Land Use 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.

Assessing the environmental factors affecting the sustainability of Aini Falaj system.

This study investigates the spatial distribution patterns and environmental factors influencing the Aini Falaj system in a specific study area. The research findings are presented through the lens of the following four categories: collinearity diagnostics, spatial autocorrelation analysis, kernel density (KD) findings, and multivariate geographically weighted regression (MGWR) analysis. The collinearity diagnostics were applied to examine the interrelationships among 18 independent environmental variables. The results indicate the absence of significant multicollinearity concerns, with most variables showing values below the critical threshold of five for variance inflation factors (VIFs). The selected variables indicate minimal intercorrelation, suggesting that researchers should be confident utilizing them in subsequent modelling or regression analyses. A spatial autocorrelation analysis using Moran's Index revealed positive spatial autocorrelation and significant clustering patterns in the distribution of live and non-functional Aini Falajs. High concentrations of live or dead Falajs tended to be surrounded by neighbouring areas with similar characteristics. These findings provide insights into the ecological preferences and habitat associations of Aini Falajs, thereby aiding conservation strategies and targeted studies. The kernel density (KD) analysis depicted distribution patterns of live and dry Aini Falajs through hotspots and cold spots. Specific regions exhibited high-density areas of live Falajs, indicating favourable environmental conditions or historical factors contributing to their concentrated distribution. Identifying these high-density zones can enhance our understanding of the spatial patterns and potential factors influencing the prevalence and sustainability of Aini Falajs. The multivariate geographically weighted regression (MGWR) models revealed strong associations between the live or dead status of Aini Falajs and environmental factors. The precipitation, topographic wetness index (TWI), aspect and slope exerted positive impacts on the live status, while evaporation, solar radiation, distance to drains and drain density exerted negative influences. Similar associations were observed for the dead status, emphasising the importance of controlling evaporation, shading mechanisms, proper drainage planning and sustainable land-use practices. This study provides valuable insights into the spatial distributions and factors influencing the live and dead status of Aini Falajs, thereby contributing to our understanding of their ecological dynamics and guiding conservation efforts and management strategies.

Vulnerability Assessment of Groundwater Influenced Ecosystems in the Northeastern United States

Groundwater-influenced ecosystems (GIEs) are increasingly vulnerable due to groundwater extraction, land-use practices, and climate change. These ecosystems receive groundwater inflow as a portion of their baseflow or water budget, which can maintain water levels, water temperature, and chemistry necessary to sustain the biodiversity that they support. In some systems (e.g., springs, seeps, fens), this connection with groundwater is central to the system’s integrity and persistence. Groundwater management decisions for human use often do not consider the ecological effects of those actions on GIEs. This disparity can be attributed, in part, to a lack of information regarding the physical relationships these systems have with the surrounding landscape and climate, which may influence the environmental conditions and associated biodiversity. We estimate the vulnerability of areas predicted to be highly suitable for the presence of GIEs based on watershed (U.S. Geological Survey Hydrologic Unit Code 12 watersheds: 24–100 km2) and pixel (30 m × 30 m pixels) resolution in the Atlantic Highlands and Mixed Wood Plains EPA Level II Ecoregions in the northeastern United States. We represent vulnerability with variables describing adaptive capacity (topographic wetness index, hydric soil, physiographic diversity), exposure (climatic niche), and sensitivity (aquatic barriers, proportion urbanized or agriculture). Vulnerability scores indicate that ~26% of GIEs were within 30 m of areas with moderate vulnerability. Within these GIEs, climate exposure is an important contributor to vulnerability of 40% of the areas, followed by land use (19%, agriculture or urbanized). There are few areas predicted to be suitable for GIEs that are also predicted to be highly vulnerable, and of those, climate exposure is the most important contributor to their vulnerability. Persistence of GIEs in the northeastern United States may be challenged as changes in the amount and timing of precipitation and increasing air temperatures attributed to climate change affect the groundwater that sustains these systems.

