Land Use Management Practices Research Articles

Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

Shift in microbial biomass, soil and microbial stoichiometry in different land uses of Northeast India

The change in soil microbial biomass and stoichiometry in different land uses of Northeast India were assessed by using the fumigation extraction method. The pattern of microbial biomass C, N, and P followed the sequence of forest (650.36, 62.86 and 254.54μgg−1) > grassland (62.86, 39.30 and 31.76 μgg−1> cropland (31.84,18.62 and 15.54 μgg−1), and exhibits seasonality with the lowest concentrations during the winter season across all land uses. The maximum concentrations were recorded during the rainy season in the forest and the summer season in both grassland and cropland. Microbial ratios (C: N, C: P and N: P) and proportions of microbial biomass to total soil nutrients vary with a variance in land use types. Soil microbial biomass exhibited a positive significant relation with soil nutrients but negatively related with soil temperature and moisture in all the study sites. Two-way ANOVA of soil microbial biomass exhibits significant differences due to seasons and land use types (p< 0.01). The microbial stoichiometry of the present study indicates N limitations in the study sites, while the proportion of microbial nutrients to total soil nutrients reveals nutrient mineralization in the forest and immobilization and competition in grassland and cropland. Furthermore, this study indicates that landuse and soil management practices interfere with microbial stoichiometry and nutrient release and immobilization patterns. Improving the retention of organic matter in ecosystems may enhance microbial activity and soil health.

Carbon Sequestration Dynamics in Peri-Urban Forests: Comparing Secondary Succession and Mature Stands under Varied Forest Management Practices

This study examines the impact of silvicultural and land-use management practices on carbon sequestration in peri-urban forest ecosystems, with a particular focus on human-induced carbon dynamics. The study area’s complex profile spans from a compact native forest to varying degrees of fragmentation. This included areas undergoing secondary succession forest without silvicultural interventions (No-SI) alongside sites subjected to high-intensity (High-SI) and low-intensity silvicultural interventions (Low-SI). The research assessed carbon stocks and sequestration in different carbon pools (living biomass, dead organic matter and soil) using field data, allometric equations and laboratory analysis. Findings reveal a significant correlation between the intensity of anthropogenic interventions and variations in carbon stocks. The CASMOFOR model facilitated the reconstruction of carbon stock and carbon-stock change dynamics over four decades (1980–2022), showing disparities in carbon storage capabilities linked to the structural characteristics of the sites. The Low-SI site had the highest carbon stock in all carbon pools (378 tonnes C ha−1), which is more than double compared to High-SI (161 tonnes C ha−1) or No-SI sites (134 tonnes C ha−1). However, the secondary succession forest (No-SI) demonstrated the highest annual carbon stock change (4.4 tonnes C ha−1 year−1), two times higher than the Low-SI mature stand (2.2 tonnes C ha−1 year−1), emphasising the resilience of forest ecosystems to recover and sustain carbon sequestration capacities after harvesting if forest land use remains unchanged. The study underscores the significant importance of anthropogenic interventions on carbon dynamics, especially for living tree biomass, which has consequences in enhancing carbon sequestration and contributing to emission reduction targets.

A Study of the Influence of the Type of Land Use on the Enzymatic Activity of Soils in Southwestern China

