School of BioSciences - Theses
Permanent URI for this collection
Search Results
1 - 1 of 1
-
ItemAssessing and managing interacting species at risk of coextinction( 2016)Interactions between organisms are ubiquitous: predators hunt prey, plants compete for light, and pollinators visit flowers to forage on nectar. Through their interactions species influence each other's population dynamics and ultimately their persistence: Darwin was already convinced that if bumblebees became extinct their food plants would follow quickly. Despite their importance, interactions are commonly ignored when we assess species' extinction risk or plan for their conservation management. My thesis is divided into six chapters, addressing two important components of conserving interdependent species. First, I assess if and how we can use a common type of data - observed interaction networks - to assess the coextinction risk of interacting species in networks, and to predict how interactions influence cascading extinctions when interdependent species are lost. Secondly, I investigate how interacting species can be protected in combined management approaches, focussing on the increasingly common method of translocating species for conservation. To answer this questions, I develop a range of statistical and mathematical modelling approaches and apply these to theoretical simulations and empirical data. In chapter 2, I investigate how quantitative methods can help to identify those species in interaction networks that are at risk of coextinction, while incorporating important factors such as uncertainty and imperfect detection of species in the field. I develop a hierarchical $N$-mixture model that accounts for imperfect detection and allows one to disentangle two factors that influence interaction frequencies between species: the probability that two species interact, and the abundances of species. This enables one to estimate with uncertainty the number of interaction partners of a species and the community size of dependents. I fit the model to data that from simulations of different parameter scenarios and to empirical networks of flower-visiting insects found on a threatened ecological community of plants from the Stirling Ranges National Park in Western Australia. In chapter 3, I extend this modelling approach to investigate how imperfect detection and uncertainty influence the progression of extinction through mutualistic networks. Therefore, I apply the modelling approach from chapter 2 to observed networks to correct these networks for sampling bias. Then, I sequentially remove plant species from the networks to investigate how extinction cascades differ between observed and corrected networks. I show that networks corrected for sampling bias, are more densely connected and the interactions between species are more diffusely distributed throughout the networks. This causes corrected networks to be less specialised, and plant species to be more redundant, leading to increased network robustness. The results of chapter 2 and 3 indicate that imperfect detection strongly affects observed interaction networks and suggests that it is unwise to draw strong inferences for the conservation status of species and the robustness of ecosystems without acknowledging imperfect detection and uncertainty. In the second part of this thesis, I investigate management actions for improving the persistence of cothreatened interacting species, with a particular focus on conservation translocations. The fourth chapter investigates how useful current single-species translocation guidelines are for conserving cothreatened species and the interactions between them. I first classify potential systems of cothreatened species and devise appropriate management options for each system. Secondly, I extend current single-species guidelines to incorporate interactions in the assessment, planning and implementation phase for the conservation of multiple interacting species. For each phase of a translocation, I present case studies of threatened interacting species where a combined translocation could save the species. In chapter 5, I examine in detail how different types of interactions influence the optimal size of founder populations and the order in which interacting species should be translocated. I use mathematical models for coupled two-species systems, in which species interact in consumer-resource, competitive or mutualistic interactions. While some common rules in translocating interacting species emerge, most decisions about necessary founder sizes and translocation order are interaction-type specific. In the two chapters about combined translocations of cothreatened species, I show that interspecific interactions are important processes that shape population dynamics, and should therefore be incorporated into the quantitative planning of multi-species translocations. Finally in chapter 6, I synthesise the findings of my work and highlight future research avenues.