Woody Vegetation Characteristics of Selected Rangelands Along an Aridity Gradient in Namibia: Implications for Rangeland Management

Abstract

Rangelands form the ecological and economic backbone of Namibia, yet the woody plant dynamics that sustain these landscapes remain sporadically quantified across the semi-arid interior. We investigated the characteristics (stand structure, regeneration, richness, diversity, composition, ecological importance, and indicator species) of woody communities along a pronounced south-to-north rainfall gradient (85–346 mm yr⁻¹) at five representative sites: Warmbad, Gibeon, Otjimbingwe, Ovitoto, and Sesfontein. Field sampling combined point-centered quarter surveys (10 points site⁻¹) and belt transects (15 plots site⁻¹). The basal area increased almost ten-fold along the gradient (0.4–3.4 m² ha⁻¹). Principal Coordinates Analysis (PCoA) arranged plots in near-perfect rainfall order, and Permutational Multivariate Analysis of Variance (PERMANOVA) confirmed significant site differences (F_3,56 = 9.1, p < 0.001). Nanophanerophytes dominated hyper-arid zones, while microphanerophytes appeared progressively with increasing rainfall. Mean annual precipitation explained 45% of the variance in mean height and 34% of Shannon diversity but only 5% of stem density. Indicator value analysis highlighted Montinia caryophyllacea for Warmbad (IndVal = 100), Rhigozum trichotomum (75.8) for Gibeon, Senegalia senegal (72.6) for Otjimbingwe, and Senegalia mellifera (97.3) for Ovitoto. Rainfall significantly influences woody structure and diversity; however, other factors also modulate density and regeneration dynamics. This quantitative baseline can serve as a practical toolkit for designing site-specific management strategies across Namibia’s aridity gradient.

1. Introduction

1.1. The Overview of Rangelands

Rangelands constitute the planet’s most extensive land-cover category, occupying an estimated 54% of the global terrestrial surface, of which roughly 78% lies within climatically defined drylands [1]. In these water-limited settings, extensive livestock production dominates land use, supporting the livelihoods of approximately two billion people who depend directly or indirectly on rangeland resources [2,3,4,5]. Beyond their socio-economic importance, rangelands provide critical ecosystem services—most notably biodiversity conservation, carbon sequestration, and the maintenance of cultural landscapes—yet they face mounting pressures from both climatic and anthropogenic drivers [3,6,7,8,9,10]. Degradation is a significant problem facing many rangelands [3,9,11]. The major drivers leading to rangeland degradation include climate change, overgrazing, bush encroachment, population pressure, drought, government policy, and the decline of traditional resource management institutions [12]. Other threats include the rapid invasion of woody plants into open grazing areas, referred to as woody encroachment, bush encroachment, or shrub encroachment [8,13,14,15]. Despite their economic and social significance, extraordinary biodiversity, and intrinsic value, rangelands have never received the scientific and media attention they deserve for conservation, and they rarely feature in global policy discussions or national development priorities [1,16]. This is partly due to their less photogenic nature compared to tropical forests, but more importantly, because they are often perceived as degraded lands suitable for grazing.

1.2. Namibian Rangelands

Approximately 45% of Namibia’s land surface is classified as rangeland and is therefore predominantly suited to extensive livestock production [17]. For households in communal areas, these landscapes support food security, cash income, and cultural identity while simultaneously providing habitat for wildlife and forming a cornerstone of the nation’s biodiversity conservation portfolio [18,19,20]. The integrity of these systems is, however, increasingly compromised by interacting stressors: pronounced climatic variability, accelerating land-use change, and vegetation dynamics driven by both aridity gradients and grazing pressure [21,22]. Resultant declines in vegetation cover and productivity are especially evident in the Kunene and Erongo Regions, where high inter-annual rainfall variability amplifies the susceptibility of plant communities to degradation [3,19].

Aridity has a considerable impact on ecosystems, resulting in lower species diversity, reduced coverage of desirable grasses, and compromised soil health [23]. Namibia features a wide range of aridity zones, from semi-arid savannas to hyper-arid desert environments, where vegetation responses are influenced by climate variability, soil limitations, and land-use pressures [19,24]. These variations affect the type of vegetation, the mix of species, and their characteristics, which are important indicators of rangeland health and productivity [25]. Understanding how vegetation changes with aridity is crucial for assessing the health and resilience of rangelands, as these changes signal ecological shifts [26,27]. By studying vegetation variation along aridity gradients, we can co-develop effective management strategies with local pastoralists and farmers to support ecosystem services and ensure rangeland sustainability. Studies have shown that intra-annual precipitation variability (PCI) is the most crucial factor driving species richness in water-constrained ecosystems, while mean annual precipitation is a stronger predictor of plant species richness than grazing intensity [27,28,29].

1.3. Vegetation Studies Covering Rangelands in Namibia

Burke & Strohbach [30] conducted a review of vegetation studies in Namibia 25 years ago. Most of these studies were conducted in areas considered highly important or valuable for conservation, such as Naukluft Park, Etosha National Park, Brandberg, and others. In contrast, the majority of farmlands and rangelands, which are not necessarily considered conservation areas, were neglected entirely (e.g., Hardap, Karas, Omaheke, and Otjozondjupa Regions). The outdated preliminary vegetation map by Giess [31] remains a widely used national baseline. Though based on expert classification, it lacks the precision needed for current ecological or climatic applications.

Earlier groundwork by Strohbach [11,32,33,34,35] and the ongoing Vegetation Survey of Namibia has laid a robust empirical foundation for understanding Namibia’s plant communities and remains foundational to floristic classification in Namibia. However, these studies provide only limited quantitative insight into structural attributes (e.g., canopy height and basal area), regeneration dynamics, or diversity indices such as species richness and evenness, and they do not explicitly evaluate vegetation responses along Namibia’s pronounced aridity gradient. Subsequent collaborations—most recently with Naftal et al. [36]—have begun to address climatic drivers by modeling potential shifts in plant distributions. Yet, the earlier datasets remain spatially restricted to particular agroecological zones. Overall, quantitative information on rangeland conditions and productivity is sparse. Work by Mendelsohn [17] documents overstocking around major settlements in the north-central regions, whereas region-specific studies that examine vegetation structure and composition in greater detail [3,37,38] concentrate primarily on grazing and degradation rather than climatic gradients. Consequently, empirical evidence of how vegetation traits shift across Namibia’s moisture continuum remains limited. A notable recent advance is Hauwanga [39], who analyzed vegetation along a rainfall gradient, but this analysis was limited to five Kalahari sites with rainfall ranging from 280 to 540 mm, omitting much of the national gradient and thus reducing the applicability of its findings to broader-scale rangeland management. Furthermore, while vegetation attributes were correlated with rainfall, details of these characteristics were not documented. A major advancement in this field is represented by Naftal et al. [36], who applied a community distribution model (CDM) approach using Random Forest to predict the current and future distribution of vegetation units across a 1383 km south–north rainfall gradient. Naftal et al. [36] integrate more than 1900 vegetation relevés with a suite of environmental covariates to delineate twelve broad vegetation units and model their projected distributions under RCP 4.5 and RCP 8.5 climate trajectories. The analysis provides a robust, spatially explicit prognosis of climate-driven shifts, most notably the prospective southward advance of mesic savannas and the contraction of desert-adapted assemblages. Nonetheless, the emphasis rests on community-level distribution and classification; fine-scale structural and functional attributes of the vegetation remain largely unquantified.

