1. Spatial and temporal patterns of herbaceous primary production in semi‐arid shrublands: a remote sensing approach
- Author
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Lisandro J. Blanco, Fernando Biurrun, José M. Paruelo, and Martín Oesterheld
- Subjects
0106 biological sciences ,Above-ground net primary production ,010504 meteorology & atmospheric sciences ,Growing season ,Plant Science ,010603 evolutionary biology ,01 natural sciences ,Normalized Difference Vegetation Index ,Shrubland ,Ciencias Biológicas ,Woody vegetation ,Normalized difference vegetationindex ,Grasses ,Ciencias de las Plantas, Botánica ,0105 earth and related environmental sciences ,Remote sensing ,geography ,geography.geographical_feature_category ,Ecology ,Primary production ,Herbaceous plant ,Native plant ,Arid ,Shrublands ,Environmental science ,CIENCIAS NATURALES Y EXACTAS ,Woody plant - Abstract
Questions: Can herbaceous above-ground net primary production (ANPP) be estimated from remote sensing when woody and herbaceous plants are intermingled? How does herbaceous ANPP change in space and time in an ecosystem dominated by woody species? What are the main controls of herbaceous ANPP to paddock scale?. Location: Native plant communities and buffelgrass roller chopped pastures of the Arid Chaco, western Argentina (28–32° S, 64–67° W; area: 100 000 km2). Methods: We decomposed normalized difference vegetation index (NDVI) data from MODIS (pixel size: 250 m × 250 m) into woody (W) and herbaceous (H) components. We calibrated the relationship between field estimates of herbaceous ANPP and the H component of NDVI using linear regression. The regression model fitted was applied to a 10-yr MODIS database for four paddocks to estimate herbaceous ANPP. We analysed the relationship between herbaceous ANPP and watering point distance and growing season precipitation. Results: The annual integral of NDVI × proportion of the herbaceous component [H/(H + W)] explained 71% and 91% of herbaceous ANPP variation in native plant communities and buffelgrass roller chopped pastures, respectively. The regression model fitted, however, differed (P
- Published
- 2016
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