Lowland Tropical Peatlands – A Brief Review of Their Important Role in the Global Carbon Cycle and Biodiversity Support

Tropical peatlands are crucial ecosystems, storing vast carbon reserves and supporting rich biodiversity. Despite covering a small land area, they play significant roles in global carbon cycling and climate regulation. However, these ecosystems face escalating threats from human activities, including agricultural expansion and peatland drainage. This paper provides a concise overview of tropical peatlands, focusing on their distribution, characteristics, and ecological importance in Southeast Asia, Africa, and South America. It highlights the diverse vegetation communities and notable animal species found in peat swamp forests, underscoring their conservation value. Peatland degradation leads to increased greenhouse gas emissions, land subsidence, and loss of traditional livelihoods for local communities. Addressing these challenges requires integrated approaches, including conservation efforts to protect and restore intact peat swamp forests, sustainable land-use practices, and policy interventions to regulate land management. Research collaboration between scientists, policymakers, and local communities is essential for developing evidence-based conservation strategies. By prioritizing the preservation of tropical peatlands, we can mitigate climate change impacts, conserve biodiversity, and safeguard the well-being of local communities.

Plant species phenology differs between climate and land-use scenarios and relates to plant functional traits.

Phenological shifts due to changing climate are often highly species and context specific. Land-use practices such as mowing or grazing directly affect the phenology of grassland species, but it is unclear if plants are similarly affected by climate change in differently managed grassland systems such as meadows and pastures. Functional traits have a high potential to explain phenological shifts and might help to understand species-specific and land-use-specific phenological responses to changes in climate. In the large-scale field experiment Global Change Experimental Facility (GCEF), we monitored the first flowering day, last flowering day, flowering duration, and day of peak flowering, of 17 herbaceous grassland species under ambient and future climate conditions, comparing meadows and pastures. Both climate and land use impacted the flowering phenology of plant species in species-specific ways. We did not find evidence for interacting effects of climate and land-use type on plant phenology. However, the data indicate that microclimatic and microsite conditions on meadows and pastures were differently affected by future climate, making differential effects on meadows and pastures likely. Functional traits, including the phenological niche and grassland utilization indicator values, explained species-specific phenological climate responses. Late flowering species and species with a low mowing tolerance advanced their flowering more strongly under future climate. Long flowering species and species following an acquisitive strategy (high specific leaf area, high mowing tolerance, and high forage value) advanced their flowering end more strongly and thus more strongly shortened their flowering under future climate. We associated these trait-response relationships primarily with a phenological drought escape during summer. Our results provide novel insights on how climate and land use impact the flowering phenology of grassland species and we highlight the role of functional traits in mediating phenological responses to climate.

“You never farm alone”: Farmer land-use decisions influenced by social relations

ContextFarmer land-use decisions are commonly explained and predicted by socio-demographic, economic, ecological, and psychological factors. However, these models explain only part of the empirical data without accounting for the effect of social relations. ObjectiveThis study aimed at exploring the effect of social relations on farmer land-use decisions using the status-power theory of relations. We hypothesised that farmer land-use decisions are driven by the need to comply with requirements of their salient reference groups, such as family, government, and spiritual beings. MethodsWe undertook a case study in the Mt. Kenya region where we conducted individual interviews and focus group discussions among smallholder farmers. We then used chi-square automatic interaction detection (CHAID) to explore influence of social relations on land-use practices. Results and conclusionsReported social relations were diverse and accounted for land-use decisions that could not be explained by socio-demographic, economic or ecological factors. The results showed that a farmer seemed more likely to choose a land-use option if he/she believed his/her salient reference groups would be pleased with the option. Reconciling social relations with other factors such as farmer's socio-demographic factors and geographic location also had a significant effect on the results. SignificanceInsights into the impact of social relations in farmer land-use decisions can explain the often-heterogeneous decisions and can complement the economic analysis that is the conventional focus in analysis of farmer decisions. An understanding of the effects of social relations can strengthen development of policies that motivate implementation of more sustainable agriculture options.

