BOTHALIA – African Biodiversity & Conservation ISSN: (Online) 2311-9284, (Print) 0006-8241 | Open accesshttp://abcjournal.org | | Original researchPage 1 of 62   Authors 1Philip G. Desmet  2Greer Hawley  3,4Anisha Dayaram  5R. John Power  6Reuben Heydenrych  7Catherine M. Dzerefos  5Ray Schaller  8Norbert Hahn  9Nancy Job  Affiliations 1Department of Zoology, Nelson Mandela University, P.O. Box 77000, Gqeberha 6031, South Africa. 2Rhodes University, Department of Biochemistry and Microbiology, Biological Sciences Building, Lower University Road, Makhanda 6140, South Africa. 3Biodiversity Assessment and Monitoring Division, South African National Biodiversity Institute, Private Bag X7, Claremont, Cape Town 7735, South Africa. 4Restoration and Conservation Biology Research Group, Centre for African Ecology, School of Animal, Plant & Environmental Sciences, University of the Witwatersrand, 1 Jan Smuts Ave., Braamfontein, Johannesburg, South Africa. 5Chief Directorate of Environmental Services, Department of Economic Development, Environment, Conservation & Tourism (DEDECT), North West Provincial Government, Private Bag X 2039, Mahikeng 2735, South Africa. 6313 Jeremy St, Lynnwood Park, Pretoria 0081, South Africa. 7Department of Environmental, Water and Earth Sciences, Tshwane University of Technology, Private Bag X680, Pretoria, South Africa. 8Department of Biological Sciences, Faculty of Science, Engineering and Agriculture, University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa. 9Freshwater Biodiversity Programme, South African National Biodiversity Institute, Private Bag X7, Claremont, Cape Town 7735, South Africa. Corresponding Author Philip G. Desmet; e-mail: drphil@ecosolgis.com Dates Submitted: 24 October 2023 Accepted: 12 April 2024 Published: 11 October 2024 How to cite this article: Desmet, P.G., Hawley, G., Dayaram, A, Power, R.J., Heydenrych, R., Dzerefos, C.M., Schaller, R., Hahn, N., Job, N., 2024, ‘Revision of the North West province, South Africa, vegetation map’, Bothalia 54, a10. http://dx.doi. org/10.38201/btha.abc.v54.10 Copyright: © 2024. The Authors. Licensee: SANBI. This work is licensed under the Creative Commons Attribution 4.0 International License Background: The vegetation type boundaries in the North West province as they appear in the 2018 National Vege- tation Map, for the most part, are derived from agricultural land types that were mapped in the 1980s. Aim & objectives: Given (1) the importance the National Vegetation Map plays in conservation assessment and plan- ning, as well as environmental planning and decision making; and (2) the map boundary errors reported by users, an update of the provincial vegetation map was considered necessary. Methods: A vegetation identification key using high-level environmental parameters (in order of importance: flood- ing, bioregion, terrain, geology and soil) was developed. This key was used to manually interpret high-resolution colour aerial imagery, together with existing environmental spatial datasets (land types as a proxy for soils, simplified geology and terrain/land form). The existing vegetation type concepts are sound and are mostly retained in this map. Results & conclusion: Changes to the map include: (1) all vegetation boundaries in the province are remapped; (2) Olea Sclerophyllous Forest is proposed as a sub type/com- munity related to the Northern Afrotemperate Forest vege- tation type; (3) two existing vegetation types currently not mapped as occurring in the province are brought into the province, namely, Subtropical Alluvial Vegetation and Wa- terberg Mountain Bushveld; and (4) three vegetation units recognised in previous vegetation studies and which are not indicated in the current National Vegetation Map are includ- ed here as new vegetation types, namely, Vryburg Thornveld, Morokweng Thornveld and Central Sandy Mountain Bush- veld. The descriptions of all terrestrial vegetation types oc- curring in the province are also updated and an updated an- notated global plant species list for the province is provided. Changes reflected in this vegetation map have been incorpo- rated into the National Vegetation Map Version 2024 beta. Keywords: North West, vegetation map, classification, ecosystem type, revision. Introduction The South African vegetation map is a national scale map of the terrestrial ecosystems found within the country. The cur- rent National Vegetation Map, first published in 2006 (Mu- cina & Rutherford 2006) and updated in 2018 (Dayaram et Revision of the North West province, South Africa, vegetation map https://orcid.org/0000-0003-0342-2981 https://orcid.org/0000-0002-9097-505X https://orcid.org/0000-0003-4160-812X https://orcid.org/0000-0002-0684-4007 https://orcid.org/0009-0009-2814-4958 https://orcid.org/0000-0001-6158-5039 https://orcid.org/0009-0005-1981-1422 https://orcid.org/0000-0002-1186-7713 https://orcid.org/0000-0002-4929-7592 mailto:drphil%40ecosolgis.com?subject= http://dx.doi.org/10.38201/btha.abc.v54.10 http://dx.doi.org/10.38201/btha.abc.v54.10 00400305 Highlight 00400305 Highlight | Original research | Open accesshttp://abcjournal.org | Page 2 of 62   al. 2019), includes 459 unique vegetation types of which 35 terrestrial and six azonal types occur in the North West province (NW). A beta release of the next version was released in 2024 (SANBI 2006–2024), which now incorporates revisions from work in this paper. The purpose of the National Vegetation Map is to: a) provide a coarse-filter spatial surrogate that broadly rep- resents biodiversity patterns across the whole country; b) provide ecologically relevant environmental manage- ment units; and c) provide ecologically meaningful units that can be used in environmental planning and manage- ment (Dayaram et al. 2021). Consequently, it is generally regarded as the national map of terrestrial ecosystems for the country. While itself not formally mandated by law, in practice the National Vegetation Map is regarded as one of South Africa’s foundational biodiversity datasets that has an important legislative function, as it informs a number of government environmental and biodiversity planning and management tools, such as maps of Critical Biodiversity Areas and Ecological Support Areas; protect- ed area expansion strategies; and forms a basis for en- vironmental impact assessment. Thus, poorly delineated vegetation types can lead to poor outcomes for conserva- tion planning, land management and planning decisions, and ultimately the loss of biodiversity. Each vegetation type delineates and describes the parts of the landscape that share similar plant communities that are influenced or determined by shared environmental drivers (Mucina & Rutherford 2006). These maps are es- sentially models of the natural variation observable in any landscape. They reduce the complexity and continuity of natural landscapes to a set of discrete categories. Irrespec- tive of the methods used to classify landscapes there are invariably mapping errors, especially where the transition between ecosystems is a continuum rather than being marked by a clear boundary and where landscapes have been significantly modified. The National Vegetation Map aims to map the original or historical extent of eco- systems before contemporary settlements, croplands and mining modified landscapes. This is defined as the eco- systems present prior to the advent of permanent Europe- an settlement in South Africa circa 350 years ago (Mucina & Rutherford 2006). This is a pragmatic, albeit problem- atic, threshold as it does not consider the impact of pre- colonial populations on vegetation as significant, whereas it is highly likely that these populations did have extensive and significant impacts on ecosystems (e.g., Sadr 2022). As such, ecosystem classification and mapping can be particularly problematic in highly modified landscapes. In these instances, understanding the key environmental determinants of ecosystems is very important for map- ping the original extent of vegetation. Given the central role that the South African vegetation map plays in land and environmental management and biodiversity conservation, there is an imperative to main- tain and update this map to reflect the best available data and emerging knowledge of historical vegetation. In the NW, concerns were raised during the preparation of the North West Biodiversity Sector Plan (NW READ 2015) that the current provincial vegetation map, which is based on the National Vegetation Map published in Mucina and Rutherford (2006), did not accurately reflect observed vegetation patterns. Three important accuracy issues were identified with respect to the 2006 vegeta- tion map: 1. Inaccurate delineation of vegetation type bounda- ries. 2. Incorrect assignment of areas to a vegetation type class that did not reflect the characteristics of com- munities observed on the ground. 3. Redundant vegetation type descriptions and the existence of new or undescribed vegetation types. Therefore, the purpose of this project was to resolve these issues in the NW vegetation map using currently available datasets, and to publish the revised vegetation map while aligning to SANBI’s guidelines for revisions (Dayaram et al. 2021). Once published, the NW vege- tation map can be reviewed for incorporation into the National Vegetation Map. Whilst the current NW portion of the National Vegeta- tion Map was published in 2006, the origin of the vegeta- tion type boundaries as they currently appear in the map can be traced back to the agricultural land type maps prepared by the Department of Agriculture (Mucina et al. 2006). Land types were originally designed to serve the agricultural industry, and these would be areas with gen- erally uniform climate, terrain and soil patterns (MacVicar et al. 1974). The vegetation type boundaries as mapped in the 2006 National Vegetation Map are based on a vegetation map for the NW prepared by Bredenkamp and Brown (2003a). Unfortunately, all metadata relating to the de- velopment of this map was lost other than a hard-copy version of this map that was subsequently digitised1. The boundaries in this map, however, appear to be based predominately on the agricultural land type maps for NW. This assumption is supported by a comparison of the boundaries between the Bredenkamp and Brown (2003a) and the land type maps that indicates there is an 80% spatial coincidence of boundaries between the two maps (Figure 1). There has been significant development and refinement in the vegetation type concepts since Acocks (1953, 1975, 1988), but there has been compar- atively little refinement of the vegetation type boundar- ies in the NW. Essentially, the majority of vegetation type boundaries as they appear in the 2006 vegetation map, 1Leslie Brown and Ray