Although soil enzyme activity can act as an effective indicator of soil nutrient status, there is some uncertainty about its accuracy within soil depth across different land uses. To assess the effects of different land uses on the interactions between soil enzyme activity and nutrient status within different soil horizons, in this study we examined soil total carbon (C), nitrogen (N), and phosphorus (P) concentrations, pH, and the activities of five hydrolytic (i.e., amylase, invertase, cellulase, acid phosphatase, and urease) and three oxidative enzymes (i.e., catalase, dehydrogenase, and phenol oxidase) involved in C, N, and P acquisition and evaluated their interactions within the topsoil (0–10 cm), subsoil (10–20 cm), and deeper soil layer (20–30 cm) under various land uses (i.e., rice field, cultivated land, bamboo plantation, forest land, and barren land). We found that the levels of hydrolytic enzyme activities and nutrient concentrations were higher in the topsoil than the deeper layer. The hydrolytic enzyme activities were positive correlated with soil C, N, and P concentrations, while the activities of oxidative enzymes showed strong associations with soil pH. Furthermore, the results of fuzzy comprehensive evaluation models suggest that the overall enzyme activity can serve as an indicator of soil nutrient status in the topsoil and subsoil, but not in the deeper layer. The depth-specific nature of soil enzyme–nutrient relationships may be attributed to different land-use management practices. Our study highlights the complex interactions between soil nutrients, pH, and enzyme activities within soil profiles, and soil enzyme activity as an indicator of soil nutrient status is depth-dependent across the different land uses. The specific functional groups of enzymes and the gradients of resources and environmental conditions within the soil profile that is partly mediated by land use play crucial roles in shaping these relationships. Our results can also provide some new insights into sustainable soil management practices under the background of intense anthropogenic activities and global change.

Improving soil fertility through dual inoculation with arbuscular mycorrhizal fungi and Rhizobium on a eutric cambisol cultivated with forage legumes in a semi-arid region

The Sub-Saharan region of southern Africa is characterized by high temperatures, low rainfall, and poor land-use management practices such as continuous cropping without replenishment of soil nutrients. The combination of these factors has resulted in nutrient depletion and land degradation. The current study aimed at investigating the effect of arbuscular mycorrhizal fungi (AMF) and Rhizobium bacteria inoculation on soil chemical properties in field-grown forage legumes, namely, Mucuna pruriens (mucuna), Lablab purpureus (lablab) and Vigna unguiculata (cowpea), in the semi-arid region of the Eastern Cape Province (South Africa). Forage legumes were inoculated with the AMF species Paraglomus occulum and the Rhizobia bacteria species Bradyrhizobium strain and grown for 120 days. Soil samples were collected in the following sequence: prior to planting, before flowering and after harvesting the forage legumes in each of the two seasons (2017/2018 and 2018/2019) and soil chemical properties were determined using standard procedures. The results showed that the addition of dual inoculation over time greatly improved soil chemical properties when compared to the control treatment. This was advocated by the significant (P ≤ 0.05) increase in soil pH, soil organic carbon, soil organic matter, total nitrogen, phosphorus, calcium, potassium, magnesium, sodium, sulfur and iron in soils. The concentration of cation exchange capacity was significantly (P ≤ 0.05) higher in cowpea treated with Rhizobium as compared to other treatment combinations. The control treatment of mucuna forage greatly improved the concentrations of manganese, boron, copper, molybdenum, and zinc over other treatment combinations only before the flowering stage. However, the concentrations of micronutrients were significantly higher on the treatment combination of lablab and single inoculation of AMF after harvesting. Generally, dual inoculation with AMF and Rhizobia enhanced soil properties when compared to a single inoculation or untreated control.

Selective abiotic and biotic stressors influence the acdS gene abundance in the rhizospheric soil of pineapple plants in Lampung, Indonesia

Indonesia has faced extensive poor soil quality and health for years.Anthropogenic, climatic, and plant pathogenic activities are the major contributing factors that degrade the soil's essential life-supporting system, such as the functional gene pool. One such gene is the rhizobacterial acdS, which codes for synthesizing the ACC (1-aminocyclopropane-1-carboxylate) deaminase that cleaves ACC as an ethylene hormone precursor in the stressed plant growing under stressful conditions. This study aims to investigate the abundance of the acdS gene in different abiotic and biotic stressors of the rhizospheric soil of pineapple plantation area that has been exposed incidentally to herbicides, flooding, and pathogenic Phytophthora spp infections. Soil samples were collected by using simple randomized sampling. A quantitative real-time polymerase chain reaction (qPCR)-based method was applied to assess the gene abundance. This study reveals that the abundance of acdS in the rhizospheric soil of herbicide-treated and Phytophthora-infected symptomatic plants is relatively lower than that of non-treated ones. The highest abundance was found in the Phytophthora-infected soil of asymptomatic plants. However, there was no significant difference in abundance between the fflooded rhizospheric soil TO rhizospheric soil of flooded-exposed plants and the non-exposed ones. Hopefully, this data will help us better understand proper land-use management practices for pineapple plants.

