Geography Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2773
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Item EXPLORING AND ASSESSING LAND-BASED CLIMATE SOLUTIONS USING EARTH OBSERVATIONS, EARTH SYSTEM MODELS, AND INTEGRATED ASSESSMENT MODELS(2024) Gao, Xueyuan; Wang, Dongdong; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Anthropogenic greenhouse gas (GHG) emissions have led the global mean temperature to increase by approximately 1.1 °C since the industrial revolution, resulting in mass ice sheet melt, sea level rise, and an increase in extreme climate events, and exposing natural and human systems to uncertainties and the risks of unsustainable development. Meeting the Paris Agreement’s climate goal of keeping temperature increases well below 2 °C — even 1.5 °C — will require removing CO2 from the atmosphere beyond reducing GHG emissions. Therefore, carbon dioxide removal and the sustainable management of global carbon cycles are one of the most urgent society needs and will become the major focus of climate action worldwide. However, research on carbon dioxide removal remains in an early stage with large knowledge gaps. The global potential and scalability, full climate consequences, and potential side effects of currently suggested carbon sequestration options — afforestation and reforestation, bioenergy with carbon capture and storage (BECCS), direct air carbon capture — are uncertain. Moreover, although about 120 national governments have a net-zero emission target, few have actionable plans for developing carbon dioxide removal.This dissertation examines two major categories of land-based carbon removal and sequestration methods: nature-based solutions that rely on the natural carbon uptake of the land ecosystem, and technology-based solutions, especially BECCS. These two options were investigated using four studies with satellite and in-situ observations, Earth system models (climate models), and integrated assessment models (policy models). Study 1 provides evidence that land ecosystem is an important carbon sink, Study 2 assesses the carbon sequestration potential of forest sustainable management via numerical experiments, Study 3 monitors recent tropical landscape restoration efforts, and Study 4 extends to BECCS and explores the impacts of future climate changes on its efficacy. Overall, this dissertation (1) improved monitoring, reporting, and verification of biomass-based carbon sequestration efforts using Earth observations, (2) improved projections on biomass-based carbon sequestration potential using Earth system models and socio-economic models, and (3) provided guidance on scaling up biomass-based carbon sequestration methods to address the climate crisis.Item Monitoring Aboveground Biomass in Forest Conservation and Restoration Areas Using GEDI and Optical Data Fusion(2024) Liang, Mengyu; Duncanson, Laura I; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Forests play a critical role in the global carbon cycle by sequestering carbon in the form of aboveground biomass. Area-based conservation measures, such as protected areas (PAs), are a cornerstone conservation strategy for preserving some of the world's most at-risk forest ecosystems. Beyond PAs, tree planting and forest restoration have been lauded as solutions to combat climate change and criticized as ways for polluters to offset carbon emissions. Consistent monitoring and quantification of forest restoration can impact decisions on future restoration activities. In this dissertation, I utilized a fusion of remote sensing assets and a combination of remote sensing with impact assessment techniques, to obtain objective baseline information for reconstructing past forest biomass conditions, and for monitoring and quantifying the patterns and success of forest regrowth in areas that underwent different forest management interventions. This overarching research goal is approached in three studies corresponding to chapters 2-4. In chapter 2, PAs’ effectiveness in storing biomass carbon and preserving forest structure is assessed on a regional scale using Global Ecosystem Dynamics Investigation (GEDI) lidar data in combination with a counterfactual analysis using statistical matching. This chapter provides an assessment of the reference condition of the biomass carbon storage capacity by one of the most stringent forest management means. The study finds that analyzed PAs in Tanzania possess 24.4% higher biomass densities than their unprotected counterparts and highlights that community-governed PAs are the most effective category of PAs at preserving forest structure and aboveground biomass density (AGBD). In chapter 3, empirical models are developed to link current (2019-2020) AGBD estimates from the GEDI with Landsat (2007-2019) at a regional scale. This will allow both current wall-to-wall biomass mapping and estimation of biomass dynamics across time. We demonstrate the utility of the method by applying it to quantify the AGBD dynamics associated with forest degradation for charcoal production. In chapter 4, the same modeling framework laid out in chapter 3 will be used to derive AGBD trajectories for 27 forest restoration sites across three biomes in East Africa. To assess the effectiveness of and compare Assisted Natural Regeneration (ANR) and Active Restoration (AR) in enhancing forest AGBD growth compared to natural regeneration (NR), we used staggered difference-in-difference (staggered DiD) to analyze the average annual AGBD change. We