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Forests 2019, 10(12), 1093;

The Availability of Non-Timber Forest Products under Forest Succession on Abandoned Fields along the Wild Coast, South Africa
Department of Environmental Science, Rhodes University, Grahamstown 6140, South Africa
Author to whom correspondence should be addressed.
Received: 28 August 2019 / Accepted: 16 November 2019 / Published: 2 December 2019


Large swathes of arable fields have been abandoned in many areas of the world over the last few decades driven by a multitude of local and broader-scale factors. Many former fields experience a change in vegetation composition and structure post-abandonment, typically through a process of plant succession. The changes in species and abundance mean that the nature and quantity of ecosystem services provided by the former fields also varies. We examined the types of provisioning services obtained from non-timber forest products (NTFPs) with increasing age since field abandonment. We sampled 43 former fields ranging in age since abandonment from approximately 7 to 55 years, and seven plots in intact forests. We held seven focus group discussions with local residents to determine uses of species found in the former fields. Plant cover and species richness increased with former field age, although old field community composition was also influenced by soil chemistry. Of the 177 species recorded, 70 (40%) had one or more uses, spanning six NTFP categories namely, food, building, medicinal, craft, cultural and energy. The number of NTFP species increased with increasing age of the former field, but the proportion of NTFP species declined from 80% in the youngest former fields to 65% in the oldest ones, which were similar to the 63% recorded within intact forests. The youngest former fields had more medicinal species than the older ones, as the abundance and diversity of herbaceous species declined with increasing woody plant cover. Species used for building and food (especially fruits) peaked when the former fields became dominated by woody plants. NTFPs used for craft were most abundant in the oldest sites.
abandoned fields; field age; non-timber forest products; plant succession

1. Introduction

Land use change has significant effects on environmental, social and economic dimensions of rural livelihoods [1]. This is because most smallholder, rural communities and households are often highly dependent on the local landscapes and are tied to primary sector activities such as agriculture, forestry and the harvest of wild resources [1]. However, in many regions of the world increasing numbers of small-scale farming households are disengaging from arable production [2,3,4,5], including southern Africa [6,7,8,9]. For example, the amount of agricultural land that has been abandoned globally increased by over 150 million hectares from the 1940s to 1990s [2]. This dynamic is increasingly referred to as ‘deagrarianisation’ [10], which describes a general shift of rural livelihoods in a community or region away from being mostly agrarian to embrace increasing contributions of non-agrarian incomes, and, over time, a shift in identity away from agrarian. The underlying reasons for this land abandonment are multiple, complex and vary spatially, temporally and in relation to the scale of analysis [9,11,12]. Irrespective of the underlying reasons, this dynamic poses implications, as yet inadequately explored [9], for the livelihoods of those disengaging from agriculture, as well as the land and ecosystem goods and services the ‘abandoned’ land supplies or are in demand.
The ecosystem goods and services provided by abandoned fields vary according to the prevailing climate, soils and disturbance regimens as well as the post-abandonment trajectory. In some settings there is a turnover of plant and animal species and communities on the old lands, typically, but not always, characterised by increasing species richness, functional diversity, complexity, soil nutrients and vegetative biomass and carbon storage [13,14,15,16]. These changes are often referred to as plant succession [13,17]. After the concept of plant succession was first introduced in the late 19th century, the nature, rate and predictability of plant succession have been a central topic in ecology for decades [18,19]. Yet its application to contemporary understandings of the supply of ecosystem goods and services remains under-researched, especially in the context of the widespread abandonment of smallholder fields. In locations where a turnover of species, functions and processes is manifest, then the ecosystem services will vary accordingly. For example carbon sequestration is typically greater in the later stages of succession than in the early ones [20], as are pollination services [21]. In contrast, herbaceous forage production will probably be greater in the early stages [14]. Thus, there is a need to examine successional patterns within an ecosystem services framework, and how the mix and quantity of ecosystem services is contingent on where in a successional sequence a particular parcel of land might be.
Whilst rural communities rely on a great diversity of ecosystem services, provisioning services are particularly important for communities and households with limited financial or physical access to markets and non-land based livelihood options. For example, the use of locally collected wild resources, often termed non-timber forest products (NTFPs), contributes to all facets of rural life, including for energy, construction, food, health (via medicines), crafts and utilitarian items, decoration, as well as cultural products and a sense of identity [22]. A global synthesis concluded that NTFPs contribute, on average, 28% of household cash and non-cash income [23], and in some contexts or households, the contribution is on a par with, or even exceeds, agricultural income [24,25,26,27]. Thus, the availability of NTFPs is vital for many rural communities, including in the Wild Coast region of South Africa covered by this paper [15,28,29], and there is some evidence that it is especially so for poorer households and regions [30,31,32]. Consequently, factors that influence the availability and supply of NTFPs are important to identify, understand and manage. This includes changes associated with plant succession on abandoned fields. Indeed, Ashton et al. [33] opined that NTFPs can be more abundant in secondary growth forests as compared to late successional forests, however, this might not hold for all types of NTFPs. Indeed, we are unaware of any work that has previously investigated the relationship between plant succession and the availability of NTFPs other than the broad distinctions between primary and secondary forest, and in particular, whether or how the supply of NTFPs varies with plant succession on former, now abandoned, agricultural fields. Indeed, in settings where field abandonment is driven by push factors associated with cropping, such as declining soil fertility, increasing costs or labour shortages, the relative importance of NTFPs to household cash or non-cash income may conceivably increase as households attempt to compensate for the loss of agricultural produce or income from the now deactivated fields. Shackleton et al. [15] reported that abandoned fields were important sources of NTFPs in the Willowvale area of the Wild Coast. Thus, knowing what NTFPs are available and how that changes with post-abandonment age of the field would be extremely useful.
Within this context this study sought to examine how forest succession affects the composition and abundance of NTFPs. Two objectives were considered, (i) To identify when the delineated arable lands stopped being cultivated and assess the subsequent rate and nature of succession, and (ii) Assess any changes in richness, composition and abundance of plant NTFPs with succession.

