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This study presents the integration of light detection and range (LiDAR) and hyperspectral remote sensing to create a three-dimensional bird habitat map in the Greenbelt Corridor of the Elm Fork of the Trinity River. This map permits to examine the relationship between forest stand structure, landscape heterogeneity, and bird community composition. A biannual bird census was conducted at this site during the breeding seasons of 2009 and 2010. Census data combined with the three-dimensional map suggest that local breeding bird abundance, community structure, and spatial distribution patterns are highly influenced by vertical heterogeneity of vegetation surface. For local breeding birds, vertical heterogeneity of canopy surface within stands, connectivity to adjacent forest patches, largest forest patch index, and habitat (vegetation) types proved to be the most influential factors to determine bird community assemblages. Results also highlight the critical role of secondary forests to increase functional connectivity of forest patches. Overall, three-dimensional habitat descriptions derived from integrated LiDAR and hyperspectral data serve as a powerful bird conservation tool that shows how the distribution of bird species relates to forest composition and structure at various scales.

The Arctic cryosphere is experiencing a higher rate of warming compared to the rest of the world due to Arctic amplification. As glacier elevation change provide reliable evidence of climate change it is routinely measured by satellite altimeters. Satellite altimetry, while a valuable tool for monitoring elevation change over time, is subject to inherent uncertainties caused by, among other factors, the small scale surface roughness of the target surfaces. Previous studies have identified surface roughness as a key source of uncertainty when measuring sea ice freeboard and studies suggest the surface roughness strongly influences the Synthetic Aperture Radar (SAR) signatures of sea ice. Similar studies over snow- and glacier surfaces, are rare. In this context, we attempt to conduct a small scale calibration and validation (cal/val) campaign over glacier surfaces, using the ideal location and infrastructure of the University Centre in Svalbard. We demonstrate the process, from planning through field data collection and data analysis. By doing so, we identify good as well as bad practices. Using high resolution in-situ LiDAR data, collected under two ICESat-2 (IS2) overpasses in Svalbard we generated Digital Elevation Models (DEM) and calculated surface roughness estimates across glacier- and snow surfaces. The surface roughness was quantified by calculating the Root Mean Square (RMS) of deviations from the overall topography of the surfaces. The DEMs were used for direct comparison with the satellite elevation retrievals and the observed elevation differences were tested for correlation with surface roughness at different length scales. We then investigated the effect of surface roughness on the photon cloud of the lower level ATL03 ICESat-2 data products, by quantifying the precision in the data. We found little to no correlation between RMS roughness and the observed elevation differences between in-situ and satellite data sets, possibly explained by errors in georeferencing the DEMs. We show moderate to strong correlation between photon cloud precision and along- and across-track absolute surface slopes, with correlation coefficients of 0.6–0.8. Correlation between photon cloud precision and RMS roughness was found, with a maximum correlation coefficient of 0.9 for a roughness length scale of 1m. The results suggest IS2 is sensitive to surface roughness at similar length scales but we identify a need for more data, covering a wider range of surfaces and potential roughness scenarios, to draw strong conclusions. We demonstrate how a small team can carry out a cal/val campaign in the high arctic and collect coincident data under satellite overpasses, data which is typically rare for the remote high Arctic regions.

This dissertation investigates environmental degradation of a wetland ecosystem in the northeast Peruvian Amazon: the palm swamps, or aguajales, mostly located in the region of Loreto, Peru. This ecosystem is dominated by the dioecious palm species Mauritia flexuosa, locally known as aguaje. Female aguaje palms produce a valuable fruit which is widely consumed in the region, and especially in the capital city Iquitos. The most common method of harvesting this fruit is to chop the female palms. Concern is growing over environmental degradation that results from this practice, such as high carbon emissions released from the peat soils upon which most aguajales grow. This dissertation investigates environmental degradation of the palm swamps from multiple scales. Using a mixed-methods analysis, this dissertation asks: 1) What is the magnitude and distribution of palm swamp degradation, and what is the contribution of this process to carbon emissions? 2) What is the relative influence of physical and social underlying drivers explaining the spatial distribution of palm swamp ecosystems with different palm swamp densities? 3) How do underlying social-ecological/political-ecological driving forces occurring at different scales influence the sustainable use and conservation of palm swamp ecosystems? Degradation is mapped at the regional scale using remote sensing techniques over two periods of time: 1990-2007 and 2007-2018. Underlying drivers of degradation are investigated at the regional and district levels using spatially explicit statistical models. Finally, qualitative data acquired in the field is used to investigate why some communities successfully manage their palm swamps while others do not. This dissertation produces the first regional map of palm swamp degradation and first temporal analysis of how degradation has changed over three decades. It is the first study to analyze both physical and socioeconomic drivers of degradation and the first study to analyze how physical drivers change over time. It contributes to the literature of land change science by demonstrating a method of testing socioeconomic data at an aggregated scale against degradation data derived from remote sensing. Finally, this study provides a detailed and nuanced analysis of the aguaje social-ecological system, demonstrating that the choice of some communities to chop palms for harvest is not one made of ignorance, but rather is a logical option in marginalized communities where the aguaje fruit cannot provide a sufficient contribution to a community’s material needs. This work contributes to the literature of critical conservation by demonstrating cases of conservation success that were achieved without coercive state power. / Accompanied by 1 PDF file: chap1.pdf

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