Next Article in Journal
Effects of Biochar on Soil Organic Carbon Stability in Degraded Alpine Grasslands—A Study on Arid Regions in Central Asia
Previous Article in Journal
Spatial Mismatch Between Transportation Development and Tourism Spatial Vitality in Yunnan Province in the Context of Urban–Rural Integration
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Desertification as a Social–Ecological Trap: How Does It Come About and What Are Namibian Freehold Farmers Doing About It?

1
ISOE—Institute for Social-Ecological Research, Hamburger Allee 45, D-60486 Frankfurt am Main, Germany
2
Institute of Physical Geography, Goethe University Frankfurt, Altenhöferallee 1, D-60438 Frankfurt am Main, Germany
3
Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Georg-Voigt-Straße 14, 60325 Frankfurt am Main, Germany
*
Author to whom correspondence should be addressed.
Land 2025, 14(5), 1016; https://doi.org/10.3390/land14051016
Submission received: 7 March 2025 / Revised: 30 April 2025 / Accepted: 2 May 2025 / Published: 7 May 2025

Abstract

:
Desertification, accompanied by the loss of perennial grasses and bush encroachment, affects more than 10% of the world’s drylands, thereby placing increasing pressure on rangelands and farmers’ livelihoods. In Namibia, rangeland desertification is exacerbated by external shocks such as droughts, market changes, and new regulatory frameworks that have led to profound social and ecological changes within this tightly coupled social–ecological system (SES). In this context, the interrelationship among system components, drivers, and external factors, as well as the impact of strategies to halt desertification, remain poorly understood. The present study employed a retrospective mixed-methods approach to investigate the drivers of desertification on Namibia’s freehold farms by applying the social–ecological trap (SET) concept. Our approach combined remote sensing methods with semi-structured interviews and a literature review. The aim was to decipher the underlying processes and self-reinforcing feedback loops and to identify associated changes in the social and ecological subsystem. Our results revealed that inadequate grass availability, coupled with income deficits, serves as a pivotal catalyst for rangeland desertification, perpetuating a self-reinforcing feedback loop. To avoid or mitigate the effects of ecological regime shifts and to help farmers escape the SET of desertification, it will be necessary to implement changes in the dominant feedback loops through long-term risk mitigation strategies, such as rangeland restoration measures, as well as on- and off-farm income diversification. These strategies will provide a foundation for subsequent research on effective long-term mitigation strategies to prevent further rangeland desertification and to secure the livelihoods of farmers.

1. Introduction

Globally, about one billion people depend on dryland ecosystem services on a daily basis, although almost two-thirds of the world’s drylands are arid or semi-arid rangelands with erratic rainfall [1,2]. Desertification, defined as persistent reduction in biological productivity [3], affects more than 10% of the world’s drylands [4], putting increasing pressure on fodder resources and farmers’ livelihoods [5,6,7]. Several factors, such as climate change, population growth, and inadequate land use practices contribute to desertification and poor rangeland conditions [5]. However, the causes and resulting changes in rangelands are highly complex and vary by location, making a single-cause explanation inadequate. Consequently, local studies are imperative for the identification of desertification trends, along with their underlying causes and consequences [7,8].
In Namibia, the driest country in sub-Saharan Africa, more than a third of the land is used for cattle farming and is particularly vulnerable to desertification [9]. Commercial cattle farming plays an important economic role, directly contributing around two percent to the gross domestic product [10,11]. For several decades, the abundance of fodder resources for livestock and game has been threatened by the ongoing process of rangeland desertification, accompanied by the loss of perennial grasses and bush encroachment [5,12]. The literature on desertification in Namibia shows that, over the past 100 years, external shocks such as droughts, profound market changes, and new regulatory frameworks have repeatedly led to social and ecological changes on freehold cattle farms, forcing farmers to adopt short-term risk coping strategies and long-term risk mitigation strategies in order to maintain their farms [13,14,15,16,17]. These strategies encompass dynamic herd and fodder supply management as well as income diversification [18]. Nevertheless, the farmers’ adaptive capacity appears to be inadequate to mitigate effectively the impact of external shocks such as an increased frequency and severity of droughts [19].
Such external shocks, as well as gradual changes (e.g., climate change, habitat loss, and market prices), may also affect the prevailing social–ecological feedback loops within the rangeland social–ecological system (SES) [20,21]. Should the ecosystem pass a certain threshold (i.e., tipping point) and subsequently undergo a transition from a ‘healthy’ ecosystem state (i.e., characterized by abundant perennial grasses) into a ‘degraded’ ecosystem state (i.e., bush encroached or barren rangeland), a regime shift will occur. This is accompanied by a reorganization of the system’s social–ecological feedback loops, as human actions—e.g., land management decisions, policies, and livelihood adaptations—both influence and respond to ecological changes [22,23]. Such reorganization may induce trap situations in which communities are caught in self-reinforcing cycles that favor unfavorable conditions and ultimately drive the regime shifts associated with desertification. In the SES community, such trap situations causing and/or reinforcing unfavorable system states are often referred to as social–ecological traps (SETs) [22,24,25]. The conceptualization of SETs is grounded in empirical case studies [26]; for example, Cinner (2011) [24] examined the role of SETs in East African reef fisheries, Brinkmann et al. (2021) [27] identified a nested set of SETs that subsistence farmers in southwestern Madagascar fall into, while Hanh and Boonstra (2018) [28] investigated the diversity of responses to SETs in Vietnamese small-scale fisheries and aquaculture.
Boonstra and De Boer 2014 [29] argue that the concurrence of social and ecological events in time plays a pivotal causal role in explaining the emergence of path-dependent SETs. However, the interrelation between drivers and external factors, as well as the impact of mitigation strategies in the establishment and/or prevention of traps, remains poorly understood [28,29,30]. Furthermore, there is a dearth of knowledge regarding strategies to escape from SETs. Trap situations may also create new opportunities to navigate ‘out of the trap’ into a new regime state if farmers apply strategies that allow them to cope with the situation or even break out of such traps. With regard to rangelands, considered as SESs [31], the literature indicates that both the ecological and the social subsystems of these SESs have the capacity to cope with disturbances and to respond to change with adaptation or transformation [32].
Although the SET concept promises a better understanding of the underlying feedback loops of desertification (see also Easdale and Domptail [33], who described the desertification process as a vicious circle with self-reinforcing feedback loops), it has not yet been applied to rangeland SESs.
Our study shows how the SET concept can be used for an empirical case study on rangeland desertification in the Waterberg region in Namibia. The complex interplay of the various factors that contribute to the desertification of rangeland and bush encroachment and their drivers was analyzed in a previous study for the entire Waterberg region by Brinkmann et al. [17]. In the current study, we sought to uncover the underlying self-reinforcing feedback loops that lead to SETs in order to provide important information for the design of sustainable adaptation strategies for rangeland management. The objectives of our study were, therefore, to (i) analyze underlying drivers that lead to SETs and associated social–ecological regime shifts in freehold farms by using a retrospective, mixed-method approach, (ii) investigate freehold farmers’ short-term risk coping and long-term risk mitigation strategies to escape the SETs, and (iii) identify the common patterns and feedback loops within the SET in a qualitative model.

