4 research outputs found

    Can climate data from METEOSAT improve wildlife distribution models?

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    P. 629-636Global climate change generated by human activities is likely to affect agroecosystems in several ways: reinforcing intensification in northern and western Europe, and extensification in the Mediterranean countries. If we are to predict the consequences of global warming for wildlife, distribution models have to include climate data. The METEOSAT temporal series from EWBMS offers an attractive alternative to using climatic surfaces derived from ground stations. The aim of this paper is to test whether this climatic satellite data can improve the distribution models obtained previously by Suárez‐Seoane et al. using habitat variables for three agro‐steppe bird species: great bustard, little bustard and calandra lark in Spain. Rainfall, radiation balance, evapotranspiration and soil moisture images were incorporated together with the other variables used as predictors in the published stepwise GAM models. Changes in the predicted distributions from the habitat only and climate‐habitats models were assessed by reference to the CORINE land cover categories. Inclusion of climatic variables from METEOSAT led to statistically superior models for all three species. There were large differences in the climatic variables selected and the original variables dropped among the species. Evapotranspiration variables were the most frequently selected. Maps of the differences between the habitat and climate‐habitat models showed very different patterns for the three species. Inclusion of climate variables led to a wider range of land cover types being deemed suitable. Despite the statistical superiority of models, care is needed in deciding whether to use climatic variables because they may emphasize the fundamental rather than the realized niche. Used together, however, habitat and climate models can provide new insights into factors limiting species distributions and how they may respond to climate change.S

    Fluorescence explorer (FLEX): An optimised payload to map vegetation photosynthesis from space

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    The FLuorescence EXplorer (FLEX) mission proposes to launch a satellite for the global monitoring of steady-state chlorophyll fluorescence in terrestrial vegetation. Fluorescence is a sensitive probe of photosynthetic function in both healthy and physiologically perturbed vegetation, and a powerful non-invasive tool to track the status, resilience, and recovery of photochemical processes and moreover provides important information on overall photosynthetic performance with implications for related carbon sequestration. The early responsiveness of fluorescence to atmospheric, soil and plant water balance, as well as to atmospheric chemistry and human intervention in land usage makes it an obvious biological indicator in improving our understanding of Earth system dynamics. The amenability of fluorescence to remote, even space-basedobservation qualifies it to join the emerging suite of space-based technologies for Earth observation. FLEX would encompass a three-instrument array for measurement of the interrelated features of fluorescence, hyperspectral reflectance, and canopy temperature. FLEX would involve a space and ground-truthing program of 3-years duration and would provide data formats for research and applied science
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