Impact Of Changes Research Articles

Disaster induced displacement and durable solutions in Africa

AbstractClimate change represents a significant challenge to the sustainability of the global economy. Many African countries have suffered the repercussions of environmental and climate deterioration, most notably internal displacement. This article sought to examine the impact of climate change within the context of internal displacement in Africa and to preview and describe the trends of internally displaced people in Africa. The study used a mixed methods approach. Qualitative data was obtained from online repositories, and it was analyzed using content analysis. Quantitative data was obtained from World Bank portal and it was analysed using descriptive statistics. Research findings have shown that Africa is plagued by a high number of internally displaced people. It was also established that climate change leads to income inequality, the exposure of people to poverty, and the destruction of infrastructure. These adverse effects affect the capacity of African economies to attain selected Sustainable Development Goals. In terms of policy recommendations, it was suggested that there is a need to strengthen the regional and continental bodies, invest in climate change adaptation measures, broaden the definition of refugees to include climate refugees, and promote robust research and capacity building.

Projecting the impact of climate change on honey bee plant habitat distribution in Northern Ethiopia

Climate change significantly affects the diversity, growth, and survival of indigenous plant species thereby influencing the nutrition, health and productivity of honey bees (Apis mellifera). Hypoestes forskaolii (Vahl) is one of the major honey bee plant species in Ethiopia’s Tigray region. It is rich in pollen and nectar that typically provides white honey, which fetches a premium price in both local and inter-national markets. Despite its socio-economic and apicultural significance, the distribution of H. forskaolii has been declining, raising concerns regarding its conservation efforts. However, there is limited knowledge on how environmental and climatic factors affect its current distribution and response to future climate change. The study investigates the current and projected (the 2030s, 2050s, 2070s, and 2090s) habitat distributions of H. forskaolii under three future climate change scenarios (ssp126, ssp245, and ssp585) using the Maximum Entropy Model (MaxEnt). The results show that land use (50.1%), agro-ecology (28%), precipitation during the Driest Quarter (11.2%) and soil texture (6.1%) predominantly influence the distribution of H. forskaolii, collectively explaining 95.4% of the model's predictive power. Habitats rich in evergreen trees and mosaic herbaceous with good vegetation cover are identified as the most suitable for H. forskaolii. The spatial distribution of H. forskaolii is concentrated in the highlands and mid-highlands of the eastern and southern parts of Tigray, characterized by a colder temperature. Across the three climate change scenarios, the size of suitable habitat for H. forskaolii is projected to decrease over the four time periods studied. Predictions under the ssp585 scenario reveal alarming results, indicating a substantial decrease in the suitable habitat for H. forskaolii from 4.26% in the 2030s to 19.09% in the 2090s. Therefore, given the challenges posed by climate change, research efforts should focus on identifying and evaluating new technologies that can help the H. forskaolii species in adapting and mitigating the effects of climate change.

Disaster induced displacement and durable solutions in Africa

AbstractClimate change represents a significant challenge to the sustainability of the global economy. Many African countries have suffered the repercussions of environmental and climate deterioration, most notably internal displacement. This article sought to examine the impact of climate change within the context of internal displacement in Africa and to preview and describe the trends of internally displaced people in Africa. The study used a mixed methods approach. Qualitative data was obtained from online repositories, and it was analyzed using content analysis. Quantitative data was obtained from World Bank portal and it was analysed using descriptive statistics. Research findings have shown that Africa is plagued by a high number of internally displaced people. It was also established that climate change leads to income inequality, the exposure of people to poverty, and the destruction of infrastructure. These adverse effects affect the capacity of African economies to attain selected Sustainable Development Goals. In terms of policy recommendations, it was suggested that there is a need to strengthen the regional and continental bodies, invest in climate change adaptation measures, broaden the definition of refugees to include climate refugees, and promote robust research and capacity building.

