Conservation strategies are mainly focused on species existing in an environment shaped by natural and anthropogenic pressures. Yet, evidence shows that climate is changing faster than ever and expected to continue to change in the near future, which can be devastating for plants with restricted ranges.
Turkey harbors many endemic species that might be affected from these changes. However, available data is scarce and biased, complicating the anticipation of future changes. Aim of this study is to improve our understanding of endemic species distributions and forecasting effects of climate change via species distribution modelling (SDM).
The study is based on two Anatolian (Crocus ancyrensis and Crataegus tanacetifolia) and two Ankara (Salvia aytachii and Centaurea tchihatcheffii) endemics. Independent presence and absence data (ranging between 19-68 and 38-61, respectively) for each species was collected through fieldwork in and around the Upper Sakarya Basin in 2008 and 2009.
With the software Maxent, SDMs were performed by using 8 least correlated environmental features and random presence records (of which 25% were used for confusion matrix). SDMs for current distributions of C. ancyrensis, C. tchihatcheffii and C. tanacetifolia were reliable enough for future extrapolations despite errors originating from scale, non-equilibrium status and biotic interactions, respectively. The model for S. aytachii failed due to absence of limiting factor (soil type) in the model.
Future projections of those three species modelled using CCCMA-CGCM2 and HADCM3 climate models indicated three possible responses to climate change: (1) Extinction, especially for habitat specialists / (2) Range expansion, especially for generalist species / and (3) Range contradiction, especially for Euro-Siberian mountainous species.
Species modelling can be used to understand possible responses of plant species to climate change in Turkey. Modelling techniques should to be improved, however,
especially by integrating other parameters such as biotic interactions and through a better understanding of uncertainties.
Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613538/index.pdf |
Date | 01 July 2011 |
Creators | Beton, Damla |
Contributors | Bilgin, Cemal Can |
Publisher | METU |
Source Sets | Middle East Technical Univ. |
Language | English |
Detected Language | English |
Type | Ph.D. Thesis |
Format | text/pdf |
Rights | To liberate the content for public access |
Page generated in 0.0122 seconds