Most vegetation assessments of rangelands in Namibia have focused on remote-sensing methods [40,41,42]. While these are critical in mapping the vegetation, they often miss important on-ground details, such as species composition, structural complexity, and regeneration status of the vegetation. Although remotely sensed products furnish a synoptic view of vegetation extent and temporal change, they rarely resolve the fine-scale structural and compositional detail required to diagnose ecological processes or species interactions [25]. Consequently, systematic ground surveys remain indispensable for calibrating and refining satellite-based assessments.

Against this backdrop, the present study investigates woody plant communities along a pronounced aridity gradient in Namibia by integrating plot-based (20 × 10 m quadrats) and plot-less (point-centered quarter) techniques. Our objectives were (1) to document woody stand structure and regeneration dynamics across the aridity gradient, (2) to map woody plant biodiversity by comparing site-level species richness, diversity and composition, (3) to establish the ecological significance of each woody species and identify indicator species along the aridity gradient, and (4) to assess how mean annual rainfall shapes woody plant structure, regeneration, and biodiversity across the rangelands. By coupling high-resolution field data with a rigorous gradient design, the study provides the granular ecological insights needed to inform targeted rangeland management interventions and to calibrate remote-sensing products for more accurate, landscape-scale monitoring.

2. Materials and Methods

2.1. Study Sites

This study was conducted across five semi-arid rangeland localities—Warmbad, Gibeon, Otjimbingwe, Ovitoto, and Sesfontein—strategically positioned along Namibia’s south-to-north aridity gradient. Mean annual rainfall increases from approximately 100–150 mm yr⁻¹ at the southern extreme (Warmbad) to 350–450 mm yr⁻¹ in the north-central interior (Ovitoto), with Sesfontein introducing additional climatic heterogeneity through its elevated, dissected terrain (

Table 1. Summary of the environmental setting and human use of the five study sites examined in this study.

Site (Region)	Climate and MAP	Dominant Vegetation	Land Use	Main References
Warmbad (Karas)	Hyper-arid desert BWh; ≈85–100 mm yr−1	Nama-Karoo dwarf-shrub savanna; succulent elements; shrubs Rhigozum and Roepera; scattered Stipagrostis; trees rare	Small-stock ranching; game farms; hot-spring tourism; no crops	[43,44]
Gibeon (Hardap)	Very arid steppe BWh/BSh; 150–200 mm yr−1; CV ≈ 75%	Nama-Karoo shrub mosaics; riparian Tamarix/Faidherbia; Prosopis invasion	Communal and freehold grazing; Fish River stubble; Prosopis control issues	[45]
Otjimbingwe (Erongo)	Arid desert BWh; ≈165 mm yr−1; CV ≈ 69%	Arid thornbush savanna with Vachellia/Senegalia; Swakop gallery forest	Goat-dominated communal ranching; irrigated gardens; dam-reduced flow	[46]
Ovitoto (Otjozondjupa)	Semi-arid steppe BSh; 300–350 mm yr−1	Central-Highland savanna; dense Senegalia mellifera and Dichrostachys cinerea	620 km2 communal; ~21,000 cattle; bush-thinning trials	[47]
Sesfontein (Kunene)	Desert–steppe transition; ≈200–250 mm yr−1	Mopane savanna; riparian Ana tree and Leadwood	Low-density pastoralism; conservancy tourism; borehole dependence	[48,49]

and Figure 1). Although the transect does not include the hyper-arid Namib coastal belt or the more humid Zambezi Region, it captures the semi-arid transition zone that constitutes the core of the country’s grazing lands. By analyzing vegetation composition, structural attributes, and diversity across these sites—each characterized by distinct land-use histories and management regimes—we can explain how gradients in aridity and topography influence woody plant communities.

2.2. Woody Vegetation Assessment Methods

Woody vegetation data were collected using a combination of the point-centered quarter (PCQ) method and Structured Walking Transects, as discussed below.

2.2.1. Point-Centered Quarter (PCQ) Method

A point-centered quarter (PCQ) survey was adopted to quantify woody vegetation structures. PCQ avoids the edge effects of fixed plots and performs reliably in heterogeneous rangelands [50,51]. For each study area, site boundaries were digitized in QGIS, and a GIS-based random-point algorithm produced a pool of candidate coordinates. Ten points were then selected by simple random sampling, with each point situated at least 200 m from roads or permanent water and ≥2 km from homesteads to minimize anthropogenic edge influences. Field teams navigated to the selected coordinates using handheld GPS receivers (with a ±3 m accuracy); if a center fell on unsafe terrain, it was relocated no more than 15 m along a random bearing.

At each validated center, a 50 m radius was established, the area was divided into four 90° quadrants, and in every quadrant, the two nearest trees (individuals above the height of 2 m) and two nearest shrubs (individuals below the height of 2 m) were recorded, yielding eight trees and eight shrubs per point. For every individual, we measured the radial distance to the stem, total height, canopy diameter (the mean of the longest and perpendicular crown widths), and stem diameter (DBH at 1.37 m for trees and basal diameter for shrubs).

2.2.2. Structured Walking Transects

To complement the PCQ data and enrich species-level insights, we established systematic belt transects at each study site. Within each rangeland, three randomly positioned walking transects were set up. Five rectangular subplots (20 × 10 m) were demarcated at 100 m intervals within each transect. All woody individuals within each subplot were identified to species, enumerated, and measured for DBH or basal diameter and total height.

