Land snail biogeography and endemism in south-eastern Africa: Implications for the Maputaland-Pondoland-Albany biodiversity hotspot

limits of the Albany COE for flora [20], land snail endemism in this area extends westward recovering a single Albany-Knysna COE. The overlap of the distribution of forest and Albany thicket biomes with COEs for land-snails (Fig 4D) is noteworthy for further investigation, par- ticularly at a finer scale, while the present study confirms a congruence of endemism between plants and land snails. The data revisited The species selected comprise a representative sample of endemic land snail lineages of SEA and their distributions collectively span much of the study area. More importantly, the land snail genera selected for the study are some of the best collected throughout the study area and PLOS ONE Land snail endemism in the Maputaland-Pondoland-Albany biodiversity hotspot PLOS ONE | https://doi.org/10.1371/journal.pone.0248040 March 4, 2021 17 / 26

vertebrates [22, 24]. Standard methods endorsed by Kreft & Jetz [39] for biogeographical regionalisation, which have been followed by the majority of subsequent studies throughout the world were used for the main analysis of our research, i.e. agglomerative hierarchical clus- tering with UPGMA algorithm. Using this method, we regionalised the area and further iden- tified the geographic clusters of the dendrogram with an aggregation of range overlapping endemic species as COEs. However, we further attempted establishing the AOEs using PAE described by Morrone [59], being the most widely used method for the identification of AOEs (see Morrone [100] for a detailed discussion). PAE is designed for incidence data matrices of equal area grid cells and it performs best using such OGUs. Our data matrix uses pre-defined eco-geographical units as OGUs, and hence several equal area grid cells with ecological similarity are already combined in a single OGU, possibly lowering the power of PAE to define the complete hierarchy of AOEs, as it makes it difficult to numerically establish the strict sympatry of taxa, however still being able to define AOEs based on the clades in area cladogram. Perera et al. [22] described the delimitation of our OGUs through a qualitative overlaying of range maps in identification of endemic vertebrate distributions (= biochoria [70] for endemic vertebrates), which are bio- geographical area units other than AOEs [101, 102]. Therefore, using such units here for iden- tification of AOEs of land snails is not circular and warranted. The determination of AOEs

was the prime objective of carrying out a PAE in our study, while those identified AOEs are perfectly congruent to COEs identified from the UPGMA clustering. PAE has exclusively been used in regionalisation attempts to provide hierarchical area cladograms of geographic units in some global to sub-continental scale studies on entire faunas [24, 60, 61], in which more endemics are captured, increasing the power of the analysis. However, we believe the power of PAE in doing so depends on several factors such as (a) higher numbers of endemic taxa in the matrix, (b) higher number of OGUs being occupied by more than one species, and (c) whether the study uses equal area OGUs defined by a grid of squares. Our OGUs were not equal area units nor were they square in shape, while the matrix had only 73 species with 15 out of 40 OGUs being occupied only by a single or no species (parsimony uninformative), thence PLOS ONE Land snail endemism in the Maputaland-Pondoland-Albany biodiversity hotspot PLOS ONE | https://doi.org/10.1371/journal.pone.0248040 March 4, 2021 18 / 26

resulting in a low level of hierarchical structuring in the PAE area cladogram. Hence, with a restricted spatial extent and taxonomic coverage in our study, we did not attempt a regionali- sation exclusively based on PAE as done in previously mentioned studies. However, less struc- turing in our PAE area cladogram does not necessarily negate the hierarchical structure suggested by the UPGMA clustering, as it depends only on the similarity coefficients between each of the OGUs based on entire species (either endemics or not) assemblages. Consequently, we acknowledge that the present dataset indicates limitations in matching the hierarchical out- puts from PAE and UPGMA clustering approaches. However, in order to test the robustness of endemicity findings, we performed a BEA [63], including a parametric bootstrap test for clustering of distribution areas [64]. Similar to PAE, the BEA has also been designed to be used in grid-based equal area OGUs and hence have a lower power in detecting the structuring in our OGUs, as OGUs with varied shapes result in a neighbourhood matrix with uneven numbers of neighbouring units. However, the BEA indi- cated our data also show a certain degree of clustering (with a test statistic lower than expected by the null model, although with a lower level of statistical significance (p = 0.33)). In evidence to the diminished power of BEA when using non-grid based OGUs, our statistical significance was increased to (p = 0.21), by adjusting our neighbourhood data considering only four neigh-

