Biodiversity assessment at multiple scales: linking remotely sensed data with field information

Nagendra, Harini ; Gadgil, Madhav (1999) Biodiversity assessment at multiple scales: linking remotely sensed data with field information Proceedings of the National Academy of Sciences of the United States of America, 96 (16). pp. 9154-9158. ISSN 0027-8424

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We examine the efficacy of a scheme of multiscale assessment of biodiversity linking remote sensing on larger spatial scales with localized field sampling. A classification of ecological entities from biosphere to individual organisms in the form of a nested hierarchy is employed, such that entities at any level are differentiated in terms of their composition/configuration involving entities at the next lower level. We employ the following hierarchy: biosphere (1014 m2), ecoregions (1011-1012 m2), ecomosaics (108-1010 m2), ecotopes (103-106 m2), and individual organisms (10-4-102 m2). Focusing on a case study of West Cost-Western Ghats ecoregion (1.7 × 1011 m2) from India, we demonstrate that remotely sensed data permit discrimination of 205 patches of 11 types of sufficiently distinctive ecomosaics (108-1010 m2) through unsupervised classification by using distribution parameters of the Normalized Difference Vegetation Index, with a pixel size of (3.24 × 106 m2). At the ecomosaic scale, Indian Remote Sensing LISS-2 satellite data with a pixel size of 103 m2 permit discrimination of ≈30 types of sufficiently distinctive ecotopes on the basis of supervised classification. Field investigations of angiosperm species distributions based on quadrats of 1-102 m2 in one particular landscape of 27.5 × 106 m2 show that the seven ecotope types distinguished in that locality are significantly different from each other in terms of plant species composition. This suggests that we can effectively link localized field investigations of biodiversity with remotely sensed information to permit extrapolations at progressively higher scales.

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Source:Copyright of this article belongs to National Academy of Sciences, USA.
ID Code:10334
Deposited On:04 Nov 2010 06:00
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