DOI: 10.5061/dryad.547d7wm7v
title: Range-wide population viability analyses reveal high sensitivity to wildflower harvesting in extreme environments

description: 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
description: 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 (martinatreurnicht@gmail.com) upon
 reasonable request and with the permission of these
 organisations. -Treurnicht, M., Pagel, J., Esler, K.J.,
 Schutte‐Vlok, A., Nottebrock, H., Kraaij, T. <i>et al.</i>
 (2016) Environmental drivers of demographic variation across the global
 geographical range of 26 plant species. <i>Journal of
 Ecology</i>, <b>104</b>, 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.
 <i>Proceedings of the National Academy of Sciences</i>
 <b>117</b>, 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) <i>South African Atlas of Climatology and
 Agrohydrology,</i><i> </i><i>Technical Report
 1489/1/06</i>. 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.
 <i>Proceedings of the National </i><i>Academy of
 Sciences of the USA</i>, <b>112</b>,
 9058–9063.
description: 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':
 <b>PVA.R</b> R script to perform the described
 population viability analyses for populations in different environments
 across species’ geographic ranges
 <b>PVA_Fun.r</b> R script defining auxiliary
 functions used in PVA.R
 <b>ProteaModel.dll</b> Compiled dynamic link library
 that implements the stochastic model of local population dynamics and is
 called from the R scripts
 <b>ProteaModel.c</b> C source code of
 ProteaModel.dll
 <b>ModelParameters</b> Folder containing the
 species-specific global and spatial parameters used in the population
 viability analyses