controlled for pre-intervention AGBD change rate between AR/ANR and NR and estimated the effectiveness with explicit consideration of intervention duration. This study finds that AR and ANR outperform NR during long-term restoration. Using the most suitable restoration interventions in each biome and timeframe, 4% suitable areas could enhance 2.40 ± 0.78 Gt (billion metric tons) forest carbon uptake over 30 years, equivalent to 3.6 years of African-wide emissions. Overall, this dissertation develops remote sensing methodological frameworks for using GEDI data and its fusion with Landsat time series to quantify and monitor forest AGBD. Moreover, by combining remote sensing-derived AGBD dynamics with impact assessment techniques, such as statistical matching and staggered DiD, the dissertation further assesses and compares different conservation and restoration means’ effectiveness in increasing AGBD and carbon uptake in forests. The dissertation therefore advances the applications of state-of-the-art remote sensing data and techniques for sustainably managing forests towards climate mitigation targets.Item Characterizing the Multi-scale Post-fire Forest Structural Change in North American Boreal Forests using Air- and Space-borne Lidar Observations(2024) Feng, Tuo; Duncanson, Laura; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Wildfire is the dominant stand-replacing disturbance regime in boreal North America, shaping the pattern, structure and composition of forested landscapes. Forest losses and gains through wildfires are two linked ecological processes, despite their varied functionalities in terrestrial carbon budgets. Combustion of forest biomass through wildfires results in the release of terrestrial carbon, whereas subsequent forest recovery process would re-sequestrate atmospheric CO2 back to the plants, and therefore at least partially offsets fire-induced carbon emissions. However, the magnitude of forest carbon fluxes and its association with wildfires is highly uncertain, especially under the context of large anomalies in fire regimes during the past few decades due to climate change. To fill the knowledge gaps, this dissertation focuses on integrations of air- and space-borne Light Detection and Ranging (lidar) to assess the magnitudes of forest structure and Aboveground Biomass Density (AGBD) changes with respect to wildfires. This dissertation starts with a systematic evaluation of multi-resolution Ice, Cloud and land Elevation Satellite -2 (ICESat-2) terrain and canopy height estimates over boreal North America. As one of the first ICESat-2 validation studies, this work demonstrates ICESat-2 as a suitable platform for large-scale terrain and canopy height measurements, and further provides a suite of standards for ICESat-2 data filtering over boreal forests. Thereafter, I analyze magnitude of forest structure and AGBD changes through wildfire events with multi-temporal airborne lidar and Landsat. This study establishes quantitative linkages between multispectral and structural measurements of fire effects on forest damage, and further reveals burn severity levels, pre-fire forest structure and fire-return intervals as dominant drivers for the magnitude of forest damage through fires. Finally, this dissertation investigates continental-scale forest recovery rate through a full-collection of high-resolution ICESat-2 observations, Landsat-based disturbance history and multi-decadal climatology records. The forest recovery rates under different warming trend are found to be converging over the past few decades, demonstrated as the growth rate of forests across high-latitudinal North gradually approaching their counterparts over Southern boreal zones. This work further reveals a positive effect of growing season warming on forest deciduousness shift, and concludes that regions with warming and associated increase in deciduous compositions would experience greatest growth rate acceleration. This dissertation leverages the potential of multi-sourced remote sensing datasets to assess spatial extents, magnitudes, and underlying drivers of forest carbon feedbacks to climate change and wildfires over North American boreal ecosystem.Item Advances in Mapping Forest Biomass and Old-Growth Conditions Using Waveform Lidar(2023) Bruening, Jamis; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne waveform lidar sys- tem that has transformed scientific understanding of the world’s forests through billions of pre- cise measurements of ecosystem structure. Relative to forest processes that operate on decadal to millennial timescales, the four year period during which GEDI collected these measurements is short, and GEDI’s ability to analyze how forest structure changes over time is mostly unproven. However, fusion efforts that integrate GEDI data with forest inventory measurements and ecosys- tem models hold immense potential for discovery. In this dissertation, I explore the limitations and capabilities of GEDI data for inference into structural and successional dynamics within east- ern US forests. First, I used a forest gap model to quantify uncertainty in biomass predictions for individual GEDI waveforms, and discovered a relationship between biomass uncertainty and successional stage. Next, I investigated uncertainties and errors in large-scale GEDI biomass estimates relative to unbiased estimates from the US forest inventory. I developed a novel mod- eling framework based on fusion between GEDI and the US forest inventory