2. Study Area

The study was conducted in the Willowvale/Gatyana area towards the Indian Ocean coastline from Willowvale town (32°15′47′′ S; 28°28′50′′ E in the Eastern Cape, South Africa (Figure 1). The Willowvale area consists of dispersed rural villages and homesteads between the town of Willowvale and the coast, generally characterised by a lack of infrastructure, poor transport systems, and limited local markets [34]. It is regarded as amongst the poorest districts in the country [35], and over 90% of households have cash incomes below the national poverty line and unemployment is above 75% [36]. Livelihoods are diverse, with a combination of arable farming, home gardening, livestock husbandry and collection of NTFPs, alongside ad hoc employment, remittances from migrant family members working in urban centres and government social grants [36]. The population density is approximately 26 persons/km2 and 55% of households are female-headed.
The area was chosen because of the prevalence of abandoned agricultural fields, forests and woodlands regenerating on the former fields and the use of NTFPs by the local people as reported in previous studies conducted in the area [15,36]. The area is dominated by rolling hills and valleys of the Indian Ocean Coastal Belt biome [37]. It is situated at an altitude of approximately 660 m above sea level and receives approximately 1000 mm of rainfall per year, with March as the peak rainfall month [38]. It has a warm and mild climate with February being the hottest month at an average temperature of 20.5 °C and July being the coldest month at an average of 13.3 °C [38]. The area falls within the Maputaland-Pondoland-Albany biodiversity hotspot, characterised by its high level of biodiversity and approximately 1900 endemic species [39]. The natural vegetation in the area of Willowvale is a mosaic of forest, thornveld, dune thicket and grasslands [15,37]. Forests in the area are naturally fragmented and concentrated on the moist, deeper soils in valleys, whereas grasslands dominate on the hill slopes and crests, often with successional acacia woodland in the transition zone between the two vegetation types [39]. Land is held under communal tenure and allocated by traditional authorities [29,34]. Each household receives a site to build a home and cultivate a small food garden. Households may also apply for a larger piece of land (1–3 ha), usually some distance from the homestead, for cultivation [7,15]. It is these larger fields that were of interest in our study. All lands not used for homesteads or cultivation are open to all residents for grazing of domestic livestock and collection of NTFPs [15,34]. In the early stages of field deactivation fields remain the ‘property’ of the household because of the possibility that they may recultivate it at some stage. But, with the prolonged lack of cultivation the old field becomes accessible to all.