2. Materials and Methods

2.1. Study Site: Waterberg Region, Namibia

The Namibian Waterberg region is located approximately 250 km north of Windhoek in the Otjozondjupa Region and is part of the Kalahari Sandveld [34]. The semi-arid climate is characterized by a dry season (May–Oct) and a rainy season (November–April) with annual precipitation ranging from 350 to 400 mm (Atlas of Namibia Team, 2022). Due to the highly variable spatio-temporal distribution of precipitation, extreme interannual variability can occur [35]. Extensive droughts approximately occur every 14 years and are typically associated with El Niño events [36,37]. As a result, rainfall is an unreliable source of water for livestock; thus, farmers rely primarily on groundwater resources. The study area is dominated by erosion-prone, sandy soils with limited water- and nutrient-holding capacity [34]. The dominant thornbush savanna is a mosaic of shrubs and trees of the genus Acacia and perennial grasses [35], with considerable variation in shrub density, grass availability, and composition. The study area has a dual land tenure system, comprising both freehold and communal land, in which several communal conservancies were established in 2005. It also includes the Waterberg Plateau Park, proclaimed in 1972. Within this region, this study focused on 17 freehold farms comprising a total area of 1679 km2 (Figure 1). Three farm types could be distinguished: (1) pure cattle farms, (2) guest/hunting farms, and (3) mixed farms. This categorization was based on the share of different income-generating activities in the total farm income. Pure cattle farms derived most of their income from cattle husbandry, the breeding and sale of cattle, cattle market speculation, and livestock husbandry-related activities (e.g., hay making and sale), while guest and hunting farms derived most of their income from safari and hunting tourism on their premises. In addition to livestock husbandry and tourism, mixed farms derive a significant proportion of their income from off-farm activities. The sale of live game and game meat, crop production, and charcoal production also play different roles for different farm types.

2.2. Baseline Analysis: Literature Review and Interviews with Freehold Farmers

The recent academic literature, as well as the literature from colonial archives (i.e., the Digital Collection German Colonialism), was used in order to explore the general historical context and evolution of the farming conditions that have shaped today’s freehold cattle rangeland in Namibia and that may have contributed to regime shifts and trap situations. In addition, laws and policies, as well as events affecting livestock husbandry and game farming such as droughts, animal disease epidemics, and market changes, were extracted from the literature.
All farmers in the region whose contact details were publicly available or otherwise available to the project team were contacted and invited for initial interviews. Based on the available time and their willingness to participate, semi-structured interviews were then conducted in 2019 with the freehold farmers (n = 10) in the study region to collect baseline data on rangeland management and the challenges experienced, including the farmers’ strategies to cope with these SET-related challenges. In addition, a snowball method [38] was used to expand the contact network through interviewee recommendations of potential participants for further interviews.
As fieldwork could not be carried out in 2020 due to the COVID-19 pandemic, additional (n = 7) farmers were interviewed using an online survey tool (LimeSurvey, Cloud version 3.27.19) between November 2020 and March 2021, with a follow-up at mid-term. A total of 22 freehold farmers were invited directly to the survey, where contact details were available online and via the local branch of the Namibia Agricultural Union mailing list. The interview guidelines included questions on general farm characteristics, rangeland management practices, and animal husbandry from 1970 to the present and perceptions of land use changes (see Appendix S1). The aim was to identify land use, land cover, and socio-economic changes and their possible drivers from the farmers’ perspective. Interviews were recorded and transcribed and coded using MAXQDA 2022 [39]. We analyzed the interviews using qualitative content analysis, structuring the content based on main thematic categories [40]. Main thematic categories were deductively derived from the research questions and tested for applicability by coding 10% of the text material. Relevant passages were then assigned to these categories, and inductive sub-categories were developed to further refine the analysis.

2.3. In-Depth Analysis of Farm Changes for Analyzing Underlying Narratives That Lead to SETs

Based on the interview and survey responses (n = 17), a customized interview guideline (see Appendix S2) was developed for qualitative, in-depth interviews with selected freehold farmers on their farm history and rangeland changes (n = 4). We focused on farms that represented the main farm type with mixed income-generating activities and where cattle still played an important role. Farmers were then selected based on their willingness to participate in the in-depth interviews and based on the availability of historical aerial imagery.
In order to analyze the changes in the rangelands of the farms and to explore the dynamics of the most prominent ecological regime shift associated with desertification—namely, the shift from grass-dominated savanna to shrubland—farmer-reported observations were used as the primary data source. These observations were supplemented with a remote sensing analysis of land use and land cover changes on four selected farmlands (n = 4) from 1961 onward. The imagery-based classification (Table 1), which used simplified land cover classes including woodland, shrubland, grassland savanna, and barren land/sand/water (Table 2), served to support and cross-check the qualitative assessments provided by farmers.
Image segmentation and classification were performed in QGIS 3.10.12 with GRASS 7.8.4 using the sequential maximum a posteriori (SMAP, i.smap) algorithm. To improve the classification results, ancillary information was used as an additional band consisting of the Normalized Difference Vegetation Index (NDVI) for the Sentinel-2 and texture parameters for the panchromatic images [41,42]. The accuracy of the classification was evaluated using the AcATaMa plug-in version 19.11.21 [43] in QGIS (version 3.10.12 A Coruña). The accuracy assessment points (in this case, 396) were generated using the stratified random sampling scheme. The total evaluated area of the geospatial analysis was 304 square kilometers.

3. Results and Discussion

3.1. Baseline Analysis of Rangeland Management, Coping and Mitigation Strategies

3.1.1. Farm Characteristics and Rangeland Management

All the freehold farms studied in the 2019 interviews, the online survey, and the in-depth analysis were owned and managed by farmers of German and South African origin and were established at different times: four of them after the German–Herero War (1904–1908), ten of them during the South African Administration (1915–1990), the First World War (1914–1918), and the Second (1939–1945) World War, and three after Namibia’s independence (1990). The pre-independence farms were either in their third or fourth generation of ownership, with subsequent generations already involved in farm management. The two post-independence farms were and still remain family owned; these were purchased by the current farm owners in 2009/2017. The farm size ranged from 31 km2 to 410 km2, with a mean of 98.76 km2 (SD = 85.89; Table 3). Approximately two-thirds of the 17 farmers were tertiary educated, while all but 3 were trained in agricultural science; the remaining farmers were exclusively trained by their fathers. Although all the farms were initially pure cattle farms, the current income-generating activities showed a considerable degree of diversification and heterogeneity in farm orientation. Compared to the past, off-farm activities and tourism have become more important for the livelihood of the farmers. Salaries for farm workers, ongoing maintenance, supplemental feed, and bush control, i.e., the removal of shrubs, were the main ongoing farm expenses. Farmers who focused on tourism employed an above-average number of permanent staff, regardless of the size of the farm or the number of cattle.
The interviews revealed that the farmers’ overall management objectives were to maximize income, to pass on a well-maintained farm, and to be sustainable and environmentally friendly. It is noteworthy that the farm with the most livestock did not have the largest rangeland area, and this was reflected in its relatively high stocking rate. Overall, small ruminants (e.g., sheep or goats) were found to play only a minor role in livestock husbandry. Livestock husbandry was characterized by a variety of approaches to rotational grazing. These included formal or informal rules for rotation between fenced paddocks, known as camps, resting, and grazing periods, as well as stocking densities and camp sizes (Table 3). The camps were arranged around posts with boreholes that supplied groundwater and were often surrounded by game-proof fencing and frequently included grazing and resting pens. According to the farmers interviewed, the overall objectives of the fencing were to establish a rotational grazing system, to facilitate controlled and consistent grazing, to allow for short grazing periods with high grazing pressure, and to distribute cattle more easily to available water points. In addition, smaller camps were found to improve both camp supervision and cattle handling. In the interviews, farmers mentioned rotational grazing as a targeted strategy to enhance rangeland quality, improve soil health, and mitigate bush encroachment into the camps.
Livestock were moved from camp to camp either according to fixed rules, according to plant readiness and grass availability, or based on a holistic consideration of various factors (e.g., camp size, herd size, water availability, the camp’s condition, and supplemental feed consumption). The farmers had installed various types of fencing to regulate game access to the rangelands. Typical rangeland game species included browsers (e.g., giraffe, eland, kudu, and black rhino), grazers (e.g., oryx, zebra, and wildebeest), and mixed feeders (e.g., impala and warthog). The farmers were also found to capture, hunt, and/or release game to control the numbers and composition. Farmers reported that at least half of these herbivores were grazers, with up to 80% competing with cattle. The main predators reported to threaten livestock and herbivores were leopards and cheetahs.
In addition to rotational grazing, the farmers used supplemental fodder consisting of self-produced or purchased hay, purchased minerals, and concentrates. The decision to produce hay on the farm is more of a long-term investment strategy, likely driven by the expectation of recurring droughts or other climatic factors. Conversely, the purchase of fodder is a more short-term compensatory practice aimed at mitigating the need to downsize herds or improving body condition before the market. In the context of the severe drought conditions in 2019, six of the farmers interviewed started using self-produced or purchased bush fodder; however, only two farmers continued this practice beyond 2019. The main problems associated with livestock husbandry were the long-term effects of drought, bush encroachment, low cattle prices, and fodder quality. Further problems mentioned were cattle rustling, predator invasion, and lack of water for livestock.