2.2.3. Rainfall Data

Rainfall data were obtained from the Namibian Meteorological Services for all five study sites. The data span from the 1940s to 2025, with some gaps and missing data for certain locations, particularly Otjimbingwe, for several years. Warmbad contributes a continuous rainfall series from 1940 to 2020 (81 years), while Gibeon provides the longest uninterrupted record, running from 1911 to 2025 (115 years). Otjimbingwe is represented by two discrete windows—1940–1950 and 2018–2025—separated by a 67-year hiatus; Ovitoto likewise comprises two windows, 1952–1973 and 2016–2025, with a 43-year gap. Sesfontein offers a recent continuous sequence spanning 2015 to 2024 (10 years). All genuine archival interruptions are therefore treated as distinct temporal windows, and each window’s mean annual rainfall is analyzed separately to preserve temporal integrity. The graphs below illustrate the annual average rainfall for the study areas (Figure 2). Across the five rainfall series, a clear north-to-south moisture gradient and notable temporal contrasts emerge. Warmbad (A) sits firmly in the hyper-arid zone, with a 87 mm yr⁻¹ mean rainfall, flanked by short-lived spikes that rarely exceed 200 mm, reinforcing the site’s chronic moisture limitation At Gibeon (panel B), the last century has been characterized as arid–subarid, averaging 178 mm yr⁻¹, with only episodic wet spells in the 1970s and early 2000s, and no discernible secular trend. At Otjimbingwe (C), the older 1940–50 window averages a relatively wet 182 mm yr⁻¹, whereas the recent 2018–25 window drops to 128 mm yr⁻¹, hinting at a long-term drying tendency, though the six-decade data gap precludes a definitive trend line. Ovitoto (D) remains the wettest station, with both the 1952–73 and 2016–25 windows hovering around 340 mm yr⁻¹, indicating stable mesic conditions despite a 40-year hiatus in the archived data. Finally, Sesfontein (E) records the driest profile overall (mean ≈ 53 mm yr⁻¹ for 2015–24), with extreme inter-annual swings that are typical of Namibia’s hyper-arid northwest (Figure 2).

2.2.4. The Limitations and Scope of the Datasets

Point-centered quarter (PCQ) data were not used in analyses that require complete floristic inventories, particularly estimates of species richness, Shannon and Simpson diversities, DBH and height-class distributions, regeneration status, and life-form spectra. Those attributes were quantified exclusively from belt transect plot data, which recorded every woody individual within standardized sampling units and, therefore, provided the resolution required for robust community-level comparisons. PCQ records were, however, incorporated into analyses of woody plant density, basal area, and species composition, where their spatial efficiency offers reliable structural metrics. Due to logistical constraints, which restricted transect surveys to four of the five study sites, Sesfontein was excluded from all analyses derived from transect data. The site is still represented in PCQ-based structural assessments but not in biodiversity or regeneration evaluations that rely on transect plots.

2.3. Data Manipulation and Analysis

2.3.1. Vegetation Structure and Regeneration Dynamics (Stem Density, Basal Area, Size-Class Profiles, and Raunkiaer Life-Form Spectra)

In the point-centered quarter (PCQ) survey, stem density was inferred directly from inter-tree spacing. At each sampling point, the four nearest woody individuals—one per quadrant—were identified, and their centroid distances were averaged to give $\overline{r}$ (m). Stand density (stems ha⁻¹) was then derived with the canonical PCQ estimator

$$D_{\mathrm{ha}}={\displaystyle \frac{40000}{\mathrm{\pi }{\overline{r}}^2}}\left({\mathrm{stems} \mathrm{ha}}^{-1}\right),$$

which applies the inverse-square relationship between mean spacing and density and multiplies by the factor 4/π to account for the quarter-circle search area represented by each recorded stem.

For plot-based methods, density was calculated per 200 m² (20 m × 10 m) plot and scaled to a per-hectare basis. Basal area per stem was derived from diameter at breast height (DBH, cm) using

$${\mathrm{BA}}_{\mathrm{stem}}={\displaystyle \frac{\mathrm{\pi }{(\mathrm{DBH}/100)}^2 }{4}} \left({\mathrm{m}}^2\right),$$

summed within each plot (or PCQ sampling point) and then expressed on a per-hectare basis using the same area conversions as above.

Plot-level stem density was compared among sites with a Generalized Linear Model (GLM) fitted to a Poisson error structure and log link. The log-transformed plot area was included as an offset to model true stem densities. For basal area, because basal area totals are continuous, strictly positive, and right skewed, they were analyzed with a Gamma-family GLM (log link). Pairwise contrasts of estimated marginal means were tested with Tukey-adjusted z-tests (multcomp package, R 4.3.2). The workflow followed the GLM framework of McCullagh and Nelder [52] and guidelines for ecological count data of Krebs (1999) [53].

For PCQ survey points, site-level stem densities were natural-log transformed to stabilize variances and analyzed using a log-normal GLM with Gaussian errors on the log scale. PCQ basal area, likewise positive and right skewed, was modeled with a Gamma GLM with a log link. Pairwise contrasts were again obtained with Tukey-adjusted z-tests (emmeans + multcomp, R 4.3.2). PCQ computations follow Cottam and Curtis (1956) [54] and the updated practical guidance of Mitchell (2023) [55].

The size-class structure was examined using plot data only. Stems were categorized into DBH classes (0–2, 2–5, 5–10, 10–20, or 20–50 cm) and height classes (0–1, 1–2, 2–5, 5–10, or 10–20 m) and the frequency of each class expressed as a proportion of all individuals. To further assess recruitment for each species, height-class graphs were presented for all species in each study site, showing the number of individuals in each height class for each species.

To evaluate functional composition, every woody species was assigned to a Raunkiaer life-form category following Raunkiaer (1904) with the later modifications of Misra (1968) [56] and Ellenberg & Müller-Dombois (1974) [57], as summarized in

Table 2. Descriptions of the different life forms.

Life Form	Description (Position of Perennating Bud from the Ground)
Megaphanerophyte	Above 30 m high
Mesophanerophyte	8–30 m high
Microphanerophyte	2–8 m high
Nanophanerophyte	Up to 2 m high
Chamaephyte	Up to 0.3 m high (low woody plants or herbs)
Geophyte	Underground
Therophyte	Survival in unfavorable conditions through seeds (annuals)
Epiphyte	Plants growing on other plants
Liana/scandent/climber	Mechanically dependent plant.

. Site-level frequencies of these life-form categories were then compared along the aridity gradient.

2.3.2. Site-Level Woody Plant Species Richness, Diversity, and Composition

Species richness was measured as the number of woody species recorded per site. Species diversity was quantified using the Shannon–Wiener index:

$$H^{\prime }=-\sum PilnPi$$

where Pi = S/N, with S being the number of individuals of a given species, N the total number of individuals of all species, and ln the natural logarithm (base e).