Carbon Distribution Characteristics and Sequestration Potential of Various Land-Use Types in a Stony Soil Zone of the Arid Mountainous Regions on the Eastern Tibetan Plateau

In arid mountainous areas with stony soils in the Eastern Tibetan Plateau, intensively managed orchards (which include the need for plowing, irrigation, and soil stone removal), eco-forests, and grasslands, all converted from croplands, are becoming increasingly popular. We randomly collected soil samples at 0–15, 15–30, 30–45, and 45–60 cm depths from the four land-use types on the northern and southern slopes in the region. Differences in soil organic carbon (SOC) content/stock, soil water content (SWC), and rock fragment content (RFC) in land-use types and slopes were analyzed using two-way ANOVA. The factors’ contributions to SOC variation were assessed using mixed-effect models. Results showed the following: (1) In topsoil (0–30 cm), SOC contents followed the order eco-forest &gt; orchard &gt; grassland ≈ cropland; in subsoil (30–60 cm), the order was orchard &gt; eco-forest &gt; cropland ≈ grassland. SOC stocks (0–60 cm) were higher in orchards (93.72 Mg ha−1) and eco-forests (92.44 Mg ha−1) than in grasslands (53.65 Mg ha−1) and croplands (53.05 Mg ha−1). Contributions of SOC stocks at the 0–15 cm depth level to total SOC were above 40% for GL and EF and between 27 and 35% for OL and CL; at the 45–60 cm level, OL contributed 16–20% and was higher than 10–15% for the other land-use types. (2) Eco-forests and grasslands showed increased SOC contents/stocks at all soil layers on the northern slope than on the southern one. Orchards and croplands, however, showed no differences in contents between slopes. (3) Land-use types, TN, SWC, RFC, slope aspect, and management practices significantly affected SOC variation. Our results suggest that forest plantations (orchards and eco-forests) in arid mountainous regions, through active management practices (e.g., irrigation and fertilization), are vital for improving soil carbon sinks and achieving peak carbon/carbon neutrality goals.

Linking forest management to surrounding lands: a citizen-based approach towards the regional understanding of land-use transitions

The Southeastern United States has high landscape heterogeneity, with heavily managed forestlands, developed agriculture, and multiple metropolitan areas. The spatial pattern of land use is dynamic. Expansion of urban areas convert forested and agricultural land, scrub forests are converted to citrus groves, and some croplands transition to pine plantations. Previous studies have recognized that forest management is the predominant factor in structural and functional changes forests, but little is known about how forest management practices interact with surrounding land uses at the regional scale. The first step in studying the spatial relationships of forest management with surrounding landscapes is to be able to map management practices and describe their proximity to various land uses. There are two major difficulties in generating land use and land management maps at the regional scale by any method: the necessity of large training data sets and expensive computation. The combination of crowdsourced, citizen-science mapping and cloud-based computing may help overcome those difficulties. In this study, OpenStreetMap is incorporated into mapping land use and shows great potential for justifying and monitoring land use at a regional scale. Google Earth Engine enables large-scale spatial analysis and imagery processing by providing a variety of Earth observation datasets and computational resources. By incorporating the OpenStreetMap dataset into Earth observation images to map forest land management practices and determine the distribution of other nearby land uses, we develop a robust regional land-use mapping approach and describe the patterns of how different land uses may affect forest management and vice versa. We find that cropland is more likely to be near ecological forest management patches; few close spatial relationships exist between land uses and preservation forest management, which fulfills the preservation management strategy of sustaining the forests, and production forests have the strongest spatial relationships with croplands. This approach leads to increased understanding of land-use patterns and management practices at local to regional scales.