Schaller pers. comm. | Original research | Open accesshttp://abcjournal.org | Page 3 of 62   and subsequent 2018 map, were first mapped some- time in the 1980s. With the current availability of high- resolution aerial imagery, the emergence of desktop Geo- graphic Information System (GIS) mapping technology, as well as the increased importance and use of the vege- tation map for site-based environmental management, these have exposed the boundary errors inherent in the 2006 map and have highlighted the need to update the boundary mapping in this map. The vegetation concepts and descriptions in the NW vegetation map draw on concepts in previous vegeta- tion maps of South Africa (Acocks 1988; Low & Rebelo 1996), as well as the Bredenkamp and Brown (2003a) vegetation map. There are at least 93 published studies or reports relating directly to the vegetation of the NW. This body of literature, however, discusses almost exclu- sively vegetation concepts at the plant community scale. There are few quantitative studies that explicitly explore the floristic and environmental relationships between phytosociological units at the scale of the vegetation type, and none that attempt to define vegetation types using phytosociological approaches or discuss relationships be- tween phytosociological units and vegetation types. This is not unexpected as the bulk of the relevant vege- tation science literature predates the current vegetation type concepts published in 2006. Post-2006 there has been very little phytosociological research published that covers the northwest region of South Africa. The absence of research directly exploring the relationships between phytosociological units and vegetation types, whilst not unexpected, highlights a very important veg- etation science research gap. There is a clear need for more quantitative vegetation science research to devel- op and refine the current vegetation type concepts at the spatial scale at which they are conceived, as this provides the scientific justification for the concepts which is necessary to affirm the application of vegeta- tion types in legislative and legal processes. Bredenkamp and Brown (2003b) used a phytosociolog- ical approach to define higher-order vegetation associ- ation concepts for the Bankenveld in the Highveld re- gion that are at a similar conceptual scale to vegetation types. Similarly, Winterbach (1998) and Winterbach et al. (2000) defined higher-order vegetation association concepts in the Arid Sweet Bushveld region of the NW to derive units that approach vegetation types. Van der Meulen and Westfall (1979) used agricultural land types as the basis to define and delineate vegetation units. In all these studies the same basic set of environmental elements are associated with these higher-order units, Figure 1. The spatial relationship between the vegetation type boundaries mapped in Bredenkamp and Brown (2003a) versus agricultural land types. | Original research | Open accesshttp://abcjournal.org | namely, soil (clay vs sandy soils on plains), terrain (plains vs mountains) and geology (quartzite vs igneous). The spatial extent of individual vegetation studies rele- vant to the NW varies considerably. Some studies accept the agricultural land types as acceptable vegetation map- ping units and conduct phytosociological analyses within these units (Bezuidenhout et al. 1993; Bezuidenhout et al. 1994a, 1994b) or across these units (Van der Meulen & Westfall 1979; Smit 2000). Other studies are conduct- ed at a broader general geographic area (Morris 1976; Bredenkamp et al. 1989; Bezuidenhout & Bredenkamp 1990; Du Preez & Venter 1990a, 1990b; Bezuidenhout et al. 1994c, 1994d), or geological area (Bezuidenhout et al. 1988; Bezuidenhout et al. 1994b), or protected area (Van Zyl 1965; Coetzee 1975; Bredenkamp & Bezuid- enhout 1990; Bredenkamp et al. 1994; Stalmans & De Wet 2003), or even part of a protected area (Brown & Bredenkamp 1994; Brown et al. 1995, 1996). There are at least 29 published papers or reports that include fine-scale vegetation maps for their respective study areas that are relevant to the NW (Figure 2). Ex- cluded from this list are phytosociological studies that used agricultural land types as the mapping unit rather than generating their own vegetation maps (e.g. Be- zuidenhout et al. 1993; Bezuidenhout et al. 1994a, 1994b; Smit 2000; Van der Meulen & Westfall 1979). Collectively, these fine-scale maps cover 260 000 ha or 2.5% of the province. Despite there being a reason- able wealth of vegetation studies relevant to the region, there is a relative paucity in the extent of published vegetation maps. Added to this is the lack of curation of this information with none of the vegetation maps having spatial data in an accessible data archive. Whilst the vegetation type concept has been accepted and used in South Africa at least since Acocks (1953), it was only in the 2006 version of the vegetation map that the current vegetation type concept was clearly articulat- ed and defined (Mucina et al. 2006). Despite this major advance in the vegetation map, at least for the vegetation types occurring in the NW, it is not clear in the current delineation and description of the vegetation types what are the environmental variables or factors and species or communities that differentiate one vegetation type from another. These variables are implicit in the ‘verbal mod- els’ used to define and delineate vegetation types (Muci- na et al. 2006). However, a clear functional understand- ing or description of the differentiating factors between vegetation types is absent in the current descriptions of vegetation types. This is often cited by users of the NW vegetation map as being a limitation to using and inter- preting the current map at the site level. Figure 2. The extent of published fine-scale vegetation maps and available relevé data in and around the North West province (NW). Page 4 of 62   | Original research | Open accesshttp://abcjournal.org | The National Vegetation Map is mapped at a broad spatial scale of a whole region or landscape. At the site level there will inevitably be boundary errors when us- ing the vegetation map due to the difference between the scale of map production and scale of use. There- fore, users invariably have to interpret on-the-ground observations of vegetation patterns to ‘fine scale’ the vegetation map and determine the appropriate vege- tation type or types occurring at a site. For users of the vegetation map to be able to make this interpretation at the site level, an understanding of the relationship be- tween underlying environmental variables and the de- lineation of vegetation types is necessary. Having a clear understanding or model for where and why vegetation types occur is essential for the consistent and defensi- ble mapping of vegetation boundaries, and ultimately the integrity of the vegetation type concept. Whilst this thinking is implicit in the current delineation of vegeta- tion types, it is not, however, always made explicit or clear in the current vegetation type descriptions. Given these observations and limitations of the current National Vegetation Map in the NW, the objectives of this project were to: 1. Draw on the existing vegetation type classification and descriptions to develop an identification key to vegetation types in the NW based on broad envi- ronmental variables. 2. Review existing studies, expert inputs and field ob- servations to determine if there are redundant veg- etation types (i.e., two vegetation types that can be merged) or undescribed vegetation types that need to be added to the map and, where possible, sup- port proposed changes with numerical data, and use this information to update the current vegeta- tion type descriptions. 3. Using the identification key in conjunction with available environmental spatial data and current high-resolution aerial imagery, remap vegetation type boundaries at a higher spatial resolution. Study area The NW is located on the African Plateau in central southern Africa on the border between South Africa and southern Botswana. The province is 104 881 km2 and measures roughly 550 km (east–west) by 380 km (north– south). It straddles three major physiographic regions: in the west, parts of the Kalahari region, in the northeast, the Bushveld region and in the southeast, the Highveld region. These broad geographic regions are associated with three major drainage systems, namely the Molopo catchment in the Kalahari, Vaal catchment in the High- veld and Limpopo catchment in the Bushveld. The Mol- opo and Vaal systems drain towards the west into the Orange River and ultimately the Atlantic Ocean, whereas the Limpopo system drains to the northeast into the Indi- an Ocean (Figure 3A). The median elevation of the NW is 1 271 m (mean 1 263 m, minimum 904 m, maximum 1 817 m). It is a relatively flat to gently undulating landscape punctuated with few and scattered regions of hills or mountains (Figure 3A). The major mountain ranges of the province are to be found in the Northern Bankenveld entailing the Dwars- berg and Rant van Tweedepoort, the Southern Bankenveld entailing the Magaliesberg, Witwatersberg, Enzelsberg and Swartruggens (Partridge et al. 2010), the Pilanesberg, the hilly landscape spanning between Wolmaransstad to Hart- beesfontein known as the Maquassi Hills, the predomi- nantly east-facing low cliffs of the Ghaap Plateau forming a west dipping cuesta on the border between the NW and Northern Cape, and the Vredefort Dome in the south- east bordering Gauteng and Free State provinces. For all these mountain ranges the elevational range between the surrounding plains, valleys and summits rarely exceeds 300 m. The largest altitudinal gradient is located in the western Magaliesberg and Pilanesberg, where the maxi- mum elevational range is approximately 600 m. The climate of the NW is humid to semi-arid subtrop- ical in character. Rainfall ranges from near 800 mm per annum in the Highveld on the eastern border with Gauteng and decreases to 250 mm in the extreme west of the province. There is a single summer-rainfall season from October through to April. Temperatures are cool- est with higher incidence of frost on the Highveld, while the northern savannas are warmest. The Kalahari region has the warmest summer temperatures and the Bushveld region the mildest winters (Figure 4 and 5). Mucina and Rutherford (2006) described the climate of each vegeta- tion type in more detail. The geology of the region is varied (Figure 6); however, a singular dominant factor influencing vegetation patterns across the province is the widespread presence of Ter- tiary aeolian Kalahari sand. Outside of the Kalahari re- gion, relic pockets of these sands can be encountered throughout most of the