data that corrected these errors, and I produced unbiased and precise maps of forest biomass for the continental US. Lastly, I assessed GEDI’s ability to identify and map different types of old-growth forests, and discovered that GEDI can detect some old forests more effectively than others. This research identified key limitations associated with using GEDI to study forest dynamics, and I leveraged these discoveries to develop new ways of using GEDI data for ecological and successional in- ference. These discoveries will inform new uses of GEDI data and its integration with inventory data and ecosystem modeling to better characterize changes within forest ecosystems.Item LONG-TERM IMPACTS OF AMAZON FOREST DEGRADATION ON CARBON STOCKS AND ANIMAL COMMUNITIES: COMBINING SOUND, STRUCTURE, AND SATELLITE DATA(2020) Rappaport, Danielle I; Dubayah, Ralph; Morton, Douglas; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Amazon forest plays a vital role in the Earth system, yet forest degradation from logging and fire jeopardizes carbon storage and biodiversity conservation along the deforestation frontier. Polices to reduce forest carbon emissions (REDD+) will fall short of their intended goals unless carbon and biodiversity losses from forest degradation can be monitored over time. Emerging remote sensing tools, lidar and ecoacoustics, provide a means to monitor carbon and biodiversity across spatial, temporal, and taxonomic scales to address data gaps on species distributions and time-scales for recovery. This dissertation draws from a novel multi-sensor perspective to characterize the long-term ecological legacy of Amazon forest degradation across a 20,000 km2 landscape in Mato Grosso, Brazil. It combines high-density airborne lidar, 1100 hours of acoustic surveys, and annual time series of Landsat data to pursue three complementary studies. Chapter 2 establishes the bedrock of the investigation by using fine-scale measurements of structure sampled across a large diversity of degraded forests to model the initial loss and time-dependent recovery of carbon stocks and habitat structure following fire and logging. Chapter 3 models the interactions between sound and structure to predict acoustic community variation, and to account for attenuation in dense tropical forests. Lastly, Chapter 4 uses sound to go beyond structure to identify the specific degradation sequences and pseudo-taxa that give rise to variation in the ‘acoustic guild’ over time. Soundscapes reveal strong and sustained shifts in insect assemblages following fire, and a decoupling of biotic and biomass recovery following logging that defy theoretical predictions (Acoustic Niche Hypothesis). The synergies between lidar and acoustic data confirm the long-term legacy of forest degradation on both forest structure and animal communities in frontier Amazon forests. After multiple fires, forests become carbon-poor, habitats become simplified, and animal communication networks became quieter, less connected, and more homogenous. The combined results quantify large potential benefits to protecting already-burned Amazon forests from recurrent fires. This dissertation paves the way for greater integration of remote sensing and analysis tools to enhance capabilities for bringing biomass and biodiversity monitoring to scale. Building on this research with species-level and multi-temporal measurements will reduce uncertainty around the breakpoints that drive carbon and biodiversity loss following degradation.Item EFFECT OF VEGETATION STRUCTURE ON UNDERCANOPY SOLAR RADIATION USING LIDAR REMOTE SENSING(2017) Anand, Anupam; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Estimation of under-canopy radiation is crucial for characterizing vegetation–energy interactions and for a better understanding of its implications for ecosystem studies and forestry applications. Under-canopy radiation regimes are difficult to model due to the complex interaction of light with vegetation structure. Also, measuring radiation under the canopy over large areas is challenging using traditional field-based procedures. In this context, LiDAR remote sensing shows great potential for radiation estimation because it directly measures the three-dimensional canopy structure. The primary aim of this dissertation is to improve the understanding of under-canopy light regime using discrete return LiDAR and estimate solar radiation in forests with different structural characteristics. Based on the availability of LiDAR data, research sites were chosen in the coniferous forests of Sierra National Forest (SNF), California, and a chronosequence of mixed deciduous forest plots located in the Smithsonian Environmental Research Center (SERC), Maryland. First, LiDAR-derived digital surface models with and without vegetation canopy were used to assess the first-order effect of vegetation on solar radiation in SNF. The results showed a significant difference (p value < 0.001) in insolation values between the two surface models, with the mean solar irradiation over the bare surface almost three times higher than vegetation canopy surface. Next, a ray-tracing method was used to estimate beam radiation using LiDAR point clouds, and estimates were compared with in situ pyranometer measurements across three forest plots in SERC and were found to be in good agreement (RMSE = 13.94 W/m2). Lastly, LiDAR-derived vertical light transmittance values were compared with measurements from field-based PAR sensors, across five forest plots