The integration of nature conservation in land-use management practices in rural municipalities: A case study of four rural municipalities in Norway

This paper investigates how land-use management practices incorporate nature conservation concerns in four Norwegian rural municipalities. It focuses on nature conservation, which is vital both to maintain nature’s ability to store carbon and to preserve ecosystems, as key aspects of the environmental dimension of sustainable development. The paper analyses the perceptions of local, regional and state stakeholders relating to four rural municipalities following diverging land-use trajectories. We find land policy in all four cases to be highly entangled with strategies to achieve growth in terms of income, job creation and population. When nature conservation was not in line with wider economic or social considerations, it was less integrated into land-policy practices. In three of the municipalities, the construction of residential units, holiday-homes or renewable energy parks was prioritized over the preservation of nature areas or cultural landscapes. One case presented a contrasting trajectory, as it involved a clear alignment between nature conservation and economic growth. Here, conservation was considered a key strategy to both sustain the traditional fishery industry and to accommodate the growing tourism. However, while this municipality’s restrictive land use was based on a nature conservation understanding, it was also connected to the greenhouse-gas emissions, resource exhaustion and waste generation traditionally associated with international tourism. The study concludes by highlighting the importance of rural municipalities being equipped with sufficient resources if they are to prioritize environmental concerns over the economic and social dimensions of sustainability in their land-use management practices.

Difficult times for amphibians: Effects of land-use change at the local and landscape scales in the Iberá Wetlands

Land-use change and management practices have led to habitat loss, one of the greatest factors in biodiversity decline. Particularly, amphibians comprise the highest number of threatened vertebrate species at the global scale. In this work, amphibian communities were analysed in three differing landscapes: a protected wetland, a livestock-impaired rangeland and a pine afforestation. In each landscape, amphibian species were sampled. Land-cover type and composition, as well as primary vegetation types were characterised at the landscape and local scale, respectively. The relationship between these environmental variables and the amphibian communities was analysed. Twenty-one amphibian species were identified; the protected and afforested landscapes were the richest, whereas the rangeland showed the lowest species richness and diversity estimates. At the local scale, vegetation, water coverage and land-use category explained the higher presence of amphibian species and their abundance. These results show how different land-uses, especially livestock farming, modify the composition of amphibian communities. This work constitutes a foundation for the development of sustainable management practices for conserving amphibians in landscape-level altered habitats.

A Data-Driven Approach for Building the Profile of Water Storage Capacity of Soils

The soil water storage capacity is critical for soil management as it drives crop production, soil carbon sequestration, and soil quality and health. It depends on soil textural class, depth, land-use and soil management practices; therefore, the complexity strongly limits its estimation on a large scale with conventional-process-based approaches. In this paper, a machine learning approach is proposed to build the profile of the soil water storage capacity. A neural network is designed to estimate the soil moisture from the meteorology data input. By taking the soil moisture as a proxy in the modelling, the training captures those impact factors of soil water storage capacity and their nonlinear interaction implicitly without knowing the underlying soil hydrologic processes. An internal vector of the proposed neural network assimilates the soil moisture response to meteorological conditions and is regulated as the profile of the soil water storage capacity. The proposed approach is data-driven. Since the low-cost soil moisture sensors have made soil moisture monitoring simple and the meteorology data are easy to obtain, the proposed approach enables a convenient way of estimating soil water storage capacity in a high sampling resolution and at a large scale. Moreover, an average root mean squared deviation at 0.0307m3/m3 can be achieved in the soil moisture estimation; hence, the trained model can be deployed as an alternative to the expensive sensor networks for continuous soil moisture monitoring. The proposed approach innovatively represents the soil water storage capacity as a vector profile rather than a single value indicator. Compared with the single value indicator, which is common in hydrology, a multidimensional vector can encode more information and thus has a more powerful representation. This can be seen in the anomaly detection demonstrated in the paper, where subtle differences in soil water storage capacity among the sensor sites can be captured even though these sensors are installed on the same grassland. Another merit of vector representation is that advanced numeric methods can be applied to soil analysis. This paper demonstrates such an advantage by clustering sensor sites into groups with the unsupervised K-means clustering on the profile vectors which encapsulate soil characteristics and land properties of each sensor site implicitly.

