Can we predict butterfly diversity along an elevation gradient from space?

Can we predict butterfly diversity along an elevation gradient from space?

An important challenge in ecology is to predict patterns of biodiversity across eco-geographical gradients. This is particularly relevant in areas that are inaccessible, but are of high research and conservation value, such as mountains. Potentially, remotely-sensed vegetation indices derived from s...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:Ecography. - Nordic Society Oikos, 1992. - 34(2011), 3, Seite 372-383
1. Verfasser: Levanoni, Oded (VerfasserIn)
Weitere Verfasser: Levin, Noam, Pe'er, Guy, Turbé, Anne, Kark, Salit
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2011
Zugriff auf das übergeordnete Werk:Ecography
Schlagworte:Biological sciences Physical sciences Business Applied sciences
LEADER 01000caa a22002652 4500
001 JST124902081
003 DE-627
005 20240625082520.0
007 cr uuu---uuuuu
008 190103s2011 xx |||||o 00| ||eng c
035 |a (DE-627)JST124902081 
035 |a (JST)41239378 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Levanoni, Oded  |e verfasserin  |4 aut 
245 1 0 |a Can we predict butterfly diversity along an elevation gradient from space? 
264 1 |c 2011 
336 |a Text  |b txt  |2 rdacontent 
337 |a Computermedien  |b c  |2 rdamedia 
338 |a Online-Ressource  |b cr  |2 rdacarrier 
520 |a An important challenge in ecology is to predict patterns of biodiversity across eco-geographical gradients. This is particularly relevant in areas that are inaccessible, but are of high research and conservation value, such as mountains. Potentially, remotely-sensed vegetation indices derived from satellite images can help in predicting species diversity in vast and remote areas via their relationship with two of the major factors that are known to affect biodiversity: productivity and spatial heterogeneity in productivity. Here, we examined whether the Normalized Difference Vegetation Index (NDVI) can be used effectively to predict changes in butterfly richness, range size rarity and beta diversity along an elevation gradient. We examined the relationship between butterfly diversity and both the mean NDVI within elevation belts (a surrogate of productivity) and the variability in NDVI within and among elevation belts (surrogates for spatial heterogeneity in productivity). We calculated NDVI at three spatial extents, using a high spatial resolution QuickBird satellite image. We obtained data on butterfly richness, rarity and beta diversity by field sampling 100 m quadrats and transects between 500 and 2200 m in Mt Hermon, Israel. We found that the variability in NDVI, as measured both within and among adjacent elevation belts, was strongly and significantly correlated with butterfly richness. Butterfly range size rarity was strongly correlated with the mean and the standard deviation of NDVI within belts. In our system it appears that it is spatial heterogeneity in productivity rather than productivity per se that explained butterfly richness. These results suggest that remotely-sensed data can provide a useful tool for assessing spatial patterns of butterfly richness in inaccessible areas. The results further indicate the importance of considering spatial heterogeneity in productivity along elevation gradients, which has no lesser importance than productivity in shaping richness and rarity, especially at the local scale. 
540 |a Copyright © 2011 Ecography 
650 4 |a Biological sciences  |x Biology  |x Zoology  |x Animals  |x Invertebrates  |x Arthropods  |x Insects  |x Butterflies 
650 4 |a Biological sciences  |x Biology  |x Biological taxonomies  |x Species 
650 4 |a Physical sciences  |x Earth sciences  |x Geography  |x Geomorphology  |x Topography  |x Topographical elevation 
650 4 |a Business  |x Business economics  |x Commercial production  |x Productivity 
