Dealing with biological complexity in Population Viability Analysis
(2012)
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Details
- Authors
- Supervisors
- Schtickzelle, Nicolas
- Abstract
- (en) Conservation biology, the science aiming at the preservation of biodiversity on Earth, uses tools and models to forecast the fate of threatened species. Being a “crisis discipline”, it must often provide management guidelines despite incomplete evidence and constant threat of species extinctions. One of the priorities of quantitative conservation biologists is to find the balance between the investment (time, money and manpower) in model development and the reliability of its predictions. This PhD thesis focussed on Population Viability Analysis (PVA) models of two threatened butterfly species: Boloria eunomia and Maculinea alcon, with a simple and a more complex life cycle, respectively. I developed a series of PVA models differing in their complexity and compared them in terms of cost/benefit ratio. Firstly, in a series of laboratory and field experiments I estimated the vital rates of B. eunomia and used them to predict the overall population fate with a simple matrix model. Next, I compared four individual-based PVA models (IBM), differing in environmental factors affecting the survival of B. eunomia, in their ability to reproduce a series of empirical patterns. I then contrasted the best IBM with its more aggregated counterpart, a yearly stage-based model, showing the latter is sufficient for ranking climate change scenarios, whereas the daily IBM can be used for asking some more specific questions about population functioning. Finally, I developed a spatially and financially explicit stage-based PVA model for M. alcon and used it to find the most cost-effective management scenario. This thesis concludes that there is no a-priori and predefined answer as to which model complexity is the most suitable in each specific situation. Furthermore, developing a set of different models rather than using a single one brings a deeper and more complete understanding of the natural system.
- Affiliations
UCLouvain SST/ELI/ELIB - Biodiversity
Citations
Radchuk, V. (2012). Dealing with biological complexity in Population Viability Analysis. https://hdl.handle.net/2078.5/160436