Original Research

Can anthropogenic variables be used as threat proxies for South African plant richness?

M. Keith, M. Warren
Bothalia | Vol 37, No 1 | a305 | DOI: https://doi.org/10.4102/abc.v37i1.305 | © 2007 M. Keith, M. Warren | This work is licensed under CC Attribution 4.0
Submitted: 15 August 2007 | Published: 18 August 2007

About the author(s)

M. Keith, Threatened Species Programme, South African National Biodiversity Institute. Department of Zoology and Entomology, University of Pretoria, South Africa
M. Warren, Department of Zoology and Entomology, University of Pretoria

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Abstract

Human demographic and socio-economic measures (anthropogenic variables) reflect the detrimental impact of humans on plant diversity globally. The Pretoria (PRE) Computerised Information System (PRECIS) of the South African National Biodiversity Institute (SANBI), provided three sets of South Afncan plant richness data, overall (OPR), endemic (EPR), and threatened (TPR), to investigate the relationships between richness and six anthropogenic variables. Spearman’s Rank order correlations, Kruskal Wallis Analysis of Variance (ANOVA) and Generalized Linear Models (GLZ) were used. Although all three plant richness measures were correlated with anthropogenic variables, individual anthropogenic variables contributed a small fraction to the explained variation in richness. Differences in spatial and temporal scaling of the datasets, or the response to another causal mechanism, may have contributed to this low explained variation. Because more variation was accounted for in OPR than EPR or TPR, OPR is a more suitable surrogate measure of plant biodiversity when investigating the anthropogenic variables used here. Average human density (HD), infrastructure (degree of urbanization and road cover) (LRU) and percentage land area transformed and degraded (LTD) were identified as useful surrogates of human impacts on OPR. LTD may be a more inclusive human impact measure when conducting analyses of human impacts using OPR. LTD includes the effects of urban expansion, road networks and other land transformation impacts, such as agriculture.


Keywords

endemic species; human population density; land transformation; setting conservation priorities

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