3.1.2. Short-Term Risk Coping Strategies and Long-Term Risk Mitigation Strategies of Farmers

The interview results revealed that the farmers had different strategies to improve rangeland conditions and their livelihoods and/or to respond to external shocks, such as drought events, and desertification. We grouped these strategies into short-term risk coping strategies, often applied as an immediate response to drought, and long-term risk mitigation strategies in response to dwindling fodder resources due to desertification (Figure 2). The latter could improve rangeland conditions in the long term as reported by farmers.
Short-term risk coping strategies included the adaption of camp rotation, using supplementary fodder to compensate for severe fodder shortages (i.e., minerals, lucerne pellets, and bush fodder), reducing the number of livestock and game, and using drought reserve camps that have also been utilized in other regions of Namibia [46,47]. The farmers often applied these strategies in successive stages during the droughts, depending on the severity and duration, in order to maintain their farming activities and to avoid over-exploitation of their rangelands. Camp rotation was adapted to longer grazing periods per camp, and gates between the camps were opened, if required, to allow cattle to roam freely.
Severe droughts often required a reduction in livestock and game (i.e., live or meat sales) and the investment in supplementary fodder to reduce grazing pressure. During the severe drought of 2019, some farmers (n = 6) used bushes as supplementary fodder: half of them by producing it themselves by mechanically debushing their rangelands and the other half by purchasing it. After the severe drought, farmers either continued to produce their own bush fodder or bought supplementary fodder if resources were still insufficient. A total of 88% of the farmers surveyed believed that maintaining grazing pressure during and after droughts would lead to rangeland degradation in the form of bush encroachment and loss of perennial grasses. These farmers, therefore, adjusted their stocking rates during these periods. Such strategies in response to drought events tended to be reactive or adaptive in nature, leading to short-term improvements but lacking crucial long-lasting improvements. The analysis of the local knowledge of farmers in the Waterberg region about the causes and effects of desertification confirms this finding [14]: farmers pointed out the inefficiency of such short-term strategies and the need for long-term strategies, which are, however, difficult to implement due to higher investment risks.
Long-term risk mitigation strategies applied by the interviewed farmers included income diversification and restoration measures to improve rangeland conditions, such as bush control, soil restoration measures including grass reseeding and the construction of water dams to increase water infiltration, holistic rangeland management, and fire management to improve rangeland conditions and fodder availability. In holistic management, the livestock are managed in a way that is intended to emulate the behaviors of ancient wild herds, while a further difference to traditional rotational grazing is the consideration of other factors, such as soil health, water management, and biodiversity, to improve the overall ecosystem health [48].
To secure income more effectively in the long term, most of the interviewed farmers had diversified their on-farm income activities over the past few decades with some of them even adopting off-farm income activities. These acted as an additional insurance buffer and facilitated investment in farm management. Altogether, 13 of the 17 farms had diversified their income, with 11 of them generating at least 30% of their income from off-farm (service jobs and trade) and/or on-farm activities other than livestock husbandry: safari and hunting tourism, the sale of live game and game meat, crop production, and charcoal production. Two of the farms surveyed had totally given up cattle farming in the 1990s and switched to game farming (including the raising and hunting of game) and safari tourism. In addition, livestock production as a source of income was found to have changed in recent decades as the farmers shifted from meat sales to live cattle sales and speculative activities due to unfavorable market conditions.
In the face of continuing bush encroachment and declining grass availability as reported by the surveyed farmers, one of the most frequently applied long-term risk mitigation strategies was the use of bush control to improve fodder availability. However, the frequency with which bush control measures were applied varied widely between farms depending on their financial resources, the size of the area to be cleared, and the objectives being pursued. The farmers stated that bush control measures were costly, and therefore, the frequency of application depended on their financial resources at the time. The interview results showed that farms larger than 70 km2 used chemical bush control and additionally produced charcoal in all but one case, while farms smaller than 70 km2 mainly used mechanical bush control in all but one case. Mechanical bush control was found to be the preferred method as it is labor-intensive but relatively inexpensive compared to chemical bush control, which is preferred by those who can afford it but is too expensive for small farms. The farmers interviewed applied chemical bush control by plane or by hand, mechanical bush control by bulldozer or by hand, and also slash-and-burn. They experienced both positive and negative effects including an overall increase in grass availability and a simultaneous invasion of herbaceous weeds. There were two exceptions to bush control: both pure cattle farms did not use any bush control methods whatsoever. One of those farmers thought it would make more sense to reduce the size of the herd if there is less forage due to bush encroachment and one does not yet use bush control methods but plans to do so in the near future.
The farmers also applied various soil restoration measures; however, they mentioned that the seeding of new grass was not very promising, while the construction of dams to keep rainwater on the soil surface was promising but too expensive. Holistic rangeland management was only applied by one farmer who reported difficulties in its practical implementation. Nevertheless, he did point out the potential for its long-term improvement in rangeland conditions since he had experienced this on another farm.
Fire management is the second-least applied long-term risk mitigation strategy because it is risky and requires a lot of experience and precise planning. However, from the interviews, one farmer shared his success story with fire management. He started to implement this strategy after switching to pure game farming in the 1980s and, since then, reported an increase in grass availability on his land. Other farmers reported positive effects of natural fire events on the grass availability on their rangelands but emphasized that they would not use fire management on their land because of the risks and uncertainties involved. Although recent studies have emphasized that fire management is a helpful tool for managing bush encroachment [48,49], the willingness of farmers to implement these measures is low, which can be attributed to a general negative attitude toward fire during the colonial periods that continues even today [49].
From the perspective of the farmers interviewed, income diversification combined with bush control has been shown to have the greatest potential to improve farm conditions. The two go hand in hand, as diversification improves the financial situation and thus enables the use of various methods to improve the ecological conditions on the farm.

