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Sequestering carbon and restoring renosterveld through fallowing: a practical conservation approach for the Overberg, Cape Floristic Region, South Africa


  • Editor Ashwini Chhatre


Anthony J. Mills, Department of Soil Science, University of Stellenbosch, Matieland 7602, South Africa. Tel/fax: +27-21-715-1560.

E-mail: mills@sun.ac.za


Carbon credits are a potential source of funding for restoration initiatives that contribute to achieving conservation targets in important biodiversity areas. Here we investigated whether fallowing sequesters carbon; a first step in assessing the viability of using carbon financing to promote restoration of threatened vegetation in agricultural landscapes. We used renosterveld, a critically endangered shrubland vegetation of the Cape Floristic Region, as a case study. Carbon stocks of soil and biomass in active fields, fallow fields and intact renosterveld were compared. The total carbon stocks measured in fallow fields (82 Mg C ha−1) show that fallowing can sequester carbon lost in the conversion from intact renosterveld (84 Mg C ha−1) to active fields (69 Mg C ha−1) and that revenues of US$ 10 – 48 ha−1 yr−1 from carbon credits could accrue. Our findings suggest that carbon financing could be used to incentivise ecological restoration in marginal agricultural landscapes.


An effective way to reduce global biodiversity loss is to focus conservation activities on important biodiversity areas (Eken et al. 2004). To meet conservation targets, new initiatives increasingly focus on complementing protected area networks (Margules & Pressey 2000). However, important biodiversity areas are often densely populated which tends to result in degradation (see Cincotta et al. 2000). Conservation targets are consequently difficult to meet through protection alone (e.g. von Hase et al. 2010). It is therefore increasingly recognized that systematic landscape restoration is an additional important way to meet conservation targets in these regions (Crossman & Bryan 2006).

In marginal agricultural landscapes, carbon sequestration through fallowing (CSF; i.e. taking previously ploughed fields out of production) may be a viable mechanism to finance ecological restoration (see Venter et al. 2009). Indeed fallow systems in sub-Saharan Africa have considerable potential for soil carbon sequestration (Vågen et al. 2005). However, carbon stocks vary with climate, topography and soil type (Vågen et al. 2005). Returns of soil carbon in fallows range from 0.1 to 5.3 Mg of carbon ha−1 yr−1 in sub-Saharan Africa (Vågen et al. 2005) and translate to US$ 0.5–53 ha−1 yr−1 (see Peters-Stanley et al. 2011 for carbon prices). Not only does carbon financing from fallowing offer an alternative income stream for landowners but it can benefit biodiversity. For example: (i) Australia's Carbon Farming Initiative (Anonymous 2011) supports landscape restoration; and (ii) in Europe and the United States, set-aside agricultural land—for the purpose of reducing agricultural production and conserving soil—has resulted in increased species richness and population numbers of indigenous plants, insects, spiders and birds (127 monitoring studies reviewed by van Buskirk & Willi 2004).

Here we investigated the potential of CSF as: (i) a viable alternative to crops associated with low and/or unpredictable incomes; and (ii) a means for incentivizing large-scale restoration of marginal agricultural landscapes. Specifically, we: (i) measured soil and above-ground (AG) biomass carbon stocks in active fields (under production), fallow fields (no production) and intact renosterveld vegetation; (ii) calculated the potential revenue of carbon credits from fallowing; and (iii) compared carbon financing options with revenues from current farming practices in the study region.

The study was undertaken in renosterveld vegetation in the Overberg region, Western Cape, South Africa. Renosterveld is a vegetation type situated in the Cape Floristic Region biodiversity hotspot (Cowling et al. 2003) that has been identified as being 100% irreplaceable in systematic conservation plans (von Hase et al. 2003). It is a localized, critically endangered, Mediterranean-type vegetation that is adapted to a relatively frequent, low-intensity fire regime and is characterized by Asteraceous shrubs, a high diversity of geophytic plants and a grassy component (Boucher 1995; Cowling 1990). Historically, commercial agriculture (farm sizes mostly > 500 ha) has been the mainstay of the economy in this region and it continues to provide livelihoods to farmers (von Hase et al. 2003, Winter et al. 2007). Further, many farmers see limited value (economic or other) in conserving renosterveld (Winter et al. 2007). Consequently, more than 90% of renosterveld has been transformed, with the remaining fragments being unprotected and on private land within an agricultural matrix (Mucina & Rutherford 2004). Renosterveld fragments are as a result subjected to livestock grazing, inappropriate fire management regimes and occasional ploughing (O'Farrell et al. 2009). Existing off-reserve conservation interventions are limited (von Hase et al. 2010) and the existing renosterveld fragments are too small to meet regional conservation targets (Driver et al. 2005). As a result, restoration of degraded renosterveld is the only feasible way to reach conservation targets (Cowling et al. 2003). This study shows that carbon finance can potentially fund restoration initiatives via fallowing and contribute to achieving conservation targets in important biodiversity areas.


