Miombo Research Articles

Regeneration and Restoration Status of Miombo Woodland Following Land Use Land Cover Changes at the Buffer Zone of Gile National Park, Central Mozambique

In the context of the current intensified disturbances of Miombo woodland, its regenerating capacity is fundamental to endure such disturbances. Miombo woodland in the buffer zone of Gile National Park (GNAP) is facing land cover change. This study aimed to assess regeneration structure, the status of restoration, and factors affecting the regeneration of Miombo woodland in the buffer zone of GNAP. In total, 12 transects, 48 plots, and 240 subplots were sampled in dense Miombo woodland (DMWL), open Miombo woodland (OMWL), and abandoned agricultural land (AAL) to collect data. Household interviews, focus group discussions (FGD), and key informant interviews(KIIs) were used to collect socio-economic data. Descriptive statistics, Kruskal-Wallis, chi-square, and regression, were used to analyze data. A total of 1863 matured woody individuals representing 85 species and 29 families were identified. Matured woody species density was significantly different between AAL&DMWL and DMWL & OMWL. However, there was no significant difference between OMWL and AAL. Nine hundred three regenerated individuals representing 70 species and 23 families were registered. Regeneration density was significantly different between land-use types. The mean regeneration density in DMWL, AAL, and OMWL were 39.87±13.82, 50.25±21.1, and 23 ± 9.98 stems ha−1, respectively. The most regenerated family was Fabaceae. All respondents reported that no assisted restoration activity was/is taking place in the area. The five most important factors affecting the regeneration of Miombo woodland were identified. Slash and burn agriculture and animal grazing were ranked first and last, respectively. Increasing pressure for land demand is determining factor for Miombo woodland regeneration. The buffer zone of GNAP is characterized by a moderate diversity of woody species, with the number of regenerated woody species increasing in AAL. Our findings suggest the importance of diversifying sources of income, creating a market value chain for their product, and strengthening collaboration between the park and the community surrounding the park could reduce the dependence of the community on slash and burn agriculture as well as safeguard the park from degradation and at the same time maintain the livelihood of the community.

Comparison on Vegetation Composition and Structure in Fire Prone Forest of Ilunde and Fire Suppressed Forest of Kitwe in Tanzania

Fire is among the factors influencing survival and development of plants in ecosystems. This study was conducted in frequently burnt and fire suppressed miombo woodlands of Ilunde and Kitwe, respectively. Tree stem density, basal area and composition of plants were determined. The methods used involved recording the numbers of tree stems, diameter at breast height and classifying vegetation to species level. In Kitwe forest, mean stem density of 582.7 ± 52.90 stems ha– was higher than 356.8 ± 38.98 stems ha– which was recorded in Ilunde forest (t = 15.98, df = 29, p < 0.05). Similarly, a higher mean tree basal area of 16.14 ± 1.32 m2 ha– was recorded in Kitwe forest, while 8.54 ± 0.94 m2 ha– being recorded in Ilunde forest (t = 3.34, df = 14, p < 0.05). Czekanowski’s similarity coefficients for trees, shrubs and saplings, and herbs and grasses were 0.46, 0.34 and 0.22, respectively. Fire adapted species were recorded in Ilunde forest. Fire prone miombo woodland had lower tree stem density, basal area and dominated by fire adapted species. Similarity coefficient between the two forests was also low. Prescribed burning is recommended in miombo woodlands for sustainable species composition and tree structure.
 Keywords: vegetation; composition, structure, fire prone, miombo.

