Abstract
Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR-based GIMMS-NDVI version G (GIMMSg) series, and its recent successor version 3g (GIMMS3g), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT-VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMSg), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMSg, particularly in Eurasia where greening is especially pronounced in the GIMMS3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem-response to climate change using satellite-derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas.
Highlights
The primary productivity of vegetation sets the baseline for the terrestrial carbon sink, transferring carbon from the atmosphere to the biosphere, and is critical to understanding the extent and implications of climate change (Goodale et al, 2002; Pan et al, 2011)
We found that GIMMS-normalized difference vegetation index (NDVI) version G (GIMMSg) NDVI consistently ranked years more to that of Moderate Resolution Imaging Spectroradiometer (MODIS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and Satellite Pour l’Observation de la Terre (SPOT) than did GIMMS3g (Fig. 6c)
We observed a large difference between the GIMMSg and GIMMS3g data sets, both in the magnitude of NDVI as well as in the direction of growing season NDVI (GS-NDVI) trends, and found it was necessary to provide a comprehensive comparison with the modern, higher quality NDVI data sets derived from the MODIS, SeaWiFS, and SPOT sensors
Summary
The primary productivity of vegetation sets the baseline for the terrestrial carbon sink, transferring carbon from the atmosphere to the biosphere, and is critical to understanding the extent and implications of climate change (Goodale et al, 2002; Pan et al, 2011). At the southern extent of the boreal forest, future climates are increasingly likely to exceed drought tolerances of extant tree species, which combined with altered disturbance regimes, will likely cause losses in ecosystem carbon stocks (Koven, 2013), while changing albedo dynamics associated with deciduous, rather than evergreen, species dominance (Rogers et al, 2013). To anticipate such biome-level shifts, it is critical that ongoing changes in vegetation productivity can be accurately monitored at local to global scales
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