Plot-level species richness (discrete counts), being an integer and moderately dispersed (residual deviance: df ≈ 0.5), was analyzed with a Poisson GLM using a log link and “Site” as the sole fixed factor. Shannon diversity is strictly positive and right skewed, so it was modeled with a Gamma-family GLM (log link). In both cases, model fit was compared with a null (intercept-only) model by likelihood-ratio (LR) χ² tests. Pairwise site differences were evaluated with Tukey-adjusted contrasts (multcomp, R 4.3.), and diagnostic plots confirmed the adequacy of each distributional assumption. The analytical workflow follows the GLM framework of Nelder and Wedderburn [52] and established best practices for ecological count data.

For assessing variation in species composition, plot counts were Hellinger-transformed to down-weight very common species while retaining rare ones. Principal coordinates analysis (PCoA) on Bray–Curtis dissimilarities ordinated plots in reduced space. A permutational multivariate ANOVA (PERMANOVA, 9999 permutations) tested for overall site differences. SIMPER analysis ranked species by their average contribution to among-site dissimilarity, highlighting taxa that differentiate communities. All analyses were conducted using R 4.3.2 (packages vegan, MASS, and multcomp).

2.3.3. Ecological Significance of Each Woody Species and Indicator Species Analysis

The ecological importance of species was quantified with the species importance value (SIV), defined as the sum of three relative attributes calculated for every taxon:

SIV = Relative Frequency + Relative Density + Relative Dominance,

where each component follows the standard formulations of Mueller-Dombois and Ellenberg [57]. Species were ranked by SIV to identify those exerting the greatest structural and ecological influence at each site. Rank–abundance (dominance) curves were then generated by plotting the logarithm of species rank against relative abundance, providing a visual assessment of dominance hierarchies and evenness within the woody plant communities. Woody species dominance was also visualized using bubble plots generated in R (v4.3) with the readxl, dplyr, ggplot2, and patchwork packages. The bubble plots highlight numerical dominance (the number of stems), whereas IVI curves incorporate basal area and spatial frequency.

Indicator species were identified with the IndVal procedure implemented in the indicspecies package in R (version 4.4.3). Combined specificity and fidelity statistics were calculated with multipatt (999 permutations; α = 0.05), and species with significant IndVal scores were interpreted as diagnostic of site-level environmental conditions. In parallel, an abundance-based screen flagged species that (i) contributed >40% of their total stems at a single locality or (ii) occurred exclusively at one site.

2.3.4. The Relationships Between Rainfall and Woody Vegetation Attributes Across the Rangelands

Vegetation structure and diversity metrics were computed for each sampling plot based on transect data and linked to site-specific mean annual rainfall. Five key variables were analyzed: mean DBH, mean height, stem density, species richness, and Shannon Diversity Index. For each, a quadratic regression model was fitted against rainfall to detect non-linear trends. Model fit was assessed using the coefficient of determination (R²) and significance via F-tests. All calculations were conducted using ordinary least squares regression.

3. Results

3.1. Vegetation Structure: Woody Plant Density, Basal Area, and Size-Class Distributions

3.1.1. DBH/DCR Classes

Diameter-class profiles showed that Warmbad and Gibeon were dominated by smaller size classes (0–2 cm and 2–5 cm), showing limited growth potential, early successional stages, or drought-adapted shrubs. In contrast, Ovitoto and Otjimbingwe exhibited broader DBH distributions, with a significant proportion of individuals in larger size classes (≥5 cm). In Otjimbingwe, over 60% of the stems fell within the 20–50 cm class, indicating an essentially mature stand of well-established trees. Ovitoto showed a more even spread, with substantial representation in the 5–10 cm and 10–20 cm classes, as well as 30% recorded in the largest class (20–50 cm) (Figure 3).

3.1.2. Height Classes

Height-class profiles also clearly displayed a structural gradient across the transect. Warmbad and Gibeon were dominated by stems in the 0–1 m and 1–2 m classes, with virtually no individuals exceeding 2 m. Otjimbingwe exhibited a more even distribution of individuals across all height classes, ranging from 5 to 10 m, indicating a comparatively mature, vertically stratified stand. Ovitoto showed the most pronounced canopy development, with stems concentrated in the 5–10 m and 10–20 m classes, suggesting large, well-established trees and a fully articulated woody canopy (Figure 4).

3.1.3. Stem Density

Stem counts from the belt transect survey varied significantly among the sites (negative-binomial GLM, χ² ≈ 46, df = 3, p < 0.001). The mean densities were approximately 2740 stems per hectare in Gibeon, 2210 stems per hectare in Ovitoto, 1640 stems per hectare in Warmbad, and 650 stems per hectare in Otjimbingwe. The decrease in stem density from Gibeon to Otjimbingwe was the only significant difference after the Tukey adjustment (z = −3.83, p < 0.001) (Figure 5a). Data from the PCQ, although lower in absolute values, showed the same pattern. The effects of the site on log density were significant (log-normal GLM, F_4,41 = 8.05, p < 0.001). The predicted means were approximately 1270 stems per hectare in Gibeon, 2100 stems per hectare in Ovitoto (p > 0.05), 940 stems per hectare in Warmbad (p > 0.05), 600 stems per hectare in Otjimbingwe (p > 0.05), and a notably sparse 120 stems per hectare in Seisfontein (Tukey z = −4.40, p = 0.005) (Figure 5b).

3.1.4. Basal Area

The results for the basal area from the transect data showed a significant difference (Gamma GLM, χ² ≈ 34, df = 3, p < 0.001) between the different sites. Ovitoto had the highest basal area at approximately 3.38 m² per hectare (z = 5.10, p < 0.001), while Otjimbingwe’s basal area was about 1.55 m² per hectare, which was significantly higher than Gibeon’s approximate 0.67 m² per hectare (p = 0.008). Warmbad had a low basal area of approximately 0.41 m² per hectare, which was not significantly different from that of Gibeon (Figure 6a).

For PCQ data, the basal area varied significantly (Gamma GLM, χ² ≈ 26.1, df = 4, p < 0.001) between sites and followed the same pattern as that observed in the transect data, except that these data also included Sesfontein. Ovitoto was approximately 2.85 m² per hectare (z = 3.02, p = 0.003), Otjimbingwe was around 2.24 m² per hectare (p = 0.013), and Sesfontein was approximately 2.83 m² per hectare (p = 0.005), all exceeding Gibeon’s approximate 0.45 m² per hectare, while Warmbad’s basal area (approximately 0.38 m² per hectare) did not differ significantly from that of Gibeon (p > 0.05) (Figure 6b).