in SERC and were found to be in good agreement (R2 = 0.84). These results suggest that LiDAR remote sensing can provide reliable fine-scale estimates of beam radiation and vertical transmittance values under the vegetation canopy without the need for extensive ground measurements. This information provides a better understanding of radiation variability under the canopy and can help potentially improve the estimates from a range of land surface models such as snowmelt and hydrological models, and possibly help downscale general circulation model (GCM) predictions.Item LAND USE AND LAND COVER CHANGE AS A DRIVER OF ECOSYSTEM DEGRADATION ACROSS BIOMES(2016) Noojipady, Praveen; Prince, Stephen D; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The expansion and intensification of agricultural production in human-dominated landscapes threaten efforts to sustain natural ecosystems and maintain agricultural production in a changing climate. Long-term use of agricultural lands, combined with conversion of natural ecosystems for agricultural production, can rapidly degrade the health of remaining natural ecosystems. The fundamental goal of this dissertation was to assess the impacts of anthropogenic degradation on stocks and sequestration of carbon. Although degradation alters a range of ecosystem services, case studies of ecosystem degradation in this dissertation focus on reductions in vegetation productivity, carbon stocks, and the extent of natural forest cover as a result of human activity. Time series of satellite remote sensing data were used to track forest and rangeland degradation in the southwestern United States, forest carbon emissions from cropland expansion in the Brazilian Cerrado, and fire-driven forest conversion for oil palm plantations in Southeast Asia. Three major themes link the regional case studies: expansion and intensification of agricultural production, market demand and certification, and agricultural management in response to climate variability. Conclusions from the dissertation underscore the widespread influence of land management on vegetation productivity and forest carbon stocks. In the Southwest United States, reductions in net primary production on managed lands were higher in forested landscapes than other cover types. In contrast, Native American Indian Reservations, often considered to be more degraded, actually had smaller absolute reductions in net primary productivity during 2000-2011. Multi-year droughts in the southwest present new challenges for managing forests and rangelands, and climate projections suggest dry conditions will intensify in the coming century. In Southeast Asia, industry-led efforts to certify sustainable palm oil production were evaluated using satellite data on fires and forest loss. Rates of fire-driven deforestation and total fire activity declined following certification, highlighting the potential for certification to reduce ignitions during El Niño years and protect remaining fragments of lowland and peat forest. Aligning certification criteria for sustainable palm oil with satellite monitoring capabilities may help accelerate compliance with environmental legislation and market demands for deforestation-free products. In Brazil, government and industry actions to limit Amazon deforestation have largely overlooked the neighboring Cerrado biome. Forest carbon emissions from deforestation for soy expansion in the Cerrado increased substantially after the implementation of the Soy Moratorium in the Brazilian Amazon, partially offsetting recent reductions in Amazon deforestation carbon emissions. The success of policies to support sustainable agricultural production therefore depends on efforts to minimize cross-biome leakage and the ability to monitor compliance and unintended consequences. Solutions for management must also confront the growing influence of climate variability. Time series of satellite data may allow early detection of degradation impacts and support efforts to mitigate the influence of sustained agricultural production on natural systems. Changes in vegetation carbon stocks from ecosystem degradation varied across case studies, underscoring the diverse nature of direct and indirect drivers of degradation across different land use systems. Direct human drivers of ecosystem degradation in the southwest United States from management of livestock grazing resulted in gradual changes in vegetation productivity, whereas mining and oil extraction areas showed large and permanent reductions. Forest carbon emissions from agriculture expansion in the Cerrado were a one-time process, as native vegetation is cleared for cropland expansion. In contrast, the carbon emissions from Southeast Asia’s forest and peatland conversion involve both sudden and gradual processes, as carbon accumulation in oil palm plantations partially compensates for emissions from forest conversion. Overall, this research made contributions to understanding of the regional impacts of human activity and the potential for climate change mitigation from sustainable land use practices in human-dominated landscapes.Item Integrating Forest Ecological Processes, Management, and Carbon Payments to Assess Ecosystem Service Tradeoffs(2016) Ling, Pui-Yu; Prince, Stephen D; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Due to the current crisis on global warming and species extinction, scientists and economists have proposed to quantify ecosystem goods and services to establish policies that can