In-depth Exploration of Temperature Trends in Morocco: Combining Traditional Methods of Mann Kendall with Innovative ITA and IPTA Approaches

AbstractThis study examines trends in minimum and maximum temperatures at various climate stations located in different regions of Morocco for a period of five decades (1970 to 2019). Mann–Kendall, Sen’s estimator, Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) were used in the analysis. The results show significant fluctuations, at different time scales, between minimum and maximum temperatures at all stations. In coastal areas, such as Rabat Sale, minimum temperatures fell during January and February while other months saw increases. Average minimum temperatures in Rabat Sale tend to fall by 0.5 °C. On the other hand, maximum temperatures in Rabat Sale rose by 0.2 °C. A decrease of 0.4 °C for Tmin and 1.6 °C for Tmax were observed in higher continental regions, such as Meknes. Other stations, such as Fez Sais (0.6 °C Tmin and 2.6 °C Tmax) and Taza (1.1 °C Tmin and 2.6 °C Tmax) showed an upward trend. Trends also vary, with notable increases in minimum and maximum temperatures, indicating different climatic dynamics according to altitude and locality. In particular, the ITA highlights a significant increase in annual maximum temperatures, with a P-value < 0.05 and trend slopes ranging from 0.0015 °C per year in Rabat Sale to 0.0076 °C per year in Taza. In addition, the IPTA results confirm diversity of upward and downward trends on monthly and seasonal scales, highlighting impact of geographical factors such as proximity to sea, topography, and continentality that contribute to formation of regional microclimates. The results highlight significant impact of climate change in Morocco.

The Indirect Effect of Entrepreneurship on Pay Dispersion: Entry Cost Reduction, Mobility Threat, and Wage Redistribution Within Incumbent Firms

Past research has examined the link between initiatives promoting entrepreneurship and compensation, but scholars have predominantly focused on earnings of individuals directly engaged in the founding process, such as founders, cofounders, and start-up employees. Shifting our focus to incumbent workers, we instead propose that a decline in the cost of entrepreneurship increases the variance in pay among incumbent workers who are not involved in entrepreneurial activities. We posit that, as entrepreneurship becomes a more attractive career option, due to institutional changes, the outside option value of entrepreneurship increases. The resulting increase in mobility threat will disproportionately benefit high earners or those employees who are more difficult to replace: As their bargaining power increases, incumbents will disproportionately reward these workers, especially when they are systematically more inclined to leave for entrepreneurship. We explore these arguments using a difference-in-differences methodology, based on the enactment of an entry reform that reduced the cost of entry in Portugal between 1995 and 2009. We find that an exogenous decrease in the administrative costs of establishing a new venture led to high earners capturing disproportionate rewards relative to low earners. We further show that this relationship was especially pronounced among high earners who (a) exhibited a higher ex ante propensity to transition into entrepreneurship; (b) had fewer credible outside options in paid employment; and (c) operated in industries with decentralized wage bargaining arrangements. By documenting the impact of institutional changes that promote entrepreneurship on incumbent workers’ pay, our study contributes to recent debates about the impact of entrepreneurship on individual earnings. Funding: This work was supported by the CY Initiative, the FCT—Portuguese Foundation of Science and Technology, and the Knowledge, Technology and Organization Research Center at Skema. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.16201 .

Climate change impact on Mediterranean viticultural regions and site-specific climate risk-reduction strategies

The global increase in extreme weather and climate events may dramatically impact agriculture, food safety, and socioeconomic dynamics. The Mediterranean basin is already exposed to extreme climatic events, severely challenging viticulture, a pivotal Mediterranean agro–industry. This study aims to understand better how climate is expected to evolve in six viticulturally important Mediterranean regions in Portugal, Italy, Turkey and Morocco, using a 4–member ensemble of climatic model projections under Representative Concentration Pathways (RCP) 4.5 and 8.5 for 2041–2070, and using the 1981–2010 period as a baseline. By comparing the main specific challenges these locations will face, we comparatively define the best strategies to reduce the impacts of climate change at the national and regional levels. Projections show increases in overall temperatures, up to + 3.6°C than the historical baseline, whilst precipitation projections indicate decreases that could reach 36% of the overall annual precipitation. Biological effective degree days, consecutive dry days, growing season length, tropical nights, or very heavy precipitation days, also show challenging prospects for viticulture in these countries. A screening of the adaptative strategies already undertaken in the studied countries suggests that growers are taking reactive rather than preventive strategies. Moreover, the discussion of the most suitable strategies in this study is region–specific, i.e., prioritised by the specific needs of each location. The conclusions drawn herein may support local growers, improving their decision–making based on the most adequate adaptive strategies to their conditions, thus optimising their sustainable production under changing climates.

