Using the satellite-derived NDVI to assess ecological responses to environmental change.

By Nathalie Pettorelli, Jon Olav Vik, A. Mysterud, J. Gaillard, Compton J. Tucker, Nils Chr. Stenseth. Trends in Ecology & Evolution, 2005

3,423 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/9ea494770ed507b7d4a68ab71de663db65101ff4

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Citations in the corpus

Potential of remote sensing to predict species invasions (2015, background): “This is because missing variables, inadequate duration, temporal and spatial gaps and declining coverage are pervasive limitations of field data (Clark et al., 2001; Pettorelli et al., 2005).”
Assessing global patterns in mammalian carnivore occupancy and richness by integrating local camera trap surveys (2017, background): “Carnivores are also known to be positively associated with permanent water sources (Epps, Mutayoba, Gwin, & Brashares, 2011; Schuette, Wagner, Wagner, & Creel, 2013) and with vegetation cover and productivity, probably because of their relationship with prey abundance (Pettorelli et al., 2005).”
Linking variability in species composition and MODIS NDVI based on beta diversity measurements (2009, methodology): “Recently, exploring regional floristic patterns using data derived from satellite imagery, such as the normalized difference vegetation index (NDVI) has drawn considerable research interests among ecologists.”
Linking fluctuations in rainfall to nonbreeding season performance in a long-distance migratory bird, Setophaga ruticilla (2007, background): “Recent advances in the application of remote sensing using the normalized difference vegetation index (NDVI) have broadened the scale and level of resolution with which ecological responses to precipitation can be examined (Pettorelli et al. 2005).”
Shifting plant phenology in response to global change. (2007, background): “Satellite observations are increasingly important for studies of phenological and ecological responses to environmental changes over space and time [ 46 ].”
Using a proxy of plant productivity (NDVI) to find key periods for animal performance: the case of roe deer (2006, positive): “Some imprecision in the exact spatial location of the pixel have been reported before (Pettorelli et al. 2005b), especially at the 1 km scale.”
Spatial and Temporal Variation of NDVI in Response to Climate Change and the Implication for Carbon Dynamics in Nepal (2018, methodology): “The NDVI distribution and trends in different ecological zones indicate a good ecological status with a positive level of photosynthetic activities, biomass, productivity and ecosystem balance [19,23,87,88], as well as a lengthening of the growing season [89–91].”
Spring Normalized Difference Vegetation Index (NDVI) predicts annual variation in timing of peak faecal crude protein in mountain ungulates (2009, background): “1994 and Pettorelli et al. 2005 for more details).”
Partial migration in roe deer: migratory and resident tactics are end points of a behavioural gradient determined by ecological factors (2011, methodology): “For this, the ranges of migrants and non-migrants could be compared for plant productivity in summer using a large scale index, such as NDVI (Pettorelli et al. 2005, Hebblewhite et al. 2008).”
Shrub encroachment and vertebrate diversity: A global meta‐analysis (2018, methodology): “; Pettorelli et al., 2005).”