3. Methods

3.1. Data Collection

The first step was to identify and determine the approximate age of former fields. Available aerial photographic images (1: 30,000) of the region, taken approximately every decade, were obtained from the national directorate for Geo-Spatial Information ( for the years 1942, 1961, 1972, 1985, 1995 and 2009 (the photos from the early 1950s were unclear and could not be used). On each photo, cultivated fields were identified and then followed through time on each of the subsequent photos. Those that were cultivated in a photo at time t, but not in the subsequent photos were deemed to have been abandoned, and the date of deactivation was approximated as midway between the date when last cultivated and the date when first not cultivated. This date was deducted from 2016 (when the fieldwork was done), which gave an approximate age of each former field at the time of fieldwork. On the aerial photo the aerial cover of woody trees and shrubs was estimated for each former field through time by placing a 1 cm2 square (representing 200 m2 on the ground) more or less in the centre and visually estimating the woody cover as a percentage of the square.
In summer 2016, the various former fields delineated on the aerial photos were sampled in the field to determine plant species richness, composition and abundance. Approximately 10 fields were selected per decade since abandonment, with a total of 43 former fields. Additionally seven plots were sampled in intact forests (forest stands without any obvious signs of previous clearing, cultivation or heavy use during fieldwork or from the aerial photos) to represent the relatively undisturbed state, regarded as typical of late succession. Plots of 10 m × 20 m were laid out in the centre of each former field and all plant species recorded. The number of grass species was underestimated due to many of the former fields being extensively grazed, and some burnt. Specimens of unfamiliar species were collected and sent to the Selmar Schonland Herbarium for identification. Species richness was calculated as the number of species recorded in each plot [40]. The cover-abundance of each species was estimated by means of the seven-point Braun-Blanquet scale [41,42]. Slope position was recorded on a five-point scale, slope angle with an Abney level, altitude via a GPS and notes on the site and signs of disturbance were made. In each 200 m2 plot, four 5 m × 5 m quadrats (in the centre of each quadrant of the plot) were used to visually estimate the percentage cover of rocks, bare ground, litter and herbaceous cover. Soil samples were collected from each quadrant to a depth of 10 cm, mixed per plot, and sent to a commercial laboratory to be analysed for texture (silt, clay and sand) and soil nutrients (Calcium (Ca), Potassium (K), Carbon (C), Magnesium (Mg), Sodium (Na), Ammonium nitrate (NH4NO3) and Phosphorus (P)).
Lastly, seven focus group discussions were held with 6–10 participants to determine which plant species were used by the local communities and for what purpose. Each focus group was carried out in a location near to every group of former fields that had been ecologically assessed. Knowledgeable participants were identified with the aid of the local headmen in various parts of Willowvale. Emphasis was placed on encouraging a diversity of participants across age, gender and livelihood experiences within each focus group. Each was conducted in the local language, isiXhosa, and generally lasted two to three hours. After introductions, the purpose of the research was explained, and participants were afforded opportunities to ask questions of the researcher as a means of promoting their understanding of the project. It was also emphasised that all opinions were valid, that there were no wrong or right answers, and that rather it was a learning process through knowledge sharing within the group. Participants were also reassured that their comments and contributions would not be recorded by name. Thereafter, photographs of all the plant species recorded during the ecological assessment were projected into a wall, which would then kick start a conversation of what the plant was, its local name, if it had any uses, and if so, what it was used for. After plant identification, there would be a discussion around the use and how important it was in everyday life or cultural importance and after consensus, each species was given an importance rating on a scale of 1 to 5, with 1 being not important at all and 5 being extremely important.