EFFECT OF LEAF PHENOLOGY, TOPOGRAPHY AND WIND SPEED ON FOREST CANOPY HEIGHT AND ABOVE GROUND BIOMASS ESTIMATION USING OPTICAL UAV DATA IN MALAWI’S MIOMBO WOODLANDS

The study investigated the effect of tree leaf phenology, topography and wind speed on estimating forest canopy height (FCH) and above ground biomass (AGB) using optical drone data in Miombo Woodlands of Malawi. Data were acquired in 2019 from thirteen plots of Ntchisi Forest Reserve, in two-fold; tree measurements from 0.1ha in-situ plots and airborne RGB ortho-images overlaid on the terrestrial plots from 50 ha boxes. The imagery were acquired by DJI Phantom-4 Unmanned Aerial Vehicle (UAV) at ~7cm pixel resolution. These were processed using Structure-from-Motion photogrammetry algorithm in Agisoft Metashape Professional software. Malawi’s local allometry was used to estimate AGB while the Analysis of Variance was employed to test accuracy. Results reveal that leaf phenology, topography and wind speed significantly (P<0.05) affected estimation of FCH and AGB using the airborne observations. Wind speed contributed highly (53.95% and 55.52%) to the total variation of FCH and AGB, respectively. Furthermore, wind speed upsurge >5m.s-1 (-666.90±27.62%; -64.78±8.47%), topography >15% slope (-114.53±2.92%; -17.07±2.31%) and leaf-off condition (-188.45±25.62%; -27.80±7.98 %) bore higher errors for FCH and AGB, respectively. A significant variation of relationship (R2=0.71; P<0.05) was observed between ground-based height and UAV canopy height. Nevertheless, the variation of the relationship strongly increased by 10% to R2=0.81 when two plots highly affected by the wind speed were excluded from the analysis. Similarly, a significant variation of relationship (R2=0.81; P<0.05) was registered between the ground-based and UAV-based AGB. Correspondingly, a very strong variation of relationship (R2= 0.95; an increase by 14%) was yielded when the two plots highly affected by wind speed were excluded from the analysis. These findings imply that seasonal leaf-fall, slope and wind speed significantly influence the accuracy of FCH and AGB estimations in Miombo Woodlands. Hence, for accurate results, it is a pre-requisite to consider leaf-phenology, topography and wind speed prior to undertaking ground and airborne inventory in the Woodlands.

Trends in elephant poaching in the Mid‐Zambezi Valley, Zimbabwe: Lessons learnt and future outlook

Trends in elephant poaching in the <scp>Mid‐Zambezi</scp> Valley, Zimbabwe: Lessons learnt and future outlook

COMPARISON OF VARIED FOREST INVENTORY METHODS AND OPERATING PROCEDURES FOR ESTIMATING ABOVE-GROUND BIOMASS IN MALAWI’S MIOMBO WOODLANDS

This study assessed forest inventory methods and standard operating procedures (SOPs) for estimating above-ground biomass (AGB) and carbon, as employed in the key REDD+ Miombo Forest Reserves of Malawi. Analysis of Variance statistical technique was applied to investigate the following methods and SOPs: (i) allometry, (ii) sample plot configuration, and (iii) dendrometric measurements. Results indicate that the allometric equations parameter significantly (P&lt;0.001) affected the AGB estimations and was the highest contributor (97.95%) of the total variation. Malawi’s specific allometry provided the highest AGB estimate (113.08±1.56 t/ha). In contrast, the Pan-Tropical/generalized allometric models substantially underestimated AGB within the range of 16.7-67.9%. Furthermore, the findings demonstrate that the use of varied sampling plot sizes significantly (P&lt;0.001) affected the estimates of AGB. However, the plot size parameter contributed only 1.65% to the total variation. The 20m radius plot size registered the highest AGB (75.31±0.77 t/ha) compared to the 17.84m radius plot (66.12±1.61 t/ha). This signifies that the plot size of 17.84m radius underestimated the AGB by 12.2%. However, results on dendrometric measurements showed no significant (P&gt;0.05) differences in the AGB estimates between the use of diameter tape (D-tape) and calliper in measuring dbh of individual trees despite the former yielding higher estimates of AGB (74.65±0.93 t/ha) than the latter (72.53±0.98 t/ha). This demonstrates that the use of calliper in measuring dbh underestimated AGB t/ha by only 2.8% compared to the use of D-tape. Therefore, the study recommends; employment of local allometry, adoption of a circular sampling design of 20m radius, and consistent use of D-tape in measuring dbh for AGB in Malawi’s Miombo Woodlands. In conclusion, incorporation of these changes is envisaged to facilitate quick realisation of Malawi’s REDD+ carbon payments, smooth running of the National Forest Inventory system, robust implementation and global recognition of the REDD+ efforts.

