European Farmland Bird Distribution Explained by Remotely Sensed Phenological Indices |
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Authors: | Eva Ivits Graeme Buchanan Linda Olsvig-Whittaker Michael Cherlet |
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Institution: | (1) Joint Research Centre, Institute for Environment and Sustainability, TP 460, Via E. Fermi 1, 21020 Ispra, Varese, Italy;(2) RSPB, 2 Lochside View, Edinburgh Park, EH12 9DH Edinburgh, UK;(3) Science and Conservation Division, Israel Nature and Parks Authority, 3 Am Ve Olamo Street, Givat Shaul, 95463 Jerusalem, Israel |
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Abstract: | Birds are important components of biodiversity conservation since they are capable of indicating changes in the general status
of wildlife and of the countryside. The Pan-European Common Bird Monitoring Scheme (PECBM) has been launched by the BirdLife
Partnership in Europe, where the European Bird Census Council has been collecting data from 20 independent breeding bird survey
programs across Europe over the last 25 years. These data show dramatic declines in European farmland birds. We suggest that
seasonal characteristics of vegetation cover derived from high temporal resolution remote sensing images could facilitate
the monitoring the suitability of farmland bird habitats, and that these indicators may be a better choice for monitoring
than climate data. We used redundancy analysis to link the PECBM data of the estimated number of farmland birds in Europe
to a set of phenological and climatic indicators and to the biogeographic regions of Europe. Variance partitioning was used
to account for the variation explained by the phenological and climate variables and by the area of the environmental strata
individually, to define the pure effect of the variables, and to extract the total explained variance. The analysis revealed
high statistical significance (p < 0.001) of the correlations between species and environment. Phenological indices explained 38% of the variance in community
composition of the 23 farmland bird species, whereas climate explained 30% of the variance. After partitioning the other variables
as covariables, the pure effect of phenology, climate, and environmental strata were 16%, 8%, and 16%, respectively. Based
on the probability results, we suggest that phenological indicators derived from remote sensing may supply better indicators
for continental scale biodiversity studies than climate only. In addition, these indicators are cost and time effective, are
on continuous scale, and are readily repeatable on a large spatial coverage while supplying standardized results. |
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