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Aspalathus linearis (Burm. f.) R. Dahlgren (rooibos) is endemic to the Fynbos Biome of South Africa, which is an internationally recognized biodiversity hot spot. Rooibos is both an invaluable wild resource and commercially cultivated crop in suitable areas. Climate change predictions for the region indicate a significant warming scenario coupled with a decline in winter rainfall. First estimates of possible consequences for biodiversity point to species extinctions of 23% in the long term in the Fynbos Biome. Bioclimatic modelling using the maximum entropy method was used to develop an estimate of the realized niche of wild rooibos and the current geographic distribution of areas suitable for commercially production. The distribution modelling provided a good match to the known distribution and production area of A. linearis. An ensemble of global climate models that assume the A2 emissions scenario of high energy requirements was applied to develop possible scenarios of range/suitability shift under future climate conditions. When these were extrapolated to a future climate (2041–2070) both wild and cultivated tea exhibited substantial range contraction with some range shifts southeastwards and upslope. Most of the areas where range expansion was indicated are located in existing conservation areas or include conservation worthy vegetation. These findings will be critical in directing conservation efforts as well as developing strategies for farmers to cope with and adapt to climate change.
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- Data and Methods
- Conflict of Interest
There is compelling evidence of climate change induced impacts on species diversity through among others, species composition changes (Bertrand et al. 2011; Ruiz-Labourdette et al. 2013), range shifts (Bertin 2008; Colwell et al. 2008), and altered phenology (Cleland et al. 2007; Prieto et al. 2009; Hulme 2011). Given the rate and magnitude of changes in the global and regional climate, knowledge of what determines species ranges is critical in understanding the potential consequences for agriculture, forestry, and biodiversity conservation (Araùjo and Rahbek 2006; Falk and Mellert 2011; Bradley et al. 2012). Increasing attention has, therefore, been focussed on implementing a proactive approach through developing plausible scenarios of future climate change and modelling the associated species range and ecosystem shifts.
Decision tools such as correlative spatial distribution models (SDMs) have become key in assessing biodiversity responses to climate change (Midgley et al. 2003; Guisan and Thuiller 2005; Heikkinen et al. 2006; Araùjo et al. 2011; Rodríguez-Castañeda et al. 2012). Several SDM methods have been developed and applied to investigate species' geographic ranges and possible shifts under global climate change. These include mechanistic models, climatic envelope methods, and machine learning techniques (Yates et al. 2010). All of these methods estimate a species actual or potential geographic range through relating field observations of species occurrences to environmental and climatic variables. This relationship can then be used to assess species' range shifts under different climate scenarios to undertake risk assessments in specific focal areas.
In light of the importance of accurately modelling species' responses to a changing climate, numerous studies have been devoted to exploring the relevance, application, and shortcomings of these models (Guisan et al. 2006; Heikkinen et al. 2006; Elith and Leathwick 2009; Soberòn and Nakamura 2009; Miller 2010; Araújo and Peterson 2012). Some cross-cutting objections against these models are as follows: (1) They do not include biotic interactions and assume species distribution is primarily affected only by climatic variables; (2) when extrapolating to the future they make the assumption that the limiting factors and biotic interactions will remain the same; (3) the spatial and temporal resolution at which data are collected and applied raises several statistical issues; (4) while species distribution models usually deal with the mean climatic range of a species potential current and future suitability, it is more often the changes in climatic variability and occurrence of extreme events that determine their distribution range. A prerequisite for distribution modelling is, therefore, a thorough understanding and interpretation of the many factors interacting within the environment where the species occur. Modelling range shifts also requires an in-depth understanding and rigorous analysis of the species at hand. By acknowledging and being aware of the limitations of these methods, we can make them useful support tools exploring climate change associated range shifts.