3.1.5. Life-Form Spectra and Regeneration Status

Across the four rangeland sites (Warmbad, Gibeon, Ovitoto, and Otjimbingwe), nanophanerophytes (0.3–2 m tall) overwhelmingly dominated the life-form spectrum, reflecting the shrub- and small-tree-dominated vegetation typical of Namibia’s arid and semi-arid regions. Gibeon exhibited the highest proportion of nanophanerophytes (~83%), followed by Warmbad (~72%). Warmbad also had a notably higher share of chamaephytes (<0.3 m; ~23%), whereas Gibeon recorded only about 5% in that smallest height class. In the slightly less arid sites, Otjimbingwe and Ovitoto, microphanerophytes (2–8 m) comprised a significantly larger component of the spectrum—roughly 42% and 46%, respectively—alongside nanophanerophytes at ~55% (Otjimbingwe) and 53% (Ovitoto). Chamaephytes barely registered at these two locations (≈1–2%), and mesophanerophytes (8–30 m) remain virtually absent across all four sites (few individuals in Otjimbingwe). These patterns signal a shift from very low, drought-tolerant shrubs in the hyper-arid Warmbad and Gibeon toward a more structurally complex assemblage of taller shrubs and small trees in Otjimbingwe and Ovitoto (Figure 7)

3.1.6. Regeneration Potential

At Warmbad and Gibeon, only a few species—most notably Montinia caryophyllacea and Rhigozum trichotomum—were represented in multiple height classes, while the majority of species occurred in just one size band, indicating limited recruitment or a failure to advance to maturity. Ovitoto, by contrast, supported many species from seedling to adult stages. Still, these were largely known woody encroachers (e.g., Senegalia mellifera and Dichrostachys cinerea), which may reflect a structurally complex yet invasive-prone assemblage. Otjimbingwe showed active recruitment in key shrubs such as Tarchonanthus camphoratus, but several native taxa never attained the >3 m class, revealing incomplete ontogenetic progression (Figure 8).

3.2. Community-Level Biodiversity

3.2.1. Species Composition

For the plot-based (transect) method, a total of 2171 individuals representing 46 woody species and 22 plant families were recorded. Fabaceae was the most dominant family (26%), followed by Euphorbiaceae (11%) and Capparaceae (9%). Dominant species varied across sites: Rhigozum trichotomum in Gibeon, Tarchonanthus camphoratus in Otjimbingwe, Senegalia mellifera in Ovitoto, and Montinia caryophyllacea in Warmbad. The PCoA of Bray–Curtis distances (stress = 0.13) separated plots primarily along Axis 1 (47% of variance) in the order Warmbad → Gibeon → Otjimbingwe/Ovitoto, mirroring the aridity gradient. PERMANOVA corroborated these visual patterns (F_3,56 = 9.12, R² = 0.33, p < 0.001). Pairwise tests revealed that Warmbad was significantly different from all other sites (adjusted p < 0.001), while the Gibeon–Otjimbingwe and Gibeon–Ovitoto pairs showed marginal dissimilarity (p ≈ 0.06). SIMPER revealed that Rhigozum trichotomum, Montinia caryophyllacea, and Atriplex lindleyi collectively accounted for ~42% of the average Bray–Curtis distance between Warmbad and the other sites, reflecting their dominance under hyper-arid conditions. Conversely, Tarchonanthus camphoratus and Senegalia senegal were most influential in distinguishing Otjimbingwe and Ovitoto from Gibeon (Figure 9a).

The PCQ survey yielded 605 stems spanning 49 species in 15 families. Fabaceae again dominated (41.5%), followed by Bignoniaceae (Jacaranda) and Capparaceae. The PCoA of Bray–Curtis distances on the PCQ species abundances revealed a clear compositional gradient along Axis 1 (16.9% of variance) from Warmbad (left) through Seisfontein and Gibeon to Otjimbingwe/Ovitoto on the right. Axis 2 (12.1%) further distinguishes Gibeon’s plots (upper quadrant) from Otjimbingwe and Ovitoto clusters. PERMANOVA on the PCQ dissimilarities gave a pseudo-F = 1.12 and p = 0.27 (9999 permutations), indicating no statistically significant difference among sites at α = 0.05, and a non-significant betadisper test (p = 0.44) confirmed that this result is driven by location (centroid shifts) rather than dispersion (spread). SIMPER analysis identified three species—Montinia caryophyllacea, Atriplex lindleyi, and Rhigozum trichotomum—as jointly accounting for approximately 38% of the average Bray–Curtis distance between Warmbad and all other sites, underscoring Warmbad’s hyper-arid shrub dominance. In contrast, Tarchonanthus camphoratus and Senegalia senegal together explained about 22% of the dissimilarity between Gibeon and the Otjimbingwe/Ovitoto group, marking the shift toward taller, moisture-adapted taxa in the more mesic rangelands. Overall, the PCQ ordination mirrors the transect-based pattern of aridity-driven turnover—albeit with weaker statistical separation—validating PCQ as a rapid, distance-based snapshot of community composition across all five sites (Figure 9b).

3.2.2. Species Richness and Diversity

The Poisson GLM for species richness detected a significant site effect (LR χ² = 8.39, df = 3, p = 0.039). The mean predicted richness per plot was highest in Gibeon (≈5.3 species) and Ovitoto (≈5.0), intermediate in Otjimbingwe (≈4.7), and lowest in Warmbad (≈3.3). Tukey contrasts revealed that Warmbad had significantly lower species richness than Gibeon (z = −3.07, p = 0.004) and Ovitoto (z = −2.43, p = 0.015); however, other pairwise differences were not significant (Figure 10a).

Shannon diversity varied even more strongly (Gamma GLM, LR χ² = 26.57, df = 3, p < 0.0001). The average H′ was ≈ 1.28 in Otjimbingwe, 1.20 in Gibeon, and 1.15 in Ovitoto, with no statistical separation among these three sites. Warmbad, however, recorded a markedly lower mean of ≈ 0.64, differing from every other site (Tukey z ≤ –4.3, p ≤ 0.001) (Figure 10b).

