88 vegetation, whereas Pteridophyta are higher pollen producers in a same sized area of vegetation. Specifically, 1m2 of Poaceae produces ≈ 3.5 times less pollen than 1m2 of Rosaceae and 1m2 of Ericaceae vegetation produces ≈ 6 times less pollen than 1m2 of Rosaceae, and Pteridophyta produces ≈ 7 times more pollen than 1m2 of Rosaceae (Chapter 4 – Table 4.5). Moreover, PPE values suggest that in a given pollen assemblage taken from the Leucosidea scrubland, Poaceae and Ericaceae are under-represented as there is theoretically a high quantity of vegetation of this taxon in a landscape which reflects only in a low abundance in the pollen spectra, and Pteridophyta are over-represented as there is theoretically a low quantity of vegetation of this taxa and this reflects in a high abundance in the pollen spectra.
5.5.1. ERV analysis: limitations and recommendations
The number of samples collected for pollen modelling research compromises RSAP and PPE calculations when running ERV models and its subsequent ability to find solutions. The more pollen and vegetation data the models have to run, the more certainty can be placed in their outputs. A recommendation to improve RSAP and PPE calculations would therefore be to have as many samples from as many sites as is possible to enhance the dependability and certainty of ERV analysis results. Furthermore, a recommendation would be to use different distance weighting models to investigate confidence levels in the use of these models and their relevance to site-specific data sets.
89 Origins of pollen modelling were theoretically developed in the 1960s beginning with Davis’
R-value model, succeeded by Andersen’s model in the 1970s and then progressing to Extended R-value models in the 1980s. Pollen modeling has, however, predominantly found mainstream interest in Europe since the 2000s. Many regions of Europe have employed models of pollen dispersal and deposition to calculate PPE and RSAP for specific environments using ERV models. These include England (Bunting et al., 2005), Finland (Räsänen et al., 2007), Sweden (Broström et al., 2004; Sugita et al., 1999; von Stedingk et al., 2008), Norway (Hjelle, 1998), Denmark (Nielsen, 2003), Switzerland (Mazier et al., 2008; Soepboer et al., 2007) and the Czech Republic (Abraham and Kozáková, 2012). To date, there has been one study undertaken in Africa. Duffin and Bunting (2008) have calculated RSAP and PPE for southern Africa savanna taxa in the Savanna Biome of the Kruger National Park.
Duffin and Bunting (2008) used ERV models to analyse modern pollen spectra from 34 surface sediment samples in association with its surrounding vegetation to analyse key savanna taxa and thus calculate PPE values and RSAP. A significant difference between this research and Duffin and Bunting’s (2008) research lies in the fact that a comparison of all distance-weighting methods were used as opposed to only Sutton’s taxon-specific weighting.
The RSAP for all sites was estimated at 700 m, which is considerably greater than the approximated 150 m in this study. A key point here is that Duffin and Bunting (2008) sampled small ponds, not soil samples, and so had much larger sampling basins to work with.
RSAP differences could also be attributed to the different sampling strategies in zones A and B of the vegetation surveys done between the two research projects or due to the differences in openness of the Kruger National Park landscape and the topographical complexity of Cathedral Peak (Gaillard et al., 2008).
Species’ dispersal ability has a direct influence on RSAP estimations as the better dispersed taxa will result in larger RSAP values in a landscape (Gaillard et al., 2008). PPE values of taxa between the two research projects are not so easily compared, as different taxa assemblages exist in these two environments and moreover were used for modelling. The aim of Duffin and Bunting’s (2008) research was to present these PPE and RSAP estimates as a basis for improved interpretation of past and future fossil pollen archives collected from the savanna biome. This aim is aligned to objectives of this research, and so Duffin and Bunting’s (2008) work was a key text. Considering it is the only study done in South Africa pertaining to ERV analysis and the calculation of PPE and RSAP values for African taxa, it
90 illustrated that these European developed pollen models of dispersal and deposition can be suitably used in an African context. This research builds on this view, and results attest to the suitability of using these models in African pollen research.
In sum, data extracted from 15 surface soil samples and its associated surrounding modern vegetation inventory in Cathedral Peak were used to run pollen models in an Afro-montane landscape. While model outputs were not ‘perfect’ as would be the case in an open, homogeneous European landscape (and for which these models were expressly developed), they show that sound and applicable information can be produced for an environment such as Cathedral Peak. Furthermore, results produced in this research suggests that future pollen research in the Cathedral Peak region, particularly those concerning fossil pollen studies and palaeoenvironmental reconstructions, have a reliable tool and resource on which they can supplement, and moreover, base their interpretations on. In this regard, future researchers can use the PPE values determined here for dominant taxa in Cathedral Peak vegetation communities in association with the HUMPOL software suite to simulate numerical past vegetation abundances, and use RSAP estimates to attach spatial attributes to vegetation assemblages when reconstructing past environments. RSAP calculations can also help future research to assess dispersal abilities of taxa in Cathedral Peak, make inferences of basin sizes and how these influence the pollen assemblages extracted from Cathedral Peak environments.
This research and its positive findings thus have significant implications and influences for prospective fossil pollen research and palaeoecological science in the Cathedral Peak area.
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