The title of this blog-post sounds like I want to solve all problems that exist when dealing with “Landscape” in scientific works. In fact this is in some way or the other even the overall or major aim of scientific work. Since I want to answer at least some of the questions that arise when one asks about which role “landscape” plays in understanding ecosystems and since my first scientific work is a meta-analysis about how small mammals depend on landscape composition and fragmentation, I at least want to try to give an overall answer or, more realistically, give hints on how we can find such an answer in this field. Some say that a meta-analyses wants to summarize the current status of a scientific field, but more realistically it will summarize the knowledge of one aspect only, due to the restrictions when calculating the meta-analysis. Thus, this meta-analysis tries to evaluate if it is possible to develop a general model for small mammals and the dependence of their density on landscape parameters.
With this blog-post I want to:
- give some definitions to clarify how I see and work with landscape and
- to show the techniques used to calculate the landscape parameters for the meta-analysis.
Some of the information might change, if we have to adapt something or add or remove some parameters, since they seem to be of importance. A big difference of this meta-analysis to other meta-analyses is, that we calculate a big part of the material we want to evaluate on our own and don’t rely on the reported statistics only. This is mainly due to all the nice fellow researchers which were generous enough to hand over their raw data and will in return participate as co-authors in this work! All landscape parameters are calculated from the corine land cover and the Global Forest Change (GFC) dataset. The corine dataset is provided by the European Environmental Agency and freely available to everybody. The Global Forest Change dataset has been published by Hansen, Potapov, Moore, Hancher et. al (2013) under a CC BY 4.0-license.