Sense in Sensitivity: Assessing Species Vulnerability to Climate Change
type: CreativeWork
description: This thesis investigates the impact of future climate change upon species vulnerability. Reports of shifts in species distributions are already numerous, but the pattern of change is not fully understood. This thesis looks to predict which species are likely to be most at risk under climate change and why? This thesis takes the equation; Vulnerability= Sensitivity + Exposure to better discover which species are most vulnerable to climate change. Additionally, this research explores how mitigation has a role in determining the degree to which species are vulnerable in the future. Determining a specie’s vulnerability to climate change required the creation of values representing each side of the equation, both a measure of sensitivity and exposure. The construction of a sensitivity measure required the creation of a life history and ecological traits database, and required the use of multiple methods of statistical analysis. Exposure was calculated using projections of future suitable climate space created using species distribution model Maxent. To explore the impact of mitigation on species vulnerability exposure was calculated under a range of climate change scenarios. The sensitivity and exposure scores are synthesised into a measure of vulnerability. The result of the equation, Vulnerability= Exposure + Sensitivity, has revealed which Mammal species are most vulnerable; those which will be exposed to a high degree of climate change and which life history and ecological traits make them sensitive. The most vulnerable species are those which are highly exposed and which have ‘slow’ life history traits, are range restricted, or, are climate specialist. The regions in which species are identified as most vulnerable include the Neotropical and Afrotropical zones. Mitigation is found to reduce potential vulnerability with early mitigation being the most beneficial. The deeper understanding gained through this research will help us prioritise species for conservation ba…
abstract: This thesis investigates the impact of future climate change upon species vulnerability. Reports of shifts in species distributions are already numerous, but the pattern of change is not fully understood. This thesis looks to predict which species are likely to be most at risk under climate change and why? This thesis takes the equation; Vulnerability= Sensitivity + Exposure to better discover which species are most vulnerable to climate change. Additionally, this research explores how mitigation has a role in determining the degree to which species are vulnerable in the future. Determining a specie’s vulnerability to climate change required the creation of values representing each side of the equation, both a measure of sensitivity and exposure. The construction of a sensitivity measure required the creation of a life history and ecological traits database, and required the use of multiple methods of statistical analysis. Exposure was calculated using projections of future suitable climate space created using species distribution model Maxent. To explore the impact of mitigation on species vulnerability exposure was calculated under a range of climate change scenarios. The sensitivity and exposure scores are synthesised into a measure of vulnerability. The result of the equation, Vulnerability= Exposure + Sensitivity, has revealed which Mammal species are most vulnerable; those which will be exposed to a high degree of climate change and which life history and ecological traits make them sensitive. The most vulnerable species are those which are highly exposed and which have ‘slow’ life history traits, are range restricted, or, are climate specialist. The regions in which species are identified as most vulnerable include the Neotropical and Afrotropical zones. Mitigation is found to reduce potential vulnerability with early mitigation being the most beneficial. The deeper understanding gained through this research will help us prioritise species for conservation ba…
author: Mcdougall, Amy
language: en
date published: 2013-12
date modified: 2026-07-24T02:12:10Z
provider: University of East Anglia
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of East Anglia