province. In terms of the under- lying geology, important rock types with strong influences on vegetation are quartzite-rich sedimentary rocks giving rise to dystrophic sandy soils contrasted with mafic and ultramafic rocks giving rise to base-rich clay soils. The flora of the NW is discussed in some detail by Hahn (2013). The flora is characterised by comprising mostly widespread species with very low levels of endemism. There are at least 2 786 species (2 387 indigenous and 399 not indigenous) recorded in the NW (see Supple- mentary Material 1) with 16 species (0.6%) known to be endemic or near-endemic to the province (Hahn 2013). Five species (44%) within this group of endemic species are associated with dystrophic quartzite geology of the Magaliesberg and Swartruggens regions, which is as- signed to the Gold Reef Mountain Bushveld vegetation type (Table 1). Page 5 of 62   | Original research | Open accesshttp://abcjournal.org | Figure 3. A, elevation and hydrology; B, mean annual precipitation in the North West province. A B Page 6 of 62   | Original research | Open accesshttp://abcjournal.org | Figure 4. A, daily mean temperature for warmest; and B, coldest months in the North West province. A B Page 7 of 62   | Original research | Open accesshttp://abcjournal.org | Figure 5. The number of frost days in the North West province. Page 8 of 62   Table 1. Known endemic (E) and near-endemic (nE) species to the North West province after Hahn (2013). Q = species endemic to the quartzite geology of the Gold Reef Mountain Bushveld vegetation type. R = Rare according to the national Red List categories ID Species name Endemicity Quartzite endemic 1 Aloe peglerae nE Q 2 Blepharis angusta E 3 Brachystelma canum E, R 4 Brachystelma gracillimum E, R Q 5 Ceropegia insignis nE 6 Euphorbia knobelii E Q 7 Frithia pulchra nE Q 8 Gladiolus filiformis nE 9 Indigofera commixta E 10 Ledebouria atrobrunnea nE 11 Miraglossum laeve nE 12 Nuxia glomerulata nE 13 Pentzia stellata nE 14 Senecio holubii E, R Q | Original research | Open accesshttp://abcjournal.org | A Figure 6. Spatial datasets used to inform the revision of the North West province vegetation map: A, simplified geology based on the 1:250 000 Geology of South Africa dataset; B, agricultural land types. B Page 9 of 62   | Original research | Open accesshttp://abcjournal.org | A Figure 7. Spatial datasets used to inform the revision of the North West province vegetation map: A, Bredenkamp and Brown (2003a) vegetation map of the North West province; and B, the current 2018 National Vegetation Map (NVM) of South African vegetation types for the North West province (Dayaram et al. 2019). Page 10 of 62   B | Original research | Open accesshttp://abcjournal.org | Methods Vegetation mapping Vegetation type polygons were manually mapped using a heads-up digitising technique (Kennedy 2009). The vegetation types were delineated by interpreting pat- terns observed in colour aerial imagery overlayed with data layers representing the environmental variables used in the identification key to define vegetation types, namely: (1) land types as a proxy for soils, (2) simplified geology, and (3) terrain. In total 24 spatial datasets were used to inform the mapping process (Table 2). In addition to the vegetation type identification key that provides a regional-scale framework for interpreting and mapping vegetation types, field observations and published descriptions of landform-vegetation relation- ships were also used to interpret patterns in aerial imag- ery at the local scale. Examples of landform–vegetation relationships include catena vegetation sequences or agricultural landtype map descriptions of landform–soil relationships. Different vegetation communities are as- sociated with different landforms, and the landform– vegetation patterns tend to differ between vegetation types. Vegetation identification key To map vegetation in a logical and defensible manner it is necessary to have a framework for how vegetation types are classified and related to one another based on vegetation and floristic patterns and underlying en- vironmental variables or determinants of vegetation types. Mucina et al. (2006) describe such a classification framework for how vegetation types in South Africa are circumscribed that forms the basis for how vegetation types are defined and mapped in the current National Vegetation Map. As described in the introduction, in the NW it is often not clear from the existing verbal models describing vegetation types what the defining features are of a vegetation type and what separates one vegetation type from another. Therefore, before any remapping of vegetation type boundaries could be attempted it was necessary to distil from existing vege- tation type descriptions, expert inputs, published veg- etation studies and field observations what the key en- vironmental determinants are for each vegetation type, and use this information to develop an identification key to the vegetation types being mapped. Vegetation type mapping is generally not concerned with mapping plant assemblage boundaries, but rather mapping higher-order spatial scale environmental dis- continuities such as aspect, slope, elevation, soil, geol- ogy and landform. These are the same variables used to define land types, hence the close historic association between land types and vegetation types. The identi- fication key developed here uses only broad environ- mental variables to define vegetation units stratified by bioregions or biomes, which represent the major cli- matic gradients present in the province. As the first step in remapping the vegetation type boundaries of the NW, a basic identification key to the vegetation types of the province based on mappable en- vironmental variables was developed. This key provid- ed the quantitative framework within which input en- vironmental and imagery datasets could be interpreted and vegetation boundaries mapped in the GIS. The key was based primarily on environmental attributes, but to increase utility for vegetation type identification in the field, broad vegetation structural attribute data was also included in the key. Vegetation structural characteristics are a function of underlying environmental attributes but are not always observable in single observation co- lour aerial imagery and therefore are not necessarily a reliable variable to use for mapping vegetation. Species data Plant species information was collated from existing data sources, as well as from data collected by this proj- ect. Data sources include: 1. Herbarium record data from SANBI’s POSA data- base (SANBI 2016). 2. Published vegetation surveys that have been col- lated and archived in SANBI’s National Vegetation Map Database (NVD). 3. Rapid vegetation survey plots and species obser- vations conducted by this project and added to iNaturalist. A current global species list for the province was cre- ated from herbarium record data. The purpose of the global species list was to provide a total flora context for the vegetation survey plot data and also provide a master species list against which to compare and correct plot species data. Data from SANBI’s POSA database was obtained via a direct data request. The NW includes all or part of 229 unique quarter degree squares (QDS). Vegetation survey plot data from most of the phyto- sociological studies that have been undertaken in the province have been collated and archived in the NVD. This is a national database that strives to archive all published vegetation survey data in South Africa. The database currently hosts data for about 58 000 plots. Plots from in and around the NW were extracted from this database for analysis. The purpose of this data was to: (1) inform the important species information in the vegetation type descriptions; and (2) to con- duct an ordination analysis to compare the numerical Page 11 of 62   | Original research | Open accesshttp://abcjournal.org | Ta bl e 2. S um m ar y of th e in pu t d at as et s in fo rm in g th e m ap pi ng p ro ce ss O ri gi na l d at a so ur ce D er iv ed d at a la ye r na m e D at a fo rm at So ur ce D ig ita l E le va tio n M od el (D EM ) 1 El ev at io n (JA XA 3 0m D EM ) ( Fi gu re 3 A) Ra st er Ja pa n Ae ro sp ac e Ex pl or at io n Ag en cy (J AX A) 2 Sl op e Ra st er Th is pr oj ec t u sin g Ar cG IS a nd W hi te bo x te rr ai n an al ys is to ol s 3 As pe ct Ra st er 4 To po gr ap hi c po sit io n Ra st er G eo lo gy 5 1: 25 0 00 0 G eo lo gy o f S ou th A fri ca s im pl ifi ed to b as ic g eo lo gi ca l t yp es (F ig ur e 6A ). Li th os tra tig ra ph ic n om en cl at ur e of g eo lo gi ca l t yp es a re di sp en se d w ith in fa vo ur o f s im pl ifi ed g eo lo gi ca l d es cr ip tio ns th at li nk m or e cl os el y w ith g eo lo gy g en er al p hy sic al a nd c he m ic al p ro pe rti es . Ve ct or p ol y C ou nc il fo r G eo Sc ie nc e Si m pl ifi ed ty pe s – th is pr oj ec t M od el le d hy dr ol og y fro m D EM 6 St re am lin es Ve ct or li ne Th is pr oj ec t u sin g W hi te bo x hy dr ol og ic al to ol s 7 C at ch m en ts Ve ct or p ol y 8 Fl ow a cc um ul at io n (in di ca tio n of c at en a po sit io n) Ra st er H yd ro lo gy 9 D W A Q ui na ry C at ch m en ts Ve ct or p ol y D ep ar tm en t o f W at er a nd S an ita tio n (D W S) 10 1: 50 0 00 to po gr ap hi ca l m ap s tre am lin es Ve ct or li ne N at io na l G eo -s pa tia l I nf or m at io n (N G I) W et la nd m ap s 11 N at io na l W et la nd A tla s M ap 6 B et a Ve ct or p ol y So ut h Af ric an N at io na l B io di ve rs ity In st itu te (S AN BI ) 12 M od el le d de pr es sio n w et la nd s of th e Va al s ub ca tc hm en t Ve ct or p ol y SA N BI H ig h- Re so lu tio n Ae ria l I m ag er y 13 Ar cG IS P ro O nl in e W or ld Im ag er y Ra st er En vi ro nm en ta l S ys te m s Re se ar ch In st itu te , In c. (E SR I) 14 G oo gl e Ea rth Ra st er G oo gl e Ea rth 15 N G I R SA 2 01 2 25 c m c ol ou r a er ia l Ra st er N G I Ve ge ta tio n m ap s 19 N W B re de nk am p an d Br ow n 20 03 a (F ig ur e 7A ) Ve ct or p ol y N or th W es t D ep ar tm en t o f E co no m ic D ev el op m en t, En vi ro nm en t, C on se rv at io n an d To ur ism (N W D ED EC T) 20 N at io na l V eg et at io n M ap 2 01 8 (F ig ur e 7B ) Ve ct or p ol y SA N BI 21 Ag ric ul tu ra l l an d ty pe s (F ig ur e 6B ) Ve ct or p ol y D ep ar tm en t o f A gr ic ul tu re , L an d Re fo rm an d Ru ra l D ev el op m en t A gr ic ul tu re G eo gr ap hi c In fo rm at io n Sy st em (A G IS ) Sp ec ie s da ta 22 N at io na l V eg et at io n D at ab as e of e xi st in g re le vé s (F ig ur e 2) Po in t SA N BI 23 PO SA q ua rte r d eg re e sq ua re (Q D S) h er ba riu m re co rd s Po ly go n SA N BI 24 Fi el d su rv ey p lo ts a nd o bs er va tio ns (i N at ) Po in t Th is pr oj