|Ph.D Student||Troupin David|
|Subject||Incorporating Dynamic Scenarios of Anthropogenic and|
Natural Land Cover Change Processes into
Systematic Conservation Planning
|Department||Department of Architecture and Town Planning||Supervisor||PROF. Yohay Carmel|
|Full Thesis text|
Protected areas constitute a central tool in the effort to halt the global loss of biodiversity. Systematic conservation planning aims to optimally locate, prioritize, and design conservation area networks, in which biodiversity is well-represented, protected, and sustainable. An often-noted shortcoming of most conservation planning studies is that they do not account for process dynamics or future uncertainty. The goal of my thesis was to develop an approach for selecting protected area networks that will improve biodiversity representation and persistence, by incorporating ecological and anthropogenic processes and future uncertainty. The case-study focused on Israel’s Mediterranean region and its breeding bird species (N=87).
I modeled two major land cover change processes: urban development and vegetation dynamics. I simulated two alternative scenarios for each process 60 years into the future using DINAMICA-EGO, a cellular-automata simulation model. For urban development the regulated and unregulated development scenarios differed in the spatial distribution and rate of development. Compared to regulated development, unregulated development resulted in larger areas of built-up land, distributed over a larger number of smaller patches. The two vegetation dynamics scenarios were moderate climate change (continuation of observed past trends) and severe climate change (altered fire regime and succession patterns). The severe climate change scenario resulted in a more even distribution of the different vegetation formations whereas in the moderate climate change scenario, dense woodlands became the predominant formation over time. The combination of unregulated development and moderate climate change was the least favorable scenario for the study species, resulting in the greatest loss of suitable habitats. Subsequently, for each scenario ran the conservation planning software MARXAN I using the suitable habitat distributions for each species as input in order to identify conservation priority areas for each scenario.
I compared the robustness to future uncertainty of conservation area portfolios constructed using three different approaches: (1) considering the entire range of scenarios (all-scenarios portfolio); (2) considering only specific scenarios; and (3) a reference strategy based only on current distributions (current distributions portfolio). The performance of the conservation area portfolios was assessed by the number of species for which representation targets were met in each scenario. On average, compared with the current distributions portfolio, the all-scenarios portfolio achieved representation targets for five additional species (approximately 33 versus 28 species, respectively). The average difference in the number of represented species between the all-scenarios portfolio and the portfolios that were based on a specific scenario were smaller but consistent - the all-scenarios portfolio was expected to achieve representation targets for 1-3 additional species. The all-scenarios portfolio consistently performed better than the other portfolios, and was more robust to errors - representation targets were met for a larger number of species when an assumed scenario did not occur. These results reveal the limitations of the common practice of conservation planning based on current distributions and land cover, or assuming that the ‘worst-case’ scenario approach will perform well under a wide range of scenarios, and highlight the importance of considering a meaningful and broad range of future scenarios when planning conservation areas.