bouring OGUs for a given unit. Our argument can be further supported by Hausdorf & Hen- nig’s [63] observation that the same dataset when used at different scales clustered well at the 2˚ grid scale, but not at a finer 1˚ grid scale. This illustrates one of the biggest issues in numerical biogeographical analysis, i.e. although the use of equal area grid cells is recommended as the standard practice, it is accompanied by trade-offs of data completeness at fine scales, and distortion of natural boundaries and con- glomeration of habitat heterogeneity (especially crucial if patchy habitats are important for the study lineage) at large scales of equal area grid cells. However, Hennig & Hausdorf [103] pro- poses an approach to be used under such issues of data incompleteness at an appropriate scale of equal area grid cells, which is unsuitable for our data matrix with uneven OGUs. Our study marks (a) the first ever analysis on the biogeography of land snails in south-east- ern Africa and (b) the first attempt to study the biogeography of an invertebrate group of the area using UPGMA based phenetic hierarchical clustering of OGUs. However, an incidence data matrix for the weevil genus Sciobius, at 2˚ grid squares for the same study area has been used by Morrone [59] to introduce and substantiate the application of PAE. Several more stud- ies have used the same dataset to conduct various numerical biogeographic analyses and com- pare their results, viz. Szumik et al. [104] introducing an optimality criterion for AOE

identification; Mast & Nyffeler [105] proposing the use of a null model to recognise significant co-occurrence of taxa; Hausdorf & Hennig [63] introducing BEA also using a null model to test for clustering; Hennig & Hausdorf [103] to account for incomplete sampling in BEA and Escalante [106] comparing PAE with Analysis of Endemicity. Therefore, we not only analysed our dataset using the PAE and BEA in addition to the UPGMA clustering of OGUs, but also checked for cross taxon congruence of our land snail AOEs with those for Sciobius weevils. Our biotic elements support all five COEs of land snails in south-eastern Africa including those six AOEs derived from PAE for the same data set. Furthermore, our land snail COEs and AOEs correspond well with the AOEs and biotic elements of other studies [59, 63, 104– 106] derived for a 2˚ equal area OGU based dataset of Sciobius weevils in south-eastern Africa as summarised in the Table 4. Additionally, two of our biotic elements (elements 7 and 2) sup- port the Knysna extension of the proposed greater MPA region, while two more (elements 9 and 3) supports the argument of the Knysna transition zone between the greater MPA prov- ince proposed here and the greater CFR delimited by Born et al. [70]. PLOS ONE Land snail endemism in the Maputaland-Pondoland-Albany biodiversity hotspot PLOS ONE | https://doi.org/10.1371/journal.pone.0248040 March 4, 2021 19 / 26

A few OGUs such as Drakensberg-Eastern Cape escarpment, northern Natal, southern Middleveld, Waterberg, Highveld-upper Karoo and Inhambane that were inappropriately placed in the cluster dendrogram with comparatively low species richness and endemism may indicate gaps in biogeographic knowledge or more likely artefacts of sampling biases. Northern Natal and Waterberg have recorded none of the selected species while only two species have been recorded from Highveld-upper Karoo, which may indicate gaps in sampling. It is appar- ent that those areas need prioritised attention with respect to malacofaunal inventorying surveys. The northern Natal and Transkei Midlands (adjacent to Drakensberg-Eastern Cape escarp- ment) were also recognised as gaps for vertebrate endemism [22], the latter supporting the idea of a Transkei Gap [107]. However, even if such a real biogeographical gap exists for land snails along the Transkei Midlands/escarpment, it certainly does not extend to the coastal belt, instead identifying the extended Pondoland as one of the most prominent COEs (see Figs 4 and 5). The MPA hotspot, the greater MPA region of endemism and conservation implications While the hotspot status of the MPA is further confirmed by its malacofauna, the greater MPA region provides a zoogeographically delimited broader region of land snail endemism with five COEs serving as local conservation priorities. A remarkable 72% of the species restricted to COEs are narrow endemics, highlighting the habitat heterogeneity provided within the