ec t Page 12 of 62   | Original research | Open accesshttp://abcjournal.org | classification plot data versus the current classification of vegetation types. The purpose of the rapid vegetation survey was to gath- er species and vegetation type (plant community and dominant species) observation data and photographs of vegetation types over as wide an area as possible in a limited time period. Field work was carried out over two growth seasons (2021/22 and 2022/23). The sam- pling method relied on noting discernible changes in the vegetation type along a catenal sequence then filling in a prescribed data sheet. A mobile version of the veg- etation map was available on the CarryMap application for use in the field. This included both the 2018 version of the national map, as well as an unpublished NW veg- etation map created by P. Desmet (NW READ 2015). This mobile app allowed for the live tracking of an in- dividual as they move through the landscape and the identification of the existing mapped vegetation type present at a sampling location. Dominant species for a vegetation type were identified and noted and species with ethnobotanical importance, limited distribution or threatened and protected species were photographed and lodged on the iNaturalist App (https://www.inat- uralist.org). Representative photographs of the vegeta- tion type at each site were also uploaded with each species observation, and these were linked to the South African Vegetation Map project in iNaturalist. Additional vegetation observation data from two previ- ous field campaigns conducted by the authors in 2015 and 2018 were also collated and added to the obser- vation database. Expert data Vegetation experts with experience of either mapping or using the provincial vegetation map were also en- gaged to canvas their opinion on what needed to be changed or updated in the revised map. Input from ex- perts comprised either (1) verbal inputs, (2) relevé data- sets that were not currently in the NVD or, (3) relevant documents or spatial data such as unpublished reports or GIS shapefiles that were not considered in Mucina and Rutherford (2006). Results Species data In total 2 985 plots were extracted from the NVD that fall in or within 20 km of the NW (Figure 2). Of this 1 608 (54%) have no accurate georeference, i.e., local- ity information comprising a description only with no sample point latitude/longitude. For these plots, a geo- location was added based on the nearest town or area Ra nk G ra ss (P oa ce ae ) s pe ci es % W oo dy s pe ci es Fa m ily % Fo rb s pe ci es Fa m ily % 1 Ar ist id a co ng es ta 54 .3 G re w ia fl av a M al va ce ae 27 .0 Fe lic ia m ur ic at a As te ra ce ae 17 .6 2 Th em ed a tr ia nd ra 48 .2 Zi zi ph us m uc ro na ta Rh am na ce ae 24 .6 C om m el in a af ric an a C om m el in ac ea e 15 .1 3 H et er op og on c on to rt us 33 .0 D ic hr os ta ch ys c in er ea Fa ba ce ae 18 .9 Se ne ci o ve no su s As te ra ce ae 14 .1 4 D ig ita ria e ria nt ha 32 .1 Va ch el lia k ar ro o Fa ba ce ae 18 .2 D ic om a an om al a As te ra ce ae 13 .7 5 Br ac hi ar ia s er ra ta 28 .3 Va ch el lia to rt ili s Fa ba ce ae 17 .6 An th os pe rm um ri gi du m Ru bi ac ea e 13 .3 6 Er ag ro st is cu rv ul a 27 .9 D io sp yr os ly ci oi de s Eb en ac ea e 13 .4 H ill ia rd ie lla o lig oc ep ha la As te ra ce ae 13 .2 7 Er ag ro st is le hm an ni an a 26 .8 El ep ha nt or rh iz a el ep ha nt in a Fa ba ce ae 13 .0 Sc hk uh ria p in na ta As te ra ce ae 12 .8 8 El io nu ru s m ut ic us 26 .5 Eh re tia ri gi da Bo ra gi na ce ae 11 .2 Ba rle ria m ac ro st eg ia Ac an th ac ea e 12 .6 9 Se ta ria s ph ac el at a 26 .0 Se ne ga lia c af fra Fa ba ce ae 10 .9 As pa ra gu s la ric in us As pa ra ga ce ae 11 .8 10 M el in is re pe ns 24 .0 Va ch el lia e rio lo ba Fa ba ce ae 10 .9 Po lli ch ia c am pe st ris C ar yo ph yl la ce ae 11 .5 Ta bl e 3. T he m os t a bu nd an t s pe ci es in N or th W es t p ro vi nc e pe r gr ow th fo rm in th e N VD p lo t d at a. O cc ur re nc e is ex pr es se d as p er ce nt ag e (% ) p re se nc e in 2 9 85 p lo ts a na ly se d. S pe ci es n am es a re ab br ev ia te d to s pe ci es le ve l o nl y w ith n o su bs pe ci fic ta xa c on sid er ed in th e an al ys is Page 13 of 62   https://www.inaturalist.org https://www.inaturalist.org | Original research | Open accesshttp://abcjournal.org | Ra nk G ra ss (P oa ce ae ) s pe ci es % W oo dy s pe ci es Fa m ily % Fo rb s pe ci es Fa m ily % 11 C yn od on d ac ty lo n 23 .4 Se ar sia le pt od ic ty a An ac ar di ac ea e 10 .8 As pa ra gu s su av eo le ns As pa ra ga ce ae 11 .4 12 C ym bo po go n po sp isc hi lii 23 .1 G ym no sp or ia h et er op hy lla C el as tra ce ae 10 .8 C ra bb ea a ng us tif ol ia Ac an th ac ea e 11 .2 13 D ih et er op og on a m pl ec te ns 21 .9 Se ne ga lia m el lif er a Fa ba ce ae 10 .7 Ky ph oc ar pa a ng us tif ol ia Am ar an th ac ea e 10 .8 14 Er ag ro st is rig id io r 19 .5 Ta rc ho na nt hu s ca m ph or at us As te ra ce ae 10 .0 As pa ra gu s af ric an us As pa ra ga ce ae 10 .7 15 Po go na rt hr ia s qu ar ro sa 18 .0 Se ar sia la nc ea An ac ar di ac ea e 9. 4 Ju st ic ia a na ga llo id es Ac an th ac ea e 10 .3 16 Sc hm id tia p ap po ph or oi de s 17 .9 Va ch el lia h eb ec la da Fa ba ce ae 8. 6 G az an ia k re bs ia na As te ra ce ae 9. 1 17 Er ag ro st is ra ce m os a 17 .5 Zi zi ph us z ey he ria na Rh am na ce ae 8. 6 So la nu m c am py la ca nt hu m So la na ce ae 9. 0 18 Tr ac hy po go n sp ic at us 17 .4 Se ar sia p yr oi de s An ac ar di ac ea e 8. 1 In di go fe ra d al eo id es Fa ba ce ae 8. 8 19 Sc hi za ch yr iu m s an gu in eu m 16 .1 C om br et um m ol le C om br et ac ea e 8. 0 M on so ni a an gu st ifo lia G er an ia ce ae 8. 5 20 Pa ni cu m m ax im um 15 .3 Te rm in al ia s er ic ea C om br et ac ea e 7. 6 H er m an ni a de pr es sa M al va ce ae 8. 4 21 St ip ag ro st is un ip lu m is 14 .7 D om be ya ro tu nd ifo lia M al va ce ae 7. 4 C ya no tis s pe ci os a C om m el in ac ea e 8. 3 22 M el in is ne rv ig lu m is 14 .4 C om br et um a pi cu la tu m C om br et ac ea e 7. 1 H er m an ni a to m en to sa M al va ce ae 8. 3 23 Er ag ro st is su pe rb a 14 .2 Va ch el lia n ilo tic a Fa ba ce ae 6. 2 Li pp ia s ca be rr im a Ve rb en ac ea e 8. 3 24 C ym bo po go n ca es iu s 14 .0 Eu cl ea u nd ul at a Eb en ac ea e 5. 9 C ha m ae cr ist a m im os oi de s Fa ba ce ae 8. 2 25 Eu st ac hy s pa sp al oi de s 13 .8 C om br et um z ey he ri C om br et ac ea e 5. 7 In di go fe ra c om os a Fa ba ce ae 8. 0 26 Ar ist id a st ip ita ta 13 .2 Va ng ue ria in fa us ta Ru bi ac ea e 5. 5 N id or el la h ot te nt ot ic a As te ra ce ae 8. 0 27 An dr op og on s ch ire ns is 12 .9 Eu cl ea c ris pa Eb en ac ea e 5. 3 H ib isc us p us ill us M al va ce ae 7. 7 28 Tr ira ph is an dr op og on oi de s 12 .6 Za nt ho xy lu m c ap en se Ru ta ce ae 5. 2 W al th er ia in di ca M al va ce ae 7. 7 29 Tr ag us b er te ro ni an us 12 .5 Pr ot ea c af fra Pr ot ea ce ae 5. 0 Ko ha ut ia a m at ym bi ca Ru bi ac ea e 7. 4 30 Lo ud et ia s im pl ex 12 .0 Pa pp ea c ap en sis Sa pi nd ac ea e 5. 0 Li m eu m v isc os um Li m ea ce ae 7. 4 Ta bl e 3. T he m os t a bu nd an t s pe ci es in N or th W es t p ro vi nc e pe r gr ow th fo rm in th e N VD p lo t d at a. O cc ur re nc e is ex pr es se d as p er ce nt ag e (% ) p re se nc e in 2 9 85 p lo ts a na ly se d. S pe ci es n am es a re ab br ev ia te d to s pe ci es le ve l o nl y w ith n o su bs pe ci fic ta xa c on sid er ed in th e an al ys is (c on tin ue d) Page 14 of 62   | Original research | Open accesshttp://abcjournal.org | that could be determined from the plot locality descrip- tion data, or failing this, locality clues present in the title of the project or source publication. The sampling density of plots is low. For the 2 985 plots selected from the NW plus 20 km buffer, this is a sampling density of approximately 1 plot per 50 km2; however, only 785 plots fall within the NW equating to a sampling density of approximately 1 plot per 130 km2. In total the NVD dataset contains 28 705 records for 1 610 species (Table 3). This equates to a sampling den- sity of approximately 1 record per 5 km2. Note that only genus and species are considered here and no subspe- cific taxa are considered. In contrast to the vegetation survey plot data, the global species list, derived from POSA herbarium record data for the province at the genus and species levels, contains 3 040 taxa of which 407 are not native (Table 4). That means for indigenous species (2 633 taxa) only 61% of species known to oc- cur in the province have been recorded in nearly 3 000 vegetation survey plots. Vegetation type identification key An identification key for the vegetation types of the NW (Table 6) was developed based on 15 broad environ- mental variables grouped into five variable categories (Table 5). The identification key is able to discriminate and identify all 36 terrestrial vegetations types that oc- cur in the province plus the three ‘azonal’ types associ- ated with hydrologically driven ecosystems. Summary of changes made to the vegetation map Changes to the NW vegetation map are summarised according to the potential types of changes described by the National Vegetation Map Committee (Table 7). The changes in vegetation type extents are summarised in Table 8. Sp ec ie s na m e Fa m ily Q D S Sp ec ie s na m e Fa m ily Q D S Sp ec ie s na m e Fa m ily Q D S 1 Ar ist id a co ng es ta Po ac ea e 10 3 35 Ap to sim um e lo ng at um Sc ro ph ul ar ia ce ae 51 69 G ym no sp or ia b ux ifo lia C el as tra ce ae 40 2 Er ag ro st is cu rv ul a Po ac ea e 94 36 O zo ro a pa ni cu lo sa An ac ar di ac ea e 51 70 In di go fe ra d al eo id es Fa ba ce ae 40 3 C om m el in a af ric an a C om m el in ac ea e 93 37 Zi zi ph us m uc ro na ta Rh am na ce ae 51 71 Pa ni cu m m ax im um Po ac ea e 40 4 D ig ita ria e ria nt ha Po ac ea e 92 38 H el ic hr ys um n ud ifo liu m As te ra ce ae 50 72 Pa ve tta z ey he ri Ru bi ac ea e 40 5 Ar ist id a st ip ita ta Po ac ea e 78 39 So la nu m c am py la ca nt hu m So la na ce ae 49 73 Pa vo ni a bu rc he lli i M al va ce ae 40 6 St ip ag ro st is un ip lu m is Po ac ea e 75 40 Va hl ia c ap en sis Va hl ia ce ae 49 74 W ah le nb er gi a un du la ta C am pa nu la ce ae 40 7 M el in is re pe ns Po ac ea e 74 41 Po lli ch ia c am pe st ris C ar yo ph yl la ce ae 48 75 C yp er us d ec ur va tu s C yp er ac ea e 39 8 Se ar sia p yr oi de s A na ca rd ia ce ae 74 42 Ba rle ria m ac ro st eg ia Ac an th ac ea e 47 76 Er ag ro st is rig id io r Po ac ea e 39 9 D io sp yr os ly ci oi de s Eb en ac ea e 71 43 H er m bs ta ed tia o do ra ta Am ar an th ac ea e 47 77 H ib isc us p us ill us M al va ce ae 39 10 G re w ia fl av a M al va ce ae 70 44 La nt an a ru go sa Ve rb en ac ea e 47 78 Po ly ga la h ot te nt ot