Geography
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Item Developing an Integrated Remote Sensing Based Biodiversity Index for Predicting Animal Species Richness(MDPI, 2018-05-10) Wu, Jinhui; Liang, ShunlinMany remote sensing metrics have been applied in large-scale animal species monitoring and conservation. However, the capabilities of these metrics have not been well compared and assessed. In this study, we investigated the correlation of 21 remote sensing metrics in three categories with the global species richness of three different animal classes using several statistical methods. As a result, we developed a new index by integrating several highly correlated metrics. Of the 21 remote sensing metrics analyzed, evapotranspiration (ET) had the greatest impact on species richness on a global scale (explained variance: 52%). The metrics with a high explained variance on the global scale were mainly in the energy/productivity category. The metrics in the texture category exhibited higher correlation with species richness at regional scales. We found that radiance and temperature had a larger impact on the distribution of bird richness, compared to their impacts on the distributions of both amphibians and mammals. Three machine learning models (i.e., support vector machine, random forests, and neural networks) were evaluated for metric integration, and the random forest model showed the best performance. Our newly developed index exhibited a 0.7 explained variance for the three animal classes’ species richness on a global scale, with an explained variance that was 20% higher than any of the univariate metrics.Item An Evaluation of the Climate Change Preparedness of Terrestrial Protected Areas(2022-05-01) Panday, Frances Marie; Hurrt, George; Lamb, RachelThe rate at which the climate changes and the direction of these shifts is highly variable across the landscape. As proposed by Loarie et al. (2009), the concept of a climate change velocity (CV) adds a spatial component to the rate at which the temperature increases across the landscape. Identifying where regions will experience the most significant changes in climate conditions is highly valuable for the management of areas with high ecological and societal value, such as protected areas (PAs). To examine the relationship between climate velocity and protected areas, Loarie et al. (2009) proposes the concept of a climate residence time (CRT), which estimates the length of time current climate conditions will remain in a given spatial location before shifting. Current infrastructure design managing protected areas is outdated and may be ill-equipped to handle future changes in climate. Current work examining the relationship between protected area and the CV is relatively new, but results are promising. Here, we evaluate the climate-change preparedness of terrestrial protected areas in MD by first, quantifying the magnitude of future changes using the climate residence time, and second, evaluating their capacity to manage changes by qualitatively scoring their associated management plans for climate adaptation and/or mitigation language. This two-fold approach showed that most PAs have climate residence times less than or equal to 1.5 years and had plans with little to no language addressing climate change and its associated impacts. This suggests that PAs in MD are poorly prepared for future changes in climate. Given these results, including CVs and CRTs within PA management plans would improve a park’s adaptive capacity but also signal the need for a cross-coordinated management effort that transcends different management and governance scales.Item Characterizing tree species diversity in the tropics using full-waveform lidar data(2019) Marselis, Suzanne; Dubayah, Ralph; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Tree species diversity is of paramount value to maintain forest health and to ensure that forests are able to provide all vital functions, such as creating oxygen, that are needed for mankind to survive. Most of the world’s tree species grow in the tropical region, but many of them are threatened with extinction due to increasing natural and human-induced pressures on the environment. Mapping tree species diversity in the tropics is of high importance to enable effective conservation management of these highly diverse forests. This dissertation explores a new approach to mapping tree species diversity by using information on the vertical canopy structure derived from full-waveform lidar data. This approach is of particular interest in light of the recently launched Global Ecosystem Dynamics Investigation (GEDI), a full-waveform spaceborne lidar. First, successful derivation of vertical canopy structure metrics is ensured by comparing canopy profiles from airborne lidar data to those from terrestrial lidar. Then, the airborne canopy profiles were used to map five successional vegetation types in Lopé National Park in Gabon, Africa. Second, the relationship between vertical canopy structure and tree species richness was evaluated across four study sites in Gabon, which enabled mapping of tree species richness using canopy structure information from full-waveform lidar. Third, the relationship between canopy structure and tree species richness across the tropics was established using field and lidar data collected in 16 study sites across the tropics. Finally, it was evaluated how the methods and applications developed here could be adapted and used for mapping pan-tropical tree species diversity using future GEDI lidar data products.Item Correlates of Terrestrial Vertebrate Species Richness: an Evaluation of Environmental Hypotheses over the Western Continental USA(2006-04-24) Slayback, Daniel Andrew; Prince, Stephen D; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)An explanation for the unequal distribution of life forms across the Earth's surface has been a persistent and problematic question in modern ecology ever since these patterns were first noted, over 100 years ago. Most empirical research supports one of three environmental hypotheses to explain these patterns: environmental energy (ambient environmental energy or ecosystem productivity); climatic variability; or habitat heterogeneity. This research examines these hypotheses using better datasets than those commonly considered, and using a consistent methodology that addresses often neglected statistical and analytic details. The environmental datasets used in this study are derived from time series of satellite and ground station data, including the Daymet climate data, and net primary productivity data from the GLOPEM model. Species richness is derived from the individually modeled vertebrate distributions provided by the individual state Gap Analysis Projects for the western US states of California, Oregon, Washington, Idaho, Montana, Wyoming, Utah, and Colorado, which define the spatial extent of this study. The study methodology relies upon the summary of results from many model variants for each hypothesis. These variants are constructed by creating regression models at each of four different spatial scales (8, 16, 32, and 64 km grid cells), for each class of vertebrates (amphibians, birds, mammals, reptiles, and all), and over each of the eight states considered. Preliminary studies found that ordinary least squares would be a sufficient model form, although conditional autoregressive models were extensively considered. Other preliminary work examined issues of spatial autocorrelation and variable selection. The results indicate that the energy/productivity hypothesis consistently outperforms all other hypotheses in explaining species richness, across almost all spatial scales, geographic regions, and vertebrate classes. The performance of the climatic variability and habitat heterogeneity hypotheses varies for particular states or vertebrate classes. Vertebrate data quality was important; results for Colorado and Washington were frequently unusual, suggesting an incompatibility between their modeled vertebrate distributions and those of other states. Models of reptile richness also often showed substantially different characteristics than those for other vertebrates. Overall the results provide additional support to the energy/productivity hypothesis, from a more comprehensive methodological basis.Item Simulated impact of global climatic change on the geographic distribution of plant diversity(2005-01-13T14:03:37Z) Kleidon, AxelElevated concentrations of atmospheric carbon dioxide (pCO2) are likely to lead to substantial warming in the coming century with altered hydrological regimes, thereby affecting the distribution of plant species. Here I use an individual-based modeling approach to plant diversity to estimate the impact of global climatic change on the geographic distribution of plant diversity. Differences in temperature, precipitation, and light use efficiency (to represent stimulation of photosynthesis due to higher pCO2) are used in isolation and in combination in order to investigate the role of these drivers. I find that the general warming associated with elevated pCO2 leads to profoundly different responses of simulated diversity in temperature-limited and tropical environments. While the growing season is lengthened in northern latitudes and therefore enables more plant growth strategies to be successful, elevated autotrophic respiration rates lead to higher mortality during plant establishment in the tropics, therefore reducing the range of successful plant growth strategies. The overall impact of elevated pCO2 on plant diversity will clearly be a combination of various factors. What these model results nevertheless point out is that global climatic change may alter plant diversity patterns disproportionally by reducing the overall success of plant establishment.