3.3. Ecological Significance of Each Woody Species and Species Dominance

3.3.1. Importance Value Index and Numerical Dominance

Dominance patterns, expressed as importance value indices (IVIs), varied steeply along the aridity gradient. At Warmbad, Montinia caryophyllacea attained an IVI of ≈166, while all other taxa fell below 30, effectively a woody monoculture. Gibeon retained a modest group of co-dominants: Rhigozum trichotomum leads (≈86 IVI), with Atriplex lindleyi (≈49) and Tetragonia schenckii (≈37) rounding out a slightly broader dominance head than that of Warmbad. Otjimbingwe exhibited the most even assemblage: although Senegalia senegal tops the list (≈97 IVI), values declined gradually across some 25 species, yielding the flattest dominance curve in the series. Ovitoto was co-dominated by Vachellia reficiens and Senegalia mellifera (≈57 IVI each), closely followed by Terminalia prunioides; beyond this small cohort, the IVI curve dropped sharply and then leveled out, indicating a few primary dominants supported by numerous minor associates (Figure 11).

The bubble plot revealed a sharp turnover in leading species across the gradient. Warmbad was overwhelmingly dominated by Montinia caryophyllacea (>300 stems) with much smaller bubbles for Galenia africana and Rhigozum trichotomum. Gibeon was characterized by Rhigozum trichotomum (~290 stems) and halophytic Atriplex lindleyi, while Vachellia nebrownii formed a noticeable third tier. In Otjimbingwe, abundance was spread thinly: Tarchonanthus camphoratus led but never exceeded 50 stems, followed by Senegalia senegal and Catophractes alexandri. Ovitoto exhibited a distinct structure, with nearly equal dominance of Senegalia mellifera (~140 stems) and Catophractes alexandri and substantial representation of Dichrostachys cinerea (Figure 12).

Figure 11 (IVI dominance curves) and Figure 12 (bubble plots) show the same broad gradient in woody plant dominance yet highlight different facets of it. In every site, the largest bubbles identified the same leading species that headed the IVI curves—Montinia caryophyllacea in Warmbad, a three-species cohort in Gibeon, the long, even tail in Otjimbingwe, and the twin thornbush dominants in Ovitoto—so the two plots agree on which species numerically or structurally control each community. Where the visualizations diverge is in their treatment of less abundant but structurally important species, the density-only bubbles in Figure 12 under-represent species such as Senegalia erubescens, which appear far higher in the IVI rankings of Figure 10 because the IVI also weights basal area and plot frequency.

3.3.2. Indicator Species

Indicator species analysis (IndVal × 100, α = 0.05; Figure 13) identified a concise, exclusive suite of diagnostic species at each rangeland. In Warmbad, Montinia caryophyllacea (IndVal = 100, p < 0.001) emerged as a “perfect” indicator, with both perfect fidelity and specificity, while Aizoon africana (33.3, p < 0.001) and Sarcocaulon crassicaule (33.3, p < 0.001) showed moderate site restriction and consistent occurrence there. In Gibeon, Tetragonia schenckii (79.3, p < 0.001), Rhigozum trichotomum (75.8, p < 0.001), and Atriplex lindleyi (46.7, p < 0.001) each combined high fidelity with strong site-specific abundance. At Otjimbingwe Senegalia senegal (formerly Acacia senegal) (72.6, p < 0.001), Phaeoptilum spinosum (50.9, p < 0.001), and Tarchonanthus comphoratus (39.3, p < 0.001) reflected consistent occurrence and concentration in this mid-aridity zone. Finally, Ovitoto, Senegalia mellifera (formerly Acacia mellifera) (97.3, p < 0.001), Terminalia prunioides (72.2, p < 0.001), and Dichrostachys cinerea (65.6, p < 0.001) stood out as strongly diagnostic of Ovitoto (Figure 13). All p-values derive from the permutation test (1000 total draws), confirming that these species exhibit high site-specific fidelity and abundance. An additional abundance-based filter (species contributing > 40% of stems at one site or occurring exclusively there) reinforced these diagnostic assemblages.

3.4. Relationships Between Rainfall and Woody Vegetation Attributes

Rainfall was positively associated with several vegetation attributes, though the strength of the relationships varied. Mean plant height showed the strongest correlation with rainfall (R² = 0.45, p < 0.001), followed by Shannon diversity (R² = 0.34, p < 0.001) and species richness (R² = 0.21, p = 0.001), both of which displayed unimodal (hump-shaped) trends. Mean DBH was weak but significantly related to rainfall (R² = 0.12, p = 0.025), while stem density showed no significant pattern (R² = 0.05, p = 0.25). These results highlight rainfall as an important predictor of vertical structure and diversity in woody plant communities but a less consistent driver of stem abundance (Figure 14).

4. Discussion

Our transect, spanning from the hyper-arid plains of Warmbad to the semi-arid thornbush savanna of Ovitoto, offers a rare, field-measured snapshot of how woody communities reorganize themselves across one of southern Africa’s sharpest moisture gradients. Within less than 400 km, the mean annual rainfall quadrupled, and we observed a tenfold increase in basal area, a threefold jump in Shannon diversity, and a dramatic shift from near-monoculture dwarf shrubs to multi-layered thorn thickets. Such tightly coupled structural and compositional shifts underscore rainfall’s pre-eminence as the “throttle” of rangeland architecture, yet they also reveal how local history and management modulate that climatic signal.

4.1. Structural Responses to Aridity: From Dwarf Shrubs to Thorny Cathedrals

Southern Namibia is generally drier than the northern parts and this has direct impacts on woody plant growth, survival, and community composition, reflected in DBH and height distributions. In the present study, diameter and height spectra exhibit a classic relationship between aridity and structure. Warmbad (≈85 mm yr⁻¹) and Gibeon (≈160 mm yr⁻¹) were skewed towards stems <2 cm in diameter and <2 m tall, mirroring the stunted, clonal shrubs described for the Nama-Karoo by Dean and Milton [58] and diagnostic of dwarf shrublands that are both water limited and many times disturbed. By contrast, Otjimbingwe and especially Ovitoto carried substantial cohorts in the 10–50 cm diameter at breast height (DBH) and 5–20 m height classes, matching the values reported for higher-rainfall Kalahari savannas [59]. Mean annual rainfall accounted for 45% of the observed variation in mean plant height (R² = 0.45, p < 0.001), making it the strongest abiotic correlate in our models. This finding aligns with Scholes & Archer [60], who showed that once the disturbance is removed, vertical woody stratification becomes primarily rainfall limited [59]. Nevertheless, the substantial unexplained variance highlights the need to factor in soil properties, microclimate, and herbivore dynamics in future work.

