SETIBING RANGELAND HEALTH REPORT
Mafantiri,T;`Molaoa,M;Polane,M
6/22/2022
MINISTRY OF FORESTRY,RANGE AND SOIL CONSERVATION
DEPARTMENT OF RANGE RESOURCES MANAGEMENT,LESOTHO
JUNE 2022
1.0 INTRODUCTION
1.1 BACKGROUND
Rangeland biomes encompasses much of the area where pastoral livestock production is a major land use, cover 51% of the earth’s land area but support 78% of the global grazing area (Asner et al., 2004). They play a key role in social, cultural, economic and ecological demands. For instance, provision of food, a variety of plants for different purposes like medicines ( Mussa et al., 2016; Kobisi, 2019) and trading livestock and livestock products, such as wool and mohair (WAMPP- PDR, 2014). Rangelands are ecologically important for carbon dioxide (CO2) sequestration, biodiversity conservation and provide habitat for both flora and fauna (Range Policy, 2014).
Water from wetlands within rangeland ecosystems is used locally in Lesotho for hydropower generation, agricultural and industrial purposes. It is further exported to the Republic of South Africa through the Lesotho Highlands Water Project. Importantly, the pride and wealth of Basotho are rooted and reflected in the rearing and ownership of livestock which depend entirely on rangelands (WAMPP- PDR, 2014). The Ministry of Forestry, Range and Soil Conservation, through the Department of Range Resources Management (DRRM) is charged with the responsibility of assessing rangeland health status for sustainable grazing in Lesotho. Despite the importance of rangelands and its ecosystem services, there is a high rate of rangeland degradation experienced across Lesotho (Range Policy, 2014). It is mostly caused by poor range management practices and overgrazing, which emanates from overstocking and exceeding the rangeland carrying capacity (Mussa et al., 2016; Briske et al. 2003). Therefore it becomes imperative to devise techniques that will help to estimate carrying capacity and stocking rate of an area for sustainability, productivity and management of the rangeland.
Rangelands in Lesotho are utilized through a seasonal transhumance system between highlands and summit plateaus (A Grazing Area), Village Grazing Area (C Grazing Area) and transitional areas between A and C grazing Areas (B Grazing Area). Grazing system usually implemented in these areas is rotational grazing system along with seasonal suitability system.
The Government of Lesotho has been concerned about the degradation of rangelands for a considerable time now. Rangeland degradation has resulted in reduced livestock productivity and increased soil erosion. With support from several development partners, various range management initiatives have been implemented. It is against this backdrop that Department of Range Resources Management in direct conjunction with ReNoka and Lesotho Highlands Development Authority is conducting rangeland health assessment to compare areas treated under mechanical brush control and no brush control.
Cover methods quantify vegetative communities in only 2 dimensions. The addition of height measurements to cover data, resulting in canopy volume estimates, provide a more practical level of description for shrub communities.canopy volume estimates have been used for predicting biomass or current-year twig production of shrubsSince canopy volume is an important attribute in shrub communities and its estimation is becoming more common(Mark S. Thorne et al.2002).
Using canopy volume method, managers can better describe and monitor trends in the structural diversity of shrub communities. This canopy volume technique appears to be sensitive to changes in plant size over short time intervals (Thorne 1998), so it can be used to evaluate annual impacts to shrub communities such as herbivory, disease, drought, and various land uses. Other uses might include evaluating wildlife habitat quality and forage production (Taylor 1986, Manoukian 1994). In monitoring our rangeland resources, a methodology that is efficient, precise, and repeatable is clearly desirable. This canopy volume technique can be applied with minimal training and is precise, efficient, and repeatable. It can also be consistently applied by an individual observer as well as by a team of observers to sample larger geographical areas.
1.2 OBJECTIVES
The DRRM Headquarters and Maseru District staff with support from ReNoka in direct conjunction with Lesotho Highlands Development Authority (LHDA) embarked on joint exercise with the following aims:
a) To assess Setibing rangeland health condition and productivity on plots under brush control and those not under brush control.
b) To map range rehabilitation interventions at Setibing2.0 METHODS AND TOOLS
2.1 STUDY AREA
The study area covers 99.3 hectares.It is located in the Likolobeng community council.It is used both by Setibing and Ha Chalalisa communities in Maseru district.
2.2 DATA COLLECTION AND SAMPLING
Stratified random sampling was used.Sample plots were generated using randomisation tool in QGIS 3 desktop.The points were uploaded onto Trimble TDC 100 handheld device with Locus Map App installed.The device was used to navigate to the study plots.Open Data Kit(ODK)form authored by DRRM was uploaded onto device used for data collection.Collected and normalized data was uploaded onto server for storage,wrangling and analysis.
