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.
|Number of pages
|Published - 2012
|2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany
Duration: Jul 22 2012 → Jul 27 2012
|2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
|07/22/12 → 07/27/12