3.2. In-Depth Analysis of Farm Changes for Analyzing Underlying Narratives That Lead to SETs

The land cover classification showed an accuracy of 0.93 to 0.99 according to the assessment (see Appendix S3). The land cover changes examined for the four farms of our in-depth analysis revealed an increase in shrubland of 18.5% from the 1960s to 2020, mainly at the expense of grassland savanna, which decreased by 19.2 % overall; this indicates a regime shift in rangelands from grassland savanna to shrubland. This general trend is consistent with the results of a recent study of the Waterberg Landscape region, which shows an increase in shrubland of +22% between 1965 and 2020 [17].
In our study, the investigated farms differed in their temporal dynamics of land cover changes and bush encroachment and the applied long-term risk mitigation strategies, as shown below for the periods studied.
In the 1960s, the earlier established farms, Farms A (in 1908) and B (in 1926), had significantly higher shrub cover than Farms C and D (Figure 3); the latter were established in the 1940s and, here, the bush encroachment became a serious problem much later, in the 1990s. All farms began as pure cattle farms when established and remained so into the 1960s, with farmers noting that various political and economic developments during this period provided support. In the 1930s, drought relief programs were introduced to support farmers with supplementary fodder and other inputs, allowing them to maintain their livestock during droughts [50]. While this buffered immediate losses, it also intensified grazing pressure on grasses already stressed by drought. Today, however, such programs are severely limited, and farmers proactively reduce their cattle numbers in response to low rainfall during the growing season.
In addition, in the 1950s and 1960s, government subsidies for agricultural infrastructure (e.g., fences and boreholes) facilitated the transition to more intensive commercial livestock farming with heavier cattle breeds. This encouraged the keeping of more cattle, which, combined with periods of favorable rainfall conditions, led to a peak in cattle numbers around 1959 [13,14].
Additionally, the formal allocation of property rights over huntable game to commercial farmers enabled wildlife management, and wildlife populations on farms increased sharply [51]. The combination of high cattle stocking rates and growing wildlife densities contributed to overgrazing during this period [12].
For the 1970s, the interviewed farmers reported low productivity and decreasing fodder resources accompanied by rapid bush encroachment—according to their own statements—which triggered the degradation of the grass layer, a trend that was observed in many regions of southern Africa [52], which was also triggered by recurrent droughts. As a result, the income deficits of the freehold farmers increased, and they reported that their parents had had to draw on their savings to buffer these deficits. In addition to recurrent droughts, farmers primarily attributed the poor rangeland conditions to constant overstocking and unsustainable land use practices by previous generations [17].
Farmers started to improve their rotational grazing system through the establishment of camps, which is reflected in our geospatial analysis by an increase in the number of camps and a decrease in the average camp size, indicating a subdivision of the rangeland into smaller management units (Figure 3).
Although droughts also occurred before the 1970s (e.g., the 1920s and 1940s), significant bush encroachment on Farms C and D became evident only after the 1970s. This delayed onset is certainly due to the fact that Farm C was established in 1946 and Farm D in 1942, more than 20 years later than Farms A and B, which had already been under intensive use since the early 20th century.
In the early 1980s and the 1990s, several drought years, accompanied by declining productivity and increasing bush encroachment, as well as bad market opportunities, increased the income deficits so that 70 % of the farmers from the survey (Table 3) started to diversify their income as a long-term risk mitigation strategy in this period. Farms A and B started diversifying their income in the late 1980s by establishing (hunting) tourism on their farms and, later, in the early 2000s, by carrying out off-farm activities (Farm B). The current owner of Farm C bought the farm in 1989 and has been engaged in off-farm activities since then, while Farm D started diversifying income relatively late, in 2004, with on-farm activities including cattle breeding and crop and hay production. Farmers A, B, and C reported that income diversification during this period alleviated income deficits, while Farm D struggled with large financial losses, pushing the farm toward an SET.
Between 1995 and 1998, farmers reported recurrent droughts. As a result, the availability of fodder grass was extremely limited, and the farmers turned to short-term coping strategies, in particular, the sale of cattle, although this led to a poor market situation; the market was flooded with cattle for sale, and market prices fell sharply. In addition, the government withdrew subsidies for fodder and supplementary feeds but did provide financial support for the above-average livestock sales to deal with overstocking during the drought periods [36]. Nevertheless, this led to a massive reduction in cattle numbers [14] that was also reported by the farmers who had reduced their herds by around 30% (A, B, and C) or about 80% (D) as a short-term coping strategy.
In response to dwindling fodder resources, many farmers started with bush control measures as another important long-term risk mitigation strategy. All farms reported an increase in grass availability after bush control but with significant differences in terms of the long-term effects and the extent of their dependence on the techniques applied and frequency. The two smaller farms (C and D) invested less in bush control measures due to financial constraints and higher risk aversion and, thus, applied mechanical bush control to a lesser extent. These small-scale measures showed no long-term success in reducing shrubland, as reported by the farmers and reflected in our land cover analysis (Figure 3). The larger farms, farms A and B, used chemical bush control and also removed shrubs from an area approximating 40% of their total farmland over the period studied. While Farm A had applied selective bush control to most of its farmland every two to three years since 1989 (which is also reflected in our analysis by the decreasing shrub cover), Farm B carried out non-selective chemical bush control applied by airplane at specific sites in 2010, 2011, and 2012; however, this was not reflected in the general trend of the land cover analysis (Figure 3). This discrepancy was found to be mainly due to the fact that only camps with good site conditions were debushed, while the bush vegetation was left to continue growing in less favorable camps. From a spatial perspective, there was, therefore, a differentiated pattern of debushed camps and heavily bushed camps.
Since 2000, periods of above-average rainfall have contributed to the national cattle population increasing again and reaching the level of the late 1950s [11,53], which was also reported for our study region. However, the farmers experienced a similar setback with the drought in 2019. The farmers interviewed were, again, forced to reduce their cattle numbers and draw on their savings that were mainly accumulated through income-generating activities other than livestock. In particular, bush fodder production attracted a lot of attention from the farmers in the Waterberg region, and many of the surveyed farmers from the baseline survey had used bush as a supplementary feed as a coping strategy, which some farmers later abandoned.
Overall, the in-depth analysis showed how farmers frequently applied short-term risk coping strategies as immediate responses to shortages of fodder that resulted from external shocks such as drought events. Thus, when the farms lacked capacity or opportunity, the farmers solely applied such strategies. In particular, the reduction in livestock and game, together with the costly use of supplementary fodder, may imply a self-reinforcing process resulting in a substantial increase in income deficits and the lack of investments in rangeland management, thus trapping the farm in the SET of desertification. In contrast to this, long-term risk mitigation strategies, such as the diversification of farm income in combination with bush control measures, have the potential to allow the farmers to break out of the crisis and SET, as shown for the larger farms, i.e., farms A and B.