Human-driven fire and vegetation dynamics on the Caribbean island of Barbuda from early indigenous to modern times

We present a multiproxy analysis of a sediment core from Freshwater Pond, Barbuda, one of just a few inland paleoenvironmental records from the Lesser Antilles. Our results shed light on the relative contributions of climate variability and Pre- and Post-Columbian human activities to vegetation and fire dynamics on Barbuda. The presence of macroscopic charcoal and pollen of ethnobotanically-useful and disturbance-indicator plant taxa in the sediment record suggests that Pre-Columbian subsistence activities occurred within a few kilometers of the pond between ~150 BCE and ~1250 CE. Our record extends anthropogenic fires back into the early Ceramic (500 BCE–1500 CE) and possibly late Archaic Ages (3000–500 BCE) adding evidence to the timing of arrival of the island’s earliest inhabitants. The history of island-wide biomass burning inferred from microscopic charcoal fragments showed heightened fire activity between ~540 and ~1610 CE followed by a period of quiescence that reflected the transition from Pre- to Post-Columbian land-use practices associated with European colonization of the region. The British established a permanent settlement on Barbuda in the 1660s, but given Barbuda’s unsuitability for large-scale agriculture, timber harvesting, small-scale farming, and livestock rearing, activities that left no detectable charcoal footprints likely dominated post-colonial land use. The lack of any clear correspondence between the reconstructed histories of fire and effective moisture at Freshwater Pond supports the idea that Late-Holocene fire activity on Barbuda was driven primarily by human activity.

Spatio-temporal classification of land use and land cover and its changes in Kerala using remote sensing and machine learning approach.

Land use and land cover (LULC) analysis gives important information on how the region has evolved over time. Kerala, a land with an extensive and dynamic history of land-use changes, has, until now, lacked comprehensive investigations into this history. So the current study focuses on Kerala, one of the ecologically diverse states in India with complex topography, through Landsat images taken from 1990 to 2020 using two different machine learning classifications, random forest (RF) and classification and regression trees (CART) on Google Earth Engine (GEE) platform. RF and CART are versatile machine learning algorithms frequently employed for classification and regression, offering effective tools for predictive modelling across diverse domains due to their flexibility and data-handling capabilities. Normalised Difference Vegetation Index (NDVI), Normalised Differences Built-up Index (NDBI), Modified Normalised Difference Water Index (MNDWI), and Bare soil index (BSI) are integral indices utilised to enhance the precision of land use and land cover classification in satellite imagery, playing a crucial role by providing valuable insights into specific landscape attributes that may be challenging to identify using individual spectral bands alone. The results showed that the performance of RF is better than that of CART in all the years. Thus, RF algorithm outputs are used to infer the change in the LULC for three decades. The changes in the NDVI values point out the loss of vegetation for the urban area expansion during the study period. The increasing value of NDBI and BSI in the state indicates growth in high-density built-up areas and barren land. The slight reduction in the value of MNDWI indicates the shrinking water bodies in the state. The results of LULC showed the urban expansion (158.2%) and loss of agricultural area (15.52%) in the region during the study period. It was noted the area of the barren class, as well as the water class, decreased steadily from 1990 to 2020. The results of the current study will provide insight into the land-use planners, government, and non-governmental organizations (NGOs) for the necessary sustainable land-use practices.

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.

The Evolution of Agrarian Landscapes in the Tropical Andes.

Changes in land-use practices have been a central element of human adaptation to Holocene climate change. Many practices that result in the short-term stabilization of socio-natural systems, however, have longer-term, unanticipated consequences that present cascading challenges for human subsistence strategies and opportunities for subsequent adaptations. Investigating complex sequences of interaction between climate change and human land-use in the past-rather than short-term causes and effects-is therefore essential for understanding processes of adaptation and change, but this approach has been stymied by a lack of suitably-scaled paleoecological data. Through a high-resolution paleoecological analysis, we provide a 7000-year history of changing climate and land management around Lake Acopia in the Andes of southern Peru. We identify evidence of the onset of pastoralism, maize cultivation, and possibly cultivation of quinoa and potatoes to form a complex agrarian landscape by c. 4300 years ago. Cumulative interactive climate-cultivation effects resulting in erosion ended abruptly c. 2300 years ago. After this time, reduced sedimentation rates are attributed to the construction and use of agricultural terraces within the catchment of the lake. These results provide new insights into the role of humans in the manufacture of Andean landscapes and the incremental, adaptive processes through which land-use practices take shape.