preserve the ecosystem, provide better livelihood to the local stakeholders, and benefit society. The overarching question for this dissertation study is, ``How to quantify the trade-offs between carbon sequestration, total timber harvested, and habitat provision for sustaining biodiversity?'' In particular, when i. different management regimes; ii. carbon prices; and iii. natural disturbances; interact with each other. The first step is to develop a model that quantifies the relationship between forest management activities and the amount of timber harvested annually. To provide a general understanding of the relationship, the study area for the first step is at the county level for the whole state of North Carolina. The following 2 steps involve more specific studies to include the interaction between management activities, natural disturbances, species competition during the forest succession process. Therefore, a species-rich, heterogeneous area with an active timber industry, located in western part of North Carolina, the Grandfather Ranger District was chosen. The second step is to quantify the outcomes and analyze the trade-offs between the ecosystem services under different management scenarios, coupled with the influences from natural disturbance. The third step combines the result from the second step with different carbon prices and interest rates to obtain a fine scale and spatial analysis of the resulting revenue. The dissertation is the first step of research in developing a dynamic model that fully couples the social and forest ecological system. Besides the potential uses for fulfilling the requirements of carbon accounting, the result from the first step of the dissertation is the maps of annual volume of harvested timber of various types. The maps can be used to further study to analyze the relationship between the amount of timber harvested as a result of different policies and prices at different places. The second step demonstrated a way to quantify the trade-offs between the selected ecosystem services under different forest management regimes and influences from natural disturbances events. Maps of revenue from both selling the carbon credit and harvested timber for scenarios of different carbon prices and interest rates were produced in the last step. The choice of future timber production as a result of carbon and roundwood prices can partly be understood by utilizing the maps from the first step in this dissertation. If the factors affect individual choices of harvest at the local level and those affect the supply of harvested timber at the regional level are understood, then a dynamic model that consists of management decisions, natural disturbance, ecosystem service valuation policies, and forest ecosystem response can be developed. Such model can help better understand the ecosystem services valuation policy on the financial well-being of foresters and the health of the forest ecosystem.Item DYNAMICS OF THE SHORT TERM AND LONG TERM AVIAN DISTRIBUTIONS IN NORTH AMERICA - THE ROLES OF VEGETATION HEIGHT HETEROGENEITY AND CLIMATIC FACTORS(2015) Huang, Qiongyu; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.Item Carbon Sequestration and Agents of Woody Encroachment in Southeastern Arizona Semi-arid Grasslands(2014) O'Neal, Kelley; Justice, Christopher; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Woody encroachment and proliferation within dryland ecosystems is potentially the second largest portion of the North American carbon sink and one of the largest areas of uncertainty. This dissertation examines a semi-arid grassland located in southeastern Arizona to better understand woody encroachment, agents of change, and the resultant carbon storage from 1984-2008. The objectives were to quantify changes in woody cover, rank agent importance, estimate carbon density, and calculate voluntary market value. The first objective of mapping changes in woody cover was addressed using a Landsat time-series to measure woody cover and calculate the change, rate of change, and change relative to initial cover over the 25-year time period. Results show the change in woody cover varies spatially and ranges from approximately -2 to 11% with most areas experiencing a 5% increase and 92% relative increase over initial cover, indicating woody cover nearly doubled in the region. The second objective of ranking the importance of agents was achieved using an ensemble classifier. Agents examined included grazing, number of times burned, soil texture, soil productivity, elevation, slope, aspect, and initial woody cover. Initial woody cover, number of times burned, elevation, and grazing were ranked as the most important agents of woody encroachment, indicating the importance of historical land management and disturbance, frequent fire, topography and correlated precipitation, and land use. The third objective of producing carbon estimates and calculating economic opportunity in the voluntary carbon markets was accomplished by applying cover to biomass, root:shoot, and carbon equations to the final woody plant cover maps to calculate carbon stocks, carbon density, and voluntary market value. Results show very low carbon density in the study area relative to similar ecosystems and other ecosystems in general. Given the insignificant annual accumulation of carbon on the small ownership parcels, current low carbon trading prices, and high beef prices, management for storage is not economically viable in the study area at this time.