78 research outputs found

    The Value of Global Earth Observations

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    Humankind has never been so populous, technically equipped, and economically and culturally integrated as it is today. In the twenty-first century, societies are confronted with a multitude of challenges in their efforts to manage the Earth system

    Use of Cross-Taxon Congruence for Hotspot Identification at a Regional Scale

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    One of the most debated problems in conservation biology is the use of indicator (surrogate) taxa to predict spatial patterns in other taxa. Cross-taxon congruence in species richness patterns is of paramount importance at regional scales to disclose areas of high conservation value that are significant in a broader biogeographical context but yet placed in the finer, more practical, political context of decision making. We analysed spatial patterns of diversity in six arthropod taxa from the Turkish fauna as a regional case study relevant to global conservation of the Mediterranean basin. Although we found high congruence in cross-taxon comparisons of species richness (0.241<r<0.645), hotspots of different groups show limited overlap, generally less than 50 per cent. The ability of a given taxon to capture diversity of other taxa was usually modest (on average, 50 percent of diversity of non-target taxa), limiting the use of hotspots for effective conservation of non-target groups. Nevertheless, our study demonstrates that a given group may partially stand in for another with similar ecological needs and biogeographical histories. We therefore advocate the use of multiple sets of taxa, chosen so as to be representative of animals with different ecological needs and biogeographical histories

    Ecological Thresholds in the Savanna Landscape: Developing a Protocol for Monitoring the Change in Composition and Utilisation of Large Trees

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    BACKGROUND: Acquiring greater understanding of the factors causing changes in vegetation structure -- particularly with the potential to cause regime shifts -- is important in adaptively managed conservation areas. Large trees (> or =5 m in height) play an important ecosystem function, and are associated with a stable ecological state in the African savanna. There is concern that large tree densities are declining in a number of protected areas, including the Kruger National Park, South Africa. In this paper the results of a field study designed to monitor change in a savanna system are presented and discussed. METHODOLOGY/PRINCIPAL FINDINGS: Developing the first phase of a monitoring protocol to measure the change in tree species composition, density and size distribution, whilst also identifying factors driving change. A central issue is the discrete spatial distribution of large trees in the landscape, making point sampling approaches relatively ineffective. Accordingly, fourteen 10 m wide transects were aligned perpendicular to large rivers (3.0-6.6 km in length) and eight transects were located at fixed-point photographic locations (1.0-1.6 km in length). Using accumulation curves, we established that the majority of tree species were sampled within 3 km. Furthermore, the key ecological drivers (e.g. fire, herbivory, drought and disease) which influence large tree use and impact were also recorded within 3 km. CONCLUSIONS/SIGNIFICANCE: The technique presented provides an effective method for monitoring changes in large tree abundance, size distribution and use by the main ecological drivers across the savanna landscape. However, the monitoring of rare tree species would require individual marking approaches due to their low densities and specific habitat requirements. Repeat sampling intervals would vary depending on the factor of concern and proposed management mitigation. Once a monitoring protocol has been identified and evaluated, the next stage is to integrate that protocol into a decision-making system, which highlights potential leading indicators of change. Frequent monitoring would be required to establish the rate and direction of change. This approach may be useful in generating monitoring protocols for other dynamic systems

    Wind Power Persistence Characterized by Superstatistics

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    Mitigating climate change demands a transition towards renewable electricity generation, with wind power being a particularly promising technology. Long periods either of high or of low wind therefore essentially define the necessary amount of storage to balance the power system. While the general statistics of wind velocities have been studied extensively, persistence (waiting) time statistics of wind is far from well understood. Here, we investigate the statistics of both high- and low-wind persistence. We find heavy tails and explain them as a superposition of different wind conditions, requiring q-exponential distributions instead of exponential distributions. Persistent wind conditions are not necessarily caused by stationary atmospheric circulation patterns nor by recurring individual weather types but may emerge as a combination of multiple weather types and circulation patterns. This also leads to Fréchet instead of Gumbel extreme value statistics. Understanding wind persistence statistically and synoptically may help to ensure a reliable and economically feasible future energy system, which uses a high share of wind generation
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