2 resultados para return autocorrelation

em Publishing Network for Geoscientific


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As a result of intensive field activities carried out by several nations over the past 15 years, a set of accumulation measurements for western Dronning Maud Land, Antarctica, was collected, based on firn-core drilling and snow-pit sampling. This new information was supplemented by earlier data taken from the literature, resulting in 111 accumulation values. Using Geographical Information Systems software, a first region-wide mean annual snow-accumulation field was derived. In order to define suitable interpolation criteria, the accumulation records were analyzed with respect to their spatial autocorrelation and statistical properties. The resulting accumulation pattern resembles well known characteristics such as a relatively wet coastal area with a sharp transition to the dry interior, but also reveals complex topographic effects. Furthermore, this work identifies new high-return shallow drilling sites by uncovering areas of insufficient sampling density.

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Environmental conservation activities must continue to become more efficient and effective, especially in Africa where development and population growth pressures continue to escalate. Recently, prioritization of conservation resources has focused on explicitly incorporating the economic costs of conservation along with better defining the outcomes of these expenditures. We demonstrate how new global and continental data that spans social, economic, and ecological sectors creates an opportunity to incorporate return-on-investment (ROI) principles into conservation priority setting for Africa. We suggest that combining conservation priorities that factor in biodiversity value, habitat quality, and conservation management investments across terrestrial, freshwater, and coastal marine environments provides a new lens for setting global conservation priorities. Using this approach we identified seven regions capturing interior and coastal resources that also have high ROI values that support further investment. We illustrate how spatially explicit, yet flexible ROI analysis can help to better address uncertainty, risk, and opportunities for conservation, while making values that guide prioritization more transparent. In one case the results of this prioritization process were used to support new conservation investments. Acknowledging a clear research need to improve cost information, we propose that adopting a flexible ROI framework to set conservation priorities in Africa has multiple potential benefits.