Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices

Levin, Noam, Shmida, Avi, Levanoni, Oded, Tamari, Hagit and Kark, Salit (2007) Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices. Diversity and Distributions, 13 6: 692-703. doi:10.1111/j.1472-4642.2007.00372.x

Author Levin, Noam
Shmida, Avi
Levanoni, Oded
Tamari, Hagit
Kark, Salit
Title Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices
Journal name Diversity and Distributions   Check publisher's open access policy
ISSN 1366-9516
Publication date 2007
Sub-type Article (original research)
DOI 10.1111/j.1472-4642.2007.00372.x
Volume 13
Issue 6
Start page 692
End page 703
Total pages 12
Editor D. M. Richardson
Place of publication Oxford, United Kingdom
Publisher Wiley-Blackwell Publishing
Collection year 2008
Language eng
Subject C1
279999 Biological Sciences not elsewhere classified
780105 Biological sciences
Abstract Can species richness and rarity be predicted from space? If satellite-derived vegetation indices can provide us with accurate predictions of richness and rarity in an area, they can serve as an excellent tool in diversity and conservation research, especially in inaccessible areas. The increasing availability of high-resolution satellite images is enabling us to study this question more carefully. We sampled plant richness and rarity in 34 quadrats ( 1000 m(2)) along an elevation gradient between 300 and 2200 m focusing on Mount Hermon as a case study. We then used 10 Landsat, Aster, and QuickBird satellite images ranging over several seasons, going up to very high resolutions, to examine the relationship between plant richness, rarity, and vegetation indices calculated from the images. We used the normalized difference vegetation index ( NDVI), one of the most commonly used vegetation indexes, which is strongly correlated to primary production both globally and locally ( in more seasonal and in drier and/or colder environments that have wide ranges of NDVI values). All images showed a positive significant correlation between NDVI and both plant species richness and percentage tree cover ( with R-2 as high as 0.87 between NDVI and total plant richness and 0.89 for annual plant richness). The high resolution images enabled us to examine spatial heterogeneity in NDVI within our quadrats. Plant richness was significantly correlated with the standard deviation of NDVI values ( but not with their coefficient of variation) within quadrats and between images. Contrary to richness, relative range size rarity was negatively correlated with NDVI in all images, this result being significant in most cases. Thus, given that they are validated by fieldwork, satellite-derived indices can shed light on richness and even rarity patterns in mountains, many of which are important biodiversity centres.
Keyword Biodiversity Conservation
remote sensing
Ant Species Richness
Tropical Dry Forests
Elevational Gradients
Biodiversity Hotspots
Conservation Priorities
Semiarid Environments
Altitudinal Gradient
Landsat Data
Q-Index Code C1
Q-Index Status Confirmed Code

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2008 Higher Education Research Data Collection
School of Biological Sciences Publications
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Citation counts: TR Web of Science Citation Count  Cited 67 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 87 times in Scopus Article | Citations
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Created: Mon, 18 Feb 2008, 15:25:56 EST