greater MPA region of endemism. Endemism-based intuitive malacofaunal subregions pre- sented for eastern SA [13] captured similar (if not finer) geographical entities congruent with our Natal and extended Pondoland COEs as well as an eastern escarpment (sections of the great escarpment in Mpumalanga and Swaziland) extension, further supporting the greater MPA region of land snail endemism. Further, the six AOEs derived from PAE and the nine biotic elements yielded from BEA are congruent to those five COEs, well supporting our pro- posals for the greater MPA region of land snail endemism and the Knysna transition zone between the greater CFR and the greater MPA region. Table 4. Comparison of centres and areas of land snail endemism in south-eastern Africa (SEA), defined in the present study through UPGMA clustering, PAE and BEA with similar areas defined for Sciobius weevils of south-eastern Africa using various methods employed in previous studies. Reference Taxa Units Method Comparison of Results Present study Land snails of SEA COEs UPGMA Sky islands Extended Maputaland Natal Extended Pondoland Albany-Knysna AOEs PAE Soutpansberg Extended Maputaland Natal Extended Pondoland Albany-Knysna Wolkberg BEs BEA Element 4 Element 8 Elements 5 & 6 Element 1 Elements 2 & 7 Morrone [59] Sciobius weevils of SEA AOEs PAE - Area 1 (partly) Area 1 Area 3 Area 2 Szumik et al. [104] AOEs AE Sets 10 & 11 (partly) Sets 2, 10 & 11 Sets 1, 4, 5, 6, 7, 8 & 9 Set 7 Sets 3, 12, 13 & 14 Mast & Nyffeler [105] AOEs PAE - Area 1 (partly) Areas 1 Area 3 Area 2

Hausdorf & Hennig [63] BEs BEA Element 1 (partly) Element 1 Element 2 Element 4 Element 3 Escalante [106] AOEs AE Set 2 (partly) Set 2 Sets 0, 2 & 3 Set 3 Set 1 (UPGMA—phenetic hierarchical clustering with UPGMA algorithm with the Jaccard index; PAE–Parsimony analysis of endemicity; BEA–Biotic element analysis; AE— Analysis of Endemicity; BEs–Biotic Elements). https://doi.org/10.1371/journal.pone.0248040.t004 PLOS ONE Land snail endemism in the Maputaland-Pondoland-Albany biodiversity hotspot PLOS ONE | https://doi.org/10.1371/journal.pone.0248040 March 4, 2021 20 / 26

The greater MPA region for land snails is much similar to that recognized for vertebrates [24], than to the more restricted MPA hotspot. This suggests the possibility of the greater MPA being a common region of animal endemism–one that needs to be tested for cross-taxon con- gruence with other invertebrate groups. The current vertebrate bias in conservation planning needs to be addressed as more data become available for invertebrate groups, which can sub- stantially broaden the taxonomic basis for conservation prioritization [9, 108–111]. Since many invertebrate groups have limited vagility, they also facilitate the identification of CONEs, which might be overlooked in an analysis of the flora or vertebrate fauna at the same scale. A preliminary spatial comparison of CONEs with existing protected areas reveals a major gap in Pondoland and the southern Transkei coastal belt (Fig 4E), where the land snail endemism is highest (Fig 5), while Natal Midlands, Natal coastal belt-Ngoye, northern Mpu- malanga Escarpment and Soutpansberg are also not adequately protected. Hence, as acknowl- edged previously [15], the protection of CONEs identified here needs urgent attention. Mechanisms for the protection of smaller parcels of land targeted at the conservation of nar- row endemic and less vagile invertebrates need to be included into conservation planning. Supporting information S1 Appendix. Land snail species incidence matrix (n = 73; 12 genera and three families) in 40 operational geographic units (OGUs). See Fig 1 for the OGU codes. (XLSX) Acknowledgments

We thank Dayani Ratnayake-Perera, Nikara Mahadeo and Lasith Viduranga Perera for help with the data analyses, mapping and discussion. Prof. Bernhard Hausdorf, Prof. Jeff Nekola and anonymous reviewers, as well as Prof. Geerat J. Vermeij the academic editor of PLOS ONE provided insightful comments on earlier versions of this manuscript. Author Contributions Conceptualization: Sandun J. Perera, David G. Herbert, Şerban Procheş. Data curation: Sandun J. Perera, David G. Herbert. Formal analysis: Sandun J. Perera, Syd Ramdhani. Funding acquisition: Sandun J. Perera, David G. Herbert, Şerban Procheş. Investigation: Sandun J. Perera, David G. Herbert, Şerban Procheş, Syd Ramdhani. Methodology: Sandun J. Perera, Şerban Procheş, Syd Ramdhani. Project administration: David G. Herbert, Şerban Procheş. Resources: David G. Herbert, Şerban Procheş, Syd Ramdhani. Software: Şerban Procheş, Syd Ramdhani. Supervision: David G. Herbert, Şerban Procheş. Validation: Şerban Procheş, Syd Ramdhani. Visualization: Sandun J. Perera. Writing – original draft: Sandun J. Perera. Writing – review & editing: David G. Herbert, Şerban Procheş, Syd Ramdhani. PLOS ONE Land snail endemism in the Maputaland-Pondoland-Albany biodiversity hotspot PLOS ONE | https://doi.org/10.1371/journal.pone.0248040 March 4, 2021 21 / 26

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