ta Po ly ga la ce ae 39 11 Th em ed a tr ia nd ra Po ac ea e 65 45 Se nn a ita lic a Fa ba ce ae 47 79 Tr ic ho ne ur a gr an di gl um is Po ac ea e 39 Ta bl e 4. T he 1 00 m os t w id es pr ea d in di ge no us p la nt s pe ci es in N or th W es t p ro vi nc e as r ec or de d in th e PO SA h er ba riu m d at as et . Q D S = th e nu m be r of u ni qu e qu ar te r de gr ee s qu ar es in th e N or th W es t p ro vi nc e in w hi ch a s pe ci es is re co rd ed (t ot al Q D S in N W = 2 29 ) Page 15 of 62   | Original research | Open accesshttp://abcjournal.org | Sp ec ie s na m e Fa m ily Q D S Sp ec ie s na m e Fa m ily Q D S Sp ec ie s na m e Fa m ily Q D S 12 D ic om a an om al a A st er ac ea e 64 46 C om m el in a liv in gs to ni i C om m el in ac ea e 46 80 Eu st ac hy s pa sp al oi de s Po ac ea e 38 13 Rh yn ch os ia to tta Fa ba ce ae 62 47 M on so ni a an gu st ifo lia G er an ia ce ae 46 81 H el ic hr ys um ar gy ro sp ha er um As te ra ce ae 38 14 C ym bo po go n po sp isc hi lii Po ac ea e 61 48 Zi zi ph us z ey he ria na Rh am na ce ae 46 82 Ph yl la nt hu s pa rv ul us Ph yl la nt ha ce ae 38 15 Er ag ro st is le hm an ni an a Po ac ea e 61 49 C ym bo po go n ca es iu s Po ac ea e 45 83 C ro to n gr at iss im us Eu ph or bi ac ea e 37 16 Er ag ro st is su pe rb a Po ac ea e 61 50 Er ag ro st is gu m m ifl ua Po ac ea e 45 84 C yp ho ca rp a an gu st ifo lia Am ar an th ac ea e 37 17 Fe lic ia m ur ic at a A st er ac ea e 61 51 N id or el la re se di fo lia As te ra ce ae 45 85 Li m eu m v isc os um Li m ea ce ae 37 18 Se ta ria s ph ac el at a Po ac ea e 59 52 Tr ag us b er te ro ni an us Po ac ea e 45 86 Sc ho en op le ct us m ur ic in ux C yp er ac ea e 37 19 Sc hm id tia p ap po ph or oi de s Po ac ea e 58 53 C or ch or us a sp le ni fo liu s M al va ce ae 44 87 Ar ist id a ad sc en sio ni s Po ac ea e 36 20 Sp or ob ol us fi m br ia tu s Po ac ea e 58 54 Er ag ro st is ch lo ro m el as Po ac ea e 44 88 El ep ha nt or rh iz a el ep ha nt in a Fa ba ce ae 36 21 Va ch el lia k ar ro o Fa ba ce ae 57 55 H ill ia rd ie lla e la ea gn oi de s As te ra ce ae 44 89 Er ag ro st is pa lle ns Po ac ea e 36 22 Er ag ro st is tr ic ho ph or a Po ac ea e 56 56 Sp he da m no ca rp us p ru rie ns M al pi gh ia ce ae 44 90 Ip om oe a bo lu sia na C on vo lv ul ac ea e 36 23 Po go na rt hr ia s qu ar ro sa Po ac ea e 56 57 Ta rc ho na nt hu s ca m ph or at us As te ra ce ae 44 91 Sc ab io sa c ol um ba ria D ip sa ca ce ae 36 24 Bu lb os ty lis b ur ch el lii C yp er ac ea e 55 58 Li pp ia s ca be rr im a Ve rb en ac ea e 43 92 Si da c hr ys an th a M al va ce ae 36 25 En ne ap og on s co pa riu s Po ac ea e 55 59 El io nu ru s m ut ic us Po ac ea e 42 93 Tr ira ph is an dr op og on oi de s Po ac ea e 36 26 G ei ge ria b ur ke i A st er ac ea e 54 60 G az an ia k re bs ia na As te ra ce ae 42 94 C hl or op hy tu m fa sc ic ul at um Ag av ac ea e 35 27 H et er op og on c on to rt us Po ac ea e 54 61 G om ph oc ar pu s fru tic os us Ap oc yn ac ea e 42 95 O le a eu ro pa ea O le ac ea e 35 28 Pa ni cu m c ol or at um Po ac ea e 54 62 Ip om oe a ob sc ur a C on vo lv ul ac ea e 42 96 Sa lv ia ru nc in at a La m ia ce ae 35 29 An th ep ho ra p ub es ce ns Po ac ea e 53 63 Se ar sia le pt od ic ty a An ac ar di ac ea e 42 97 Sc hi za ch yr iu m sa ng ui ne um Po ac ea e 35 30 C yn od on d ac ty lo n Po ac ea e 53 64 Te uc riu m tr ifi du m La m ia ce ae 42 98 Te rm in al ia s er ic ea C om br et ac ea e 35 31 C yp er us m ar ga rit ac eu s C yp er ac ea e 53 65 Xe no st eg ia tr id en ta ta C on vo lv ul ac ea e 42 99 As pa ra gu s su av eo le ns As pa ra ga ce ae 34 32 Ae rv a le uc ur a A m ar an th ac ea e 52 66 Fi ng er hu th ia a fri ca na Po ac ea e 41 10 0 C ha m ae cr ist a bi en sis Fa ba ce ae 34 33 Br ac hi ar ia n ig ro pe da ta Po ac ea e 52 67 H er m an ni a to m en to sa M al va ce ae 41 34 An th os pe rm um ri gi du m Ru bi ac ea e 51 68 M un du le a se ric ea Fa ba ce ae 41 Ta bl e 4. T he 1 00 m os t w id es pr ea d in di ge no us p la nt s pe ci es in N or th W es t P ro vi nc e as r ec or de d in th e PO SA h er ba riu m d at as et . Q D S = th e nu m be r of u ni qu e qu ar te r de gr ee s qu ar es in th e N or th W es t p ro vi nc e in w hi ch a s pe ci es is re co rd ed (t ot al Q D S in N W = 2 29 ) ( co nt in ue d) Page 16 of 62   | Original research | Open accesshttp://abcjournal.org | Key level Environmental variable Vegetation type 1 Alluvial Vegetation Vegetation types where the occasional presence of surface water is a primary determinant of the vegetation type, such as valley bottoms, alluvial, wetland or occasionally flooded. Also referred to as azonal vegetation types. 1.1 North: Central Bushveld Bioregion 1 Subtropical Alluvial Vegetation 1.2 West: Eastern Kalahari Bioregion 2 Southern Kalahari Mekgacha 1.3 South: Grassland Bioregion 3 Highveld Alluvial Vegetation 2 Terrestrial Vegetation 2.1 North: Central Bushveld Bioregion 2.1.1 Mountains and koppies 2.1.1.1 Shale and mudstone 4 Dwarsberg-Swartruggens Mountain Bushveld 2.1.1.2 Dolomite 5 Madikwe Dolomite Bushveld 2.1.1.3 Norite/gabbro (mafic) 6 Norite Koppies Bushveld 2.1.1.4 Pilanesberg 7 Pilanesberg Mountain Bushveld 2.1.1.5 Quartzite and sandstone 8 Waterberg Mountain Bushveld 2.1.1.6 Granite (felsic) 9 Central Sandy Mountain Bushveld 2.1.2 Plains 2.1.2.1 Heavy clay (vertisols) 2.1.2.1.1 West 10 Dwaalboom Thornveld 2.1.2.1.2 Swartruggens (clay soils) 11 Zeerust Thornveld 2.1.2.1.3 Central/Rustenburg 12 Marikana Thornveld 2.1.2.1.4 East/Springbokvlakte 13 Springbokvlakte Thornveld 2.1.2.2 Sand Table 5. Summary of the environmental variables used to construct the identification key in Table 6 used to define and map vegetation types Hierarchical order of variable Variable category Variable name 1 Flooding (a) alluvial (b) terrestrial 2 Bioregion (a) Bushveld (b) Kalahari (c) Highveld 3 Terrain (a) plains (b) mountainous/rocky habitats (including pediments) 4 Geology (a) aeolian (b) quartzite and sandstone (c) shale and mudstone (d) dolomite (e) igneous mafic (f) igneous felsic 5 Soil (a) sand (b) clay Table 6. An identification key to the vegetation types of the North West province based on broad environmental and vegetation structure characteristics Page 17 of 62   | Original research | Open accesshttp://abcjournal.org | Key level Environmental variable Vegetation type 2.1.2.2.1 Aeolian/Kalahari sand 2.1.2.2.1.1 West of Crocodile River/Pilanesberg 14 Western Sandy Bushveld 2.1.2.2.1.2 East of Crocodile River/Pilanesberg (more mixed veld broadleaf and acacia) 15 Western Sandy Bushveld (East) 2.1.2.2.2 Fersiallitic soils (medium sandy clay loams with good drainage, derived from mafic (basic) rocks)/undulating landscapes with pronounced catenas 16 Central Sandy Bushveld 2.1.2.2.3 Silica rich sand in valleys derived from quartzite hills (and sometimes Kalahari sand), valleys of the Magaliesberg 17 Moot Plains Bushveld 2.2 West: Eastern Kalahari Bioregion 2.2.1 Mountains and koppies 18 Kuruman Mountain Bushveld 2.2.2 Plains 2.2.2.1 Calcrete or dolomite 2.2.2.1.1 Thornveld 19 Morokweng Thornveld 2.2.2.2.2 Bushveld 20 Ghaap Plateau Vaalbosveld 2.2.2.2 Deep sand over calcrete 2.2.2.2.1 East 21 Stella Bushveld 2.2.2.2.2 West 22 Kuruman Vaalbosveld 2.2.2.3 Deep sand over dorbank 2.2.2.3.1 Sand eroding, dorbank and calcrete (along streams) exposed 23 Vryburg Thornveld 2.2.2.3.2 Deep sand (mixed), Molopo catchment 24 Mafikeng Bushveld 2.2.2.3.2 Deep sand (mixed), east of Harts River 25 Schweizer-Reneke Bushveld 2.2.2.3.4 Deeper sand (red) 26 Molopo Bushveld 2.2.2.4 Deep alluvial soils, no occasional flooding 27 Schmidtsdrif Thornveld 2.3 South: Grassland Bioregion 2.3.1 Mountains and koppies 2.3.1.2 Quartzite 2.3.1.2.1 29 Gold Reef Mountain Bushveld 2.3.1.2.2 Montane above 1600 m/pockets of deep sandy soils 30 Waterberg-Magaliesberg Summit Sourveld 2.3.1.3 Shale and mudstone 31 Gauteng Shale Mountain Bushveld 2.3.1.4 Igneous (basalt: dolerite, andesite, etc.) 32 Andesite Mountain Bushveld 2.3.1.5 Granite (includes koppies and plains) 33 Vredefort Dome Granite Grassland 2.3.2 Plains 2.3.2.1 Sandy soils 2.3.2.1.1 Potchefstroom eastwards (soil clay content > 20%, depth > 0.5 m) tall grassland > 0.5 m, average annual rainfall > 600 mm 34 Rand Highveld Grassland 2.3.2.1.2 Central (soil clay content < 20%, depth > 0.5 m) tall grassland >0.5 m, average annual rainfall < 600 mm 35 Vaal-Vet Sandy Grassland Table 6. An identification key to the vegetation types of the North West province based on broad environmental and vegetation structure characteristics (continued) Page 18 of 62   | Original research | Open accesshttp://abcjournal.org | Table 6. An identification key to the vegetation types of the North West province based on broad environmental and vegetation structure characteristics (continued) Table 7. Summary of the changes made to the North West province vegetation map. Changes are summarised according to the potential type of changes described in the South African National Ecosystem Classification System Handbook* (SANBI 2023) Key level Environmental variable Vegetation type 2.3.2.1.3 West (soil clay content < 25%, depth < 0.5 m) short grassland < 0.5 m often with calcrete in the landscape, average annual rainfall < 600 mm 36 Western Highveld Sandy Grassland 2.3.2.2 Dolomite 2.3.2.2.1 Mostly grassland 37 Carletonville Dolomite Grassland 2.3.2.2.2 Prominent woody element present, sinkholes filled with Aeolian sand (dolines) 38 Vaal Reefs Dolomite Sinkhole Woodland 2.3.2.3 Clay, undulating landscapes with shallow stony soils derived from igneous, sedimentary or metamorphic rocks 2.3.2.3.1 West of Bloemhof (Vachellia tortilis), average annual rainfall < 500 mm, < 35 frost days per annum 39 Kimberley Thornveld 2.3.2.3.2 East of Bloemhof (Vachellia caffra and V. karroo), average annual rainfall > 500 mm, > 35 frost days per annum 40 Klerksdorp Thornveld 2.4 Evergreen forest 41 Northern Afrotemperate Forest No. Types of change Minor change MN1 Boundary shifts (realignment) All vegetation type boundaries have been remapped from scratch. See text for rational behind updating boundary mapping. As the current map is based on a map first developed in the 1980s, it is inevitable that most boundaries will change given the better mapping tools and resolution of spatial data available for mapping. Remapping of boundaries does not imply that the original land type map or concept is wrong, just that the boundaries are inaccurate. MN2 Creation of a subtype/community within an existing vegetation type Within FOz 2 Northern Afrotemperate Forest a new subvegetation type, Olea Sclerophyllous Forest, is discussed but not proposed as a recognised unit as yet. This forest unit is widespread in eastern southern Africa within other vegetation types typically on slopes where fire is excluded. MN3 