Geography Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1641

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Subject: search.filters.subject.biodiversity

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    Developing an Integrated Remote Sensing Based Biodiversity Index for Predicting Animal Species Richness
    (MDPI, 2018-05-10) Wu, Jinhui; Liang, Shunlin
    Many 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.
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    An Evaluation of the Climate Change Preparedness of Terrestrial Protected Areas
    (2022-05-01) Panday, Frances Marie; Hurrt, George; Lamb, Rachel
    The 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.
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    Simulated impact of global climatic change on the geographic distribution of plant diversity
    (2005-01-13T14:03:37Z) Kleidon, Axel
    Elevated 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.