3.2. Data Analysis

Data were entered into Microsoft Excel which was used for calculation of descriptive statistics. The data were then imported into Statistica (v13; Statsoft, Oklahoma) for formal statistical testing, including linear regression between former field age and both woody cover and species richness. In the regressions the age of intact forests was set at 100 years following Shackleton et al. [15]. The full suite of floristic composition analytical tools in PRIMER (v6; Primer, Plymouth) was used for analysis of floristic composition, including a Similarity Percentage analysis (SIMPER) of similarities between the former fields, a Similarity Profile Analysis (SIMPROF), and an Analysis of Similarities (ANOSIM) to examine differences in species composition between different-aged old fields and between the old fields and forests [43]. Multi-dimensional scaling (MDS) was used to assess how the plots were grouped and the environmental variables that separated them. Lastly, a BEST analysis was used to assess which of the environmental factors best described the vegetation data and the species composition in the delineated lands. See Clarke [44] for discussion of the basics of floristic community analysis.

4. Results

4.1. Change in Woody Cover with Increasing Age of Former Fields

The oldest and the youngest group of the sampled former fields were abandoned approximately 55 and 7 years ago, respectively. Immediately after field abandonment, there was little vegetation cover but it gradually increased through time, with a positive relationship between former field age and woody cover (R2 = 0.43; p < 0.05). However, even after 55 years, the woody cover in the former fields was still only approximately half of that of intact forests (Figure 2).

4.2. Change in Plant Species Richness with Increasing Age of Former Fields

Mean plant species richness per plot increased with the approximate age of the former field (R2 = 0.12; p < 0.05). (Figure 3). Of a total of 177 plant species recorded across all sample plots (including intact forests), 75 (42%) of them were shrubs, such as Coddia rudis (E.Mey. ex Harv.) Verdc. and Searsia glauca (Thunb.) Moffett, 72 (40%) were herbaceous perennials and annuals (only two were grasses) and 30 (17%) were trees such as Brachylaena discolor DC. and Cussonia spicata Thunb. The youngest former fields were dominated by herbaceous and shrub species, with tree species making only a gradual appearance with time. The SIMPER analysis where plot type (old field/forest) was used as a factor, indicated the top five species for old lands were Vachellia karroo (Hayne) Banfi & Glasso Lantana camara L., Centella asiatica L. Hyparrhenia hirta (l.) Stapf. nd Diospyros lycioides Desf. and the most dominant species in forests were Dalbergia obovata E.Mey., Monanthotaxis caffra (Sond.) Verdc., Buxus natalensis (Oliv.) Hutch., Senegalia caffra (Thunb.) P.J.H.Hurter & Mabb. and Canthium inerme (L.f.) Kuntze.

4.3. Community Classification

The SIMPROF cluster analysis clustered six of the seven forest plots as distinct from former fields, which using a multi-dimensional scaling (MDS), were clearly separated by age. This was, however, barring one forest plot that was grouped with old fields. However, the community composition of the former fields was not significantly differentiated by age. Rather the classification grouped the former fields into four significantly different communities. The clusters (communities) were also used as a factor in a SIMPER to show the different species contributing the most to each community. A BEST analysis highlighted the environmental or site variables that best explained the species composition in the community clusters.
Table 1 presents the top five species that contributed the most to the average similarity percentage within the groups, how much they contribute and the similarity in species composition within the plots of the same group. The Hyparrhenia-Centella community was characterised by herbaceous species and only a few shrub species. The Coddia community had the highest average similarity between group members, although still only a Bray-Curtis similarity measure of 48%, indicating relatively weak similarity. Although the Coddia community had a mixture of both shrubs and herbaceous species, shrubs dominated as the top five species to the group. The Lantana-Diospyros and the Helichrysum communities showed similar characteristics with the first and second communities, respectively. The most common shrubs in the former field communities were Vachellia karroo (a shrubby coppice form), Lantana camara (an invasive alien species), Coddia rudis and Diospyros lycioides. The most common herbaceous species were Hyparrhenia hirta, Centella asiatica Helichrysum odoratissimum (L. Sweet), Falkia repens Thunb. and Hibiscus trionum L.