Geo-Spatial Investigation of Climate Change Impacts on Irrigation Demand of Dry Season Boro Rice in Northwest Bangladesh

The present study is an attempt to assess the irrigation demand of the dry season Boro rice in the northwest regions of Bangladesh using climatic, soil and crop data. The FAO-56 Penman–Monteith method was applied to calculate reference evapotranspiration and irrigation demand of Boro rice has been estimated using CROPWAT model. Both the observed and downscaled Representative Concentration Pathway (RCP) climatic data were used in the study. The result reveals that there is no significant change in irrigation demand of Boro rice from 1975 to present. However, the demand will increase significantly in future. The study projects that future irrigation demand of Boro rice in climate change situation for RCP 8.5 will be increased by 180-220 mm in 2075. It is expected that the findings will contribute in devising appropriate agricultural and irrigation plans for the region. The Chittagong Univ. J. B. Sci.,Vol. 10(1 &2):217-235, 2020

Integrating the land–water–climate nexus approach with spatial-based sustainable agriculture production

CONTEXTA policy on agricultural land zoning, based on land suitability maps, has been introduced to optimize the use of resources for crop production in Thailand. However, the impact of activities occurring during cultivation in different land suitability classes has not been considered. A land–water–climate nexus index (LWCNI) has therefore been introduced as a holistic analysis that integrates three indicators––land-use intensity, water-use intensity, and climate change impact in terms of GHG emissions. This can guide resource allocation by highlighting areas that need improvement. OBJECTIVEWe aimed to assess the land–water–climate nexus in different land-suitability classes for sugarcane and cassava in Thailand in order to compare the nexus performances and improve the planning and management of resources for sustainable production. METHODSThe LWCNI was developed and assessed by combining it with geographic information system–based tools for evaluating the nexus performances of sugarcane and cassava cultivation as per the agricultural zoning policies. The scope of the work was “from cradle to farm-gate”, and the final products considered were sugarcane and fresh cassava. RESULTS AND CONCLUSIONSThe results revealed that sugarcane cultivation in moderate-suitability areas is the most effective, with the best LWCNI score being 0.87, suggesting efficient cultivation practices with a minimal use of land and water resources, and a minimal climate change impact. The three indicators of land-use intensity, water-use intensity, and GHG emissions for sugarcane were estimated at 0.010 ha/t, 108 m3/t, and 6.2 kg carbon dioxide equivalent (CO2e)/t, respectively. Cassava cultivation in the high-suitability area was the most efficient, with the best LWCNI score, at 0.95, and using less land, fewer water resources, and having less of a climate change impact. The land-use intensity, water-use intensity, and GHG emissions of cassava were estimated at 0.030 ha/t, 255 m3/t, and 35.7 kgCO2e/t, respectively. Growing crops in marginal and unsuitable areas presented a risk of a high climate change impact as well as competition for water resources due to limited local resources. We found that, even in the same land-suitability class, the amount of fertilizer used by the farmers varied depending on their knowledge, experience, and finances. Excessive fertilizer application increased GHG emissions, which in turn brought about a decrease in the LWCNI score, leading to a poorer nexus performance. SIGNIFICANCEThe findings emphasize the relationship between land and water use and climate change impact across varying spatial contexts. The LWCNI approach offers valuable insights for supporting agricultural zoning policy.

Impact of stress regime change on the permeability of a naturally fractured carbonate buildup (Latemar, the Dolomites, northern Italy)

Abstract. Changing stress regimes control fracture network geometry and influence porosity and permeability in carbonate reservoirs. Using outcrop data analysis and a displacement-based linear elastic finite-element method, we investigate the impact of stress regime change on fracture network permeability. The model is based on fracture networks, specifically fracture substructures. The Latemar, predominantly affected by subsidence deformation and Alpine compression, is taken as an outcrop analogue for an isolated (Mesozoic) carbonate buildup with fracture-dominated permeability. We apply a novel strategy involving two compressive boundary loading conditions constrained by the study area's NW–SE and N–S stress directions. Stress-dependent heterogeneous apertures and effective permeability were computed in the 2D domain by (i) using the local stress state within the fracture substructure and (ii) running a single-phase flow analysis considering the fracture apertures in each fracture substructure. Our results show that the impact of the modelled far-field stresses at (i) subsidence deformation from the NW–SE and (ii) Alpine deformation from N–S increased the overall fracture aperture and permeability. In each case, increasing permeability is associated with open fractures parallel to the orientation of the loading stages and with fracture densities. The anisotropy of permeability is increased by the density and connectedness of the fracture network and affected by shear dilation. The two far-field stresses simultaneously acting within the selected fracture substructure at a different magnitude and orientation do not necessarily cancel each other out in the mechanical deformation modelling. These stresses affect the overall aperture and permeability distributions and the flow patterns. These effects – potentially ignored in simpler stress-dependent permeability – can result in significant inaccuracies in permeability estimation.

Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble

Abstract. ​​​​​​​Severe floods with extreme return periods of 100 years and beyond have been observed in several large rivers in Bavaria in the last 3 decades. Flood protection structures are typically designed based on a 100-year event, relying on statistical extrapolations of relatively short observation time series while ignoring potential temporal non-stationarity. However, future precipitation projections indicate an increase in the frequency and intensity of extreme rainfall events, as well as a shift in seasonality. This study aims to examine the impact of climate change on the 100-year flood (HF100) events of 98 hydrometric gauges within hydrological Bavaria. A hydrological climate change impact (CCI) modeling chain consisting of a regional Single Model Initial-condition Large Ensemble (SMILE) and a single hydrological model was created. The 50 equally probable members of the Canadian Regional Climate Model version 5 large ensemble (CRCM5-LE) were used to drive the hydrological model WaSiM (Water balance Simulation Model) to create a hydro-SMILE. As a result, a database of 1500 model years (50 members × 30 years) per investigated time period was established for extreme value analysis (EVA) to illustrate the benefit of the hydro-SMILE approach for a robust estimation of HF100 based on annual maxima (AM) and to examine the CCI on the frequency and magnitude of HF100 in different discharge regimes under a strong-emission scenario (RCP8.5). The results demonstrate that the hydro-SMILE approach provides a clear advantage for a robust estimation of HF100 using the empirical probability of 1500 AM compared to its estimation using the generalized extreme value (GEV) distribution of 1000 samples of typically available time series sizes of 30, 100, and 200 years. Thereby, by applying the hydro-SMILE framework, the uncertainty from statistical estimation can be reduced. The study highlights the added value of using hydrological SMILEs to project future flood return levels. The CCI of HF100 varies for different flow regimes, with snowmelt-driven catchments experiencing severe increases in frequency and magnitude, leading to unseen extremes that impact the distribution. Pluvial regimes show a lower intensification or even decline. The dynamics of HF100 driving mechanisms depict a decline in snowmelt-driven events in favor of rainfall-driven events, an increase in events driven by convective rainfall, and almost no change in the ratio between single-driver and compound events towards the end of the century.

Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble

Abstract. ​​​​​​​Severe floods with extreme return periods of 100 years and beyond have been observed in several large rivers in Bavaria in the last 3 decades. Flood protection structures are typically designed based on a 100-year event, relying on statistical extrapolations of relatively short observation time series while ignoring potential temporal non-stationarity. However, future precipitation projections indicate an increase in the frequency and intensity of extreme rainfall events, as well as a shift in seasonality. This study aims to examine the impact of climate change on the 100-year flood (HF100) events of 98 hydrometric gauges within hydrological Bavaria. A hydrological climate change impact (CCI) modeling chain consisting of a regional Single Model Initial-condition Large Ensemble (SMILE) and a single hydrological model was created. The 50 equally probable members of the Canadian Regional Climate Model version 5 large ensemble (CRCM5-LE) were used to drive the hydrological model WaSiM (Water balance Simulation Model) to create a hydro-SMILE. As a result, a database of 1500 model years (50 members × 30 years) per investigated time period was established for extreme value analysis (EVA) to illustrate the benefit of the hydro-SMILE approach for a robust estimation of HF100 based on annual maxima (AM) and to examine the CCI on the frequency and magnitude of HF100 in different discharge regimes under a strong-emission scenario (RCP8.5). The results demonstrate that the hydro-SMILE approach provides a clear advantage for a robust estimation of HF100 using the empirical probability of 1500 AM compared to its estimation using the generalized extreme value (GEV) distribution of 1000 samples of typically available time series sizes of 30, 100, and 200 years. Thereby, by applying the hydro-SMILE framework, the uncertainty from statistical estimation can be reduced. The study highlights the added value of using hydrological SMILEs to project future flood return levels. The CCI of HF100 varies for different flow regimes, with snowmelt-driven catchments experiencing severe increases in frequency and magnitude, leading to unseen extremes that impact the distribution. Pluvial regimes show a lower intensification or even decline. The dynamics of HF100 driving mechanisms depict a decline in snowmelt-driven events in favor of rainfall-driven events, an increase in events driven by convective rainfall, and almost no change in the ratio between single-driver and compound events towards the end of the century.