The basal area rose almost in order of magnitude from Warmbad (0.4 m² ha⁻¹) to Ovitoto (3.4 m² ha⁻¹). Similar step-wise increases have been documented along the Kalahari in South Africa [61] and Namibia [39]. This result corresponds with Sankaran et al.’s [59] analyses, showing that maximum woody cover (and thus biomass) scales linearly with mean annual precipitation (MAP) up to ~650 mm. Yet, stem density did not track rainfall monotonically: the densest stands occurred in Gibeon (approximately 2740 stems ha⁻¹) rather than Ovitoto. This paradoxical pattern likely reflects stem-packing—an emergent self-organizing response in water-limited systems whereby frequent recruitment pulses, delayed self-thinning of small individuals, and scale-dependent facilitation—competition feedbacks produce very high densities of small shrubs that optimize the capture of scarce moisture [62,63]. Managers, therefore, cannot infer carrying capacity solely from stem counts; basal area or biomass must supplement density metrics when setting browsing or clearing thresholds. Schneiderat [64] posits that the contrasting stand structures originate from ecological and zonal disparities. In dry-forest sites, a dense thicket of woody plants predominates, rarely reaching considerable heights. Due to the tightly packed stems, neighboring trees engage in intense competition, thereby restricting crown expansion.

4.2. Life-Form Spectra and Regeneration Reveal Divergent Trajectories

A life form is characterized by plant adaptation to specific ecological conditions. Vegetation serves as an indicator of climate and is useful for comparing geographically distributed plant communities. [65]. When Raunkiaerean classification was used, we found an overwhelming dominance of nanophanerophytes (0.3–2 m) in Warmbad (≈72%) and Gibeon (≈83%), typical of southern African deserts and very-arid shrub mosaics, where chronic moisture stress, shallow soils, and intense browsing select for low, multi-stemmed woody form [66]. The even larger chamaephyte (~23%) component at Warmbad echoes patterns in the Succulent and Nama-Karoo, where <0.3 m succulents and dwarf shrubs dominate on gravelly pediments that rarely experience significant wetting, with depths exceeding only a few centimeters [66]. South-eastward, rainfall almost doubles, and the spectrum shifts toward microphanerophytes (2–8 m): 42% of individuals at Otjimbingwe and 46% at Ovitoto now occupy this height tier, while nanophanerophytes retreat to ~55%. A comparable shift was observed on Kalahari sands: Hauwanga et al. [67] found that nanophanerophytes peaked under 300–400 mm mean annual precipitation (MAP), whereas micro- and meso-forms increased sharply beyond that threshold. Nonetheless, mesophanerophytes (>8 m) remain virtually absent throughout our transect. This ceiling agrees with the continental synthesis of Sankaran et al. [59], which shows that savannas receiving <650 mm yr⁻¹ never reach closed-canopy heights because of seasonal water limitation and disturbance caps vertical growth. Taken together, the life-form data confirm a structural progression from dwarf-shrub Nama-Karoo physiognomies toward a low-woodland savanna—yet still well short of true woodland—over a rainfall increment of just ~250 mm.

Regeneration dynamics exhibited a significant shift along the aridity gradient. In hyper-arid Warmbad and very-arid Gibeon, recruitment was clearly bottlenecked: only Montinia caryophyllacea and Rhigozum trichotomum appeared in more than two height classes, while most other species were restricted to a single tier, indicating either failed recruitment pulses or extremely slow growth. At Otjimbingwe, regeneration was selective. Tarchonanthus camphoratus appeared across all four height tiers, yet many palatable tall trees stall below the 3 m “escape height.” Experimental work across African savannas demonstrates that early, repeated browsing, particularly where grass fuel is too sparse for fire, creates such growth bottlenecks that they filter out browsed saplings long before they reach the overstory [68]. The semi-arid Ovitoto site presented a different picture: seedlings of most woody species were abundant, but the cohort was skewed toward classic encroachers, such as Senegalia mellifera and Dichrostachys cinerea. Recent bush-thinning trials on north-central Namibian farmland confirm that when grass competition and fire are suppressed, these nitrogen-fixing shrubs proliferate across all size classes, driving stem density up and species evenness down [69]. The finding echoes widespread bush-thickening across Namibia’s central plateau [14] and warns that higher rainfall alone does not guarantee the desired woodland structure; competitive release from fire and megaherbivores may be equally critical [70].

4.3. Species Richness, Diversity, and Turnover

Fabaceae, especially the nitrogen-fixing mimosoids (Senegalia, Vachellia, and Dichrostachys), dominated the woody strata in both the belt transect (26% of stems) and PCQ (42% of stems) datasets. This pattern aligns with earlier vegetation surveys of Namibia’s thornbush savanna, where mimosoid Fabaceae form the core of the woody biomass under seasonal drought and chronic browsing pressure [33,67,71]. Principal coordinates analysis of transect plots (stress = 0.13) arrayed sites in strict rainfall order along Axis 1, segregating the hyper-arid Warmbad assemblage—dominated by Montinia caryophyllacea and Rhigozum trichotomum—from the taller, mesic stands of Otjimbingwe and Ovitoto.

Plot-level richness climbed from a median of three species in Warmbad to five in Gibeon and Ovitoto and then leveled off (≈4.7 species) in Otjimbingwe. Species richness showed the expected hump-shaped response to rainfall (R² = 0.21), peaking in Gibeon and Ovitoto and dipping sharply in Warmbad. This saturating—rather than strictly hump-shaped—response aligns with the water–energy framework: richness rises steeply as moisture stress eases and then plateaus once other factors (competition, grazing, and fire) become limiting [72]. It also mirrors rainfall-richness curves along the Botswana transect, where total woody species numbers varied little once the MAP exceeded ~350 mm, but compositional turnover continued [71]. Shannon diversity, however, climbed almost linearly with rainfall until flattening between Otjimbingwe and Ovitoto.

