Title :
Bioclimatic limitations on global forests as measured by a fused remote sensing-climate approach
Author :
Greenberg, Jonathan ; Santos, Maria J. ; Dobrowski, Solomon ; Ustin, Susan
Author_Institution :
Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
Underlying many studies on climate change impacts on vegetation is the often untested assumption that climate is correlated with ecosystem distributions and processes (see Nemani, others). Furthermore, there has been a strong reliance on central tendency based, correlative models in examining the relationships between ecological distributions and processes and climate predictors. The models are then applied to future climate scenarios, yielding predictions of future ecological distributions and processes. While interesting approaches they are also deemed with prediction error and uncertainty. Many of these research lines ignore basic ecological knowledge of non-climate factors known to influence the distribution of plants. Largely, we would presume, because these factors are significantly more difficult to derive at large scales than climate data which is widely available. These approaches also fail to recognize the principle of limiting factors.
Keywords :
remote sensing; vegetation; bioclimatic limitations; climate change; climate predictors; correlative models; ecological distributions; ecological processes; ecosystem distributions; ecosystem processes; fused remote sensing-climate approach; global forests; nonclimate factors; plant distribution;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6351343