2.2.1 RANGELAND HEALTH ASSESSMENT
2.2.1.1 NON-DESTRUCTIVE SAMPLING TECHNIQUE
- Land Degradation Surveillance Framework
Land Degradation Surveillance Framework (LDSF) method was used to undertake the actual measurements of vegetation parameters, Rangeland cover and woody plant measurements (Vågen T. G and Winowiecki L.A, 2020). This technique incorporates various sampling methods such as Step point technique and T-Square Sampling Method. The woody plant measurements were carried out using T Square Sampling method. Woody Plants were identified and recorded using binomial nomenclature. The height, width, length, and count of every individual woody plant in all subplots were measured using tape measures. In every sampling site 10m x 10m plot was established and woody plants were counted, their dimensions measured based on their configurations. A size of 0.1ha circular plot was used during herbaceous plants and litter depth measurements. Within that plot, step Point technique was used to carryout rangeland module. In every sampling site a crossed line transects of 28m (from South to North and from East to West) was established in a sampling area of 0.1ha. At the interval of 2m, herbaceous plant species were identified and recorded using binomial nomenclature. In point where bare patches were encountered, distance from nearest herbaceous plant was recorded.
- Disc Pasture Meter
Disc Pasture meter (DPM) method was incorporated to estimate the above ground biomass of herbaceous grass. DPM was placed along a 28 m transect (from South to North and from East to West) at 2m interval and basal cover of the grass sward readings were recorded on each point.
- Additional rangeland health surveillance methods
Remote sensing science has become a critical and universal tool for natural resource managers and researchers in government agencies, conservation organizations, and industry (Gross et al., 2006; Stow et al., 2004).Most remote sensing products consist of observations of reflectance data. That is, they are measures of the intensity of the sun’s radiation that is reflected by the earth. Reflectance is normally measured for different wavelengths of the electromagnetic spectrum. For example, it can be measured in the red, green, and blue wavelengths. If that is the case, satellite data can be referred to as “multi-spectral” (or hyper-spectral if there are many separate wavelengths). The data are normally stored as raster data (referred to as “images”). Each separate image (for a place and time) is referred to as a s “scene”. As there are measurements in multiple wavelengths, a single “satellite image” has multiple observations for each pixel, that are stored in separate raster layers. In remote sensing jargon, these layers (variables) are referred to as “bands” (shorthand for “bandwidth”), and grid cells are referred to as “pixel”.
Visual observations technique along with satellite remote sensing data was used to support decision making regarding range rehabilitation and development. Understanding vegetation health is a sine qua non for planning spatially targeted land reclamation interventions. Remote sensing (RS) is one of the robust techniques used to study vegetation. The technique employs various vegetation indices such as Normalized Difference Vegetation Index (NDVI). NDVI is computed thus: \[NDVI = (NIR-RED)/(NIR+RED)\] where NIR is Near Infrared and RED portion of electromagnetic spectrum.
2.2.2 SHRUB MEASUREMENT
Woody plant species dimensions were measured as described under LDSF method. Based on shrub configurations,circular volume method was used to predict biomass as shown the equations below.
Mathematical expressions of the predictors for shrub biomass estimation are as follows: Crown Diameter is given by \[CD = (a1+ b1)/2\] where a1 is the maximum crown diameter and b1 is its perpendicular diameter while Circular Cylinder Volume(V1) is represented as \[{V1} = πCD^2h/4\] (Yao 2021).
2.2.3 RANGE REHABILTATION MAPPING
QGIS 3 Desktop and ArcGIS 10.8 Desktop was used to map rehabilitated area with guidance of indigenous knowledge systems.’Points Along Geometry’ tool in QGIS was used to generate altitudinal points along contour map for the study area.Areal feature geometry was computed and area was expressed in hectares. Coordinate Reference System used was Universal Transverse Mercator Zone 35S with WGS 84 used as reference ellipsoid, and metric unit used as a measurement metric.
3.0 RESULTS AND DISCUSSION
3.1 RESULTS
Before analysis,rangeland module and woody plant data collected from the field was loaded into R Studio Source Editor.
R packages such as ggplot2 for creating elegant data visualisations using grammar of graphics;ggridges for visualising changes in distribution over time or space;correlation for correlation analysis and dplyr for grammar of data manipulation were loaded using pacman.R Markdown and Knitr were used for creating/generating dynamic document and report for this study area.
3.1.1 RANGELAND HEALTH CONDITION
Fig.2 : Species Composition for Sekhutlong(Treatment) and
Tiping(Control
Aristida diffusa (increaser III) constitues the largest fraction of all species at Sekhutlong while Agrostis lachnatha (increaser II) constitutes the greatest at Tiping. However,comparatively,Sekhutlong(17 %) has higher fractional cover of decreaser species than Tiping(0 %).