650 4 |a Biological sciences  |x Ecology  |x Plant ecology  |x Vegetation 
650 4 |a Biological sciences  |x Biology  |x Botany  |x Plants 
650 4 |a Applied sciences  |x Research methods  |x Vegetation index 
650 4 |a Biological sciences  |x Biology  |x Conservation biology  |x Biodiversity conservation 
650 4 |a Biological sciences  |x Biology  |x Conservation biology  |x Environmental conservation 
650 4 |a Biological sciences  |x Ecology  |x Population ecology  |x Synecology  |x Biodiversity  |x Plant biodiversity 
655 4 |a research-article 
700 1 |a Levin, Noam  |e verfasserin  |4 aut 
700 1 |a Pe'er, Guy  |e verfasserin  |4 aut 
700 1 |a Turbé, Anne  |e verfasserin  |4 aut 
700 1 |a Kark, Salit  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Ecography  |d Nordic Society Oikos, 1992  |g 34(2011), 3, Seite 372-383  |w (DE-627)320639789  |w (DE-600)2024917-2  |x 16000587  |7 nnns 
773 1 8 |g volume:34  |g year:2011  |g number:3  |g pages:372-383 
856 4 0 |u http://dx.doi.org/10.1111/j.1600-0587.2010.06460.x  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_JST 
912 |a GBV_ILN_11 
912 |a GBV_ILN_20 
912 |a GBV_ILN_22 
912 |a GBV_ILN_23 
912 |a GBV_ILN_24 
912 |a GBV_ILN_31 
912 |a GBV_ILN_32 
912 |a GBV_ILN_39 
912 |a GBV_ILN_40 
912 |a GBV_ILN_60 
912 |a GBV_ILN_62 
912 |a GBV_ILN_63 
912 |a GBV_ILN_69 
912 |a GBV_ILN_70 
912 |a GBV_ILN_73 
912 |a GBV_ILN_74 
912 |a GBV_ILN_90 
912 |a GBV_ILN_95 
912 |a GBV_ILN_100 
912 |a GBV_ILN_101 
912 |a GBV_ILN_105 
912 |a GBV_ILN_110 
912 |a GBV_ILN_120 
912 |a GBV_ILN_138 
912 |a GBV_ILN_150 
912 |a GBV_ILN_151 
912 |a GBV_ILN_161 
912 |a GBV_ILN_165 
912 |a GBV_ILN_170 
912 |a GBV_ILN_171 
912 |a GBV_ILN_187 
912 |a GBV_ILN_213 
912 |a GBV_ILN_224 
912 |a GBV_ILN_230 
912 |a GBV_ILN_266 
912 |a GBV_ILN_285 
912 |a GBV_ILN_293 
912 |a GBV_ILN_370 
912 |a GBV_ILN_374 
912 |a GBV_ILN_602 
912 |a GBV_ILN_636 
912 |a GBV_ILN_702 
912 |a GBV_ILN_2001 
912 |a GBV_ILN_2003 
912 |a GBV_ILN_2004 
912 |a GBV_ILN_2005 
912 |a GBV_ILN_2006 
912 |a GBV_ILN_2007 
912 |a GBV_ILN_2008 
912 |a GBV_ILN_2009 
912 |a GBV_ILN_2010 
912 |a GBV_ILN_2011 
912 |a GBV_ILN_2014 
912 |a GBV_ILN_2015 
912 |a GBV_ILN_2018 
912 |a GBV_ILN_2020 
912 |a GBV_ILN_2021 
912 |a GBV_ILN_2025 
912 |a GBV_ILN_2026 
912 |a GBV_ILN_2027 
912 |a GBV_ILN_2034 
912 |a GBV_ILN_2037 
912 |a GBV_ILN_2038 
912 |a GBV_ILN_2044 
912 |a GBV_ILN_2048 
912 |a GBV_ILN_2049 
912 |a GBV_ILN_2050 
912 |a GBV_ILN_2055 
912 |a GBV_ILN_2056 
912 |a GBV_ILN_2057 
912 |a GBV_ILN_2059 
912 |a GBV_ILN_2061 
912 |a GBV_ILN_2064 
912 |a GBV_ILN_2068 
912 |a GBV_ILN_2088 
912 |a GBV_ILN_2093 
912 |a GBV_ILN_2106 
912 |a GBV_ILN_2107 
912 |a GBV_ILN_2108 
912 |a GBV_ILN_2110 
912 |a GBV_ILN_2111 
912 |a GBV_ILN_2118 
912 |a GBV_ILN_2122 
912 |a GBV_ILN_2129 
912 |a GBV_ILN_2143 
912 |a GBV_ILN_2144 
912 |a GBV_ILN_2147 
912 |a GBV_ILN_2148 
912 |a GBV_ILN_2152 
912 |a GBV_ILN_2153 
912 |a GBV_ILN_2190 
912 |a GBV_ILN_2232 
912 |a GBV_ILN_2336 
912 |a GBV_ILN_2360 
912 |a GBV_ILN_2470 
912 |a GBV_ILN_2472 
912 |a GBV_ILN_2507 
912 |a GBV_ILN_2522 
912 |a GBV_ILN_2548 
912 |a GBV_ILN_2939 
912 |a GBV_ILN_2946 
912 |a GBV_ILN_2949 
912 |a GBV_ILN_2951 
912 |a GBV_ILN_4012 
912 |a GBV_ILN_4035 
912 |a GBV_ILN_4037 
912 |a GBV_ILN_4046 
912 |a GBV_ILN_4112 
912 |a GBV_ILN_4125 
912 |a GBV_ILN_4126 
912 |a GBV_ILN_4242 
912 |a GBV_ILN_4246 
912 |a GBV_ILN_4249 
912 |a GBV_ILN_4251 
912 |a GBV_ILN_4305 
912 |a GBV_ILN_4306 
912 |a GBV_ILN_4307 
912 |a GBV_ILN_4313 
912 |a GBV_ILN_4322 
912 |a GBV_ILN_4323 
912 |a GBV_ILN_4324 
912 |a GBV_ILN_4325 
912 |a GBV_ILN_4326 
912 |a GBV_ILN_4333 
912 |a GBV_ILN_4334 
912 |a GBV_ILN_4335 
912 |a GBV_ILN_4336 
912 |a GBV_ILN_4338 
912 |a GBV_ILN_4346 
912 |a GBV_ILN_4393 
912 |a GBV_ILN_4700 
951 |a AR 
952 |d 34  |j 2011  |e 3  |h 372-383