Stump height: a potential escalator of wood volume and carbon removals in miombo woodlands of mainland Tanzania

Stump height: a potential escalator of wood volume and carbon removals in miombo woodlands of mainland Tanzania

Effects, Monitoring and Management of Forest Roads Using Remote Sensing and GIS in Angolan Miombo Woodlands

Angola’s forests are abundant and highly productive with enormous potential to support local needs and exportation. The forests are well distributed across the country, but the existing road network is generally poor and, in some cases, inappropriate. Based on our previous work examining deforestation patterns and the modeling of primary tree attributes of vegetation types, we proposed forest management zones (MZ) for future planning in Huambo province in Angola. Herein, that same framework is applied for the detection of the existing road network in Huambo and the proposal of alternative routes inside the MZ. We used analytic hierarchy process (AHP) and geographic information systems (GIS) to optimize connectivity among the existing forest plantations and their distance to the closest major cities within the province. We developed road suitability maps based on AHP and GIS to ensure safer driving conditions and contribute to the forest planner’s access to the current plantations. According to the suitability map created, 59.51% of the total area is suitable for road development and is counted in classes 4 and 5 in automatic classification. Parameters such as geology, slope, distance from roads to the railway, soil types, elevation, flow accumulation, and aspect were used. We provide a completed assessment of the state of existing roads and evaluate the safety of the observed road sections based on the AHP method. The calculated weights of the factors were all consistent with the model used (consistency ratio was 0.09 &lt; 0.1). Finally, we proposed the best alternative routes to the existing cities, MZ in miombo woodlands, and forest plantations inside the province. Our findings indicated that flow accumulation, soil type, and geology were the most significant factors impacting road construction. Overall, our framework is an important starting point for further research activities towards developing a spatial decision support system (SDSS) for planning road networks in Angola.

Diameter growth of trees in miombo and acacia woodland in an eroded landscape in NE Tanzania

AbstractDiameter increment of trees typical of miombo and acacia woodland was studied during a period of 20 years in Kondoa district, Tanzania. The study was performed in permanent plots in a severely degraded area subjected to considerable restoration efforts. A total of 15 species were selected from a database collected within a project for monitoring the landscape recovery. Growth performance of African woodland species was searched for in the literature for comparison, and a comprehensive list of citations was compiled. We found growth to fall within the range reported in earlier studies, although growth varied both between and within species. There are reports that the radial increments of trees are unimodal over their lifespan, but we found no clear support. In several species, the annual growth increased with stem diameter. Growth during the rainy ENSO year 1997/98 was pairwise compared with the preceding two years and was found to be significantly higher during the wet year, pointing to soil water as a limiting factor. We conclude that free development is an alternative to tree planting on marginal land.

Dependency, Distribution and Diversification (3Ds) of livelihoods in the Miombo woodlands: learning from Tanzania

ABSTRACT The Miombo woodlands that cover around 93% of forested area in Tanzania are central to livelihoods of rural dwellers. Nevertheless, there is paucity of scientific studies and associated knowledge on the dependence, distribution, and diversification aspects of livelihoods in such ecosystems. Our empirical case-based findings indicate the dependence on Miombo woodlands was relatively high contributing 33.8% to total annual household income after tobacco cultivation at 39.6%. As such, forest incomes are vital for rural households living around such ecosystems. Among the poorest groups, forest income contributed to 40% of the total annual income whilst decreasing slightly as wealth increased reaching 32% among the better-off. On issues of livelihood distribution, forest incomes played a role in equalizing income distribution with a Gini change of about 0.05, however, it was tobacco cultivation that was more responsible for lowering the gap between income inequality levels with a Gini change of 0.08. In terms of diversification, rural households displayed a high level of diversity of livelihood options at a diversity index of 0.7 and forests were a diversification option. These findings contribute a policy lesson that reduced access to the miombo woodlands through exclusionary conservation mechanisms would result in considerable negative impacts on rural households’ welfare and exacerbate income differentiation in the area.