Study sites

The Overberg region (Fig. 1) has a Mediterranean climate and a mean annual precipitation ranging from 250 to 600 mm per annum (Mucina & Rutherford 2004). As a first step towards assessing the potential for using carbon financing to incentivize renosterveld restoration, we examined the variability in ecosystem carbon stocks (below- and above-ground) across three land use types: active fields (used for wheat production); fallow fields (unploughed for 10–25 years; grazed); and intact renosterveld (never ploughed; grazed). Because rainfall is likely to influence carbon stocks, and therefore carbon sequestration potential (Don et al. 2011), we conducted our work in these three land uses in two regions: (i) near Bredasdorp (∼400 mm per annum); and (ii) near Swellendam (∼500 mm per annum). Based on findings from Mills and Fey (2004) and Mills et al. (2005), we predicted that carbon stocks would be greater in intact renosterveld than in fallow fields and greater in fallow fields than in active fields, and that these differences would be greater in the higher rainfall region.

Figure 1.

Map depicting sampling sites in the Overberg region, Western Cape, South Africa. The renosterveld is patchy and some of the patches are very small. As a result, some of the sites (triangles on map) in the Swellendam region were located in a mix of renosterveld and Swellendam Silcrete Fynbos.

We selected 20 sites—all on parent geology of Bokkeveld shale: 10 sites in the relatively dry region (Bredasdorp); and 10 sites in the relatively wet region (Swellendam; Fig. 1). In each site, active fields, fallow fields (unploughed for 10–25 years in both regions) and intact vegetation were sampled (i.e. 60 samples in total) on a similar slope and altitude and adjacent to each other (most within 300 m). Two active field samples were excluded because of prior manure application and one fallow field sample due to wildfire—leaving a total of 57 samples.

Soil and biomass sampling

Soil and biomass sampling was undertaken in January–July of 2009. Two pits of soil were sampled in each land use at each of the 10 sites: Pit A to determine soil mass and carbon content; and Pit B to determine root mass. AG biomass and litter were collected above Pit B. In intact renosterveld and fallow fields, both pits were located under the canopy of shrubs. Carbon stocks are thus expressed in Mg C shrub ha−1 i.e. carbon stocks per surface area covered by shrub canopy.

In Pit A, three blocks of soil (10 × 10 × 15 cm = 1500 cm3) were excavated at three depths: 0–15 cm; 15–30 cm; and 30–45 cm. There was a 50 cm depth limit to sampling at many sites because of the presence of bedrock at this depth. For each excavated soil block, we measured the total mass and determined its volume using the sand-funnel method (Blake 1965), i.e. by filling the hole with sand of known bulk density and recording the mass of sand used. After sieving (<2 mm) rock volume was measured in all samples (n = 171 i.e. 57 samples at 3 soil depths) and rock mass in 100 of the 171 samples. Rock bulk density based on the latter 100 samples was used to estimate rock mass for the remaining 71 samples. Soil mass was obtained by subtracting rock mass from the total mass. Soil mass was calculated for a constant volume (CV = 1,500 cm3) as follows:

display math

Soil organic carbon was analyzed using the Walkley-Black method (Walkley 1947). This method is likely to lead to under-estimates of soil carbon content because of incomplete oxidation of organic carbon. However, the results generated are suitable for comparisons within a particular geographic area. We compared soil carbon stocks between land uses using the average equivalent soil mass (ESM) as recommended by Lee et al. (2009), i.e. the average total soil mass for a constant pit volume across land uses and regions. Assuming that average soil bulk density was originally similar within sites, this method results in a reliable estimate of changes in carbon stocks resulting from land use change. The average total soil mass (excluding rock fragments) per pit (CV = 1,500 cm3) across all land uses and regions was ∼3,000 g. We consequently compared carbon stocks between sites based on the average ESM of 3,000 g per pit corresponding to 3,000 Mg ha−1 to a depth of 45 cm. Because total soil mass collected in some pits was less than 3,000 g, we added the outstanding mass of soil from a fourth modelled layer (45–60 cm). To assess the carbon content of this fourth layer and to obtain a predicted value of carbon content at a depth of 52.5 cm for each land use in each region, the relationship between carbon content and depth for each land use in each region was modelled using a local polynomial regression. We calculated the soil carbon stock at ESM as follows:

display math

where n is the number of layers (3 or 4) used to obtain a total soil mass of 3,000 g per pit.

