Land‐cover change and vegetation dynamics across Africa

Using improved metrics and recently available MODerate resolution Imaging Spectrometer (MODIS) data, we examined the magnitude, extent, and nature of changes in photosynthetic activity and its timing across Sub-Saharan Africa. Changes in overall vegetation activity and shifts in its timing have considerable implications for a variety of processes including surface-atmosphere energy exchanges, terrestrial sources and sinks of carbon, the contribution of local evapotranspiration to the water cycle, disturbance regimes such as fires and pests, and the food security of societies using these ecosystems. While previous studies have examined broad-scale trends in phenology or provided more detailed estimates of land-cover conversion in the tropics, less is known of the year-to-year dynamics of vegetation. Here we quantified the overall changes in vegetation activity for each year between 2000 and 2004 and examined the proportion linked to differences in phenology and overall photosynthetic activity. In addition, we examined the nature of these changes in terms of frequency and duration, the proportion per ecosystem, identified areas of intensive change, and discuss the potential consequences of these changes. We found that most interannual change was not from shifts in timing or phenology, but rather largely due to differences in the amount of annual photosynthetic activity. In fact, there was as much as a 5% annual difference in vegetation activity across the continent. The changes were likely climate driven with particular vegetation types most susceptible to interannual change with high spatial and temporal variability found across the continent.

[1]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

[2]  J. Lovell,et al.  Filtering Pathfinder AVHRR Land NDVI data for Australia , 2001 .

[3]  Rasmus Houborg,et al.  Regional simulation of ecosystem CO2 and water vapor exchange for agricultural land using NOAA AVHRR and Terra MODIS satellite data - application to Zealand, Denmark , 2004 .

[4]  Compton J. Tucker,et al.  From El Niño to La Niña: Vegetation Response Patterns over East and Southern Africa during the 1997-2000 Period. , 2002 .

[5]  S. Schneider,et al.  Fingerprints of global warming on wild animals and plants , 2003, Nature.

[6]  Rasim Latifovic,et al.  Can interannual land surface signal be discerned in composite AVHRR data , 1998 .

[7]  Alan H. Strahler,et al.  An algorithm for the retrieval of albedo from space using semiempirical BRDF models , 2000, IEEE Trans. Geosci. Remote. Sens..

[8]  Ranga B. Myneni,et al.  Satellite‐based identification of linked vegetation index and sea surface temperature Anomaly areas from 1982–1990 for Africa, Australia and South America , 1996 .

[9]  Pieter P. Tans,et al.  Evidence for interannual variability of the carbon cycle from the National Oceanic and Atmospheric Administration/Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network , 1994 .

[10]  C. Woodcock,et al.  Consistency of MODIS surface bidirectional reflectance distribution function and albedo retrievals: 2. Validation , 2003 .

[11]  S. Frolking,et al.  Sensitivity of vegetation indices to atmospheric aerosols: Continental-scale observations in Northern Asia , 2003 .

[12]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[13]  Compton J. Tucker,et al.  AVHRR data sets for determination of desert spatial extent , 1994 .

[14]  Felix Kogan,et al.  Satellite-Observed Sensitivity of World Land Ecosystems to El Niño/La Niña , 2000 .

[15]  Eric F. Lambin,et al.  Land-cover changes in sub-saharan Africa (1982–1991): Application of a change index based on remotely sensed surface temperature and vegetation indices at a continental scale , 1997 .

[16]  R. Boone,et al.  Impacts of climate variability on East African pastoralists: linking social science and remote sensing , 2001 .

[17]  Garik Gutman,et al.  Normalization of multi-annual global AVHRR reflectance data over land surfaces to common sun-target-sensor geometry , 1994 .

[18]  Randal D. Koster,et al.  Influence of the Interannual Variability of Vegetation on the Surface Energy Balance—A Global Sensitivity Study , 2002 .

[19]  S. Running,et al.  Satellite Evidence of Phenological Differences Between Urbanized and Rural Areas of the Eastern United States Deciduous Broadleaf Forest , 2002, Ecosystems.

[20]  Garik Gutman,et al.  On the use of long‐term global data of land reflectances and vegetation indices derived from the advanced very high resolution radiometer , 1999 .

[21]  Alan H. Strahler,et al.  Using a multikernel least-variance approach to retrieve and evaluate albedo from limited bidirectional measurements , 2001 .