Soil microbiome dynamics associated with conversion of tropical forests to different rubber based land use management systems

The biogeochemical cycles, carbon sequestration, and climate change all are significantly influenced by tropical rainforests, which is one of the world's most productive ecosystems and hotspots for biodiversity. Plantation crops like Rubber (Hevea brasiliensis) have displaced significant forest cover in the Asia pacific in the last two centuries due to their increasing demand. As a case study, we examined the soils of native forest (NF), rubber monoculture (RP) and three different managements i.e., cover crop (CC), weed crop (WC) and inter crop (IC) to understand the changes in microbial community structure across each practice and to estimate the influence of forest conversion to rubber monoculture on the soil microbiome. Soils were collected using nested sampling pattern and subjected to physiochemical characterization and whole metagenome sequencing. Results revealed that bacteria (60.56 M reads) predominated all land use types, followed by eukaryotes (0.52 M reads) and archaea (0.72 M reads). NF exhibited significantly higher bacterial richness and diversity then other land-use type. Interestingly, total functional diversity as well as genes associated with chemotaxis, flagellar assembly, and secretion systems were significantly higher in other land-use systems as compared to NF. Altogether, the results from this study indicate that the three different land use types used here like CC, IC, and WC has high abundance of functional diversity and biological profile compared to NF and RP. The study suggests that the adoption of aforementioned land-use management practices could play a significant role in fostering sustainable plantations in the tropics.

Modeling of Gully Erosion in Ethiopia as Influenced by Changes in Rainfall and Land Use Management Practices

Gully erosion is one of the most extreme land degradation processes that exhibit spatial and temporal variation depending on topography, soil, climate, and land use and management characteristics. This study investigated the impact of changes in rainfall, land use/land cover (LULC), and land use management (LUM) practices on gully erosion in two midland watersheds (treated Kecha and untreated Laguna) in the Upper Blue Nile basin of Ethiopia by using the LANDPLANER model in combination with intensive field measurements and remote sensing products. We simulated gully erosion under past (in 2005), present (in 2021), and three potential future curve number conditions, each time under four rainfall scenarios (10, 30, 60, and 100 mm) using the dynamic erosion index (e), static topographic (esp), and erosion channel (esp_channel) thresholds. Density plot analyses showed that gullies frequently occur in low-lying gentle slope areas with relatively higher curve number values. The best predictions of gullies identified through true positive rates (TPR) and true negative rates (TNR) were achieved considering the static esp_channel &gt; 1 for Kecha (TPR = 0.667 and TNR = 0.544) and the dynamic e &gt; 0.1 for 60 mm of rainfall in Laguna (TPR = 0.769 and TNR = 0.516). Despite the 10 mm rainfall having negligible erosion-triggering potential in both watersheds, the 60 and 100 mm rainfall scenarios were 4–5 and 10–17 times, respectively, higher than the 30 mm rainfall scenario. While the LULC change in the untreated Laguna watershed increased the impact of rainfall on gully initiation by only 0–2% between 2005 and 2021, the combination of LULC and LUM significantly reduced the impact of rainfall in the treated Kecha watershed by 64–79%. Similarly, the gully initiation area in Kecha was reduced by 28% (from 33% in 2005 to 5% in 2021) due to changes in LULC and LUM practices, whereas Laguna showed little increment by only 1% (from 42% in 2005 to 43% in 2021) due to LULC change. In addition, the future predicted alternative land use planning options showed that gully initiation areas in Laguna could be reduced by 1% with only LULC conversion; 39% when only LUM practices were implemented; and 37% when both were combined. These results indicate that LUM practices outweigh the impact of LULC on gully erosion in the studied paired watersheds. Overall, LANDPLANER successfully simulated the spatio-temporal variation of gully erosion with scenario-based analyses and hence can be used to predict gullies in the study area and other data-scarce regions with similar agro-ecological settings.

