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Influence of land‐use types and climatic variables on seasonal patterns of NDVI in Mediterranean Iberian ecosystems
Author(s) -
Durante P.,
Oyonarte C.,
Valladares F.
Publication year - 2009
Publication title -
applied vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.096
H-Index - 64
eISSN - 1654-109X
pISSN - 1402-2001
DOI - 10.1111/j.1654-109x.2009.01012.x
Subject(s) - normalized difference vegetation index , ecosystem , precipitation , mediterranean climate , phenology , environmental science , vegetation (pathology) , seasonality , shrubland , physical geography , climatology , climate change , enhanced vegetation index , geography , ecology , vegetation index , meteorology , geology , medicine , archaeology , pathology , biology
Abstract Question: What is the influence of management on the functioning of vegetation over time in Mediterranean ecosystems under different climate conditions? Location: Mediterranean shrublands and forests in SE Iberia (Andalusia). Methods: We evaluated the Normalized Difference Vegetation Index (NDVI) for the 1997‐2002 time series to determine phenological vegetation patterns under different historical management regimes. Three altitudinal ranges were considered within each area to explore climate × management interactions. Each phenological pattern was analysed using time series statistics, together with precipitation (monthly and cumulative) and temperature. Results: NDVI time series were significantly different under different management regimes, particularly in highly transformed areas, which showed the lowest NDVI, weakest annual seasonality and a more immediate phenological response to precipitation. The NDVI relationship with precipitation was strongest in the summer‐autumn period, when precipitation is the main plant growth‐limiting factor. Conclusions: NDVI time series analyses elucidated complex influences of land use and climate on ecosystem functioning in these Mediterranean ecosystems. We demonstrated that NDVI time series analyses are a useful tool for monitoring programmes because of their sensitivity to changes, ease of use and applicability to large‐scale studies.