4.4. Environmental and Site Correlates

The BEST analysis highlighted four factors at 0.59 correlation that most influenced species composition of the sample plots (Table 2), namely altitude, phosphorus (P), ammonium nitrate (NH4O3) and field age. Other variables that influenced species composition in all the plots but at a marginally lower correlation (0.57) were soil calcium (Ca) and potassium (K). When the BEST analysis was performed on former fields only (without forest plots), the main correlates were altitude, P, NH4O3 and K at a correlation level of 0.40. Other correlates that had an influence on species composition of abandoned fields were Ca, age and pH at a 0.39 correlation. Thus, the majority of the variables influencing community composition on the old fields were soil attributes, rather than age, and generally the forests were richer in all soil nutrients than the former field communities.

4.5. Change in NTFPs with Increasing Age of Former Fields

Of the 177 species recorded across the 50 sample plots, 70 (40%) were identified by the focus group participants as having one or more uses. The participants grouped the NTFPs into six use categories, namely: food, building, medicinal, craft, cultural and energy. The species group with the greatest number of species was building (timber for houses, fencing, building livestock enclosures, and fibre for roofing) as well as medicinal, followed by species that have traditional or cultural significance and species that serve as foods (Figure 4). The two smallest groups were for crafting, such as making walking sticks and brooms, and firewood. The species most used as NTFPs were mainly shrubs except medicinal and craft uses where herbaceous and tree species dominated, respectively (Figure 4).
Of the 70 species with an identified use, 64% had one use, 31% had two uses and 4% had three uses. The species that had three uses were Ptaeroxylon obliquum (Thunb.) Radlk., Diospyros lycioides and Vachellia karroo. Ptaeroxylon obliquum was used for building, firewood and traditional ceremonies. Diospyros lycioides was used for building, firewood and its fruits were sometimes eaten, especially by children. Vachellia karroo was used for firewood, medicine for both humans and livestock and the resin was used as food to some people (especially children and herders).
The number of NTFP species increased with increasing age of the former field (Table 3). The oldest fields had an average of 18 NTFP species per 200 m2 sample plot, compared to the youngest former fields which had seven. However, non-NTFP species also increased with age of the old field, and at a higher rate than that of the NTFP species. Consequently, the proportion of NTFPs within the species assemblage decreased with increasing former field age. In the youngest former fields 80% of all the plant species recorded in the sample plot were NTFPs, but in the oldest former fields only 65 % were, which was similar to intact forests (63%).
Although the older successional sites had more NTFPs than the early ones, this was not the case for all NTFP use categories (Table 4). People used different quantities and kinds of NTFPs from different stages of succession. For example, most herbaceous species identified as NTFPs were listed in the medicinal category. Consequently, the early successional sites had significantly more medicinal species than the later ones, as the abundance and diversity of herbaceous species declined with increasing woody plant cover. Species used for building and fruits peaked when the former fields become dominated by woody plants. Building species increased as succession progressed. NTFPs used for craft were most abundant in the oldest sites. This is because people mostly crafted walking and fighting sticks harvested from woody plants.