Change in vegetation type name (without spatial or description changes). *Special circumstances for this change are described in the handbook. Not applicable. MN4 Change in vegetation type description, e.g., list of endemic species All vegetation type descriptions have been updated based on: (1) Mucina and Rutherford (2006) vegetation map description. (2) Bredenkamp and Brown (2003a) vegetation map descriptions. (3) Field observations. (4) Species information in the NVD relevé database. (5) Vegetation accounts in relevant scientific papers, theses and reports. (6) Inputs from expert stakeholders. Endemic species have not been re-assessed. Refer to Hahn (2013) for a detailed analysis and description of species endemic to the NW. MN5 Boundary shifts when neighbouring country or coastal borders are redefined Not applicable. Page 19 of 62   | Original research | Open accesshttp://abcjournal.org | No. Types of change MN6 The creation of new polygons of an existing vegetation type that may be disjunct from existing polygons of that type and beyond a reasonable* range extension or reduction. *To be determined by the National Vegetation Map Committee on a case-by-case basis. Two existing vegetation types are included in the province that were previously not mapped as occurring in the province, namely, Subtropical Alluvial Vegetation and Waterberg Mountain Bushveld. The current map does not have any alluvial vegetation category in the Bushveld region. Given the presence of several large rivers, as well as extensive floodplain ecosystems it is necessary to bring Subtropical Alluvial Vegetation into the province to accommodate these ecosystems. This alluvial ecosystem type is not indicated as occurring in the province in the 2018 version of the National Vegetation Map, however, it should be noted that this type was present in the 2006 version of the National Vegetation Map to accommodate the Kgomo Kgomo floodplain along the Moretele River. Waterberg Mountain Bushveld occurs just north of the province. Mountain bushveld vegetation on quartzite along the northern border of the province should be assigned to this vegetation unit as these mountains are contiguous with the Waterberg Mountain complex (Partridge et al. 2010), and while the mountain bushveld vegetation is similar to that of the northern Bankenveld in terms of structure and species, the mountains are geographically separate. Major change MJ1 Removal of a vegetation type from the classification system or downgrading a type to a level below a vegetation type, e.g., subtypes. Not applicable. MJ2 Create new vegetation type (replace existing) or upgrading of a subtype to a type. Three new vegetation types are proposed namely, Vryburg Thornveld, Morokweng Thornveld and Central Sandy Mountain Bushveld. These are not new vegetation concepts. All three types have been recognised and mapped by previous authors; however, these units were (erroneously) lumped with other vegetation types with the creation of the 2006 National Vegetation Map. Both Vryburg Thornveld and Morokweng Thornveld exist as units in the land type map and are recognised as distinct phytosociological units by Smit (2000), namely, Acacia erioloba – Acanthosicyos naudinianus – Dichrostachys cinerea vlaktes (plains) and Acacia mellifera – Acacia hebeclada – Heliotropium ciliatum sandvlaktes (sandplains), respectively. In Bredenkamp and Brown (2003a) Vryburg Thornveld is retained as unit but not Morokweng Thornveld, however, in Mucina and Rutherford (2006) both units are lost. Morokweng Thornveld (Figure 8) is associated with a karst landscape with very extensive surface calcrete and dolomite. The vegetation is a short, arid thornveld that is floristically and structurally distinct from the surrounding woodlands on deep Kalahari sand. The most closely related existing vegetation type in terms of habitat type, Ghaap Plateau Vaalbosveld, is compositionally and structurally unrelated to this vegetation unit and therefore there are no grounds for extending the Ghaap Plateau Vaalbosveld vegetation type to include the vegetation of the Morokweng karstland. Vryburg Thornveld (Figure 9) occupies the headwaters of the Molopo River catchment that is characterised by incised/eroding landscapes along stream margins. Exposed dorbank and calcrete (along streams) occurs. Frequent springs, decanting from the neighbouring Ghaap Plateau, support hydromorphic grasslands and wetlands in the valley bottoms. The vegetation here is sparse woodland dominated by very tall Vachellia erioloba trees and scattered low Vachellia hebeclada thickets. Most of the broad-leaved woody elements and dense woodland structure of the related Mafikeng Bushveld are absent. Whilst Vryburg Thornveld exists as a vegetation type name in Bredenkamp and Brown (2003a), Morokweng Thornveld is an entirely novel derivation named after the town located in this vegetation type. Central Sandy Mountain Bushveld includes the vegetation on mountains and koppies currently included within the Central Sandy Bushveld vegetation type. The definition of Central Sandy Bushveld is refined to include only the plains vegetation type within the current delimitation of the vegetation type on soils derived from igneous rocks. Vegetation on vertic clay soils within the current delimitation of Central Sandy Bushveld are reassigned to Springbokvlake Thornveld. This split of central sandy woodland vegetation in mountain bushveld and (plains) bushveld also aligns better to the vegetation type model developed here. Table 7. Summary of the changes made to the North West province vegetation map. Changes are summarised according to the potential type of changes described in the South African National Ecosystem Classification System Handbook* (SANBI 2023) (continued) Page 20 of 62   | Original research | Open accesshttp://abcjournal.org | No. Types of change Central Sandy Mountain Bushveld is being reinstated as a vegetation type having been grouped with Central Sandy Bushveld in the National Vegetaiton Map since 2006. It is a well-established vegetation type recognised by several previous authors. It is synonymous with Van der Meulen’s Combretum molle – Diheteropogon amplectens order described in his vegetation map of the western Transvaal bushveld (Van der Meulen & Westfall 1979); Brown’s Pappea capensis – Combretum apiculatum (mountain) bushveld vegetation type described for the vegetation study of the Borakalalo Nature Reserve (Brown & Bredenkamp 1994; Brown et al. 1995, 1996 and 1997); and Bredenkamp and Brown’s (2003a) Mogosane Mountain Bushveld and Central Mixed Bushveld vegetation types in their vegetation map of the NW. The rationale for why this unit was not incorporated into the 2006 National Vegetation Map is not recorded anywhere. MJ3 Reassignment of a community in a vegetation type from an existing vegetation type to another existing vegetation type Not applicable. MJ4 Extension of the range of an existing vegetation type far beyond the current extent (to be determined by committee) See MN6 above. Table 7. Summary of the changes made to the North West province vegetation map. Changes are summarised according to the potential type of changes described in the South African National Ecosystem Classification System Handbook* (SANBI 2023) (continued) Figure 8. A comparison of Morokweng Thornveld west of Morok- weng (B) to what it is currently mapped as in the National Veg- etation Map (A, Mafikeng Bushveld east of Heuningvlei), and what it is most similar to in terms of soil and geology (C, Ghaap Plateau Vaalbosveld north of Reivilo). Morokweng Thornveld is a short, open to dense thornveld dominated by the trees Sen- egalia mellifera and Vachellia hebeclada, with a sparse grass but rich herb layer and with abundant surface calcrete on dolomite geology. Mafikeng Bushveld occurs on deep red Kalahari sand and is a tall open mixed woodland with an abundance of geo- xylic shrubs. Ghaap Plateau Vaalbosveld also has an abundance of surface calcrete on dolomite geology, but the vegetation has a distinctive grassland character dominated by Themeda tri- andra and dense trees are confined to distinctive kluftkarren geological features in the landscape. A C B Page 21 of 62   | Original research | Open accesshttp://abcjournal.org | Revised vegetation map The revised vegetation map contains 1 810 polygons compared to the current vegetation map that has 159 polygons (Figure 10). Whilst the vegetation type con- cepts remain mostly unchanged from Mucina and Rutherford (2006), polygon boundaries have been entirely remapped, and this has resulted in significant changes in extent from most vegetation types (Table 8). The remapping of boundaries is an inevitable prod- uct of the much higher resolution mapping informants available to this project, as well as the application of the vegetation type identification key. Updated descriptions of North West terrestrial vegetation types The vegetation type descriptions have been updated (Supplementary Material 2: Vegetation type descrip- tions) to reflect new data available and to better align with the vegetation type identification key (Table 6). Descriptions are based on the original descriptions that appear in Mucina and Rutherford (2006) and where necessary these have been updated based on the in- puts presented in Table 9. Discussion The revised vegetation map is significantly changed mainly with respect to where the boundaries of vegeta- tion types are mapped. Whilst there are some changes proposed to the classification of vegetation types, for the most part, the current vegetation type concepts remain unchanged. The change in the mapping of vegetation type boundaries is an inevitable result of: (1) a clearer understanding of vegetation determinants (i.e., vegeta- tion type classification framework or identification key); and more importantly, (2) the much-increased resolu- tion and availability of mapping informants. It is very important to note that the significant change in mapped boundaries does not suggest or imply in any way that the current vegetation type concepts are invalid. The vegetation identification key is important for in- forming the current vegetation map revision. It also Figure 9. Examples of Vryburg Thornveld south of Ganyesa. The very open spare grassy parkland dominated by very large Vach- ellia erioloba trees and general absence of any other tall or dominant trees is characteristic of this vegetation type. Note in C, the very short form of Vachellia hebeclada that is abundant here. A C B Page 22 of 62   | Original research | Open accesshttp://abcjournal.org | Mapcode SA vegetation type name Area (ha) % Change 2006 to 2023 NVM 2006 NW 2023 AZa5 Highveld Alluvial Vegetation 175 789 424 274 141 AZa7 Subtropical Alluvial Vegetation 67 979 AZi3 Southern Kalahari Mekgacha 