3.3. Common Patterns and Feedback Loops of the SET

The results of the baseline survey and the in-depth analysis of the changes in the farms revealed common patterns of socio-ecological interactions that reinforce income deficits and favor a trap situation, in our case, the SET of desertification. These interactions form a nested set of self-reinforcing feedback loops; we have illustrated these in a qualitative model using a causal loop diagram (Figure 4).
Based on our empirical dataset and the farmers’ narratives, we identified three interacting feedback loops through which farmers fall into the SET of desertification: (A) the compensatory practice loop, (B) the rangeland management loop, and (C) the capital management loop. The linking element between all the loops, according to the analysis of the farmers’ interviews, is income deficits. In the compensatory practice loop (Figure 4, A), farmers try to compensate for income deficits, often worsened by poor market conditions and recurrent droughts, by decreasing resting periods and increasing their herd sizes during years with above-average rainfall and grass availability. While such measures are a short-term strategy to capitalize on favorable conditions, they can set the stage for overgrazing and land degradation, particularly when high livestock numbers are maintained into subsequent drought years. Rather than referring to a fixed ‘carrying capacity’, we understand capacity here as a dynamic threshold that varies annually with fodder availability. If livestock numbers remain high during unexpected declines in rainfall and rest periods in the camps are insufficient, the mismatch between grazing pressure and ecological resilience can negatively affect ecosystem services and functions (ESS/F) and trigger longer-term degradation processes. As a result, the decline in grass availability forces farmers to buy or produce supplementary fodder for their cattle. In the rangeland management loop (Figure 4, B), income deficits can stimulate the farmers’ risk aversion, which together with the lack of government subsidies, typically leads to lower investments in their rangeland management (e.g., lacking rangeland restoration measures, including bush control) making their farming operations inefficient, and this, in turn, affects the forage production and, thus, grass availability.
The self-reinforcing nature of the feedback loops A and B in combination with external shocks can contribute to a tipping point in the ecological subsystem, which can lead to an ecological regime shift, i.e., a shift from grassland to shrubland (bush encroachment), often accompanied by a shift from perennial to annual grasses and an increase in barren land [53]. While our interview data suggest that farmers tend to increase stocking rates during years with higher forage availability, it remains unclear whether and when such increases may have exceeded the given carrying capacity or directly triggered a tipping point. The literature on bush encroachment is inconclusive regarding the precise mechanisms and timing of regime shifts from grassland to shrubland, though livestock grazing pressure is widely acknowledged as a contributing factor, alongside fire suppression and climatic factors (increased atmospheric CO2 and recurrent drought) [54,55,56]. In this context, we interpret bush encroachment not as the inevitable outcome of a single trigger but as the result of interacting pressures that may push the system across ecological thresholds over time.
Both A and B feedback loops are associated with and exacerbate poor grass availability, forcing farmers to adopt short-term coping strategies (e.g., adaptation of camp rotation and the use of reserve camps if available).
In the capital management loop (Figure 4, C), farmers draw on their savings to cushion income deficits. This includes selling livestock and game as a short-term coping strategy. While this reduces the number of animals on hand, and thus household capital, it can also generate liquidity and can be one of the most effective ways to reduce grazing pressure quickly during droughts. However, due to the poor market opportunities during drought (low cattle prices), the profit is much lower than in normal years. In addition, restocking after drought periods when cattle prices rise again is limited, which can increase long-term vulnerability and exacerbate the trap situation. Income diversification through off- and on-farm activities offers a potential long-term strategy to mitigate risk and reduce dependence on livestock, potentially helping farmers navigate out of the trap. Nevertheless, it is difficult even for diversified farmers to adapt stocking densities to the highly fluctuating ecological conditions, and a high stock reduction in extreme drought years, as well as to maintain longer rest periods on camps, which may not be economically viable here.
External drivers and shocks play a fundamental role by influencing variables within the feedback loops and exacerbating the farmers’ situations to varying degrees. For example, droughts lead to poor grass availability and cause poor market situations, while laws and policies until the 1990s included financial support mechanisms that encouraged farmers to keep cattle longer than planned.
Considering the SET of desertification as a path-dependent process [15,33], it is necessary to identify the ‘antecedent conditions’ and the ‘critical juncture’ that initiate the SET and contribute to its persistence. The ‘antecedent conditions’ that constrain the possible development trajectories of cattle farming in the Waterberg region are the prevailing natural conditions characterized by high rainfall variability and, hence, fluctuating grass availability, and erosion-prone, sandy soils with limited water- and nutrient-holding capacity.
The implementation of the ‘Dairy Marketing Scheme’ in the 1950s by the South African Administration, which forced Namibia to sell its surplus of dairy products on the South African market, was followed by the promotion of commercial cattle farming through government subsidies and represents the ‘critical juncture’ of institutionalization and, thus, structural persistence within rangeland management practices. Although there is no remote sensing-based ‘evidence’ for the status of bush encroachment before 1960 due to a lack of satellite and aerial image data, the remote sensing analysis by Brinkmann et al. for the Waterberg region [17] has shown that bush encroachment was already high in the 1960s on freehold land and peaked in the 1990s. A trend was also observed in our study for Farms A and B, while for Farms D and C, we found a delayed process.
The 1950s and 1960s saw increased stocking rates linked to government incentives and infrastructure development, while environmental pressures, including droughts and reduced mobility due to fencing, gradually set the stage for ecological degradation. It was during the 1970s, when stocking rates were maintained at higher levels over extended periods, coupled with external shocks such as drought, that the system may have crossed a tipping point, triggering the onset of bush encroachment and desertification. The SET of desertification emerged at this critical juncture, characterized by self-reinforcing feedback loops within the social–ecological system of rangeland management, as illustrated in Figure 4. While the government subsidies acted as a catalyst, it was the cumulative impact of these management practices and environmental factors that led to the tipping point of bush encroachment.
In summary, it can be said that the dissolution of the SET of desertification is only possible if the dominant feedback loops in the SES are changed in the long term. In this context, a mix of long-term risk mitigation strategies, such as on- and off-farm income diversification and rangeland restoration measures, have the potential to fundamentally change and rearrange the feedback loops of the SES (e.g., [57]), whereas the more reactive short-term risk coping strategies can only temporarily compensate for income deficits. In our case studies (Farms A and B), the combination of regular bush control measures and the on-farm income diversification with a conversion to game farming, in particular, offer promising long-term risk mitigation strategies. In a more recent study, Irob et al. 2023 [58] showed how an adapted animal density and grazer browser ratio, through game farming, may increase the drought resilience of Namibian rangelands and also foster grass availability. At the same time, they recommended increased income diversification as an economic risk mitigation measure, especially during drought periods.

4. Conclusions

Our baseline analysis and in-depth analysis of farm changes have helped to unravel the underlying narratives and drivers of the rangeland desertification in Namibia’s rangelands. In addition, detailed remote sensing-based examination of specific lands allowed a direct link to be made between management actions and trends in land cover change on rangelands. Over the past 60 years, the main social and ecological changes on freehold cattle farms in Namibia’s Waterberg region have included progressive bush encroachment, its containment through debushing, the subdivision of rangelands into progressively smaller management units, and on-farm and off-farm income diversification. This in-depth analysis showed that political interventions (e.g., government subsidies for infrastructure and meat production) have led farmers to overstock their rangelands, which, combined with recurrent droughts, have degraded the grass layer of their rangelands, ultimately leading to rapid bush encroachment and laying the foundation for feedback loops that have reinforced the SET.
The qualitative model of the desertification SET at hand has provided insights into the underlying processes and feedback loops in the ecological and social subsystems. We identified a nested set of three feedback loops, namely, the compensatory practice loop, the rangeland management loop, and the capital management loop, that have revealed how farmers fall into the desertification SET. External shocks such as droughts, profound market changes, and new regulatory frameworks appear to play a key role in changing the variables within the feedback loops of this tightly coupled SES, resulting in the reinforcement of desertification as an SET. Income deficits were found to be the central link in the feedback loops within the desertification SET. Freehold farmers try to compensate for these income deficits with short-term risk coping strategies (adaptive strategies) to compensate, temporarily, for undesired effects and also with long-term risk mitigation strategies to avoid ecological regime shifts and to navigate themselves out of the trap.
In conclusion, considering desertification as an SET within a dryland SES revealed that poor grass availability, which triggers long-term income deficits, plays a key role in self-reinforcing feedback loops that contribute to rangeland desertification. However, a long-term change in the dominant feedback loops through long-term risk mitigation strategies can avoid or mitigate the effects of ecological regime shifts and help farmers escape the desertification SET. New insights into the underlying and direct drivers of rangeland desertification have been gained, providing entry points for the discussion and development of sustainable land use and effective long-term mitigation strategies to prevent desertification and secure farmers’ livelihoods.
However, the search for effective mitigation strategies requires an in-depth analysis that incorporates insights from farmers and experts and takes into account historical and current land use practices.
Accordingly, a more detailed long-term investigation of the effectiveness of the mitigation strategies applied in this study and other possible mitigation strategies is needed to develop policy recommendations for better sustainable rangeland management. In particular, strategies that alter the feedback loops in rangeland SESs in the long term and that can facilitate the escape from the desertification SET should be pursued.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land14051016/s1.