Modelling Aboveground Biomass of Miombo Woodlands in Niassa Special Reserve, Northern Mozambique

Aboveground biomass (AGB) estimation plays a crucial role in forest management and carbon emission reporting, especially for developing countries wishing to address REDD+ projects. Both passive and active remote-sensing technologies can provide spatially explicit information of AGB by using a limited number of field samples, thus reducing the substantial budgetary cost of field inventories. The aim of the current study was to estimate AGB in the Niassa Special Reserve (NSR) using fusion of optical (Landsat 8/OLI and Sentinel 2A/MSI) and radar (Sentinel 1B and ALOS/PALSAR-2) data. The performance of multiple linear regression models to relate ground biomass with different combinations of sensor data was assessed using root-mean-square error (RMSE), and the Akaike and Bayesian information criteria (AIC and BIC). The mean AGB and carbon stock (CS) estimated from field data were estimated at 56 Mg ha−1 (ranging from 11 to 95 Mg ha−1) and 28 MgC ha−1, respectively. The best model estimated AGB at 63 ± 20.3 Mg ha−1 for NSR, ranging from 0.6 to 200 Mg ha−1 (r2 = 87.5%, AIC = 123, and BIC = 51.93). We obtained an RMSE % of 20.46 of the mean field estimate of 56 Mg ha−1. The estimation of AGB in this study was within the range that was reported in the existing literature for the miombo woodlands. The fusion of vegetation indices derived from Landsat/OLI and Sentinel 2A/MSI, and backscatter from ALOS/PALSAR-2 is a good predictor of AGB.

Excessive livestock grazing overrides the positive effects of trees on infiltration capacity and modifies preferential flow in dry miombo woodlands

AbstractThe increase in livestock grazing in African drylands such as miombo woodlands threatens land productivity and ecosystem functioning. Trees have positive effects on soil hydraulic properties, but few studies have looked at grazing intensity and hydrological functioning in different land uses. Therefore, we conducted a biophysical survey in Morogoro Rural District, Tanzania, where we identified four main land uses and land cover types, that is, Forest reserve, open‐access forest, cropland under fallow, and active cropland. We assessed grazing intensity, measured infiltration capacity, and conducted dye tracer experiments to assess the degree of preferential flow in 64 plots. We also tested the effect of grazing exclusion on infiltration capacity in 12‐year‐old fenced plots. Our results show that irrespective of land use or cover type, soil bulk density increased by 10% from low to high grazing intensity, whereas infiltration capacity and soil organic carbon decreased by 55% and 28%, respectively. We found a positive relationship between infiltration capacity and tree basal area in plots with lowest grazing intensities. However, at higher grazing, the infiltration capacity remained low independently of the basal area. Preferential flow in deeper soils was six‐times higher in areas with no grazing, indicating higher deep soil and groundwater recharge potential at low grazing intensities. We conclude that the negative impacts on soil hydrological functioning of excessive livestock grazing override the positive effect of trees, but restricting grazing can reverse the impact.

Hybridization boosts dispersal of two contrasted ecotypes in a grass species.

Genetic exchanges between closely related groups of organisms with different adaptations have well-documented beneficial and detrimental consequences. In plants, pollen-mediated exchanges affect the sorting of alleles across physical landscapes and influence rates of hybridization. How these dynamics affect the emergence and spread of novel phenotypes remains only partially understood. Here, we use phylogenomics and population genomics to retrace the origin and spread of two geographically overlapping ecotypes of the African grass Alloteropsis angusta. In addition to an ecotype inhabiting wetlands, we report the existence of a previously undescribed ecotype inhabiting Miombo woodlands and grasslands. The two ecotypes are consistently associated with different nuclear groups, which represent an advanced stage of divergence with secondary low-level gene flow. However, the seed-transported chloroplast genomes are consistently shared by distinct ecotypes inhabiting the same region. These patterns suggest that the nuclear genome of one ecotype can enter the seeds of the other via occasional pollen movements with sorting of nuclear groups in subsequent generations. The contrasting ecotypes of A. angusta can thus use each other as a gateway to new locations across a large part of Africa, showing that hybridization can facilitate the geographical dispersal of distinct ecotypes of the same grass species.