There is relatively more herbaceous species at Sekhutlong than at Tiping.
There are more pioneer species at Tiping than at Sekhutlong.
There is relatively greater proportion of subclimax species at Sekhutlong than at Tiping.
Additionally, there is relatively greater abundance of climax species at Sekhutlong than at Tiping.
There is similar median litter thickness as shown in fig. 7 above.However, there is greater variability of leaf litter thickness values at Sekhutlong than at Tiping.
Correlation Matrix (pearson-method)
Parameter1 | Parameter2 | r | 95% CI | t(148) | p
---------------------------------------------------------------------
Litter | dpm | 0.35 | [ 0.21, 0.49] | 4.60 | < .001***
Dist_Tft | dpm | -0.45 | [-0.57, -0.31] | -6.12 | < .001***
p-value adjustment method: Holm (1979)
Observations: 150
There is relatively stronger,negative and significant correlation between distance to tuft values and disc pasture meter values corresponding to standing crop(r = -0.45) while there is relatively weaker,positive and significant correlation between leaf litter thickness and disc pasture meter values (r = 0.35) as shown in correlation matrix and plot above.
3.1.2 RANGELAND PRODUCTION*
Quantitative data sets were subjected to descriptive statistical analysis by using R statistical package. Spatial data was analysed using ArcGIS 10.8 and QGIS 3.22.1 software. The biomass was calculated using re-evaluated DPM calibration equation (Zambatis et al., 2006). Biomass in \[kg ha^{–1} = [31.7176 (0.32181/x) x^{0.2834}]2 \] where x is the mean DPM height in cm of a site.
there is relatively higher median yield at Sekhutlong than at Tiping as shown in fig. 9,fig. 10,appendix 1 and 2 showing distribution in terms of quartiles,yield scaling and tail probabilities.Second Quartile line/ fiftieth percentile line is greater at Sekhutlong.
There is generally lower vegetation health in the shrub encroached area in the south eastern to eastern region of the subcatchment as shown in fig.11. Notably,at higher altitude as evidenced by 10-metre-interval points generated along contours 25 metres apart,there is low NDVI.
3.1.3 SHRUB BIOMASS MEASUREMENT
Woody plants have been cleared off at Sekhutlong while there are some shrubs/trees at Tiping as shown in fig. 12
Buddleja salviifolia occupies the greatest space of all other species as shown above.
3.1. MAPPED RANGELAND UNDER REHABILITATION
Shrubified area is 48.3 hectares.Renoka initiated brush control is 32.9
hectares.LHDA initiated brush control is 18,1 hectares
4.0 DISCUSSION
Results show that there is a greater benefit in brush control.There is a greater number of unique herbaceous species at rehabilitated area(Sekhutlong) suggesting greater functional diversity.There are more pioneer species at Tiping indicative of higher ecological disturbances while trend at Sekhutlong is upwards as indicated by relatively higher climax and subclimax species characteristic of recovery following brush control.Despite presence of increaser species, there is bigger fractional cover of decreaser species at Sekhutlong while Tiping has none,indicating better management at Sekhutlong possibly due to leboella(prolonged deferred grazing).Satellite remote sensing shows that there is relatively higher vegetation health at rehabiltated area though spatial and altitudinal distribution of range improvement varies across sites.There is equal median litter thickness in all sites having implications for ecohydrological functionality and nutrient cycling as well as soil surface stability.Litter thickness is 2 cm which is said to minimize soil loss.Though there is weak strength of relationship,litter thickness offers benefits in terms of biomass increment while greater distances to tufts suggest that there is generally negative relationship.this might be due to bare area abundance which may increase erosion potential of the landscape.Another reason for the obseved change could be attributed to the fact that brush control reduces competition for resources(water,nutrients,light etc) between woody and herbaceous species.
5,0 CONCLUSION
Rangeland health has been assessed at the two sites(Sekhutlong and Tiping) suggesting that it is useful to invest in brush control.Rehabilitated area through brush control has been mapped as per goals.
6.0 RECOMMENDATIONS
It is recommended that brush control be continued for the remaining region of the subcatchment.
Soil and water conservation measures should be implemented on areas with low vegetation health taking into account contours and elevational differences as well as aspects and slope.
Grazing management plan as one of the robust approved practices in soil conservation should be developed as a matter of priority for both Setibing and Ha Chalalisa villages.
Further rangeland health data should be collected for the two above mentioned villages.
Fire Management plan should be developed for the developed rangelands.
Further studies on recovery dynamics post brush control should be undertaken
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8.0 APPENDICES