5. Discussion

The results clearly demonstrated that cultivated fields that are abandoned generally become dominated by shrubby and later, tree species, such that the woody cover steadily increased through time after cultivation ceased. This echoes findings from a number of sites from the wooded biomes of South Africa [8,9], including in the Wild Coast region [15,45]. However, the rate may vary at landscape and even plot scales due to differences in the biophysical context and the use of, or disturbance to, the former field through processes such as harvesting, herbivory, fire or invasive species [46,47,48]. The increasing cover of woody plants after field abandonment has also been reported internationally in countries such as Belarus, [47], China [14], Egypt [49], Spain [50], and the USA [20], to mention a few.
This implications of this natural reforestation are pertinent not just for the local people in the area. The forest biome is the smallest biome in South Africa, and the greatest concentration of forests occurs along the Wild Coast [39]. This is a designed biodiversity hotspot and rated highly as a priority conservation area [39]. These forests are among the most species-rich temperate forests worldwide [51]. Thus, ‘recovery’ in the area of forests, and a reduction in their fragmentation caused by fields, should promote forest integrity, health and processes at larger scales. Collection of NTFPs is likely to be more compatible with forest conservation at a landscape scale than clearance of forests for agricultural fields. However, outcomes for particular NTFP populations and species will depend on the intensity of harvest.
Plant species richness in the old fields increased with age post-abandonment, as also reported by others [14,52]. After five decades of abandonment the number of plant species at the plot scale was similar to that of intact forests. The rate of establishment of tree species was considerably slower than herbaceous or shrub species, which is not unusual for old field succession [15,40]. However, although species richness of secondary succession may be quick to mirror that of primary forests, community composition takes longer. According to Guariguata and Ostertag [13] this depends on the intensity of past land use and environmental conditions. The species composition on old fields was very distinct when compared to that of forests. When examining the dominant species between old fields and primary forest, there were some common species, including Dalbergia obovata, Searsia crenata (Thunb.) Moffet., Zanthoxylum capense (Thunb.) Harv., Diospyros lycioides, Centella asiatica and Cynoglossum hispidum Thunb. However, age did not produce differentiation in overall species composition amongst the former fields, but it did separate old fields from forest sites. The absence of clear community compositional differences based on age suggests that the rate and nature of old field succession in this region is influenced by more by site factors, such as soils, or post-abandonment uses and disturbance. For example, Jevon & Shackleton [53] reported how invasion of the alien shrub, Lantana camara, arrested recruitment of native forest species in the area. Such post-harvest dynamics would therefore influence the availability of NTFPs to local communities.
This study has corroborated several others from southern and South Africa showing that rural communities know and use a wide diversity of plant species for a range of household and cultural needs [31,54,55,56]. Seventy species were identified by the focus group participants as having one or more uses. At the plot scale, between 63% and 80% of the species were regarded as NTFPs. The proportion declined with increasing species richness of a plot. This suggests that a mix or a mosaic of different aged patches would be the best to optimise the local availability of NTFP species, i.e., increasing habitat diversity will benefit the species diversity of NTFPs. Indeed, Shackleton et al. [15] working in the same area, reported that people view old fields as important sites for the collection of NTFPs, not only for the range of species found in them, but also because they were relatively more accessible because the woody vegetation was not too dense.
