Influence of land-use types and climatic variables on seasonal patterns of NDVI in Mediterranean Iberian ecosystems.

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.

[1]  A. Strahler,et al.  Climate controls on vegetation phenological patterns in northern mid‐ and high latitudes inferred from MODIS data , 2004 .

[2]  Douglas C. Morton,et al.  Assessment of deforestation in near real time over the Brazilian Amazon using multitemporal fraction images derived from Terra MODIS , 2005, IEEE Geoscience and Remote Sensing Letters.

[3]  N. Stenseth,et al.  Scale‐dependent effects of grazing on rangeland degradation in northern Kenya: a test of equilibrium and non‐equilibrium hypotheses , 2003 .

[4]  F. Maselli Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data , 2004 .

[5]  Ferenc Kovács,et al.  Assessment of Regional Variations in Biomass Production Using Satellite Image Analysis between 1992 and 2004 , 2007, Trans. GIS.

[6]  Samuel N. Goward,et al.  Transient Effects of Climate on Vegetation Dynamics: Satellite Observations , 1995 .

[7]  P. Newton,et al.  Reduced water repellency of a grassland soil under elevated atmospheric CO2 , 2004 .

[8]  Tal Svoray,et al.  The use of remote sensing and GIS for spatio-temporal analysis of the physiological state of a semi-arid forest with respect to drought years , 2005 .

[9]  Ramakrishna R. Nemani,et al.  Real-time monitoring and short-term forecasting of land surface phenology , 2006 .

[10]  N. Pettorelli,et al.  Using the satellite-derived NDVI to assess ecological responses to environmental change. , 2005, Trends in ecology & evolution.

[11]  P. Maisongrande,et al.  Woody plant richness and NDVI response to drought events in Catalonian (northeastern Spain) forests. , 2007, Ecology.

[12]  Jennifer Small,et al.  Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa , 2007 .

[13]  W. May,et al.  Changes in the mean and extremes of the hydrological cycle in Europe under enhanced greenhouse gas conditions in a global time-slice experiment , 2002 .

[14]  T. Tadesse,et al.  A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains , 2005 .

[15]  C. Peng,et al.  Interannual variability in net primary production and precipitation. , 2001, Science.

[16]  A. Huete,et al.  A review of vegetation indices , 1995 .

[17]  Rosa Lasaponara,et al.  Quantifying intra-annual persistent behaviour in SPOT-VEGETATION NDVI data for Mediterranean ecosystems of southern Italy , 2006 .

[18]  P. S. Roy,et al.  Forest cover assessment in north-east India--the potential of temporal wide swath satellite sensor data (IRS-1C WiFS) , 2002 .

[19]  W. Bausch Soil background effects on reflectance-based crop coefficients for corn☆ , 1993 .

[20]  A. Kirmer,et al.  Spontaneous and initiated succession on unvegetated slopes in the abandoned lignite‐mining area of Goitsche, Germany , 2001 .

[21]  P. Camberlin,et al.  Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa , 2007 .

[22]  J. J. Camarero,et al.  The uncoupling of secondary growth, cone and litter production by intradecadal climatic variability in a mediterranean scots pine forest , 2007 .

[23]  J. Schaber,et al.  Responses of spring phenology to climate change , 2004 .

[24]  S. Bartsev,et al.  The analysis of seasonal activity of photosynthesis and efficiency of various vegetative communities on a basis NDVI for modeling of biosphere processes , 2007 .

[25]  Ramakrishna R. Nemani,et al.  A remote sensing based vegetation classification logic for global land cover analysis , 1995 .

[26]  Shilong Piao,et al.  NDVI-based increase in growth of temperate grasslands and its responses to climate changes in China , 2006 .

[27]  Kevin P. Price,et al.  Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains , 2001 .

[28]  C. Tucker,et al.  Recent trends in vegetation dynamics in the African Sahel and their relationship to climate , 2005 .

[29]  D. Hoare,et al.  Phenological description of natural vegetation in southern Africa using remotely-sensed vegetation data , 2004 .

[30]  Josep Peñuelas,et al.  Complex spatiotemporal phenological shifts as a response to rainfall changes. , 2004, The New phytologist.