Unraveling the Complex Dynamics of Soil Microbiome Diversity and Its Implications for Ecosystem Functioning: A Comprehensive Review

Soil microbiome diversity plays a pivotal role in shaping terrestrial ecosystems and the myriad functions. This comprehensive review delves into the intricate dynamics of soil microbial communities, exploring their composition, interactions, and responses to environmental factors. By synthesizing findings from cutting-edge research, we aim to elucidate the complex interplay between soil microbiome diversity and ecosystem functioning. We discuss the application of advanced techniques, such as high-throughput sequencing and metagenomic analysis, which have revolutionized our understanding of soil microbial diversity. The review highlights the influence of biotic and abiotic factors, including plant diversity, soil properties, climate, and land-use practices, on the structure and diversity of soil microbial communities. We examine the mechanisms through which soil microbes drive critical ecosystem processes, such as nutrient cycling, carbon sequestration, and plant productivity. The review also explores the resilience and adaptability of soil microbial communities in the face of global change pressures, such as climate change, land-use intensification, and biodiversity loss. We discuss the potential implications of altered soil microbiome diversity for ecosystem functioning and the provision of essential ecosystem services. Furthermore, we identify knowledge gaps and propose future research directions to advance our understanding of soil microbiome diversity and its role in maintaining healthy and productive ecosystems. This review provides a comprehensive framework for understanding the complex dynamics of soil microbiome diversity and underscores its critical importance in shaping the functioning and sustainability of terrestrial ecosystems in a changing world.

Indigenous Women on the Frontlines of Climate Activism

Abstract In this public address, transcribed and translated from the Portuguese, two leaders of Brazil’s pan-ethnic Indigenous rights movement, Sônia Bone Guajajara and Célia Xakriabá, describe their respective formation, their involvement in environmental and human rights struggles, and the global stakes involved in the recognition and protection of the traditional territorial claims and land-use practices of Indigenous peoples in the Brazilian Amazon and beyond.

Surface Water (SW) and Shallow Groundwater (SGW) Nutrient Concentrations in Riparian Wetlands of a Mixed Land-Use Catchment

Precipitation patterns, water flow direction, and local land-use practices affect surface water (SW) and shallow groundwater (SGW) nutrient concentrations in riparian wetlands. Given physical process complexities, spatiotemporal quantification of nutrients and physical factors influencing nutrient concentrations are needed to advance wetland water resource management. To address these needs, a study was conducted in riparian wetlands of a mixed land-use catchment in West Virginia (WV), USA. Observed data included SW–SGW levels and nutrient concentrations, including nitrate (NO3-N), nitrite (NO2-N), ammonium (NH4-N), orthophosphate (PO43-P), total nitrogen (total_N), and total phosphorus (total_P) from January 2020 to December 2021. Water samples were collected monthly from stream gauge sites (n = 4) and co-located piezometers (n = 13). Results showed that, on average, gaining stream conditions were observed in upstream sites, and losing stream conditions were observed in downstream sites. Observed nutrient profiles between SW and SGW included SW exhibiting a higher average NO3-N concentration (0.42 mg/L), while SGW displayed an elevated NH4-N concentration (1.55 mg/L) relative to other nitrogen species. Significantly high (p &lt; 0.05) SW NO3- concentrations in summer and fall were attributed to increased precipitation and corresponding water level and, therefore, pressure head and transport fluctuations. Principal Component Analysis (PCA) showed differences in nutrient concentrations based on the water source type and catchment land use, explaining 65% of data variability. Spearman correlation analysis illustrated the correlation among nutrient concentrations, land use, and water level changes in SW and SGW environments. This study provides needed baseline data on nutrient dynamics for a riparian wetland in a mixed land-use catchment, supplying science-based information to advance land and water management practices in the study watershed and similar physiographic watersheds globally.