Globally, numerous species distribution models investigating the impact of climate change on species predict that more species will experience substantial range shifts with a changing climate (Parmesan and Yohe 2003; Thuiller et al. 2005; Broennimann et al. 2006; Chen et al. 2011). Locally, climate change-related species distribution research (Midgley et al. 2002, 2003) in the Cape Floristic Region (CFR) of South Africa suggests a reduction in the geographic ranges of endemic species and reductions in species richness under climate change. The extent of the Cape Fynbos Biome could decline by between 51% and 65% depending on the warming scenario. There is consensus between climate models that the climate in the CFR is expected to become warmer and drier, with a decline in winter rainfall, especially in the western region. This could eventually result in species extinctions of 23% in the Fynbos Biome.
In this study, bioclimatic modelling was employed to model A. linearis' distribution. The objectives of the study were to (1) identify the environmental factors limiting or determining the natural distribution; (2) use this to develop a first estimate of the realized niche and potential geographic distribution of wild rooibos and the current geographic distribution of areas suitable for commercially production; (3) inform the location and design of field experiments to assess its ability to survive under different climatic conditions; and (4) develop possible scenarios of range/suitability shift under future climate conditions.
Aspalathus linearis is a leguminous shrub indigenous to the Fynbos Biome of the Cape Floristic Region (Dahlgren 1968), which has successfully made the transition from wild resource to an agriculturally important plant. Wild populations of A. linearis have a narrow geographic range within the Fynbos Biome and are largely confined to mountain ranges of the far southwestern part of the Northern Cape Province and Cederberg mountains of the Western Cape. The species grows mainly in nutrient poor, highly acidic and well-drained, sandstone-derived soils (pH 3–5.3) typical of the mountainous areas in the area (Muofhe and Dakora, 2000). Its climatic distribution is dictated particularly by the combination of winter rainfall and hot dry summers with an annual rainfall of at least 300–350 mm (Dahlgren 1968). Cultivated and wild A. linearis differ mainly in terms of morphology, growth, and flowering patterns (Malgas et al. 2010). Cultivated plants are reseeders, whereas certain ecotypes of wild A. linearis are slower growing resprouters. Rooibos is ant dispersed and its fire-stimulated seeds germinate in the early winter months after the passage of the first rain bearing cold fronts. Ant dispersal provides a number of benefits for the species. Ants may move seeds many meters away from the parent plant helping it to escape from herbivores and minimizing competition with parent plants/siblings (Bond and Slingsby, 1983). In commercially propagated rooibos, these critical stages of seed germination and seedling emergence are artificially overcome by sowing seed in well-prepared, irrigated seedbeds after which it is then removed and established in plantations.
The species was first described circa 1768, but wild plants have been collected and utilized by local inhabitants of the Cederberg and Bokkeveld mountains (Fig. 1) for centuries (Morton 1983). Based on rock art and archaeological evidence, hunter-gatherers have lived in the area for 10–20,000 years and herders (Khoi) since around 1200 AD (Barnard 1992). Rooibos has always formed an integral part of the heritage of these people, and they have a rich knowledge of managing and utilizing the plant to produce tea as well as for its medicinal and health properties. The economic value of rooibos was, however, not exploited until the 1930s when intensive research on the cultivation of the plant enabled the development of the full-fledged industry as it stands today. The industry is one of the largest providers of permanent and seasonal employment in the rural areas of South Africa (Department of Agriculture, Forestry and Fisheries 2010). Recent years have seen an unprecedented growth in the rooibos industry as the demand for rooibos from international markets has steadily increased.
Figure 1. Map of the study area: surveyed locations of wild and cultivated rooibos stretching from Nieuwoudtville in the Northern Cape, south toward Piketberg.
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Alongside the well-established commercial rooibos industry, traditional small-scale farming fulfills a vital role in maintaining the economic and social stability of historically neglected rural communities in the semiarid Cederberg region of South Africa. Small-scale farmers are concentrated in isolated and remote rural areas around Nieuwoudtville and Wupperthal. Wild rooibos is marketed by these small-scale farmers as an organic and fair trade certified product to niche markets overseas. Many rural communities therefore depend on A. linearis for their livelihoods, so the tea has ecological, economic, and cultural significance.