College of Behavioral & Social Sciences

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Now showing 1 - 4 of 4
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    Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system
    (Springer Nature, 2014-05-08) Johnson, Kristofer D; Birdsey, Richard; Finley, Andrew O; Swantaran, Anu; Dubayah, Ralph; Wayson, Craig; Riemann, Rachel
    Forest Inventory and Analysis (FIA) data may be a valuable component of a LIDAR-based carbon monitoring system, but integration of the two observation systems is not without challenges. To explore integration methods, two wall-to-wall LIDAR-derived biomass maps were compared to FIA data at both the plot and county levels in Anne Arundel and Howard Counties in Maryland. Allometric model-related errors were also considered. In areas of medium to dense biomass, the FIA data were valuable for evaluating map accuracy by comparing plot biomass to pixel values. However, at plots that were defined as “nonforest”, FIA plots had limited value because tree data was not collected even though trees may be present. When the FIA data were combined with a previous inventory that included sampling of nonforest plots, 21 to 27% of the total biomass of all trees was accounted for in nonforest conditions, resulting in a more accurate benchmark for comparing to total biomass derived from the LIDAR maps. Allometric model error was relatively small, but there was as much as 31% difference in mean biomass based on local diameter-based equations compared to regional volume-based equations, suggesting that the choice of allometric model is important. To be successfully integrated with LIDAR, FIA sampling would need to be enhanced to include measurements of all trees in a landscape, not just those on land defined as “forest”. Improved GPS accuracy of plot locations, intensifying data collection in small areas with few FIA plots, and other enhancements are also recommended.
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    Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA
    (Springer Nature, 2015-08-16) Huang, Wenli; Swatantran, Anu; Johnson, Kristofer; Duncanson, Laura; Tang, Hao; O’Neil Dunne, Jarlath; Hurtt, George; Dubayah, Ralph
    Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-derived biomass map over Maryland, USA. We conduct detailed comparisons at pixel-, county-, and state-level. Spatial patterns of biomass are broadly consistent in all maps, but there are large differences at fine scales (RMSD 48.5–92.7 Mg ha−1). Discrepancies reduce with aggregation and the agreement among products improves at the county level. However, continental scale maps exhibit residual negative biases in mean (33.0–54.6 Mg ha−1) and total biomass (3.5–5.8 Tg) when compared to the high-resolution lidar biomass map. Three of the four continental scale maps reach near-perfect agreement at ~4 km and onward but do not converge with the high-resolution biomass map even at county scale. At the State level, these maps underestimate biomass by 30–80 Tg in forested and 40–50 Tg in non-forested areas. Local discrepancies in continental scale biomass maps are caused by factors including data inputs, modeling approaches, forest/non-forest definitions and time lags. There is a net underestimation over high biomass forests and non-forested areas that could impact carbon accounting at all levels. Local, high-resolution lidar-derived biomass maps provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale maps produced in carbon monitoring systems.
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    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.
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    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.