22 392 126 031 463 FOz2 Northern Afrotemperate Forest 634 2 279 260 Gh10 Vaal-Vet Sandy Grassland 809 573 1 051 812 30 Gh11 Vredefort Dome Granite Grassland 5 354 4 449 -17 Gh12 Vaal Reefs Dolomite Sinkhole Woodland 29 856 26 543 -11 Gh13 Klerksdorp Thornveld 393 029 320 207 -19 Gh14 Western Highveld Sandy Grassland 858 938 675 345 -21 Gh15 Carletonville Dolomite Grassland 643 165 570 810 -11 Gm11 Rand Highveld Grassland 282 159 265 257 -6 Gm29 Waterberg-Magaliesberg Summit Sourveld 2 060 2 160 5 Gm8 Soweto Highveld Grassland 6 951 -100 SVcb1 Dwaalboom Thornveld 552 034 274 473 -50 Figure 10. The revised 2023 vegetation map of the North West province (NW). The legend colour scheme follows that of the existing National Vegetation Map (NVM). Table 8. Summary of the change in extent of South African vegetation types between the 2006 (2018) National Vegetation Map (NVM) and the 2023 revised North West province (NW) vegetation map Page 23 of 62   | Original research | Open accesshttp://abcjournal.org | serves a far greater purpose beyond just this vegetation map revision. Firstly, it enables users of the vegetation map to clearly understand how vegetation is assigned to different vegetation types and therefore users can apply the classification framework to mapping vegetation at finer spatial scales. When mapping vegetation at the provincial scale there are time and budget constraints limiting the amount of detail that can be mapped rel- ative to what can be observed in the informants. It is not practically possible to manually map vegetation at infinitely fine scales over large regions. Therefore, there are inherent boundary or misclassification errors in the final map product due to mapping scale. Using the veg- etation type identification key it is possible for users of the map to apply the classification framework at a fine or local spatial scale to improve mapping accuracy or interpretation for specific purposes, for example, fine- scale vegetation mapping for environmental impact assessments. Secondly, the identification key can illuminate inconsis- tencies in the current vegetation type classification and Table 8. Summary of the change in extent of South African vegetation types between the 2006 (2018) National Vegetation Map (NVM) and the 2023 revised North West province (NW) vegetation map (continued) Mapcode SA vegetation type name Area (ha) % Change 2006 to 2023 NVM 2006 NW 2023 SVcb10 Gauteng Shale Mountain Bushveld 16 907 64 636 282 SVcb11 Andesite Mountain Bushveld 63 753 179 521 182 SVcb12 Central Sandy Bushveld 259 079 304 120 17 SVcb99 Central Sandy Mountain Bushveld 29 247 SVcb15 Springbokvlakte Thornveld 157 706 22 489 -86 SVcb16 Western Sandy Bushveld 104 103 409 672 294 SVcb98 Western (Eastern) Sandy Bushveld 114 866 SVcb17 Waterberg Mountain Bushveld 523 SVcb2 Madikwe Dolomite Bushveld 74 839 83 900 12 SVcb3 Zeerust Thornveld 412 599 131 322 -68 SVcb4 Dwarsberg-Swartruggens Mountain Bushveld 264 463 412 887 56 SVcb5 Pilanesberg Mountain Bushveld 43 464 36 792 -15 SVcb6 Marikana Thornveld 151 015 126 150 -17 SVcb7 Norite Koppies Bushveld 21 859 41 946 92 SVcb8 Moot Plains Bushveld 249 632 139 696 -44 SVcb9 Gold Reef Mountain Bushveld 128 104 229 978 80 SVk1 Mafikeng Bushveld 1 401 610 1 122 451 -20 SVk10 Kuruman Mountain Bushveld 23 811 123 195 417 SVk11 Molopo Bushveld 1 569 288 1 015 032 -35 SVk2 Stella Bushveld 322 284 476 445 48 SVk3 Schweizer-Reneke Bushveld 202 752 133 540 -34 SVk4 Kimberley Thornveld 482 231 190 398 -61 SVk6 Schmidtsdrif Thornveld 44 792 66 082 48 SVk7 Ghaap Plateau Vaalbosveld 638 861 413 785 -35 SVk8 Kuruman Vaalbosveld 75 225 45 689 -39 SVk98 Vryburg Thornveld 648 532 SVk99 Morokweng Thornveld 100 159 Page 24 of 62   | Original research | Open accesshttp://abcjournal.org | thus identify where vegetation types could be split, ag- gregated or new ones defined. For example, one such inconsistency highlighted with this project relates to the definition and mapping of Central Sandy Bushveld. This vegetation type contains both plains and mountain habitat, as well as several major geological rock types (granite and quartzite/sandstone). It is likely that apply- ing a similar vegetation type classification as used here to elsewhere in South Africa will identify inconsisten- cies in the definition and mapping of vegetation types. A stated objective of this project was to conduct a quantitative floristic analysis to find support for the vegetation type concepts using the available relevé da- tabase. This objective was not achieved within the al- located project time period. Quantitative floristic anal- ysis to validate the vegetation type concepts used in the National Vegetation Map is a major research gap that should be addressed not only for the NW, but also more broadly in South Africa. These analyses should be earmarked as a future research priority. There is some support in the literature for the vegetation type concepts as framed in the vegetation type identi- fication key. For example, the Bredenkamp and Brown (2003b) analysis of the Bankenveld area supports the mountain vs plains vegetation distinction, as well as separation of grasslands based on moisture availability, soil texture and depth. Within the mountain catego- ry, vegetation units are separated based on aspect and elevation rather than geological rock type. This does suggest that within the current vegetation type classi- fication there will be a necessary and pragmatic trade- off between ecological units that are easy to map and identify (viz. discrete mountains with similar geology) versus phytosociologically correct units that are more complex to map (viz. aspect and elevation gradients). Similarly, the Winterbach (1998) and Winterbach et al. Table 9. Summary of the inputs used to update the vegetation type descriptions Distribution Where appropriate the description of vegetation type distribution within the NW has been updated to reflect the distribution as represented in the revised vegetation map Altitude Altitudinal ranges are updated for the NW based on the elevation derived from the Aster GDEM. Vegetation and landscape features Updated with Bredenkamp and Brown (2003a) and the authors observations. Geology and soils Updated with authors observations, Bredenkamp and Brown (2003a), agricultural land types and simplified geology. The lithostratigraphic geological descriptions used in the current vegetation type descriptions are dispensed with in favour of simplified descriptions of basic geological rock types that link more closely geology, general physical and chemical properties, e.g. quartzite, basalt, granite, etc. Climate Climate data is not added here as this information is deemed to remain unchanged from that published in Mucina and Rutherford (2006). Important taxa Is based on Bredenkamp and Brown (2003a), NVD relevé data, vegetation plots collected as part of this project and authors observations. Only species that are considered to be important for identifying or differentiating the vegetation type are listed. The original and more detailed list of important taxa as published in Mucina and Rutherford (2006) are dispensed with here as these tend to be lists of all taxa encountered in a vegetation type rather than being diagnostic or characteristic species of the vegetation type or specific communities with a vegetation type. Feedback from stakeholders has indicated that these lists contain little value in terms of understanding the structure and composition or differentiating vegetation types. Important taxa are listed in order of abundance or dominance (d = dominant species) where this data is available in existing descriptions. Where this information is not available species are listed alphabetically. Conservation Is not discussed here as this would require consideration of the extent of vegetation types outside of the province, as well as compilation of an updated landcover and protected area database. This analysis would be better addressed once this vegetation map has been integrated with the National Vegetation Map. Remarks Updated with authors and stakeholders’ observations. Included here are observations regarding further work that needs to be done to clarify/update the vegetation type definition, description or mapping. References Updated with relevant references post Mucina and Rutherford (2006) and includes unpublished reports. Page 25 of 62   | Original research | Open accesshttp://abcjournal.org | (2000) analysis of the Arid Sweet Bushveld region also supports the major environmental divisions associated with higher-order vegetation associations, namely, clay vs sandy soils on plains, and plains vs mountains. Both these studies suggest that it is highly likely that the cur- rent vegetation type concepts can be supported and further refined through quantitative floristic analysis. A deficit of observations on the iNaturalist app for the NW was noted. iNaturalist is a very accessible and prac- tical tool for collecting and identifying biodiversity infor- mation. Two training workshops were held with DEDECT officials to introduce them to the potential of the iNatu- ralist and the Carrymap apps. Within the province the iNaturalist app could have future applications for gath- ering biodiversity data, monitoring environmental com- pliance; to improve decision making in the EIA process; and to monitor the distribution of invasive alien species. Within the context of this study, iNaturalist proved very useful for capturing and linking field observations to a na- tional database. Species observations in iNaturalist were uploaded together with context photographs of the veg- etation type and linked to an iNaturalist National Vege- tation Map project managed by SANBI. This project is using iNaturalist to collect representative photographs of all South African vegetation types. An interesting observation with regards the species data is the large disparity between observations collected via survey plots versus herbarium records. Nearly 40% of the province’s flora has never been recorded in a veg- etation survey plot. This observation can be partly due to the fact that surveying flora for vegetation analysis (i.e., relevés) tends to under report or omit uncommon and rare species. This observation can also be due to under sampling of the province for vegetation analysis. The very low sampling density of relevés; the tendency for samples to be clumped rather than uniformly dis- tributed; and the disparity in species records between herbarium versus plot data would suggest that from a vegetation description and analysis perspective that the NW is significantly under sampled. As highlighted above there is still a need for further floristic surveys and analysis to better understand and describe our veg- etation types. This