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The impact of data precision on the effectiveness of alien plant control programmes: a case study from a protected area

  • Chad Cheney
  • Karen J. Esler
  • Llewellyn C. Foxcroft
  • Nicola J. van Wilgen
  • Melodie A. McGeoch
Original Paper

Abstract

Successful long-term invasive alien plant control programmes rely on alien plant distribution and abundance data to assess, prioritise, implement and monitor the efficacy of the programme. Here we assess the impact of data accuracy using the alien plant programme in Table Mountain National Park, South Africa. A systematic plot-based survey method was carried out to assess the distribution of alien plants in the park at a fine scale (systematic sampling). Alien plant richness, total area invaded and the degree of spatial overlap in species’ presence were compared between the systematic sample and a protected area (PA) managers’ dataset (collated from collective observations by park visitors, rangers and managers) and Working for Water (WfW) project data (data collected for the planning and implementation of the alien plant clearing programme) using a range of confusion matrix-based statistics to assess similarity and error rates between the datasets. A total of 106 alien plant taxa were detected across the three datasets, 12 in PA manager’s data, 23 in WfW data and 101 in the systematic survey. Overall, there was substantive disagreement between the datasets on the distribution of alien plants. For example both management datasets estimated species’ hectare coverage at orders of magnitude greater than indicated by systematic sampling. The inaccuracy of manager data has direct negative implications for funding allocation, which currently appears to be in excess of what is required. We recommend that contrary to perception, fine-scale surveys are a cost-effective way to inform long-term monitoring programmes and improve programme effectiveness.

Keywords

Control programme Confusion matrix Invasive species Protected area management Systematic distribution sampling 

Notes

Acknowledgements

Thanks to Leandri Gerber, Khanyisa Tyolo and Richardt Smith who undertook the infield mapping. The following funders and grants are acknowledged: The Table Mountain Fund and the AW Mellon Foundation (CC and infield work), South African National Parks (CC, LCF, NvW), the DST-NRF Centre of Excellence for Invasion Biology (KJE, LCF, NvW), Stellenbosch University (CC, KJE, LCF), the National Research Foundation of South Africa (LCF: Project Numbers IFR2010041400019 and IFR160215158271, KJE: Grant number 103841) and the Australian Research Council (MM: Grant DP150103017). We thank two anonymous reviewers for their constructive comments that helped improve the article.

Supplementary material

10530_2018_1770_MOESM1_ESM.docx (25 kb)
Supplementary material 1 (DOCX 26 kb)
10530_2018_1770_MOESM2_ESM.docx (16 kb)
Supplementary material 2 (DOCX 16 kb)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.South African National ParksCape TownSouth Africa
  2. 2.Department of Conservation Ecology and EntomologyStellenbosch UniversityStellenboschSouth Africa
  3. 3.Conservation ServicesSouth African National ParksSkukuzaSouth Africa
  4. 4.Centre for Invasion Biology, Department of Botany and ZoologyStellenbosch UniversityStellenboschSouth Africa
  5. 5.School of Biological SciencesMonash UniversityClaytonAustralia

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