimativas na bacia amazônica, e a representação dos fluxos de em áreas de floresta, pastagem e soja, na bacia do Tapajós. Os resultados mostraram que a obtenção de estimativas acuradas de ainda é um grande desafio na bacia Amazônica, principalmente em locais úmidos e sazonalmente inundados. Discrepâncias significativas entre os modelos e entre as medições foram encontradas, sendo estas discrepâncias ainda mais expressivas quando se analisou as componentes individuais de . No entanto, os resultados deste estudo demonstraram que apesar de cada modelo não apresentar um desempenho significativo em todas as condições climáticas e de vegetação, estes apresentam em conjunto, uma grande oportunidade para melhorar a acurácia das estimativas de , propiciando um aprimoramento na compreensão dos impactos nos fluxos de água e energia devido a atividades antrópicas. Deste modo, estes resultados enfatizam os potenciais e limitações das variáveis hidrológicos obtidas por sensoriamento remoto, especialmente para a , e como as mudanças LULC podem modificar este fluxo na América do Sul