Author Contributions

Conceptualization, K.B.; methodology, software, validation, formal analysis, data curation, investigation and visualization, L.G. and K.B.; Writing—original draft preparation, L.G.; writing—review & editing and supervision, K.B., L.G., M.R. and S.L.; project administration and funding acquisition, M.R. and S.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the German Federal Ministry of Education and Research (FKZ: 01LC1821E & 01LC2321E).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The empirical data used in this article were collected as part of an interdisciplinary research project entitled NamTip (“A Namibian Perspective on Desertification Tipping Points in the Face of Climate Change”). We would like to thank the Namibian farmers and relevant stakeholders who supported our research efforts. We thank Anja Linstädter for her role in setting up the NamTip project, and the project managers Eike Kiene and Thomas Bringhenti for their support through the project’s central office.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Safriel, U.; Adeel, Z. Dryland Systems. In Ecosystems and Human Well-Being: Current State and Trends; Island Press: Washington, DC, USA, 2005; pp. 625–662. [Google Scholar]
  2. UN. Global Drylands: A UN System-Wide Response; UN: Geneva, Switzerland, 2011. [Google Scholar]
  3. Safriel, U.N. Desertification. In Terrestrial Ecosystems and Biodiversity, 2nd ed.; Wang, Y., Ed.; CRC Press: Boca Raton, FL, USA, 2020; pp. 267–279. ISBN 978-0-429-44565-1. [Google Scholar]
  4. Reynolds, J.F.; Smith, D.M.S.; Lambin, E.F.; Turner, B.L.; Mortimore, M.; Batterbury, S.P.J.; Downing, T.E.; Dowlatabadi, H.; Fernández, R.J.; Herrick, J.E.; et al. Global Desertification: Building a Science for Dryland Development. Science 2007, 316, 847–851. [Google Scholar] [CrossRef] [PubMed]
  5. D’Odorico, P.; Bhattachan, A.; Davis, K.F.; Ravi, S.; Runyan, C.W. Global Desertification: Drivers and Feedbacks. Adv. Water Resour. 2013, 51, 326–344. [Google Scholar] [CrossRef]
  6. IPCC. The IPCC’s Fith Assessment Report: What’s in It for Africa; IPCC: London, UK, 2014. [Google Scholar]
  7. Mirzabaev, A.; Wu, J.; Evans, J.; García-Oliva, F.; Hussein, I.A.G.; Iqbal, M.H.; Kimutai, J.; Knowles, F.; Meza, F.; Nedjaroui, D.; et al. Desertification. Climate Change and Land: An IPCC Special Report; IPCC: London, UK, 2019. [Google Scholar]
  8. Baumhauer, R. Desertifikation Und Klimawandel. In Geographie: Physische Geographie und Humangeographie; Springer: Berlin/Heidelberg, Germany, 2020; pp. 1225–1229. [Google Scholar]
  9. MET. DEA Third National Action Programme for Namibia to Implement the United Nations Convention to Combat Desertification 2014–2024; MET: Windhoek, Namibia, 2013. [Google Scholar]
  10. Mendelsohn, J.M. Farming Systems in Namibia; Research & Information Services of Namibia: Windhoek, Namibia, 2006; ISBN 978-99916-780-4-7. [Google Scholar]
  11. MAWF. Agricultural Statistics Bulletin (2000–2009); MAWF: Windhoek, Namibia, 2011. [Google Scholar]
  12. Pfeiffer, M.; Langan, L.; Linstädter, A.; Martens, C.; Gaillard, C.; Ruppert, J.C.; Higgins, S.I.; Mudongo, E.I.; Scheiter, S. Grazing and Aridity Reduce Perennial Grass Abundance in Semi-Arid Rangelands–Insights from a Trait-Based Dynamic Vegetation Model. Ecol. Model. 2019, 395, 11–22. [Google Scholar] [CrossRef]
  13. Lau, B.; Reiner, P. 100 Years of Agricultural Development in Colonial Namibia: A Historical Overview of Visions and Experiments; National Archives of Namibia: Windhoek, Namibia, 1993. [Google Scholar]
  14. Lange, G.; Barnes, J.I.; Motinga, D.J. Cattle Numbers, Biomass, Productivity and Land Degradation in the Commercial Farming Sector of Namibia, 1915-95. Dev. S. Afr. 1998, 15, 555–572. [Google Scholar] [CrossRef]
  15. de Klerk, J.N. Bush Encroachment in Namibia: Report in Phase 1 of the Bush Encroachment Research, Monitoring and Management Project; Environmental Information Service Namibia: Windhoek, Namibia, 2004. [Google Scholar]
  16. Olbrich, R.; Quaas, M.; Baumgärtner, S. Characterizing Commercial Cattle Farms in Namibia: Risk, Management, and Sustainability. Afr. J. Agric. Res. 2016, 11, 4109–4120. [Google Scholar] [CrossRef]
  17. Brinkmann, K.; Menestrey Schwieger, D.A.; Grieger, L.; Heshmati, S.; Rauchecker, M. How and Why Do Rangeland Changes and Their Underlying Drivers Differ across Namibia’s Two Major Land-Tenure Systems? Rangel. J. 2023, 45, 123–139. [Google Scholar] [CrossRef]
  18. Espeland, E.K.; Schreeg, L.; Porensky, L.M. Managing Risks Related to Climate Variability in Rangeland-Based Livestock Production: What Producer Driven Strategies Are Shared and Prevalent across Diverse Dryland Geographies? J. Environ. Manag. 2020, 255, 109889. [Google Scholar] [CrossRef]
  19. Joyce, L.A.; Marshall, N.A. Managing Climate Change Risks in Rangeland Systems. In Rangeland Systems; Briske, D.D., Ed.; Springer Series on Environmental Management; Springer International Publishing: Cham, Switzerland, 2017; pp. 491–526. ISBN 978-3-319-46707-8. [Google Scholar]
  20. Crépin, A.-S.; Biggs, R.; Polasky, S.; Troell, M.; De Zeeuw, A. Regime Shifts and Management. Ecol. Econ. 2012, 84, 15–22. [Google Scholar] [CrossRef]
  21. Luvuno, L.; Biggs, R.; Stevens, N.; Esler, K. Woody Encroachment as a Social-Ecological Regime Shift. Sustainability 2018, 10, 2221. [Google Scholar] [CrossRef]
  22. Stockholm Resilience Centre. Social-Ecological Traps: Interaction between Social and Ecological Feedbacks Can Lock Systems into Unsustainable Pathways, Creating Social-Ecological Traps; Research Insights 5; Stockholm Resilience Centre: Stockholm, Sweden, 2016. [Google Scholar]
  23. Männer, F.; Schwarz, L.-M.; Menestrey Schwieger, D.; Amputu, V.; Bilton, M.; Brinkmann, K.; Dressler, G.; Hamunyela, N.; Heita, H.; Liehr, S.; et al. An Integrated Framework to Study Ecological Tipping Points in Social-Ecological Systems. In Proceedings of the International Grassland Congress Proceedings; Kenya Agricultural and Livestock Research Organization: Nairobi, Kenya, 2021. [Google Scholar]
  24. Cinner, J.E. Social-Ecological Traps in Reef Fisheries. Glob. Environ. Change 2011, 21, 835–839. [Google Scholar] [CrossRef]
  25. Hänke, H.; Barkmann, J.; Coral, C.; Kaustky, E.E.; Marggraf, R. Social-Ecological Traps Hinder Rural Development in Southwestern Madagascar. Ecol. Soc. 2017, 22, 1–25. [Google Scholar] [CrossRef]
  26. Eriksson, H.; Blythe, J.L.; Österblom, H.; Olsson, P. Beyond Social-Ecological Traps: Fostering Transformations towards Sustainability. Ecol. Soc. 2021, 26, art13. [Google Scholar] [CrossRef]
