Browsing by Author "Robertson, M P"

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    A proposed prioritization system for the management of invasive alien plants in South Africa
    (2003) Robertson, M P; Villet, M H; Fairbanks, D H K; Henderson, L; Higgins, S I; Hoffmann, J H; Le Maitre, D C; Palmer, A R; Riggs, I; Shackleton, C M; Zimmermann, H G
    Every country has weed species whose presence conflicts in some way with human management objectives and needs. Resources for research and control are limited, so priority should be given to species that are the biggest problem. The prioritization system described in this article was designed to assess objectively research and control priorities of invasive alien plants at a national scale in South Africa. The evaluation consists of seventeen criteria, grouped into five modules, that assess invasiveness, spatial characteristics, potential impact, potential for control, and conflicts of interest for each plant species under consideration. Total prioritization scores, calculated from criterion and module scores, were used to assess a species' priority. Prioritization scores were calculated by combining independent assessments provided by several experts, thus increasing the reliability of the rankings. The total confidence score, a separate index, indicates the reliability and availability of data used to make an assessment. Candidate species for evaluation were identified and assessed by several experts using the prioritization system. The final ranking was made by combining two separate indices, the total prioritization score and the total confidence score. This approach integrates the plant's perceived priority with an index of data reliability. Of the 61 species assessed, those with the highest ranks (Lantana camara, Chromolaena odorata and Opuntia ficus-indica) had high prioritization and high confidence scores, and are thus of most concern. Those species with the lowest ranks, for example, Harrisia martinii, Opuntia spinulifera and Opuntia exaltata, had low prioritization scores and high confidence scores, and thus are of least concern. Our approach to ranking weeds offers several advantages over existing systems because it is designed for multiple assessors based on the Delphi decision-making technique, the criteria contribute equally to the total score, and the system can accommodate incomplete data on a species. Although the choice of criteria may be criticized and the system has certain limitations, it appears to have delivered credible results.
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    Facilitating golden mole conservation in South African highland grasslands : a predictive modelling approach
    (2016) Rampartab, Chanel; Bronner, Gary N; Bennett, Nigel C; Bloomer, Paulette; Robertson, M P
    Golden moles are subterranean mammals endemic to sub-Saharan Africa and threatened by anthropogenic habitat loss. At present, little is known about the biology, taxonomy, distribution and severity of threats faced by many of these taxa. In an attempt to raise awareness of these elusive grassland flagship taxa, the Endangered Wildlife Trust's Threatened Grassland Species Programme (EWT-TGSP) identified the need for more information on the distributions and conservation status of four poorly-known golden mole taxa (Amblysomus hottentotus longiceps, A. h. meesteri, A. robustus, A. septentrionalis) that are endemic to the Grassland Biome, and which may be heavily impacted by anthropogenic habitat alteration in the Highveld regions of Mpumalanga Province. This study employed species distribution modelling to predict the distributional ranges of these taxa, and involved four main processes: (i) creating initial models trained on sparse museum data records; (ii) ground-truthing field surveys during austral spring/summer to gather additional specimens at additional localities; (iii) genetic analyses (using cytochrome-b) to determine the species identities of the newly-acquired specimens, as these taxa are morphologically indistinguishable; and (iv) refining the models and determining the conservation status of these Highveld golden moles. Initial species distribution models were developed using occurrence records for 38 specimens, based on interpolated data for 19 bioclimatic variables, continuous altitude data, as well as categorical spatial data for landtypes, WWF ecoregions and vegetation types. These initial models helped to effectively focus survey efforts within a vast study area, with surveying during the austral spring-summer of 2013-4 resulting in the acquisition of 25 specimens from across Mpumalanga, nine individuals of which (A. h. meesteri n = 2; A. septentrionalis n = 5; unknown n = 2) were captured in five new quarter-degree-squares (QDSs) where no previous golden moles have been recorded. Additionally, observed activity was also recorded in nine new QDSs (see Appendix 3), showing that the model refinement methods used (variable selection, auto-correlation, non-repeated versus cross-validated models, jackknife of variable importance and localities, independent data testing) were effective in locating golden mole populations. By using genetically-identified historical golden mole records, predictive distribution models were calibrated in maximum entropy (MaxEnt) software to focus ground-truthing efforts.