Literature DB >> 20426333

The contribution of brown vegetation to vegetation dynamics.

Gregory S Okin1.   

Abstract

Indices of vegetation dynamics that include both green vegetation (GV) and non-photosynthetic vegetation (NPV), that is, brown vegetation, were applied to MODIS surface reflectance data from 2000 to 2006 for the southwestern United States. These indices reveal that the cover of NPV, a measure of vegetation brownness and a component of ecosystems worldwide, is highly variable in both space and time in the study region. In the more mesic regions of the study area, the timing of peaks in NPV appears to result from simple senescence of GV at the end of the growing season. In these regions, the amplitude of GV cyclicity dominates the total vegetation signal. In contrast, in arid and semiarid regions, the amplitude of cyclicity of NPV dominates the total vegetation signal, showing the vegetation of these regions to be unexpectedly dynamic. Shrublands of southwestern United States exhibit temporal behavior in which the annual peak in NPV cover precedes the annual peak in GV cover by a few months. Several explanations for this behavior are offered. This study shows the importance of vegetation indices that include NPV, or vegetation brownness, in understanding terrestrial ecosystem dynamics, as well as the response to change for these ecosystems.

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Year:  2010        PMID: 20426333     DOI: 10.1890/09-0302.1

Source DB:  PubMed          Journal:  Ecology        ISSN: 0012-9658            Impact factor:   5.499


  3 in total

1.  Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery.

Authors:  Katja Berger; Tobias Hank; Andrej Halabuk; Juan Pablo Rivera-Caicedo; Matthias Wocher; Matej Mojses; Katarina Gerhátová; Giulia Tagliabue; Miguel Morata Dolz; Ana Belen Pascual Venteo; Jochem Verrelst
Journal:  Remote Sens (Basel)       Date:  2021-11-21       Impact factor: 5.349

2.  Seasonal dynamics of threshold friction velocity and dust emission in Central Asia.

Authors:  Xin Xi; Irina N Sokolik
Journal:  J Geophys Res Atmos       Date:  2015-02-21       Impact factor: 4.261

3.  Modified shape index for object-based random forest image classification of agricultural systems using airborne hyperspectral datasets.

Authors:  Eric Ariel L Salas; Sakthi Kumaran Subburayalu
Journal:  PLoS One       Date:  2019-03-07       Impact factor: 3.240

  3 in total

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