  27. Brinkmann, K.; Kübler, D.; Liehr, S.; Buerkert, A. Agent-Based Modelling of the Social-Ecological Nature of Poverty Traps in Southwestern Madagascar. Agric. Syst. 2021, 190, 103125. [Google Scholar] [CrossRef]
  28. Hanh, T.T.H.; Boonstra, W.J. Can Income Diversification Resolve Social-Ecological Traps in Small-Scale Fisheries and Aquaculture in the Global South? A Case Study of Response Diversity in the Tam Giang Lagoon, Central Vietnam. Ecol. Soc. 2018, 23, art16. [Google Scholar] [CrossRef]
  29. Boonstra, W.J.; De Boer, F.W. The Historical Dynamics of Social–Ecological Traps. AMBIO 2014, 43, 260–274. [Google Scholar] [CrossRef]
  30. Steenbergen, D.J.; Warren, C. Implementing Strategies to Overcome Social-Ecological Traps: The Role of Community Brokers and Institutional Bricolage in a Locally Managed Marine Area. Ecol. Soc. 2018, 23, art10. [Google Scholar] [CrossRef]
  31. Hruska, T.; Huntsinger, L.; Brunson, M.; Li, W.; Marshall, N.; Oviedo, J.L.; Whitcomb, H. Rangelands as Social–Ecological Systems. In Rangeland Systems; Briske, D.D., Ed.; Springer Series on Environmental Management; Springer International Publishing: Cham, Switzerland, 2017; pp. 263–302. ISBN 978-3-319-46707-8. [Google Scholar]
  32. Plummer, R.; Armitage, D. Integrating Perspectives on Adaptive Capacity and Environmental Governance. In Adaptive Capacity and Environmental Governance; Armitage, D., Plummer, R., Eds.; Springer Series on Environmental Management; Springer: Berlin/Heidelberg, Germany, 2010; pp. 1–19. ISBN 978-3-642-12193-7. [Google Scholar]
  33. Easdale, M.H.; Domptail, S.E. Fate Can Be Changed! Arid Rangelands in a Globalizing World—A Complementary Co-Evolutionary Perspective on the Current ‘Desert Syndrome’. J. Arid. Environ. 2014, 100–101, 52–62. [Google Scholar] [CrossRef]
  34. Jones, A.; Breuning-Madsen, H.; Brossard, M.; Dampha, A.; Deckers, J.; Dewitte, O.; Gallali, T.; Hallett, S.; Jones, R.; Kilasara, M.; et al. Soil Atlas of Africa; ESDAC: Luxembourg, 2013. [Google Scholar]
  35. Mendelsohn, J.; Jarvis, A.; Roberts, C.; Robertson, T. Atlas of Namibia: A Portrait of the Land and Its People; David Philip Publishers: Cape Town, South Africa, 2002. [Google Scholar]
  36. National Drought Task Force. National Drought Policy & Strategy; National Drought Task Force: Silver Spring, MD, USA, 1997. [Google Scholar]
  37. Blamey, R.C.; Kolusu, S.R.; Mahlalela, P.; Todd, M.C.; Reason, C.J.C. The Role of Regional Circulation Features in Regulating El Niño Climate Impacts over Southern Africa: A Comparison of the 2015/2016 Drought with Previous Events. Int. J. Climatol. 2018, 38, 4276–4295. [Google Scholar] [CrossRef]
  38. Parker, C.; Scott, S.; Geddes, A. Snowball Sampling. In SAGE Research Methods Foundations; SAGE Publications Ltd.: London, UK, 2020; ISBN 978-1-5264-2103-6. [Google Scholar]
  39. MAXQDA 2022, version 2022.3; VERBI Software: Berlin, Germany, 2022.
  40. Kuckartz, U. Qualitative Inhaltsanalyse: Methoden, Praxis, Computerunterstützung; 4. Auflage.; Beltz: Weinheim, Basel, 2018. [Google Scholar]
  41. Neteler, M.; Mitasova, H. (Eds.) Open Source GIS; Springer: Boston, MA, USA, 2008; ISBN 978-0-387-35767-6. [Google Scholar]
  42. Rico, E.C.; Maseda, R.C. An Object-Oriented Approach to Automatic Classification of Panchromatic Aerial Photographs with GRASS GIS and R. In Geospatial Free and Open Source Software in the 21st Century; Bocher, E., Neteler, M., Eds.; Lecture Notes in Geoinformation and Cartography; Springer: Berlin/Heidelberg, Geramny, 2012; pp. 123–137. ISBN 978-3-642-10594-4. [Google Scholar]
  43. Llano, X. AcATaMa-QGIS Plugin for Accuracy Assessment of Thematic Maps; AcATaMa: Vitacura, Chile, 2021. [Google Scholar]
  44. Jahnke, H.E.; Tacher, G.; Keil, P.; Rojat, D. Livestock Production in Tropical Africa with Special Reference to the Tsetse-Affected Zone. In International Livestock Centre for Africa (ILCA), Livestock Production in Tsetse-Affected Areas of Africa; Printed in Kenya by English Press: Nairobi, Kenya, 1987. [Google Scholar]
  45. Jacquemin, A.P.; Berry, C.H. Entropy Measure of Diversification and Corporate Growth. J. Ind. Econ. 1979, 27, 359. [Google Scholar] [CrossRef]
  46. Sweet, J. Livestock-Coping with Drought: Namibia—A Case Study; FAO: Rome, Italy, 1998. [Google Scholar]
  47. Rothauge, A. Drought Management Strategies for Namibian Ranchers; Agricola: Princeton, NJ, USA, 2001. [Google Scholar]
  48. Savory, A. Holistic Management: A New Framework for Decision Making; Island Press: Chicago, IL, USA, 2013; ISBN 978-1-55963-488-5. [Google Scholar]
  49. Lohmann, D.; Tietjen, B.; Blaum, N.; Joubert, D.F.; Jeltsch, F. Prescribed Fire as a Tool for Managing Shrub Encroachment in Semi-Arid Savanna Rangelands. J. Arid Environ. 2014, 107, 49–56. [Google Scholar] [CrossRef]
  50. Dieckmann, U. Land, Boreholes and Fences: The Development of Commercial Livestock Farming in the Outjo District, Namibia. In Pastoralism in Africa; Bollig, M., Schnegg, M., Wotzka, H.-P., Eds.; Past, Present and Future; Berghahn Books, JSTOR: New York, NY, USA, 2013; pp. 257–288. ISBN 978-0-85745-908-4. [Google Scholar]
  51. Burke, A. Range Management Systems in Arid Namibia—What Can Livestock Numbers Tell Us? J. Arid Environ. 2004, 59, 387–408. [Google Scholar] [CrossRef]
  52. O’Connor, T.G.; Puttick, J.R.; Hoffman, M.T. Bush Encroachment in Southern Africa: Changes and Causes. Afr. J. Range Forage Sci. 2014, 31, 67–88. [Google Scholar] [CrossRef]
  53. MAWLR. DVS Livestock Census. Pub. Ministry of Agriculture, Water and Land Reform & Directorate of Veterinary Services; MAWLR: Windhoek, Namibia, 2019. [Google Scholar]
  54. Rohde, R.F.; Hoffman, M.T. The Historical Ecology of Namibian Rangelands: Vegetation Change since 1876 in Response to Local and Global Drivers. Sci. Total Environ. 2012, 416, 276–288. [Google Scholar] [CrossRef] [PubMed]
  55. Archer, S.R.; Andersen, E.M.; Predick, K.I.; Schwinning, S.; Steidl, R.J.; Woods, S.R. Woody Plant Encroachment: Causes and Consequences. In Rangeland Systems; Briske, D.D., Ed.; Springer Series on Environmental Management; Springer International Publishing: Cham, Switzerland, 2017; pp. 25–84. ISBN 978-3-319-46707-8. [Google Scholar]
  56. Birch, C.; Middleton, A. Economics of Land Degradation Related to Bush Encroachment in Namibia; Namibia Nature Foundation (NNF): Windhoek, Namibia, 2017. [Google Scholar]
  57. Mahoney, J. Path-Dependent Explanations of Regime Change: Central America in Comparative Perspective. Stud. Comp. Int. Dev. 2001, 36, 111–141. [Google Scholar] [CrossRef]
  58. Irob, K.; Blaum, N.; Weiss-Aparicio, A.; Hauptfleisch, M.; Hering, R.; Uiseb, K.; Tietjen, B. Savanna Resilience to Droughts Increases with the Proportion of Browsing Wild Herbivores and Plant Functional Diversity. J. Appl. Ecol. 2023, 60, 251–262. [Google Scholar] [CrossRef]
