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Range-wide population viability analyses reveal high sensitivity to wildflower harvesting in extreme environments

Cite this dataset

Treurnicht, Martina et al. (2021). Range-wide population viability analyses reveal high sensitivity to wildflower harvesting in extreme environments [Dataset]. Dryad.


The ecological effects of harvesting from wild populations are often uncertain, especially since the sensitivity of populations to harvesting can vary across species’ geographical ranges. In the Cape Floristic Region (CFR, South Africa) biodiversity hotspot, wildflower harvesting is widespread and economically important, providing an income to many rural communities. However, with very few species studied to date, and without considering range-wide sensitivity to harvesting, there is limited information available to ensure the sustainability of wildflower harvesting.

We studied geographical variation in sensitivity to wildflower harvesting for 26 Proteaceae shrubs with fire-driven life cycles using population viability analyses. We developed stochastic, density-dependent population models that were parameterized from individual demographic rates (adult fecundity, seedling recruitment and adult fire survival) and local environmental conditions across the geographical ranges of the study species. We then simulated the effects of harvesting on populations in different environments across species ranges. Our model simulations predicted extinction risk per population, and we derived extinction probabilities over 100 years in response to different harvesting regimes. We used these population-level extinction probabilities to quantify inter- and intraspecific variation in sensitivity to wildflower harvesting, and to explore how geographical variation in sensitivity depends on environmental conditions (climate, soil fertility and fire disturbance).

We detected considerable inter- and intraspecific variation in sensitivity to wildflower harvesting for the 26 study species. This held for both ‘nonsprouters’ and ‘resprouters’ (species with low and high fire persistence ability, respectively). Intraspecific variation in sensitivity to harvesting showed varying geographical patterns and associated with environmental variation. Notably, sensitivity was high towards range edges and at the climatic extremes of species ranges, respectively.

Synthesis and applications: We show the importance of combining spatial demographic data, density-dependent population dynamics and environmental variation when assessing sensitivity to harvesting across species geographical ranges. Our findings caution against the application of general harvesting guidelines irrespective of species, geographical location or local environmental conditions. Our range-wide population viability analyses provide insights for developing species-specific, spatially nuanced guidelines for conservation management. Our approach also identifies species and areas to prioritise for monitoring to prevent the overexploitation of harvested species.23-Mar-2021


Demographic data can be found in the cited literature of this article (notably Treurnicht et al. 2016; Pagel et al. 2020 and supporting information of these published articles). These demographic data were partly used under license agreements from provincial and national conservation organisations in South Africa (CapeNature and SANParks) and are available from the lead author ( upon reasonable request and with the permission of these organisations.

-Treurnicht, M., Pagel, J., Esler, K.J., Schutte‐Vlok, A., Nottebrock, H., Kraaij, T. et al. (2016) Environmental drivers of demographic variation across the global geographical range of 26 plant species. Journal of Ecology, 104, 331–342.

-Pagel, J., Treurnicht, M., Bond, W.J., Kraaij, T., Nottebrock, H., Schutte-Vlok, A., Tonnabel, J., Esler, K.J. & Schurr, F.M. (2020) Mismatches between demographic niches and geographic distributions are strongest in poorly dispersed and highly persistent plant species. Proceedings of the National Academy of Sciences 117, 3663-3669.

Environmental data are from various sources cited in the main text of this article (Treurnicht et al. 2021) and include:

- Schulze, R.E. (2007) South African Atlas of Climatology and Agrohydrology, Technical Report 1489/1/06. Water Research Commission, Pretoria, South Africa.

- Wilson, A.M., Latimer, A.M. & Silander, J.A. (2015) Climatic controls on ecosystem resilience: postfire regeneration in the Cape Floristic Region of South Africa. Proceedings of the National Academy of Sciences of the USA, 112, 9058–9063.

Usage notes

This .zip directory contains R scripts, model code and data used to perform population viability analyses across the geographic ranges of 26 Proteaceae species in the South African Cape Floristic Region.

*refer to ReadMe file for full descriptions of the data and usage.

Usage Notes for the code and associated functions and parameters used in 'PVA.R':


R script to perform the described population viability analyses for populations in different environments across species’ geographic ranges


R script defining auxiliary functions used in PVA.R


Compiled dynamic link library that implements the stochastic model of local population dynamics and is called from the R scripts


C source code of ProteaModel.dll


Folder containing the species-specific global and spatial parameters used in the population viability analyses


German Research Foundation (DFG) grants, Award: SCHU 2259/5-1 and SCHU 2259/5-2

National Research Foundation of South Africa (NRF) through the South African Environmental Observation Network (SAEON)

Claude Leon Foundation

German Research Foundation (DFG) grants, Award: SCHU 2259/5-1 and SCHU 2259/5-2