Comparisons to other literature is inadvisable because most studies on how many NTFP species are used are usually based on free-listing, whereas our study used only those species found within the sample plots, which were old fields. Sites that would never have been cultivated (such as on steep slopes, rocky areas, shallow soils, distant from the homestead, temporarily inundated areas, etc.) were therefore not part of this survey, and consequently the total number of species, and the number of NTFPs will be lower than what may have been found via free-listing of all landscapes. Even the exclusion of active fields resulted in lower counts of useful species, especially for wild, traditional African vegetables (imifino). Most imifino species in South Africa are ‘weeds’ in disturbed sites, and consequently many species thrive in active fields [55] and are harvested from there for home consumption. Thus, there are many more imifino species in the Willowvale area [36,57] than were revealed during our study of former fields. Nonetheless, considering all the use types, the percentage values are similar to the observation by Geldenhuys [58] that approximately 77 % of sub-canopy forest tree and shrub species and 94 % of forest tree species have some traditional or commercial use. Dovie [54] examined patterns of useful and non-useful woody species around ten South African rural villages in the savanna and thicket biomes and reported that amongst the full inventory of 191 woody species, 71% had one or more uses, and at the individual plot scale (1000 m2) it varied between 80% and 100% of tree and shrub species.
The advantages of having a diversity of different aged patches is further advanced when the different use categories and life forms are examined. With respect to life forms, herbaceous species were most prevalent in the recently abandoned fields, and declined as the shrub and tree cover increased. Shrub richness was highest in old fields of intermediate age, and tree richness in the oldest abandoned fields. Consequently, residents seeking concentrations of herbaceous medicinal species would have the greatest success in relatively young sites, whereas those seeking building-timber species would probably make greater use of old former field sites or intact forests. Based on local ecological knowledge of locations and patterns or relationships between species and biophysical factors (e.g., soil type, proximity to water) most residents will know where to find particular species [59]. However, the increasing abandonment of agriculture adds another determinant of species distributions in the local landscapes. However, this determinant is not static, but changes with time, as do the effects of fire, also likely to be affected by successional changes, especially the ratio of herbaceous to tree biomass and species and corresponding fuel loads. This means that knowledge of where particular species may be found, and in what abundance will need to be adaptive to the changing circumstances [59].
The two most species-rich use categories were building timber and medicinal plants. This is very evident in the area, with most households having some traditional structures or fencing constructed wholly or partially from locally sourced materials. Although medicine was one of the major uses of NTFPs, use is not premised on a lack of access to modern healthcare facilities, but rather the use of self-medication or traditional healers for particular needs in parallel to modern health care facilities. According to Dold and Cocks [60] this is because many Xhosa people ascribe many illnesses to the spiritual world and the presence of bad spirits rather than physical health symptoms, and consequently traditional treatments are required.
In conclusion, forest succession leads to the provision of a different suite of ecosystem services than when the fields were ploughed, resulting in agricultural crops being replaced with a variety of NTFPs. Although, plant species richness increased with forest succession, the number of NTFPs did not increase at the same rate, resulting in a gradual decline in the proportion of NTFP species with succession. Moreover, particular use types of NTFPs varied according to the time since abandonment. Therefore, field abandonment in the area of Willowvale has provided the local people with more areas for the collection of NTFPs, which are an important part of local livelihoods. The policy implications span from the necessity for greater understanding of the contextualised and cross-scale causes and consequences of field abandonment [9], through to appreciating that land in the area provides a variety of ecosystem services at local and societal scales beyond just food. This study has focused on NTFPs within the successional landscapes, but similar investigations are required for any number of ecosystem services, such as sense of place and identity, biodiversity, water, carbon sequestration and nutrient cycling. This also applies to ecosystem disservices, with abandoned fields already being noted as potential nodes for invasive species in the area [15,53], or potentially dangerous animals being in closer proximity to homesteads as the forest re-establishes [61]. From a NTFPs management perspective this work reveals the benefit of having a mosaic of sites of varying successional ages. Strategies for maintenance of a range of different aged sites in support of a wide range of NTFPs will be required at local level. Currently available tools are the use of fire and browsing by domestic livestock, which in turn, may have as yet unknown differential effects on the diversity and abundance of specific NTFPs.