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.

Smallholder farmers' vulnerability to climate change and variability: Evidence from three agroecologies in the Upper Blue Nile, Ethiopia

This study delves into the profound impact of climate change on agriculture in Ethiopia, particularly the vulnerabilities faced by smallholder farmers and the resulting implications for poverty. Focusing on three distinct agroecologies, namely: highland, midland, and lowland zones. The study employed a robust methodology, combining a cross-sectional survey, spatial-temporal trend analysis using GIS, and the development of an overall vulnerability index through the balanced weighted average method. The study, encompassing 646 households, combines data from a variety of sources and analytical tools like the vulnerability index, ArcGIS 10.8, and ERDA's IMAGINE 2015. Utilizing the LVI-IPCC scale, the study shows that climate change is an immediate vulnerability in all agroecological zones. It identifies highland areas as the most sensitive and exposed regions, while lowland households are found to be the most vulnerable in terms of overall vulnerabilities. The research reveals specific challenges faced by communities, such as inadequate health facilities and insufficient food and water supplies in both highland and lowland agroecosystems. Additionally, our investigation has observed a significant alteration in land use practices, specifically the shift from communal grazing land to private cultivation and plantations, emphasizing eucalyptus. This alteration enhances the ecosystem's vulnerability to climate disturbances. The study suggests targeted interventions, such as advocating for sustainable land-use practices, afforestation, and adopting climate-smart agriculture practices. It is important to implement policy measures that prioritize conserving and restoring shrubland, grazing land, and natural forests to ensure both long-term socio-economic and ecosystem resilience. The study's nuanced insights are instrumental in understanding the diverse challenges posed by climate change in Ethiopian agriculture, supporting informed policymaking and sustainable interventions.

Assessing the performance of wind erosion prediction models of RWEQ and SWEEP by direct measurements in an arid region

Wind erosion field studies allow researchers to conduct simulations under natural conditions, thus play a significant role in investigating wind erosion processes. Direct measurements are also used to validate and improve existing erosion models. There is a need to develop sustainable land-use practices and management strategies and to assess potential current and future trends of wind erosion risk in arid and semi-arid regions. This study assessed wind erosion-induced soil losses in 11 different wind cases encountered within the wheat-fallow production system in a semi-arid region of Türkiye between 2017 and 2020 to eliminate the wind erosion threats on soil resources. Direct measurements and two estimation models (RWEQ and SWEEP) were employed to assess soil loss. Grid sampling method and BEST® sediment traps were utilized to measure wind-blown soil in the field directly. Present findings revealed that wind erosion threatened both plots in different seasons. The wheat-cultivated plot was highly susceptible to wind erosion in autumn when winter cereals are sown, while the fallow plot showed susceptibility in spring. Throughout the entire measurement period (3-years), wind erosion-induced soil transportation was measured as 1383 kg ha−1 for fallow plots and 2548 kg ha−1 for wheat-cultivated plots. Model performance was assessed through correlations (r), root mean square error (RMSE) and d-test results. The results demonstrated that the calibrated RWEQ (RWEQcal) model provided reasonably accurate estimates of wind erosion for both fallow and wheat-cultivated lands, with relatively low RMSE values of 0.34 and 0.46, d-test values of 0.26 and 0.27, and correlation coefficients of 0.69 and 0.85, respectively. Model results highlighted the importance of model calibration for local conditions; otherwise, they may produce underestimated and overestimated results.