revision of the NW vegetation map has focused on the terrestrial ecosystems of the province and there- fore the descriptions of ‘azonal’ ecosystems are not updated here. Consideration of these ecosystems is, however, central to the mapping process, as well as un- derstanding of terrestrial ecosystems. In the mapping process these ecosystems are generally always mapped first as they are often the easiest units to identify, more importantly they provide a concrete starting point for interpreting the input data in relation to the identifica- tion key and ultimately understanding vegetation/land- scape patterns. The NW has for the most part relative- ly flat landscapes that support wide floodplain/alluvial ecosystems and extensive endorheic pan ecosystems. The province also straddles three major biogeograph- ic regions that influence the vegetation composition of these ecosystems. Therefore, there is a great extent and diversity of azonal systems, and it has been necessary to map the larger occurrences of these ecosystems to have more consistent environmental and floristic definitions of terrestrial ecosystems. In the revised vegetation map the extent of azon- al ecosystems has been significantly extended from the 198 000 ha or 2% in the 2006 vegetation map to 618 000 ha or 6% of the province in the present map. Mapping has focused on azonal ecosystems associated with drainage lines and there has been no attempt to map endorheic pan systems except where these are as- sociated with drainage lines. It must be noted that during this project there was extensive discussion amongst stakeholders of the ap- propriateness of the term ‘azonal’. In the NW context these ecosystems include all ecosystem types where the occasional occurrence of surface water and wa- terlogged soils is amongst the primary environmental determinants of ecosystem structure, function and defi- nition. The term azonal could apply to any ecosystem with limited extent or that occurs widely across the landscape as a distinct feature within other ecosys- tems. The term is also discriminatory towards aquatic/ wetland ecosystems as azonal can imply ecosystems of lesser importance or status. In the terrestrial realm col- lective terms such as grassland or savanna are used to group ecosystems. These terms are broadly descriptive of the nature of the contained ecosystems. Conversely, the term azonal in the context of the NW vegetation map does not convey the very important fact that the contained ecosystems are all determined and driven by water and hydrological processes. Whilst the use of the term ‘azonal’ is retained here, it is highly recommend- ed that a new collective term for ecosystems driven by water be sought that is accepted by other terrestrial and aquatic/wetland ecologists. For the three azonal ecosys- tems considered in the NW vegetation map, the term ‘alluvial’ ecosystems would be a much more appropri- ate descriptive name. Azonal ecosystems have been grouped into three ex- isting ecosystem types, each associated with the three major river catchments/bioregions of the province. They are: 1. AZa 5 Highveld Alluvial Vegetation in the Highveld/ Vaal River catchment including AzF3 Eastern Tem- perate Freshwater Wetlands. 2. AZi 3 Southern Kalahari Mekgacha in the Kalahari/ Molopo River catchment. 3. AZa 7 Subtropical Alluvial Vegetation in the Bush- veld/Crocodile River catchment. Page 26 of 62   | Original research | Open accesshttp://abcjournal.org | Notable fluvial landscapes of the province include: 1. Kgomo-Kgomo/Tswaing area has extensive grassland floodplains (AZa 7 Subtropical Alluvial Vegetation) associated with several rivers flowing northwards out of Gauteng into the Pienaars/Moretele River and includes the Apies, Tshwane and Kutswane rivers. These floodplain ecosystems are unique within the NW and possibly within the Bushveld Bioregion. The only other area in South Africa with similar floodplain ecosystems is the Nylsvlei in Lim- popo. Unfortunately, these ecosystems are being heavily impacted by sprawling peri-urban and rural settlements. This area is in great need of conserva- tion action, as well as wetland rehabilitation. 2. The Senegalia galpinii riparian gallery forest on the Crocodile River, where the Moretele River enters, is one of the most iconic AZa 7 Subtropical Alluvial Vegetation riparian communities in the province. 3. The Mooi River catchment above the Klerkskraal Dam is possibly the largest and most intact mesic fluvial system on the western Highveld (mapped as AZa 5 Highveld Alluvial Vegetation in this map and as Temperate Freshwater Wetlands in the 2006 vegetation map), and as such should receive great- er conservation focus, as it is essentially the last re- maining intact grassland catchment landscape on the western Highveld. 4. Very extensive grassland floodplain systems (AZa 5 Highveld Alluvial Vegetation) are mostly associat- ed with Gh 14 Western Highveld Sandy Grassland. These fluvial systems cover nearly 250 000 ha. Distinct features of these fluvial systems are the presence of surface calcrete; the general lack of well-defined river channels; and are often associat- ed with networks of pans indicative of palaeo-river channels (mapped as AZi 10 Highveld Salt Pans in the SA Vegetation Map); and the singular domi- nance of the tree Searsia lancea. 5. A defining environmental characteristic of AZi 3 Southern Kalahari Mekgacha is the presence of surface calcrete indicating the ‘riverbed’. A unique vegetation feature associated with this calcrete not identified by previous authors is the abundance of species with Nama Karoo affinities such as Pentzia incana (Asteraceae), Ruschia griquensis, Ruschia semidentata, Ruschia spinosa (Aizoaceae) and var- ious Zygophyllaceae and Acanthaceae. This is the only vegetation type within the Kalahari bioregion where succulent taxa are encountered in any abun- dance and represents the only major incursion of Nama Karoo biome affinities into the NW and the Savanna biome. Much of south-central NW has been ploughed for crop production and this makes observing vegetation type boundaries on the ground, or at least where they used to occur, almost impossible to observe. This is particularly difficult across the transitions of Highveld grassland types that are the primary target of cultivation. Whilst these boundaries are not clearly observable today, having a clear vegetation–environment model does make predict- ing where these boundaries are likely to be much easier. This reinforces the importance of having such a model for mapping and describing vegetation types, and it would be beneficial if this model could be extended to include all vegetation types in South Africa. Conclusions The revised vegetation map of the NW is a significant improvement on the 2018 National Vegetation Map and has been incorporated into the current NVM 2024 beta release. Firstly, the vegetation type classification model based on five broad environmental variables (flooding, bioregion, terrain, geology and soil) provides a consis- tent and explicit framework for understanding the dis- tribution and hence mapping vegetation types. Whilst agricultural land types remain a good proxy for mapping vegetation, breaking these units down in their underly- ing environmental determinants (soil and topography) and mapping these provide better proxies for mapping vegetation. Secondly, the abundance of high-resolution remote sensing products, relative to the 1980s when land types were mapped, means that vegetation type boundary accuracy is significantly improved. Thirdly, al- though a quantitative phytosociological analysis was not able to be completed, based on the description of exist- ing vegetation types, the available literature, stakehold- er inputs and field observations, the current vegetation type concepts are valid units. It was necessary, however, to elevate three previously described vegetation con- cepts as new vegetation types to accommodate observ- able vegetation patterns in the landscape and also to align with the vegetation classification model. It is recommended that the existing azonal vegetation type category be replaced with the term alluvial for the three azonal vegetation types in the NW where occa- sional flooding or waterlogging is a primary determi- nant of vegetation. This alluvial vegetation type unit also contains the majority of wetlands in the province. This will not be the last word on the mapping of vegeta- tion in the NW. Despite the wealth of phytosociological literature available for the province, there are still major gaps in our descriptive vegetation science knowledge in the province. Also, there is no research at all that relates phytosociological vegetation concepts to the modern South African vegetation type concepts, and the vegetation classification model or framework de- veloped here might provide the basis for developing a similar framework for the entire country. Given the im- portance of vegetations types in environmental policy, planning and decision making, having clear, consistent Page 27 of 62   | Original research | Open accesshttp://abcjournal.org | and defensible environmental definitions for vegetation types will help practitioners identify and map vegeta- tion types on the ground. Acknowledgements This project was entirely funded by the North West Provincial Government Department of Economic De- velopment, Environment, Conservation and Tourism (Project number DEDECT 06/2021). The South Afri- can National Biodiversity Institute (SANBI) provided extensive technical support to the project, as well as facilitated access to data and contributed to fieldtrip expenses. We are grateful to the members of the proj- ect steering committee for their support and inputs on the project design and execution, namely, Tharina Bo- shoff, Adriaan van Straaten, Aluwani Tshiila, Malefyane Mosadi, Doug Macfarlane, Leo Quayle, Ryan Kok and Willem Boshoff. Many individuals provided valuable technical inputs, datasets or comments on the vege- tation map, namely, Andrew Skowno, Nacelle Collins, Lorraine Mills, George Bredenkamp, Jacobus Smit, Marc Stalmans, Tony de Castro, Noel van Rooyen, Naas Grové, David Hoare and Leslie Brown. The members of the National Vegetation Map Committee who re- viewed and commented on the draft manuscript are thanked for their insights: Tony Rebelo, Debbie Jewitt, Andrew Skowno and Kagiso Mogajane. Acocks, J.P.H., 1953, ‘Veld types of South Africa’, Memoirs of the Botanical Survey of South Africa 28, 1–192. Acocks, J.P.H., 1975, ‘Veld types of South Africa’, 2nd ed., Memoirs of the Botanical Survey of South Africa 40, 1–128. Acocks, J.P.H., 1988, ‘Veld types of South Africa’, 3rd ed., Memoirs of the Botanical Survey of South Africa 57, 1–146. 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