Potential for Peatland Water Table Depth Monitoring Using Sentinel-1 SAR Backscatter: Case Study of Forsinard Flows, Scotland, UK

Peatland restoration has become a common land-use management practice in recent years, with the water table depth (WTD) being one of the key monitoring elements, where it is used as a proxy for various ecosystem functions. Regular, uninterrupted, and spatially representative WTD data in situ can be difficult to collect, and therefore, remotely sensed data offer an attractive alternative for landscape-scale monitoring. In this study, we illustrate the application of Sentinel-1 SAR backscatter for water table depth monitoring in near-natural and restored blanket bogs in the Flow Country of northern Scotland. Among the study sites, the near-natural peatlands presented the smallest fluctuations in the WTD (with depths typically between 0 and 15 cm) and had the most stable radar signal throughout the year (~3 to 4 dB amplitude). Previously drained and afforested peatlands undergoing restoration management were found to have higher WTD fluctuations (depths up to 35 cm), which were also reflected in higher shifts in the radar backscatter (up to a ~6 dB difference within a year). Sites where more advanced restoration methods have been applied, however, were associated with shallower water table depths and smoother surfaces. Three models—simple linear regression, multiple linear regression, and the random forest model—were evaluated for their potential to predict water table dynamics in peatlands using Sentinel-1 SAR backscatter. The random forest model was found to be the most suited, with the highest correlation scores, lowest RMSE values, and overall good temporal fit (R2 = 0.66, RMSE = 2.1 cm), and multiple linear regression came in a close second (R2 = 0.59, RMSE = 4.5 cm). The impact of standing water, terrain ruggedness, and the ridge and furrow aspect on the model correlation scores was tested but found not to have a statistically significant influence. We propose that this approach, using Sentinel-1 and random forest models to predict the WTD, has strong potential and should be tested in a wider range of peatland sites.

Impact of land-use systems on fertility parameters and deterioration indices of soil in the sub humid Southern Plains of Rajasthan, India

Aim: This investigation was carried out to appraise the effect of different prevailing land-use systems (LUSs) on nutrient status along with deterioration indices of soil under sub-humid Southern Plains of Rajasthan. Methodology: Six dominant land-use systems: barren, agricultural, agri-horticulture, horticultural, grass, and natural forest were selected in the sub-humid Southern Plains of Rajasthan. A total of 120 composite soil samples [6-LUSs, 4- soil depths (0-20, 20-40, 40-60, and 60-80 cm), and five replications] were collected for laboratory analysis. The two-way analysis of variance was used to test the effect of different LUSs and soil depths on available nutrients, essential properties with deterioration indices of soil. Results: The results of the study showed that soil organic carbon (SOC), DTPA extractable Zn, Mn, available nitrogen, and CEC are the most degraded soil fertility parameters under studied LUSs. Barren land-use has led to the highest decline in Zn (͌75%), SOC (71%), N (66%), Cu (62%) and Fe (57%), followed by Agricultural land-use that has led to a decline in SOC (53%), Zn (46%), N (43%) and Mn (38%). The use of soil deterioration indices revealed that soils deteriorated slightly under grassland and horticultural LUSs (-11.05 and -11.81 %). However, moderate deterioration was observed in the agri-horticulture land-use soil (-22.51 %) while severe (-28.11%) and extremely severe deterioration (-47.50%) occurred under agricultural and barren LUSs, respectively. Interpretation: The result of this study implies that consistent cultivation without appropriate land-use management practices in the cultivated LUS aggravates the deterioration of soil organic carbon and essential soil fertility parameters. These results suggested that restoration of barren and agricultural lands into horticultural, agri-horticulture, and grassland-uses consequently decreased soil disturbance which could be an effective strategy for improving or maintaining the soil quality and sustainability in the study area. Key words: Deterioration indices, Land-use system, Soil depth, Soil nutrients