Author Contributions

The project conceptualization C.M.S.; methods C.M.S. and A.N.; data collection A.N.; data analysis A.N. and C.M.S.; original draft A.N.; writing, review and editing C.M.S.; supervision C.M.S.; funding acquisition C.M.S.


This research received no external funding.


We are grateful to the communities of Willowvale for their willingness to share their knowledge and participate in the study. This work was sponsored by the South African Research Chairs Initiative of the Dept of Science and Technology and the National Research Foundation of South Africa (Grant No. 84379). Any opinion, finding, conclusion or recommendation expressed in this material is that of the authors and the NRF does not accept any liability in this regard.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Location of Willowvale in the Eastern Cape province of South Africa.
Figure 1. Location of Willowvale in the Eastern Cape province of South Africa.
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Figure 2. Mean woody cover change in former fields of different ages and intact forest.
Figure 2. Mean woody cover change in former fields of different ages and intact forest.
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Figure 3. Change in mean plant species richness of trees, shrubs and herbs per plot (200 m2) with the approximate age of old field, and intact forest.
Figure 3. Change in mean plant species richness of trees, shrubs and herbs per plot (200 m2) with the approximate age of old field, and intact forest.
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Figure 4. The number of NTFP species in each use category (n = 70 species).
Figure 4. The number of NTFP species in each use category (n = 70 species).
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Table 1. Top five species that contributed the most to the average similarity percentage within the groups (SIMPER analysis), how much they contribute and the similarity in species composition within the plots of the same group.
Table 1. Top five species that contributed the most to the average similarity percentage within the groups (SIMPER analysis), how much they contribute and the similarity in species composition within the plots of the same group.
CommunityNo. of PlotsSimilarity (%)Common Plant Species
Outliers210.8Vachellia karroo (24.3%), Centella asiatica (24.3%), Diospyros lycioides (17.2%), Helichrysum nudifolium (17.16%), Taraxicum sp. (17.2%).
Hyparrhenia-Centella444.6V. karroo (26.1%), Hyparrhenia hirta (18.2%), C. asiatica (11.7%), Helichrysum odoratissimum (7.7%), Falkia repens (5.1%), Taraxicum sp., Merxmuellera disticha, Helichrysum anomalum, Lantana camara, Cotula heterocarpa, Gerbera ambigua, Spermacoce natalensis.
Coddia548.6V. karroo (10.5%), L. camara (9.5%), Coddia rudis (7.9%), D. lycioides (7.0%), C. asiatica (5.8%), Senegalia caffra, Lippia javanica, H. odoratissimum, Searsia glauca, H. anomalum, Grewia occidentalis, Fern, Taraxicum sp., M. disticha, Dyschoriste setigera, Zanthoxylum capense, F. repens, Melhania didyma, H. nudifolium, Aristea sp.
Lantana-Diopsyros1743.0L. camara (23.4%), V. karroo (16.0%), D. lycioides (7.1%), H. hirta (6.5%), C. rudis (5.7%), C. asiatica, Lippia javanica, S. glauca, Z. capense, Fern, Maesa alnifolia, Cynoglossum hispidum, Hibiscus trionum, Dalbergia obovata, Gymnosporia harveyana, Senecio pterophorus, Rubus rigidus
Helichrysum1637.4V. karroo (20.2%), Centella asiatica (17.2%), H. hirta (16.2%), H. trionum (8.7%), L. camara (7.6%), C. heterocarpa, Fern, Helichrysum cymosum, H. odoratissimum, D. lycioides, G. harveyana, L. javanica, Taraxicum sp.
Table 2. Mean ± SD (standard deviation) of the environmental variables with the highest correlation level of 0.59 from the BEST analysis.
Table 2. Mean ± SD (standard deviation) of the environmental variables with the highest correlation level of 0.59 from the BEST analysis.
Comm-UnityAltitude (m)Calcium (cmol/kg)Phosph-Orous (mg/kg)Ammonium Nitrate (%)Potassium (mg/kg)pH (mol/L)Field Age (years)
Hyparrhenia-Centella183 ± 513.1 ± 0.712.8 ± 4.10.2 ± 0.4143 ± 855.5 ± 0.238.3 ± 11.5
Coddia284 ± 95.6 ± 2.611.0 ± 6.80.3 ± 0.1359 ± 1265.7 ± 0.336.6 ± 17.3
Lantana-Diospyros120 ± 643.1 ± 1.423.2 ± 9.40.2 ± 0.1199 ± 775.0 ± 0.439.4 ± 23.0
Helichrysum138 ± 803.1 ± 1.618.1 ± 6.70.3 ± 0.1177 ± 985.3 ± 0.436.3 ± 16.2
Forest188 ± 16711.7 ± 14.633.8 ± 12.00.6 ± 0.2253 ± 1595.2 ± 0.6100 (set)
Outliers278 ± 534.1 ± 2.59 ± 4.240.21 ± 0.1106 ± 515.3 ± 0.338.2 ± 24.0
Table 3. Change in the number and proportion of NTFP species in sample plots (200 m2) with increasing age of former fields and in intact forests.
Table 3. Change in the number and proportion of NTFP species in sample plots (200 m2) with increasing age of former fields and in intact forests.
Species Per 200 m2 PlotApproximate Age of Former Field (yr)Forest
Mean no. of species8.817.521.120.627.424.8
Mean no. of NTFP species7.014.016.414.517.815.6
NTFP species as a proportion of total species (%)79.580.077.770.065.062.9
Table 4. The percentage of different uses per age of former field and intact forest.
Table 4. The percentage of different uses per age of former field and intact forest.
Age of Old FieldTraditional/Cultural (ceremonies)MedicinalFoodCraftEnergyBuilding
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