Future ecosystem service provision under land-use change scenarios in southwestern Ethiopia

ABSTRACT Continued pressure and transformation of land-use by humans are key drivers of biodiversity and ecosystem services (ES) loss. To determine the sustainability of possible future land-use practices, it is important to anticipate likely future changes to biodiversity and ES. This can help stakeholders and decision-makers to understand and assess the viability of current development policies and design alternative future pathways. Focusing on a biodiversity hotspot in southwestern Ethiopia, we considered four future land-use scenarios (namely: ‘Gain over grain’, ‘Coffee and conservation’, ‘Mining green gold’ and ‘Food first’ scenarios) that were developed in an earlier project via participatory scenario planning. We modelled and mapped the spatial distribution of six ES (erosion control, carbon storage, coffee production, crop production, livestock feed, and woody-plant richness) for the current landscape and the four scenarios. Our results show that potential ES changes differed strongly across the scenarios. Changes were strongest for land-use scenarios involving large-scale agricultural intensification; and changes were not uniformly distributed across the landscape. Smallholder farmers specializing on cash crops (‘Gain over grain’ scenario) would likely cause little change to ES generation, but major losses in ES would result from expanding either food or coffee production (‘Mining green gold’ and ‘Food first’). Finally, the ‘Coffee and conservation’ scenario appears to be the most sustainable scenario because it would secure diverse ES for the long term. Our findings provide valuable input for decision-makers and stakeholders and could help to identify sustainable land-use options.

Land-use affects pollinator-specific resource availability and pollinator foraging behaviour.

Land-use management is a key factor causing pollinator declines in agricultural grasslands. This decline can not only be directly driven by land-use (e.g., habitat loss) but also be indirectly mediated through a reduction in floral resource abundance and diversity, which might in turn affect pollinator health and foraging. We conducted surveys of the abundance of flowering plant species and behavioural observations of two common generalist pollinator species, namely the bumblebee Bombus lapidarius and the syrphid fly Episyrphus balteatus, in managed grasslands of variable land-use intensity (LUI) to investigate whether land-use affects (1) resource availability of the pollinators, (2) their host plant selection and (3) pollinator foraging behaviour. We have found that the floral composition of plant species that were used as resource by the investigated pollinator species depends on land-use intensity and practices such as mowing or grazing. We have also found that bumblebees, but not syrphid flies, visit different plants depending on LUI or management type. Furthermore, LUI indirectly changed pollinator behaviour via a reduction in plot-level flower diversity and abundance. For example, bumblebees show longer flight durations with decreasing flower cover indicating higher energy expenditure when foraging on land-use intensive plots. Syrphid flies were generally less affected by local land use, showing how different pollinator groups can differently react to land-use change. Overall, we show that land-use can change resource composition, abundance and diversity for pollinators, which can in turn affect pollinator foraging behaviour and potentially contribute to pollinator decline in agricultural grasslands.

The potency of coffee plants in agroforestry system in Baringin Village, Agam Regency, West Sumatra to support social forestry program and its contribution to mitigate climate change

This study investigates the viability of coffee agroforestry systems in supporting Indonesia’s Social Forestry Program and contributing to climate change mitigation efforts. Conducted in the KUPS Kopi Data Baringin management area of West Sumatra, this research assesses the potential of coffee cultivation within an agroforestry system in Baringin Village, Agam District. Data collection encompassed a comprehensive census for social and economic aspects and purposive sampling for vegetation analysis. Findings revealed a diverse range of 29 tree species from 16 families, alongside eight types of agricultural crops from five families. Tree species exhibited lower diversity and abundance indices, while herbaceous and shrub categories demonstrated moderate diversity. Notably, Coffea canephora, the coffee species, exhibited a carbon content of 3.49 tons per hectare, contributing to climate change mitigation efforts and functioning as a valuable CO2 equivalent sink estimated at approximately 13 tons per hectare. Furthermore, the adoption of coffee agroforestry systems resulted in a notable increase in monthly income for KUPS members. These findings underscore the potential of coffee agroforestry systems as a sustainable land-use practice, supporting the Social Forestry Program objectives and making substantial contributions to climate change mitigation in Indonesia’s forest and land management strategies.