For Pit B, the diameter of the canopy of the shrub above the pit was measured to calculate the area of ground covered by the shrub canopy. All litter under the canopy was collected and all AG biomass of the individual shrub was harvested. In active fields, there was negligible AG biomass; and litter was collected from a 1 m2 square above Pit B. Above-ground carbon stocks were calculated as follows:

display math

Blocks of soil were excavated in the same way as Pit A. Roots were extracted by wet sieving (<2 mm). Root mass at constant volume (1,500 cm3) was estimated using the formula used for soil mass. Root carbon stock at ESM—as presented below—was calculated following the same method used for soil carbon content.

display math

where n is the number of layers (3 or 4) used to obtain a total soil mass of 3,000 g per pit.

Above-ground biomass, leaf litter and root samples were dried in an oven at 60°C until constant mass. The carbon content of AG biomass and leaf litter was assumed to be 50% of the dry biomass (Birdsey 1996).

Statistical analysis

We used mixed-effects models (function lmer; package lme4; R Development Core Team, 2011) to test for differences in soil, root, above-ground biomass and total carbon stocks: (i) between land uses in the entire study area; (ii) between “wet” and “dry” regions; and (iii) between land uses in each region. In model 1, land use was considered as a fixed effect and region and site as random effects. In model 2, region was considered as a fixed effect and land use and site as random effects. In model 3, land use was considered as a fixed effect and site as a random effect. Carbon data were either log- or square root-transformed to reach normality prior to analysis. Post hoc pairwise comparisons were performed using Tukey's test.

Farming economic valuation

Information on the economics of farming in a region referred to as the Middle Rûens between Swellendam and Bredasdorp was taken from Hofmann et al. (2010). The Middle Rûens is in the drier section of the study area and is therefore particularly marginal for agriculture. Data were obtained for an average farm in the Middle Rûens on profits per annum for poor and good yields, internal rates of return on investment, predicted profits as a consequence of reduced yields under projected climate change and predicted profits with changes in input prices. Rand values in Hoffmann (2010) were converted to US dollars at a rate of 0.12.

Carbon credit valuation

We made the conservative assumption that soil carbon stocks in fallow fields and intact renosterveld outside of the shrub canopy are comparable with soil carbon stocks in active fields. We therefore calculated the increase in soil carbon stocks, because of fallowing, as the difference between active and fallow fields and multiplied this by average shrub cover (55%, unpublished data). We divided carbon gain by the shortest and longest fallowing time to obtain the range of possible carbon sequestration rates. We do note, however, that carbon sequestration is not linear over time. Future studies will be necessary to determine how carbon sequestration changes with time within fallow fields. We used a conservative range of carbon prices from the literature (Peters-Stanley et al. 2011) to calculate the potential financial value of these carbon stocks. We only calculated potential income from carbon credits. We excluded potential income from grazing (occurring on fallow and intact renosterveld) and ecotourism, making the CSF valuation conservative. However, transaction costs were also excluded from the economic evaluation.


Land use had a significant overall effect on total carbon stocks, with significantly greater values in fallow fields and intact renosterveld than in active fields (Table 1). The difference in total carbon stocks between fallow fields and intact renosterveld was not significant. Soil carbon content (%) (Tukey's test; Z value = 2.99, P = 0.003), total carbon stocks (Z = 2.21, P = 0.03), soil carbon stocks (Z = 2.04, P = 0.04) and root carbon stocks (Z = 2.73, P = 0.006) were greater in the wet region than in the dry region. However, AG carbon stocks (Z = 0.37, P = 0.71) did not differ between the regions.