Place-Based Analysis of Satellite Time Series Shows Opposing Land Change Patterns in the Copperbelt Region of Zambia

The process of land degradation needs to be understood at various spatial and temporal scales in order to protect ecosystem services and communities directly dependent on it. This is especially true for regions in sub-Saharan Africa, where socio economic and political factors exacerbate ecological degradation. This study identifies spatially explicit land change dynamics in the Copperbelt province of Zambia in a local context using satellite vegetation index time series derived from the MODIS sensor. Three sets of parameters, namely, monthly series, annual peaking magnitude, and annual mean growing season were developed for the period 2000 to 2019. Trend was estimated by applying harmonic regression on monthly series and linear least square regression on annually aggregated series. Estimated spatial trends were further used as a basis to map endemic land change processes. Our observations were as follows: (a) 15% of the study area dominant in the east showed positive trends, (b) 3% of the study area dominant in the west showed negative trends, (c) natural regeneration in mosaic landscapes (post shifting cultivation) and land management in forest reserves were chiefly responsible for positive trends, and (d) degradation over intact miombo woodland and cultivation areas contributed to negative trends. Additionally, lower productivity over areas with semi-permanent agriculture and shift of new encroachment into woodlands from east to west of Copperbelt was observed. Pivot agriculture was not a main driver in land change. Although overall greening trends prevailed across the study site, the risk of intact woodlands being exposed to various disturbances remains high. The outcome of this study can provide insights about natural and assisted landscape restoration specifically addressing the miombo ecoregion.

Marula (Sclerocarya birrea subsp. caffra, Anacardiaceae) thrives under climate change in sub‐Saharan Africa

AbstractClimate change threatens the persistence of some plant species, especially those highly adapted to their microclimates. The aim of the study was to determine the current suitable habitat of marula (Sclerocarya birrea subsp. caffra) and to forecast the habitat under different climate change scenarios. Predictions were made in Maxent using 490 occurrence records, four representative concentration pathways (RCPs) and three general circulation models (GCMs). Variables used were altitude, soil characteristics, monthly precipitation, monthly minimum and maximum temperatures and 19 bioclimatic variables. The current suitable habitat of marula largely occurs in mopane and dry miombo woodlands of southern Africa, including Madagascar. Permutation importance test showed that precipitation in November (30.1%), temperature seasonality (22.1%) and mean temperature of wettest quarter (14.3%) contributed significantly to the model of the current suitable habitat. When forecasted, the suitable habitat expanded under all GCMs and RCPs. On average in 2050, the range expanded by 26.0% (RCP2.6), 33.8% (RCP4.5), 24.8% (RCP6.0) and 42.3% (RCP8.5), while in 2070, it expanded by 30.0% (RCP2.6), 39.9% (RCP4.5), 33.3% (RCP6.0) and 45.1% (RCP8.5). The subspecies is not directly threatened by climate change, but indirect threats remain uncertain.

Termites Distribution and Diversity in Different Land Uses in Mozambique: Implications for Management

Termites play an important ecological role in ecosystems, mainly as decomposers. However, some species under certain conditions may become pests, causing damage in forests and cultivated fields. Termites are associated with native forests, forest plantations and croplands. Despite this, information regarding taxonomy, management, economic and ecological termite impacts for these land uses categories is not widely known. This study aimed to assess termite’s distribution, incidence, damage, diversity, and affinity in different land use categories. In circular 0.28ha plots in native vegetation and croplands and 1ha rectangular plots in forest plantations, termites capture was performed and, tree infestation assessed by visual inspection. Plot allocation was random-stratified by land use category. Twenty-one termite species, from nine genera and two families (Termitidae and Rhinotermitidae) were found. Of these species, fourteen, thirteen, ten and nine were respectively associated with miombo woodlands, fallow, cultivated areas and forest plantations, suggesting that species richness decreases with increasing habitat disturbance. Termite incidence is highest in plantation forests, followed by native woodlands, fallow and croplands. In forests, fallow areas, and croplands, damage severity was low, while in forest plantations it ranged from low to moderate. These results suggest that in miombo woodlands, fallow areas, and croplands, termite incidence does not necessarily imply economic damage. Economic losses in <i>Eucalyptus</i> plantations reach up to US$ 542.13/ha, reducing with increased plantation age, reaching 1.77 m³/ha in plantations two years old or less, and 0.73 m³/ha in 6-year age plantations. Efforts to combat termites are needed at early plantation stages.

