A climate change vulnerability assessment of 58 Richtersveld plant species

Pather, Keyura

A climate change vulnerability assessment of 58 Richtersveld plant species

Thesis / Dissertation

2025

Publisher

University of Cape Town

Department

Department of Biological Sciences

Faculty

Faculty of Science

Abstract

The Richtersveld is the northernmost region of the Succulent Karoo and is located in the north-western region of South Africa's Northern Cape Province. This region has an incredible arid plant diversity, with both the highest succulent plant diversity and highest rate of endemism in an arid area, globally. It forms part of both a global biodiversity hotspot and a UNESCO world heritage site. However, it is already experiencing significant climate change exposure which is predicted to worsen. Changes in the area's climate are also interacting synergistically with other anthropogenic pressures including mining, poaching and agriculture. The threats to this area, including climate change, are documented but knowledge gaps still remain – especially with regards to plants and climate change vulnerability. In this study I aimed to find which Richtersveld species are the most vulnerable to climate change while trialling a relatively novel approach in this context. I used a trait-based assessment with correlative species distribution model outputs to assess the sensitivity, adaptive capacity and exposure of 58 plant species occurring within the Richtersveld National Park. This included assessing biological, ecological, environmental and spatial traits of species that contribute to climate change vulnerability. Traits were scored based on literature, expert opinion and correlative modelling outputs. Trait scores were then combined using both additive and ordinal methods, creating a best-case scenario where unknowns were assumed to have ‘low' scores, and a worst-case scenario when these were assumed to be ‘high'. These scenarios were applied to both the ordinal and additive scoring methods. For the additive scoring method, there was an additional consideration – trait weighting. It would be inaccurate to assume all traits hold the same importance in determining a species' vulnerability to climate change. Each trait was assigned a weighting based on literature and expert opinion and applied in an additional weighted scoring approach. Therefore, each species had a total of six climate change vulnerability scores: a best-case ordinal, a worst-case ordinal, a best-case unweighted additive, a worst-case unweighted additive, a best-case weighted additive and a worst-case weighted additive score. Under the worst-case ordinal scoring method, 34 species (59 %), were scored as highly vulnerable to climate change. The most vulnerable species were those that consistently scored high vulnerability scores, across all six scoring methods. This included Cheilanthes namaquensis (Not endemic to the region nor the park and Least Concern), Trachyandra ardimontana (almost endemic to park and Endangered), Albuca etesiogaripensis (almost endemic to park and Data Deficient), Ruschia glauca (almost endemic to park and Endangered) and Schwantesia herrei (Richtersveld endemic and Least Concern). I also found a mismatch between species' Red List status and their scores in my climate change vulnerability assessment. This suggests that highly climate change vulnerable species identified in this study currently have a low Red List threat status assigned to them by the responsible conservation organisation. This finding could mean that their status does not accurately reflect their level of conservation risk – especially if climate change is not accounted for. This can cause them to be overlooked in terms of conservation resource provision and decision- making. The IUCN Red List Version 16 Section 12 provides guidelines for assessing climate change vulnerability and its application in determining a species' threat status to climate change. However, its development is relatively recent, and its use is limited, possibly due to the data and technical expertise required. My study provides a possible example of how, even in highly biodiverse region with low data availability, climate change vulnerability assessments may be carried out, and of the value for preventing extinctions. The highest concentration of climate change vulnerable species were found to be in the central western and northern areas of Richtersveld National Park. The spatial representation of these data may aid where within the Park conservation and management can be prioritized. In conclusion, I trialled an approach that has not previously been applied for Richtersveld plants. The approach produced predictions of climate change vulnerability that could be used for conservation. The approach used in this study helped identify species and areas to which climate change conservation measures could be applied. This approach can be applied to other arid areas and aid in climate- related conservation, including in section 12 of the Red Listing Guidelines (Version 16).