Table 1. Mean (±standard deviation) soil, root and above-ground carbon stocks (Mg shrub ha−1) in active fields (A), fallow fields (F), and intact renosterveld (I) and the differences in carbon stocks between the three land uses (A, F and I)
 (a) Land uses(b) Land use comparisons


  1. Significant differences are in bold (*P < 0.05; **P < 0.01; ***P < 0.001). Soil and root measures are at ESM.

Soil ESM65.8 ± 18.680.3 ± 29.283.9 ± 3014.518.1*3.6
Root ESM3.1 ± 2.46.9 ± 6.96.1 ±–0.8
Above-ground0 ± 05.2 ± 3.25.8 ± 4.75.2**5.8***0.5
Total68.8 ± 19.592.4 ± 33.095.8 ± 32.523.6**26.9**3.4

Land use had a significant effect on soil carbon content (%) in the wet region (ANOVA; Chi2 = 29.4, P < 0.001) but not in the dry region (Chi2 = 4.08, P = 0.13). In the wet region, soil carbon content was significantly greater in intact renosterveld than in fallow fields (Z = 3.41, P = 0.001) and significantly greater in fallow fields than in active fields (Z = 2.81, P = 0.01; Table 2). Land use had a significant effect on soil, root, AG and total carbon stocks (Table 3). In the wet region, soil, root, above-ground and total carbon stock components were: (i) significantly greater in intact renosterveld than in active fields; (ii) significantly greater in fallow fields than in active fields; and (iii) not significantly different between fallow fields and intact renosterveld (Table 3). In the dry region: (i) above-ground carbon was significantly greater in fallow fields than in active fields; and (ii) root and above-ground carbon stocks were significantly greater in intact renosterveld than in active fields (Table 3).

Table 2. Mean (±standard deviation) soil carbon content (%) and soil, root and above-ground carbon stocks (Mg shrub ha−1) in active fields, fallow fields and intact renosterveld in the dry (∼400 mm p.a.) and wet (∼500 mm p.a.) region


  1. Soil and root measures are at ESM.

C content1.4 ± 0.91.6 ± 11.7 ± 11.9 ± 1.31.9 ± 0.92.4 ± 1.2
Soil ESM66.1 ± 13.272.3 ± 25.968 ± 20.965.4 ± 24.887.4 ± 31.4101.5 ± 29.4
Root ESM2.5 ± 24 ± 2.84.6 ± 2.13.9 ± 2.89.5 ± 8.47.9 ± 5.4
Above-ground0 ± 05.4 ± 4.16 ± 6.30 ± 05.1 ± 2.25.5 ± 2.4
Total68.5 ± 14.281.6 ± 26.478.5 ± 22.569.2 ± 25.8102.1 ± 36.6114.9 ± 31.9
Table 3. Differences in mean soil, root and above-ground carbon stocks (Mg shrub ha−1) in active fields (A), fallow fields (F) and intact renosterveld (I) in the dry (∼400 mm p.a.) and wet (∼500 mm p.a.) region


  1. Significant differences are in bold (*P < 0.05; **P < 0.01; ***P < 0.001). Soil and root measures are at ESM.

Soil ESM6.21.9−4.322.1**36.1***14.0
Root ESM1.52.1*0.65.7*4.0*−1.6

Farming valuation for renosterveld (all data from Hoffmann 2010)

Annual profits for farming (all crops & livestock) in the Middle Rûens vary from -US$15 ha−1 (i.e. a loss) with poor yields to US$ 42 ha−1 with good yields. The internal rate of return (IRR) on investment (operating costs only) for the Middle Rûens farms in 2010 was estimated as 1.05% (range: 0.94–1.10%) with a crop price of US$ 164 per ton. Climate change is predicted to reduce crop yields in this area and the predicted IRR under a best climate change scenario (in which wheat yields decline by 12%) is 0.29%. Without consideration of climate change, a 10% increase in farm input (fertilizers, fuel, etc.) prices reduces the IRR to 0.4%. With a 10% increase in crop price the IRR increases to 1.89% and with a 10% decrease in crop price the IRR decreases to -0.04%. The net present value of farming in this region is negative.

Valuation of carbon credits from fallowing

The difference in carbon stocks between active and fallow fields was 23.6 Mg C shrub ha−1. This corresponds to a gain of 13.0 Mg C ha−1 based on the average percentage of shrub canopy in fallow fields. Calculated carbon sequestration rates range from 0.5 to 1.3 Mg C ha−1 yr−1 for fields that have been fallow for 10–25 years. This corresponds to 1.9–4.7 Mg CO2e ha−1 yr−1. A conservative range of carbon prices is US$ 5–10 Mg−1 CO2e (see Peters-Stanley et al. 2011). Potential earnings from the sale of carbon credits were therefore conservatively estimated to range from US$ 10 to 48 ha−1 yr−1.


