Advancing the use of evolutionary considerations in spatial conservation planning

Robertson, S 2020, Advancing the use of evolutionary considerations in spatial conservation planning , PhD thesis, University of Salford.

[img]
Preview
PDF
Download (2MB) | Preview

Abstract

The existence of life on earth as we know it relies on a diversity of life. Biodiversity underpins vital ecosystems services globally, at all spatial scales, and yet is being lost at an alarming rate. Current extinction rates are estimated to be 100-1000 times higher than the typical background rates observed in the fossil record, with anthropogenic influences being the major driving force. It is therefore widely accepted that biodiversity must be protected. Spatial tools, such as protected areas, are increasingly employed to meet conservation objectives. Despite continuing developments in spatial conservation methods, a fundamental aspect of biodiversity remains largely ignored, namely evolutionary processes. Evolution is the process that generates and maintains biodiversity. However, examples of where evolutionary considerations have been explicitly incorporated into spatial conservation planning remain rare, with metrics such as species richness (which ignore differences in evolutionary distinctiveness between species) more often used. This work aims to address this by focusing on the inclusion of phylogenetic diversity (PD), which measures evolutionary diversity by summing the branch lengths joining a species, or set of species, into protected area planning. A review of the literature revealed that there has been a huge increase, an average 80% increase per year in the last five years, in research around the conservation of PD. However, studies where PD has been specifically included into current spatial conservation practices, namely by incorporating PD into spatial optimisation analyses using tools such as MARXAN, remain rare, although this is changing. There is also a need for further investigation into whether species richness can act as an effective surrogate metric for PD. The dominant approach to incorporate PD into protected area planning, identified in the literature review, is to use phylogenetic tree branches as conservation features, weighted in accordance to their length. This approach, which is referred to here as the “weighted branch-based approach”, was used in a new case study on primates, using MARXAN, to compare the priority areas identified for the conservation of PD with those identified using species-based targets. Large spatial mismatches were found between planning outputs based on PD when compared to outputs based on species, although this was influenced by the availability of area, with the largest mispatches found when area was limited most. No major difference was observed between the amount of PD captured by a PD-based approach versus the amount captured by a species-based approach, suggesting that species richness may be a suitable surrogate metric for PD. Potential issues associated with constraining a planning process in order to account for PD, e.g. getting MARXAN to solve a problem (maximum coverage) that is different to one it was designed to solve (minimum set), provided the impetus to seek a new methodology that accounts for PD while still maintaining MARXAN’s core functionality. This novel method, which maximises PD though the optimised selection of species that can then act as conservation features to set coverage targets for, was tested using a case study for three mammalian orders (Artiodactyla, Carnivora, and Primates). The results of this case study show that differences in PD between species can be used to select sets of species that maximise overall PD within a spatial conservation planning exercise, without the use of penalties or thresholds that are required in a weighted branch-based approach. Despite heated debate, few studies have tried to empirically investigate the impact of changes in species-level taxonomy due to the use of different species concepts (and specifically the use of the Phylogenetic Species Concept [PSC], which tends to recognise more species than other commonly-used concepts) on the conservation of biodiversity. The final research element of this work specifically addresses this gap in knowledge by presenting the first study to analyse the impact of changes in species-level taxonomy on a PD-informed spatial conservation plan, using African bovid species (gazelles, antelopes etc.) as a case study. PD-informed spatial conservation planning has been argued to be relatively unaffected by changes in species-level taxonomy. However, the results presented here show that, while the amount of area required does not change, there are substantial impacts on the location of spatial conservation plans for African bovid species, depending on whether or not a PSC-based species-level taxonomy is used. Collectively, this thesis shows that PD can be successfully incorporated into conservation planning and that it has a major impact on spatial planning outcomes, particularly when resources (in this case, area) are limited. Based on these findings, there is a clear need for future research to investigate the potential for some metrics, for which data may be more readily available e.g. species richness, to act as surrogates for other metrics that capture important dimensions of biodiversity e.g. PD; and that in combination with surrogates there is a need for more integrated approaches to conservation that account for the multidimensional characteristics of biodiversity, as well as further investigation into the implications of taxonomy for biodiversity conservation.

Item Type: Thesis (PhD)
Contributors: Yates, KL (Supervisor), Beck, RMD (Supervisor) and Mariani, S (Supervisor)
Schools: Schools > School of Environment and Life Sciences
Funders: University of Salford
Depositing User: STUART Robertson
Date Deposited: 07 May 2021 15:18
Last Modified: 07 Jun 2021 02:30
URI: http://usir.salford.ac.uk/id/eprint/59952

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)

Downloads

Downloads per month over past year