Effects of Land-Use Dynamics on Soil Organic Carbon and Total Nitrogen Stock, Western Ethiopia

Soil organic carbon (SOC) and total nitrogen (TN) stock are key indicators of soil quality in tropical regions; however, their status is often degraded, especially due to massive deforestation in natural forest areas associated with extensive agricultural land use. The aim of this study was to investigate the dynamics of SOC and TN stock in different land-use systems in the Abobo woreda, Western Ethiopia. To analyze their status, 80 disturbed (composite) and 45 undisturbed soil samples were collected from the top 20 cm of soil in five major land-use types: natural forestlands, grasslands, recently developed commercial farmlands, old commercial farmlands, and small-scale cultivated lands. The results showed that SOC stock varied significantly across the different land-use types, with mean stock ranging from 32.23 Mg·ha−1 in recently developed commercial farmlands to 54.54 Mg·ha−1 in natural forestlands. The mean TN stock ranged from 2.54 Mg·ha−1 in recently developed commercial farmlands to 4.63 Mg·ha−1 in natural forestlands. With natural forestlands as a baseline and the duration ranging in age from 15 to 45 years since land-use conversion, the mean annual absolute rates of change in SOC and TN stock loss were 0.49, 1.49, 0.39, and 0.45 Mg·ha−1·yr−1 and 0.05, 0.14, 0.03, and 0.04 Mg·ha−1·yr−1 for grasslands, recently developed commercial farmlands, old commercial farmlands, and small-scale cultivated lands, respectively. The results of this study revealed that soil disturbance during forestland conversion to tillage enhanced the decomposition rate of organic matter in recently developed commercial farmlands. Nevertheless, after agricultural abandonment and vegetation restoration, the SOC and TN stock capacities were enriched in the old commercial farmlands. It is, therefore, important to effectively restore vegetation and implement sustainable land-use management practices.

Fire management in Ethiopia: past, present and future

Human pressure and intensified drought have seen Ethiopia recurrently affected by severe wildfire emergencies since 2019. This article reviews the history, causes and impacts of wildfires in Ethiopia, identifies gaps, and discusses plans for improving fire management using an integrated approach at national, subnational and community levels. Not having a national wildfire management strategy undermines Ethiopia’s capacity for forecasting, preventing and suppressing wildfire, and fire management must be an integral part of land-use management policies and practices. These must consider cultural values, socioeconomic realities and ecological differences where fires occur, including rangelands, dry forests and woodlands, and requires multi-level governance and devolution of responsibility and increased support for local decision-making.

Impact, adaptation, and mitigation of climate change in Indian agriculture.

Climate change poses serious risks to Indian agriculture as half of the agricultural land of the country is rainfed. Climate change affects crop yield, soil processes, water availability, and pest dynamics. Several adaptation strategies such as heat- and water stress-tolerant crop varieties, stress-tolerant new crops, improved agronomic management practices, improved water use efficiency, conservation agriculture practices and improved pest management, improved weather forecasts, and other climate services are in place to minimize the climatic risks. The agriculture sector contributes 14% of the greenhouse gas (GHG) from the country. Mitigation of GHG emission from agriculture can be achieved by changing land-use management practices and enhancing input-use efficiency. Experiments in India showed that methane emission from lowland rice fields can be reduced by 40-50% with alternate wetting and drying (AWD), growing shorter duration varieties, and using neem-coated urea according to soil health card (SHC) and leaf color chart (LCC). Dry direct-seeding of rice, which does not require continuous soil submergence, can reduce methane emission by 70-75%. Sequestration of carbon (C) in agricultural soil can be promoted with the application of organic manure, crop residues, and balanced nutrients. India has taken several proactive steps for addressing the issues of climate change in agriculture. Recently, it has also committed for reducing GHG emission intensity by 45% by 2030 and achieving net zero emission by 2070. The paper discusses the major impacts of climate change, potential adaptation, and mitigation options and the initiatives of Govt. of India in making Indian agriculture climate-smart.