Our results show that ecosystem carbon stocks in fallow fields are comparable to those in intact renosterveld in the Overberg (Table 1), West Coast renosterveld (42–81 Mg C ha−1; Mills et al. 2005) and other Mediterranean ecosystems (e.g. Luo et al. 2007), indicating that passive restoration via fallowing sequesters lost carbon. Fallowing is also likely to benefit conservation—with the restoration of renosterveld vegetation particularly shrubs (see Krug & Krug 2007 and Appendix A) facilitating the return of bird communities (Seymour & Dean 2010), insects, small mammals and ultimately ecosystem services. Indeed, a study by Walton (2006) showed that there is no significant difference in plant species richness between intact renosterveld and 30-year-old fallow fields. Our findings also indicate that potential revenues from the sale of carbon credits are likely to be large enough to incentivise landowners—especially those making losses on farming activities—to restore renosterveld. Although land is sometimes farmed at a loss—which shows that landowners consider more than just economics when taking decisions pertaining to land use and lifestyle—many landowners use a variety of other activities to supplement their income. Such activities include livestock farming, game hunting and ecotourism. On mixed production farms, game hunting is less profitable than livestock farming, and crops provide the smallest income stream (van Hoving 2011). These two points are of relevance for potential carbon project stakeholders because livestock can use fallow lands for grazing and crops would need to be forsaken within a renosterveld carbon project. Furthermore, the present diversification of activities on renosterveld farms suggests that landowners would welcome additional revenue streams.

The findings reported here are intended to inform and catalyse future evaluation of the viability of using carbon credits to finance landscape restoration. There are a number of uncertainties and factors that need to be considered by both public and private sector players when evaluating carbon sequestration projects. These include variation in carbon stocks, agricultural yields, carbon prices, crop prices, permanence, leakage and the influence of grazing and fire on ecosystem carbon stocks (see Table 4 for further details). We note that large transaction costs may need to be incurred by the public sector in the initial stages of carbon projects to reduce the above uncertainties and galvanise investment from the private sector. Public sector involvement can be justified because the end goal is protection and restoration of public environmental goods and services.

Table 4. Examples of factors to consider when evaluating the viability of using CSF projects to finance ecological restoration in marginal agricultural landscapes—using renosterveld as a case study
(1)Carbon stocks, agricultural yields, protection measures and conservation threats vary in the landscape:
 (a) carbon stocks are greater in wet areas (Mills et al. 2005);
 (b) soil carbon stocks vary with climate, topography and soil type;
 (c) agricultural yields (and profits) are greater in wetter areas (Hoffmann 2010); and
 (d) protection measures differ from lowlands to highlands (Kemper et al. 2000).
(2)Carbon stocks, carbon prices, agricultural yields and crop prices vary with time:
 (a) carbon stocks will ultimately plateau (over decades) with an initial rate of increase related to plant growth rates;
 (b) carbon prices are expected to increase through time (Johnston et al. 2011);
 (c) crop yields are expected to change with climate change (Hoffmann 2010);
 (d) soil carbon will change with climate change (Thornley & Cannell 2001); and
 (e) crop prices often vary markedly from year to year.
(3)Carbon credit prices for projects can depend on risks as well as socio-environmental co-benefits of the project (Peters-Stanley et al. 2011).
(4)Carbon sequestration projects need to be formally documented and validated:
 (a) developing carbon sequestration project documents is costly;
 (b) carbon stocks need to be verified; and
 (c) large projects are beneficial due to economies of scale with administrative costs.
(5)Public-private partnerships can be beneficial:
 (a) for funding socio-economic and biophysical research (Gregersen et al. 2010); and
 (b) for meeting project implementation funding shortfalls to landowners by using public service benefits (e.g. water flow and pollination) as motivation (Mills et al. 2010).
(6)Existing conservation initiatives can be beneficial for coordinating and implementing projects (Younge & Fowkes 2003).
(7)Wildfire is likely to influence carbon stocks:
 (a) the extent of influence of wildfires is uncertain;
 (b) a natural fire regime is required to maintain biodiversity; and
 (c) the growth of renosterbos, E. rhinocerotis, is stimulated by fire (Boucher 1995).
(8)Grazing is likely to influence carbon stocks and restoration. Farmers managing for grazing will manage for more grass because renosterbos is not palatable.
(9)The implementation of carbon sequestration projects requires landowner buy-in and local, regional and national support:
 (a) time is required to influence the perspectives of landowners; and
 (b) relevant national policies will make CSF project implementation more likely.
(10)More research is required on the biodiversity gains of fallowing in renosterveld.
(11)Permanence: fallowed fields could be returned to agriculture (Murray et al. 2007).
(12)Leakage: emissions could result outside the CSF project boundary (Murray et al. 2007).
(13)CSF projects in communal (no tenure) agricultural areas would be subjected to increased transaction costs and higher risks.

