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Patterns and controls of above‐ground net primary production in meadows of Patagonia. A remote sensing approach
Author(s) -
Irisarri J. Gonzalo N.,
Oesterheld Martín,
Paruelo José M.,
Texeira Marcos A.
Publication year - 2012
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/j.1654-1103.2011.01326.x
Subject(s) - primary production , steppe , environmental science , arid , grassland , latitude , physical geography , vegetation (pathology) , longitude , aridity index , precipitation , remote sensing , atmospheric sciences , geography , ecology , ecosystem , meteorology , geology , medicine , archaeology , geodesy , pathology , biology
Abstract Questions: (1) Can above‐ground net primary production ( ANPP ) of Patagonian meadows be estimated from remote sensing? (2) How does ANPP of Patagonian meadows change in space and time? Location: Northwestern Patagonia, meadows embedded in a steppe matrix (39–43°S, 70–72ºW; area: 85 000 km 2 ). Methods: For the first question, we contrasted field ANPP measurements with MODIS high‐spatial resolution (pixel size: 0.0625 km 2 ) data and developed a model that estimates radiation use efficiency. For the second question, we applied the model to a 6‐year MODIS record for 14 meadows whose physiognomic heterogeneity was known from previous work. Results: Up to 77% of the field‐based ANPP variation was accounted for by the absorbed photosynthetic radiation, based on a linear transformation of the normalized difference vegetation index derived from MODIS data. Mean radiation use efficiency was 0.54 g dry matter MJ −1 . ANPP ranged between 610 and 1060 g m −2 year −1 , which represents three to 5.3 times the ANPP of the surrounding arid and semi‐arid steppes. The inter‐annual coefficient of variation of ANPP was 10%, which is higher than other systems of similar productivity, but much lower than the surrounding steppes (33%). At the level of management units (paddock), ANPP spatial variations were mainly related to the proportion of Prairies, a proxy for low topographic position in the landscape, and longitude, a proxy for precipitation. ANPP inter‐annual variation was most related to latitude, a proxy for temperature. Conclusion: The model developed and tested can be used to infer ANPP from remote sensing data at a spatial resolution that allows one to detect variability within meadows and management units. Variations at both the physiognomic unit and paddock level were associated with geographic patterns and topography. Meadows were three to five times more productive and less fluctuating than nearby steppes. When compared with other ecosystems, their productivity was high, but more variable inter‐annually, likely due to exceptionally high variability of precipitation in Patagonia.