Trends and drivers of land use/cover change in W National park in Burkina Faso

Burkina Faso's W National Park (WNPB) is one of the country's biodiversity hotspots. Despite this Park's protection, illegal human activities threaten its vegetation, and little information about the on-site causes of degradation is available. Here we explored the extent and drivers of changes in land use/land cover (LULC) in the WNPB. For this purpose, we used Landsat (1988, 2001 and 2016), and ancillary data to determine the spatial structure and changes in LULC with a random forest classifier. We identified socio-economic factors influencing LULC by conducting household surveys, focus groups, and field observations. We used the ranking and binary logistic regression methods to analyze the socio-economic data. A logistic regression model assessed the relationship between land cover change and socio-economic factors. The results showed that multi-temporal classification performed significantly better than mono-temporal one in the study area. However, the combination of mono-temporal reflectances and vegetation indices for LULC classification significantly enhanced the accuracy to the level of multi-temporal classification. This result indicates that this combination is an efficient alternative to multi-temporal classification in the study area where cloud-free imagery is rare. In the WNPB, LULC dynamics from 1988 to 2001 was mainly characterized by reduction of tree savannas (9.4%) and woodland (8.8%) and expansion of bare soil (0.1%) and mixed vegetation (18.1%). From 2001 to 2016, croplands increased by 102.1%. Bush fire (77.19%), wood harvesting (48.25%), lack of rain (48.25%) and elephants’ impact (20.18%) were the leading direct causes of LULC change. In general, the perceptions of local populations about vegetation trends were in line with the observations from remote sensing. Altogether, the tree vegetation in the study area decreased significantly between 2001 and 2016, and the cause of this change appears to be unsustainable land-use rather than rainfall conditions. According to these findings, land-use management practices in this park should be more sustainable and provide education (and changing habits) to the surrounding population. It is therefore suggested that the government regulate illegal activities through forest law enforcement to protect the WNPB from over-exploitation.

A modified approach to quantify aquifer vulnerability to pollution towards sustainable groundwater management in Irrigated Indus Basin.

The quality of groundwater in the study watershed has worsened because of industrial effluents and residential wastes from the urbanized cities; therefore, there is an important need to explore the aquifer vulnerability to pollution for sustainable groundwater management in the Irrigated Indus Basin (IIB). This study proposed a novel methodology to quantify groundwater vulnerability using two fully independent methodologies: the first by reintroducing an improved recharge factor (R) map and the second by incorporating three different weight and rating schemes into a traditional DRASTIC framework to improve the performance of the DRASTIC approach. In the current study, we composed a recharge map from Soil and Water Assessment Tool (SWAT) output (namely SWAT recharge map) with a drainage density map to retrieve an improved composite recharge map (SWAT-CRM). SWAT-CRM along with other thematic layers was combined using weightage overlay analysis to prepare the maps of groundwater vulnerability index (VI). The weight scale (w) and rating scale (r) were assigned based on a survey of available literature, and we then amended them using the analytical hierarchy process (AHP) and a probability frequency ratio (PFR) technique. Results depicted that the region under high groundwater vulnerability was found to be 5-22% using traditional recharge maps, while those are 9-23% using improved SWAT-CRM. The area under the curve (AUC) revealed that groundwater vulnerability zones predicted with SWAT-CRM outperformed the DRASTIC model applied with the traditional recharge map. Groundwater electrical conductivity (EC) was>2500 mS/cm in the high groundwater vulnerability zones, while it was <1000 mS/cm in the low groundwater vulnerability zones. The outcomes of this study can be used to improve the sustainability of the groundwater resources in IIB through proper land-use management practices.