The use of fallowing to accrue income from carbon credits and restore biodiversity is likely to be useful in other marginal agricultural areas where income from CSF can rival income from crops. However, government policies that promote such initiatives would be required. Specifically, carbon-offsetting options in carbon tax legislation should not be limited to mechanisms such as the Clean Development Mechanism (http://cdm.unfccc.int/) that grants offsets without necessarily benefiting biodiversity, e.g. carbon credits from plantations of exotic trees. Rather offsets that allow for ecological restoration and which include biodiversity and community benefits should be promoted, such as offsets jointly certified by the Verified Carbon Standard (http://v-c-s.org) and the Climate, Community and Biodiversity Alliance (http://www.climate-standards.org).


We thank the Table Mountain Fund for funding this research project; the Overberg land owners for permission to work on their land; SANBI (Kirstenbosch) and Stellenbosch University (Department of Soil Science) for use of their laboratories and ovens; Tanya Medinski for laboratory work assistance; Odette Curtis for site selection assistance and botanical surveys; Peter Coetzee, Omari Asongo and the Bredasdorp team for field assistance; Mireille Lewarne and Willem Hoffmann for information on the economics of land uses in renosterveld; and Weather SA for providing climate data. Three anonymous reviewers are thanked for their constructive comments.

Appendix A

The three most dominant plant species in each region at each site. F = Fallow; I = Intact.

SwellendamFirst speciesSecond speciesThird species
F1Elytropappus rhinocerotisHelichrysum petiolareHyparrhenia hirta
I1Merxmeullera distichaE. rhinocerotisH. petiolare
F2E. rhinocerotisHelichrysum cf petiolareErica cf placentiflora
I2Muraltia cf histeriaE. rhinocerotisM. disticha
F3E. rhinocerotisAthanasia trifurcataCynodon sp.
I3M. distichaE. rhinocerotisOedera genestifolia
F4Cynodon sp.E. rhinocerotisH. petiolare
I4E. rhinocerotisAnthospermum sp.Euryops sp.
F5Berkheya sp.Selago corymbosaH. petiolare
I5H. hirtaAnthospermum sp.Bobartia sp.
F6Pteronia incanaGalenia africanaRhus sp.
I6E. rhinocerotisP. incanaG. africana
F7E. rhinocerotisCynodon sp.Metalasia sp.
I7E. rhinocerotisE. cf placentifloraH. petiolare
F8E. rhinocerotisAthanasia sp.Anthospermum sp.
I8E. cf placentifloraMetalasia sp.E. rhinocerotis
F9E. rhinocerotisHelichrysum teretifoliumCynodon sp.
I9Bobartia longicymaCliffortia sp.E. rhinocerotis
F10Cynodon sp.H. teretifoliumE. rhinocerotis
I10M. distichaE. rhinocerotisO. genestifolia
F1E. rhinocerotisCynodon sp.O. squarrosa
I1M. distichaH. cf petiolareO. squarrosa
F2E. rhinocerotisOedera squarrosaH. cf petiolare
I2Themeda triandraAspalathus nigraE. rhinocerotis
F3E. rhinocerotisBerkheya sp.H. cf petiolare
I3M. distichaE. rhinocerotisAspalathus nigra
F4O. squarrosaE. rhinocerotisEriocephalus sp.
I4M. distichaE. rhinocerotisO. squarrosa
F5E. rhinocerotisH. cf petiolareO. squarrosa
I5E. rhinocerotisO. squarrosaM. disticha
I6E. rhinocerotisO. squarrosaCymbopappus adenosolen
F7P. incanaCynodon sp.N.A.
I7E. rhinocerotisOedera unifloraRelhania garnotii
F8E. rhinocerotisO. squarrosaOxalis sp.
I8M. distichaE. rhinocerotisOedera uniflora
F9E. rhinocerotisO. squarrosaPteronia incana
I9E. rhinocerotisM. distichaC. adenosolen
F10P. incanaOxalis sp.Eriocephalus sp.
I10E. rhinocerotisEriocephalus sp.M. disticha