Assessment of Land Cover Changes in Litumbandyosi-Gesimasowa Game Reserve using Remote Sensing and GIS

As countries in Sub-Saharan Africa strive to reduce deforestation in Miombo woodlands, it is essential to use the appropriate, reliable, and cost-effective tools for assessing land cover changes. This study employed Remote Sensing and GIS techniques to assess land use and its changes in the Litumbandyosi-Gesimasowa Game Reserve between 1990 and 2020. The tools employed were GEE and Collect Earth. The study employed Sentinel-2 and Landsat-5 TM imagery and also incorporated the Atmospheric Resistant Vegetation Index (ARVI) for improving classification by overcoming the effects of Non-Photosynthetic Vegetation (NPV) and phenology. The study produced highly accurate land cover maps, with an overall accuracy of 99.53% and a kappa coefficient of 98.11% in 1990, 99.84% and a kappa coefficient of 98.69% in 2011, and 92.10% and an 89.62% kappa coefficient in 2020. The findings of the post-classification revealed an alarming change in land cover over the last 30 years, with heavy forestland decreasing by 10.77%, shrubland increasing by 12.19%, and grassland increasing by 13.35%. Furthermore, farmland expanded by 4.58%, barren land grew by 5.82%, and wetlands grew by 0.74%. Significant agents of change have been identified as forest fires, overgrazing, crop farming, and mining.

Effects of Firewood Extraction on Miombo Woodlands in Zimbabwe: The Case of Hwedza Communal Area

Effects of Firewood Extraction on Miombo Woodlands in Zimbabwe: The Case of Hwedza Communal Area

Regeneration and Restoration Status of Miombo Woodland Following Land Use Land Cover Changes at the Buffer Zone of Gile National Park's Central Mozambique

Regeneration and Restoration Status of Miombo Woodland Following Land Use Land Cover Changes at the Buffer Zone of Gile National Park's Central Mozambique

On the Potential of Sequential and Nonsequential Regression Models for Sentinel-1-Based Biomass Prediction in Tanzanian Miombo Forests

This study derives regression models for above-ground biomass (AGB) estimation in miombo woodlands of Tanzania that utilise the high availability and low cost of Sentinel-1 data. The limited forest canopy penetration of C-band SAR sensors along with the sparseness of available ground truth restrict their usefulness in traditional AGB regression models. Therefore, we propose to use AGB predictions based on airborne laser scanning (ALS) data as a surrogate response variable for SAR data. This dramatically increases the available training data and opens for flexible regression models that capture fine-scale AGB dynamics. This becomes a sequential modelling approach, where the first regression stage has linked in situ data to ALS data and produced the AGB prediction map; We perform the subsequent stage, where this map is related to Sentinel-1 data. We develop a traditional, parametric regression model and alternative non-parametric models for this stage. The latter uses a conditional generative adversarial network (cGAN) to translate Sentinel-1 images into ALS-based AGB prediction maps. The convolution filters in the neural networks make them contextual. We compare the sequential models to traditional, non-sequential regression models, all trained on limited AGB ground reference data. Results show that our newly proposed non-sequential Sentinel-1-based regression model performs better quantitatively than the sequential models, but achieves less sensitivity to fine-scale AGB dynamics. The contextual cGAN-based sequential models best reproduce the distribution of ALS-based AGB predictions. They also reach a lower RMSE against in situ AGB data than the parametric sequential model, indicating a potential for further development.

Impacts of Diffuse Land Use on Plant Diversity Patterns in the Miombo Woodlands of Western Zambia

Impacts of Diffuse Land Use on Plant Diversity Patterns in the Miombo Woodlands of Western Zambia