Figure 1. Overview map of the study area showing the location of all interviewed freehold farms (n = 17). Four were selected for in-depth interviews and geospatial analysis. Data on farm boundaries were retrieved from [35].
Figure 1. Overview map of the study area showing the location of all interviewed freehold farms (n = 17). Four were selected for in-depth interviews and geospatial analysis. Data on farm boundaries were retrieved from [35].
Land 14 01016 g001
Figure 2. Short-term risk coping strategies and long-term risk mitigation strategies applied by the surveyed freehold farmers (n = 17) to ensure fodder availability.
Figure 2. Short-term risk coping strategies and long-term risk mitigation strategies applied by the surveyed freehold farmers (n = 17) to ensure fodder availability.
Land 14 01016 g002
Figure 3. Distribution of land cover types (area in km2), mean camp size (area in km2), and number of camps from 1961 to 2020 for the inspected farms of the in-depth analysis in the Waterberg landscape region, Namibia.
Figure 3. Distribution of land cover types (area in km2), mean camp size (area in km2), and number of camps from 1961 to 2020 for the inspected farms of the in-depth analysis in the Waterberg landscape region, Namibia.
Land 14 01016 g003
Figure 4. Causal loop diagram within the rangeland SES showing the nested set of feedback loops and external drivers (black boxes) making up the social–ecological trap (SET) of desertification. The farmers’ accompanying short-term risk coping strategies (grey boxes) and long-term risk mitigation strategies (white boxes) in response to the SET are illustrated. The arrows characterize the interrelationships among the factors within the feedback loop (+ = both factor’s values change in the same direction; − = a change in one factor induces a change in the other factor in the opposite direction). ESS/F = ecosystem services and functions (mainly mentioned by farmers: erosion control, biodiversity, soil water balance, soil seed bank).
Figure 4. Causal loop diagram within the rangeland SES showing the nested set of feedback loops and external drivers (black boxes) making up the social–ecological trap (SET) of desertification. The farmers’ accompanying short-term risk coping strategies (grey boxes) and long-term risk mitigation strategies (white boxes) in response to the SET are illustrated. The arrows characterize the interrelationships among the factors within the feedback loop (+ = both factor’s values change in the same direction; − = a change in one factor induces a change in the other factor in the opposite direction). ESS/F = ecosystem services and functions (mainly mentioned by farmers: erosion control, biodiversity, soil water balance, soil seed bank).
Land 14 01016 g004
Table 1. Satellite sensor, acquisition date, classified farm area, and spectral and spatial resolution of aerial and satellite imagery used for land cover classification.
Table 1. Satellite sensor, acquisition date, classified farm area, and spectral and spatial resolution of aerial and satellite imagery used for land cover classification.
FarmSatellite (Sensor)Date (year/month)Farm Area (km2)Spectral and Spatial Resolution (m)
Aaerial image1961/08120.50Panchromatic; 0.8
Corona KH-4B1972/08Panchromatic; 1.8
Sentinel-22020/05Band 2–4, 8; 10
Baerial image1961/0878.70Panchromatic; 0.8
Corona KH-4B1972/08Panchromatic; 1.8
Sentinel-22020/05Band 2–4, 8; 10
Caerial image1968/0352.40Panchromatic; 0.8
Corona KH-4B1972/08Panchromatic; 1.8
aerial image1996/08Panchromatic; 2.1
Sentinel-22020/05Band 2–4, 8; 10
Daerial image1968/0352.40Panchromatic; 1.1
Corona KH-4B1972/08Panchromatic; 1.8
aerial image1997/08Panchromatic; 1.7
Sentinel-22020/05Band 2–4, 8; 10
Table 2. Description of the simplified land cover classes used to classify the 1961/1968, 1972, 1996/1997, and 2020 images. Classes were defined based on the Corine Land Cover (CLC) Illustrated Nomenclature Guidelines.
Table 2. Description of the simplified land cover classes used to classify the 1961/1968, 1972, 1996/1997, and 2020 images. Classes were defined based on the Corine Land Cover (CLC) Illustrated Nomenclature Guidelines.
Simplified Land Cover Classes
(1961/68, 1972, 1996/97)
Description
1Woodlandshrub/tree cover > 50%
2Shrublandshrub cover of 10–50%
3Grassland savannashrub cover < 10 %
4Barren land/sand/waterareas without vegetation cover
natural or artificial water bodies
Table 3. Farm characteristics and figures of the rotational grazing system (mean and standard deviation).
Table 3. Farm characteristics and figures of the rotational grazing system (mean and standard deviation).
All Farms
(n = 17)
Pure Cattle Farms
(n = 5)
Guest/Hunting Farms (n = 3)Mixed Farms
(n = 9)
General information
Farm size (km2)98.76 (± 85.89)78.0 (± 33.92)77.67 (± 55.64)117.33 (± 112.16)
Heads of cattle545 (± 551)455 (± 246)17 (± 29)771 (± 639)
Livestock (TLU) 1396 (± 392)334 (± 174)12 (± 20)557 (± 453)
Farm income diversification (Jacquemin–Berry Index) 20.50 (±0.38)0.051 (±0.05)0.53 (± 0.31)0.675 (± 0.33)
Grazing system
Number of camps29 (± 35)14 (± 7)2 (± 3)40 (± 41)
Camp size (km2)2.74 (± 1.76)2.75 (± 1.89)insufficient data2.73 (± 1.88)
Stocking rate (TLU km−1)0.0012 (± 0.0006)0.0013 (± 0.0010)insufficient data0.0011 (± 0.0004)
Length of grazing period (weeks)min. 0.75/max. 32min. 0.75/max. 20insufficient datamin. 1/max. 32
Length of resting period (weeks)min. 1/max. 24min. 3/max. 24insufficient datamin. 1/max. 32
1 TLU = Tropical Livestock Unit (after [44]); 2 [45].
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Grieger, L.; Brinkmann, K.; Rauchecker, M.; Liehr, S. Desertification as a Social–Ecological Trap: How Does It Come About and What Are Namibian Freehold Farmers Doing About It? Land 2025, 14, 1016. https://doi.org/10.3390/land14051016

AMA Style

Grieger L, Brinkmann K, Rauchecker M, Liehr S. Desertification as a Social–Ecological Trap: How Does It Come About and What Are Namibian Freehold Farmers Doing About It? Land. 2025; 14(5):1016. https://doi.org/10.3390/land14051016

Chicago/Turabian Style

Grieger, Lena, Katja Brinkmann, Markus Rauchecker, and Stefan Liehr. 2025. "Desertification as a Social–Ecological Trap: How Does It Come About and What Are Namibian Freehold Farmers Doing About It?" Land 14, no. 5: 1016. https://doi.org/10.3390/land14051016

APA Style

Grieger, L., Brinkmann, K., Rauchecker, M., & Liehr, S. (2025). Desertification as a Social–Ecological Trap: How Does It Come About and What Are Namibian Freehold Farmers Doing About It? Land, 14(5), 1016. https://doi.org/10.3390/land14051016

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop