Changes in total and per-capital ecosystem service value in response to land-use land-cover dynamics in north-central Ethiopia

Ecosystems provide a wide range of services crucial for human well-being and decision-making processes at various levels. This study analyzed the major land cover types of north-central Ethiopia and their impact on total and per-capita ecosystem service value (ESV). The ESV was estimated using the benefit-transfer method along the established global and local coefficient values for the periods 1973, 1986, 2001, 2016, and 2024. The findings show that agricultural lands continued to expand at a rate of 563.4 ha year−1, at the expense of forests and grasslands. As a result, the total ESV of the study area declined from $101.4 to$61.03 million and $60.08–$43.69 million, respectively. The ESV per capita was also diminished by $152.4 (37.7$257 (40.6%), respectively. However, land-cover improvement during the period 2001–2016 enhanced the total and per capita ESV in the study area. Therefore, potential future research may be required to develop a valid approach for assessing the robustness and sensitivity of value coefficients for the valuation of the ESV at the landscape level.</p

An Application of Machine-Learning Model for Analyzing the Impact of Land-Use Change on Surface Water Resources in Gauteng Province, South Africa

The change in land-use diversity is attributed to the anthropogenic factors sustaining life. The surface water bodies and other crucial natural resources in the study area are being depleted at an alarming rate. This study explored the implications of the changing land-use diversity on surface water resources by using a random forest (RF) classifier machine-learning algorithm and remote-sensing models in Gauteng Province, South Africa. Landsat datasets from 1993 to 2022 were used and processed in the Google Earth Engine (GEE) platform, using the RF classifier. The results indicate nine land-use diversity classes having increased and decreased tendencies, with high F-score values ranging from 72.3% to 100%. In GP, the spatial coverage of BL has shrunk by 100.4 km2 every year over the past three decades. Similarly, BuA exhibits an annual decreasing rate of 42.4 km2 due to the effect of dense vegetation coverage within the same land use type. Meanwhile, water bodies, marine quarries, arable lands, grasslands, shrublands, dense forests, and wetlands were expanded annually by 1.3, 2.3, 2.9, 5.6, 11.2, 29.6, and 89.5 km2, respectively. The surface water content level of the study area has been poor throughout the study years. The MNDWI and NDWI values have a stronger Pearson correlation at a radius of 5 km (r = 0.60, p = 0.000, n = 87,260) than at 10 and 15 km. This research is essential to improve current land-use planning and surface water management techniques to reduce the environmental impacts of land-use change

Analysis of the long-term agricultural drought onset, cessation, duration, frequency, severity and spatial extent using Vegetation Health Index (VHI) in Raya and its environs, Northern Ethiopia

Abstract Background Droughts cause serious effects on the agricultural and agro-pastoral sector due to its heavy dependence on rainfall. Several studies on agricultural drought monitoring have been conducted in Africa in general and Ethiopia in particular. However , these studies were carried out using the limited capacity of drought indices such as Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), and Deviation of Normalized Difference Vegetation Index (DevNDVI) only. To overcome this challenge, the present study aims to analyze the long-term agricultural drought onset, cessation, duration, frequency, severity and its spatial extents based on remote sensing data using the Vegetation Health Index (VHI) 3-month time-scale in Raya and its surrounding area, Northern Ethiopia. Both the MOD11A2 Terra Land Surface Temperature (LST) and eMODIS NDVI at 250 by 250 m spatial resolution and hybrid TAMSAT monthly rainfall data were used. A simple linear regression model was also applied to examine how the agricultural drought responds to the rainfall variability. Results Extremely low mean NDVI value ranged from 0.23 to 0.27 was observed in the lowland area than mid and highlands. NDVI coverage during the main rainy season decreased by 3–4% in all districts of the study area, while LST shows a significant increase by 0.52–1.08 °C. VHI and rainfall value was significantly decreased during the main rainy season. Agricultural drought responded positively to seasonal rainfall (R2 = 0.357 to R2 = 0.651) at p < 0.01 and p < 0.05 significance level. This relationship revealed that when rainfall increases, VHI also tends to increase. As a result, the event of agricultural drought diminished. Conclusions Remote sensing and GIS-based agricultural drought can be better monitored by VHI composed of LST, NDVI, VCI, and TCI drought indices. Agricultural drought occurs once in every 1.36–7.5 years during the main rainy season, but the frequency, duration and severity are higher (10–11 times) in the lowland area than the mid and highlands area (2–6 times) during the last 15 years. This study suggests that the effect of drought could be reduced through involving the smallholder farmers in a wide range of on and off-farm practices. This study may help to improve the existing agricultural drought monitoring systems carried out in Africa in general and Ethiopia in particular. It also supports the formulation and implementation of drought coping and mitigation measures in the study area

Changes in total and per-capita ecosystem service value in response to land-use land-cover dynamics in north-central Ethiopia

Ecosystems provide a wide range of services crucial for human well-being and decision-making processes at various levels. This study analyzed the major land cover types of north-central Ethiopia and their impact on total and per-capita ecosystem service value (ESV). The ESV was estimated using the benefit-transfer method along the established global and local coefficient values for the periods 1973, 1986, 2001, 2016, and 2024. The findings show that agricultural lands continued to expand at a rate of 563.4 ha year⁻¹, at the expense of forests and grasslands. As a result, the total ESV of the study area declined from $101.4 to$61.03 million and $60.08–$43.69 million, respectively. The ESV per capita was also diminished by $152.4 (37.7$257 (40.6%), respectively. However, land-cover improvement during the period 2001–2016 enhanced the total and per capita ESV in the study area. Therefore, potential future research may be required to develop a valid approach for assessing the robustness and sensitivity of value coefficients for the valuation of the ESV at the landscape level

The impacts of armed conflict on vegetation cover degradation in Tigray, northern Ethiopia

Efforts made to restore the degraded landscape of the Tigray region, Northern Ethiopia, over the last three decades have been relatively successful. However, an armed conflict that broke out in the region in November 2020 has significantly destroyed the restored vegetation, either directly associated with conflict (environment, pollution, fire) or indirectly (agricultural abandonment). This study aimed at assessing spatio-temporal changes in vegetation cover in a 50 km radius zone centered on Mekelle city, Tigray. Vegetation cover dynamics was evaluated using Landsat Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) datasets for the years 2000, 2020, and 2022 and analysed using ENVI 5.3 and ArcGIS 10.8.1 software. These data were analysed using the Modified Normalized Difference Vegetation Index (MNDVI), Optimized Soil Adjusted Vegetation Index (OSAVI), and Moisture Adjusted Vegetation Index (MAVI). Based on the MNDVI, results show that vegetation cover increased in the period 2000–2020 by 179 km2 or 2% of the area, whereas in the period 2020–2022, there was a decrease in vegetation cover by 403 km2 or 5% of the area. This was accompanied by a decrease in vegetation density. These vegetation changes in 2020–2022 are attributed to the impact of armed conflict on the land surface which can include farmlands and village abandonment, spread of weeds and scrub vegetation, or failure to harvest crops. Monitoring vegetation change using Landsat data can help understand the environmental impacts of armed conflict in rural agricultural landscapes, including potential food security risks

Land Use and Land Cover Change Determinants in Raya Valley, Tigray, Northern Ethiopian Highlands

Land use and land cover change (LULCC) is the result of both natural and socio-economic determinants. The aim of this study was to model the determinant factors of land cover changes in Raya Valley, Southern Tigray, Ethiopia. Multistage sampling was used to collect data from 246 households sampled from lowlands (47), midlands (104), highlands (93), and sub-alpine (2) agro-climatological zone. Descriptive statistics and logit regression model were used to analyze the field survey data. Agricultural land expansion, fuelwood extraction, deforestation, overgrazing and expansion of infrastructure were the proximate causes of LULCC in the study area. Agricultural land expansion (p = 0.084) and wood extraction for fuel and charcoal production (p = 0.01) were the prominent causes for LULCC. Persistent drought (p = 0.001), rapid population growth (p = 0.027), and climate variability (p = 0.013) were the underlying driving factors of LULCC. The determinants of LULCC need to be considered and mitigated to draw robust land use policy for sustainable land management by the smallholder farmers. This study provides important results for designing and implementing scientific land management strategies by policy makers and land managers

Analysis of drought coping strategies in northern Ethiopian highlands

Abstract One of the most detrimental concerns brought on by a changing climate that annually affects many people's lives is drought. Proactive and reactive drought coping and adapting mechanisms enable farmers to be resilient against climate–induced drought and improve the drylands' current disaster preparedness and early warning systems. The aim of this study was to assess proactive and reactive farmers' drought coping strategies at household level in Raya Valley in southern Tigray, Ethiopia. Agro–climatological based 246 households were sampled from the lowlands, midlands and highlands of the study area. The most effective drought coping mechanisms were discovered using a multinomial logit model. The study area had endured mild to extremely severe drought in the last three decades. The association between the various drought severity and household heads were significant (chi2 = 9.861, df = 3, p < 0.05). Proactive drought coping measures included collecting and storing pasture, conserving soil and water, weather prediction information to adjust saving and farming practices. Livestock feeding with roasted cactus cladode, small business loans, livestock selling, productive safety–net program, and food consumption reduction were the major reactive drought coping strategies. The proactive and reactive drought coping strategies identified in this study should be used to improve the existing disaster preparedness and early warning systems in the face of climate and weather extreme related impacts of climate variability and change