[22]  J. Privette,et al.  Early spatial and temporal validation of MODIS LAI product in the Southern Africa Kalahari , 2002 .

[23]  Ramakrishna R. Nemani,et al.  Sensitivity of a general circulation model to global changes in leaf area index , 1996 .

[24]  E. Lambin,et al.  Impact of ENSO on East African ecosystems: a multivariate analysis based on climate and remote sensing data , 2000 .

[25]  Scott J. Goetz,et al.  Interannual variability of global terrestrial primary production: Results of a model driven with satellite observations , 2000 .

[26]  Roger A. Pielke,et al.  Interactions between the atmosphere and terrestrial ecosystems: influence on weather and climate , 1998 .

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

[28]  David M. Lawrence,et al.  An annual cycle of vegetation in a GCM. Part II: global impacts on climate and hydrology , 2004 .

[29]  R. Myneni,et al.  The interpretation of spectral vegetation indexes , 1995 .

[30]  David M. Lawrence,et al.  An annual cycle of vegetation in a GCM. Part I: implementation and impact on evaporation , 2004 .

[31]  C. Tucker,et al.  Increased plant growth in the northern high latitudes from 1981 to 1991 , 1997, Nature.

[32]  S. Kalluri,et al.  The Pathfinder AVHRR land data set: An improved coarse resolution data set for terrestrial monitoring , 1994 .

[33]  Alexander Ignatov,et al.  The relative merit of cloud/clear identification in the NOAA/NASA Pathfinder AVHRR Land 10-day composites , 1996 .

[34]  S. Running,et al.  Simulated impacts of historical land cover changes on global climate in northern winter , 2000 .

[35]  C. Tucker,et al.  Interannual variations in satellite-sensed vegetation index data from 1981 to 1991 , 1998 .

[36]  S. Goward,et al.  Evaluation of the NOAA/NASA Pathfinder AVHRR Land Data Set for global primary production , 1995 .

[37]  S. Wofsy,et al.  Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data , 2004 .

[38]  J. Cihlar,et al.  Multitemporal, multichannel AVHRR data sets for land biosphere studies—Artifacts and corrections , 1997 .

[39]  E. Vermote,et al.  Absolute calibration of AVHRR visible and near-infrared channels using ocean and cloud views , 1995 .

[40]  Compton J. Tucker,et al.  Sensitivity of Climate to Changes in NDVI , 2000 .

[41]  Assaf Anyamba,et al.  Comparison of NOAA/NASA PAL and NOAA GVI Data for Vegetation Change Studies over China , 1999 .

[42]  Kevin P. Price,et al.  Relations between NDVI and tree productivity in the central Great Plains , 2004 .

[43]  G. Yohe,et al.  A globally coherent fingerprint of climate change impacts across natural systems , 2003, Nature.

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

[45]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[46]  J. Royer,et al.  Effects of “realistic” land-cover change on a greenhouse-warmed African climate , 2004 .

[47]  D. Roy,et al.  Achieving sub-pixel geolocation accuracy in support of MODIS land science , 2002 .

[48]  Menas Kafatos,et al.  Interannual variability of vegetation over the Indian sub-continent and its relation to the different meteorological parameters , 2004 .

[49]  H. Tian,et al.  Effect of interannual climate variability on carbon storage in Amazonian ecosystems , 1998, Nature.

[50]  C. Justice,et al.  Seasonal to interannual variability of vegetation and fires at SAFARI 2000 sites inferred from advanced very high resolution radiometer time series data , 2003 .

[51]  Alan H. Strahler,et al.  Change-vector analysis in multitemporal space: a tool to detect and categorize land-cover change pro , 1994 .

[52]  S. Prince.  Satellite remote sensing of primary production: comparison of results for Sahelian grasslands 1981-1988 , 1991 .

[53]  C. Justice,et al.  Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation , 1997 .

[54]  F. Achard,et al.  Determination of Deforestation Rates of the World's Humid Tropical Forests , 2002, Science.

[55]  J. Townshend,et al.  Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 1990s , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[56]  J. Canadell,et al.  Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems , 2001, Nature.

[57]  A. Huete,et al.  Optical-Biophysical Relationships of Vegetation Spectra without Background Contamination , 2000 .

[58]  Chester F. Ropelewski,et al.  Quantifying Southern Oscillation-Precipitation Relationships , 1996 .