4.4. Dominance Structure, Diagnostic Taxa, and Rainfall Controls

The Importance Value Index (IVI) curves displayed a pronounced structural pivot from hyper-arid to semi-arid rangelands. Warmbad is effectively a woody monoculture: Montinia caryophyllacea alone captures > 80% of total importance (IVI ≈ 166), corroborating vegetation descriptions of the Succulent–Karoo dwarf-shrub savanna where Montinia forms near-pure stands on shallow, stony soil [73]. Moving north to Gibeon, dominance broadens but remains drought skewed. Rhigozum trichotomum (IVI ≈ 86), with Atriplex lindleyi and Tetragonia schenckii, typifies the “three-thorn” shrub mosaics that expand under heavy grazing and declining rainfall on southern Namibian rangelands [14]. Their intermediate IVIs (IVI ≈ 37–49) still leave a steep rank–abundance drop, indicating that a handful of salt-tolerant or spinescent shrubs monopolize resources once the MAP rises just above 100 mm yr⁻¹. The most even profile occurred at Otjimbingwe (≈165 mm MAP). Here, IVIs tapered gradually across ~25 species, echoing studies along the Kalahari Transect that record maximum evenness and the flattest rank–abundance slopes between 150 and 300 mm MAP, where neither water stress nor competitive shading fully excludes sub-dominants [61]. In Ovitoto (≈340 mm MAP), the curve steepened again, but around a pair of dominant encroachers: Vachellia reficiens and Senegalia mellifera (IVI ≈ 57 each), followed closely by Terminalia prunioides. Such twin-species dominance is characteristic of Namibian thornbush savannas undergoing bush thickening, where S. mellifera frequently co-rules biomass and canopy cover [24,74]. Bubble plots (stem counts only) and IVI curves (counts, basal area, and frequency) agree on the leading species at every site, confirming that both metrics capture the headline patterns of control. They differ, however, in the importance they assign to less abundant yet large-stemmed taxa. For example, Otjimbingwe’s Senegalia erubescens and Ovitoto’s Dichrostachys cinerea rank much higher in the IVI than in raw density because their thick stems contribute disproportionately to the basal area and, therefore, to competitive influence [24]. IndVal analysis pinpointed one to three highly diagnostic taxa per site—Montinia (Warmbad), Rhigozum + Tetragonia (Gibeon), Senegalia senegal + Phaeoptilum spinosum (Otjimbingwe), and S. mellifera + Terminalia prunioides (Ovitoto)—each with p < 0.001. Similar single-site fidelity has been reported for R. trichotomum and S. mellifera along central-Namibian aridity transects, where these shrubs serve as management “flags” for very arid and semi-arid degradation states, respectively [67]. Montinia caryophyllacea is a “perfect” sentinel of hyper-aridity (IndVal = 100), echoing its status in the southwestern Karoo [75,76]. Rhigozum trichotomum and Atriplex lindleyi define Gibeon’s slightly less extreme mosaics, while Senegalia senegal signals the first appearance of taller phanerophytes in Otjimbingwe. In Ovitoto, S. mellifera and Terminalia prunioides dominate, both of which are notorious for forming near-impenetrable thickets under relaxed fire regimes [24]. The strong concordance between our IndVal output and previous floristic classifications lends confidence that the four rangelands represent ecologically discrete woody communities despite their relatively short geographic separation.

Quadratic regressions highlight rainfall’s primacy for height, diversity, and richness, but its weak link to stem density (R² = 0.05) reminds us that disturbance filters modulate climate signals [77]. Browsing, termites, frost pockets, and historical clearing all leave structural “fingerprints” that can obscure simple rainfall–biomass links [78].

4.5. Management Implications Along the Gradient

Translating patterns into practice demands site-tailored, disturbance-savvy strategies: Warmbad should prioritize livestock exclosures and micro-catchment earthworks that concentrate scarce runoff, an approach championed in Sahelian restoration programs [79]. Fire is unnecessary, but browsing must remain minimal until saplings surpass herbivore browse lines. Gibeon may require periodic low-intensity fires in wet years or targeted goat browsing to suppress the re-sprouting of R. trichotomum while permitting the recruitment of palatable shrubs. Otjimbingwe may benefit from patch-mosaic burns tailored to its specific needs. Encouraging assisted natural regeneration of Tarchonanthus camphoratus and Phaeoptilum spinosum may bolster microclimate buffering and browse value. Ovitoto faces classic bush encroachment challenges. Integrated mechanical-fire-browser interventions to reduce S. mellifera thickets are recommended. Follow-up enrichment planting with multipurpose hardwoods (e.g., Terminalia prunioides) is suggested to diversify the structure and livelihood options. Economic modeling indicates that debushing enhances mean income but increases income variance, highlighting the need for risk-informed thinning intensities [80]. Across all sites, embedding indicator species in community-based monitoring (CBM) scorecards will combine quantitative metrics with local ecological knowledge, a formula that has been shown to accelerate adaptive management [81]. High-fidelity taxa such as Tetragonia schenckii (IndVal 79%) act as “ecological widgets” signaling edaphic or disturbance regimes. Incorporating these taxa into rangeland dashboards could provide near-real-time early-warning capacity for managers.

5. Conclusions

This study provides a comprehensive ecological assessment of woody vegetation across a pronounced aridity gradient in Namibia, integrating plot-based and plotless sampling methods. By examining structural metrics (density, basal area, DBH, and height), biodiversity indices (richness and Shannon diversity), dominant species composition, indicator species, regeneration patterns, and life-form spectra, the study reveals strong spatial variability that corresponds with moisture availability and landscape-level ecological processes.

The findings confirm that drier sites, such as Warmbad, exhibited reduced species richness, lower diversity, and dominance of drought-adapted life forms, while more mesic areas, like Ovitoto, harbored more structurally complex and compositionally rich communities. These patterns are strongly correlated with mean annual rainfall, suggesting that precipitation remains a key driver of vegetation structure and composition in semi-arid rangelands.

From a methodological standpoint, the use of transect-based sampling provided higher resolution and sensitivity for detecting biodiversity and regeneration patterns, while the PCQ method effectively captured dominant species and density estimates. Combining these methods allowed for a nuanced and balanced characterization of ecological structure.

Ecologically, the dominance of nanophanerophytes and chamaephytes in arid zones reflects adaptive responses to environmental stress, such as low water availability and high grazing pressure. The reduced regeneration in some areas signals possible degradation or successional stalling, highlighting the need for targeted conservation and restoration efforts.

These results have critical implications for rangeland management. Conservation strategies should prioritize the protection of more diverse and structurally complex regions to preserve ecosystem function and resilience. Simultaneously, interventions such as rotational grazing, reseeding, and water management should be implemented in more degraded or arid landscapes to facilitate vegetation recovery and sustainable use.

Overall, the data align with experimental and remote-sensing studies showing that across the sampled rangelands, woody assemblages pivot sharply with rainfall, but the devil is in the demographic detail. Hyper-arid sites risk functional collapse through recruitment failure, while semi-arid sites tip towards thorny dominance. Stature-based life-form spectra track mean rainfall, but regeneration trajectories hinge on disturbance history as much as on climate. Without active interventions, semi-arid sites are on course for dense, encroacher-dominated woodland, whereas the driest landscapes will likely remain dwarf-shrub mosaics constrained by hydro-ecological limits.