Impact of climate change on future flood susceptibility projections under shared socioeconomic pathway scenarios in South Asia using artificial intelligence algorithms

This study investigated the impact of climate change on flood susceptibility in six South Asian countries Afghanistan, Bangladesh, Bhutan, Bharat (India), Nepal, and Pakistan—under two distinct Shared Socioeconomic Pathway (SSP) scenarios: SSP1-2.6 and SSP5-5.8, for 2041–2060 and 2081–2100. To predict flood susceptibility, we employed three artificial intelligence (AI) algorithms: the K-nearest neighbor (KNN), conditional inference random forest (CIRF), and regularized random forest (RRF). Predictions were based on data from 2452 historical flood events, alongside climatic variables measured over monthly, seasonal, and annual timeframes. The innovative aspect of this research is the emphasis on using climatic variables across these progressively condensed timeframes, specifically addressing eight precipitation factors. The performance evaluation, employing the area under the receiver operating characteristic curve (AUC) metric, identified the RRF model as the most accurate, with the highest AUC of 0.94 during the testing phase, followed by the CIRF (AUC = 0.91) and the KNN (AUC = 0.86). An analysis of variable importance highlighted the substantial role of certain climatic factors, namely precipitation in the warmest quarter, annual precipitation, and precipitation during the wettest month, in the modeling of flood susceptibility in South Asia. The resultant flood susceptibility maps demonstrated the influence of climate change scenarios on susceptibility classifications, signalling a dynamic landscape of flood-prone areas over time. The findings revealed variable trends under different climate change scenarios and periods, with marked differences in the percentage of areas classified as having high and very high flood susceptibility. Overall, this study advances our understanding of how climate change affects flood susceptibility in South Asia and offers an essential tool for assessing and managing flood risks in the region.

Exploring adaptation strategies for smallholder farmers in dryland farming systems and impact on pearl millet production under climate change in West Africa

Understanding and identifying appropriate adaptation optons for cropping systems and management practices at spatial and temporal scales is an important prerequisite for scaling. Pearl millet (Pennisetum glaucum (L) R. Br.) could be regarded as a risk-reducing measure crop under climate change when coupled with tactical agronomic management practices. In this study, we assess the impacts of adaptation strategies such as cultivar type, planting windows, and fertilizer strategies on pearl millet production under rainfed farming systems over Nigeria and Senegal using the Agricultural Production Systems Simulator (APSIM) model. The impact of climate change on millet yield was evaluated using a validated APSIM-millet module that utilized yield data collected through participatory research and extension approach (PREA) in contrasting environments. The climate model projections for the mid-century period (2040–2069) were compared against a baseline period of 1980–2009 for both locations. During the simulation, two millet varieties (improved local and dual-purpose) with two sowing regimes were considered comparing traditional farmers’ sowing window (dry sowing) and agronomic sowing window (planting based on the onset of the rainfall) at three different fertilizer levels [low (23 kg N ha−1), medium (40.5 kg N ha−1), and high (68.5 kg N ha−1) respectively]. The performance of the APSIM-millet module was found to be satisfactory as indicated by the low Root Means Square Error (RMSE) and Normalized Root Mean Square Error (NRMSE) values. The range for grain yield was between 17.7% and 25.8%, while for AGB it was between 18.6% and 21.4%. The results showed that farmers’ sowing window simulated slightly higher grain yield than the agronomic sowing window for improved local millet cultivar indicating yield increased by 8–12%. However, the projected changes in the mid-century (2040–2069) resulted in a decline in yield against baseline climate for both varieties and sowing windows, indicating the negative impact of climate change (CC) on yield productivity. The comparison between dual-purpose millet and improved local millet indicates that disseminating the improved millet variety and implementing early sowing could be an effective adaptation strategy in reducing risks and losses caused by climate change. Similarly, low magnitude impacts simulated on grain yield (< −8% in Nigeria compared to > −8% in Senegal) even though both locations are in the same agroecological zone.

Exploring adaptation strategies for smallholder farmers in dryland farming systems and impact on pearl millet production under climate change in West Africa

Understanding and identifying appropriate adaptation optons for cropping systems and management practices at spatial and temporal scales is an important prerequisite for scaling. Pearl millet (Pennisetum glaucum (L) R. Br.) could be regarded as a risk-reducing measure crop under climate change when coupled with tactical agronomic management practices. In this study, we assess the impacts of adaptation strategies such as cultivar type, planting windows, and fertilizer strategies on pearl millet production under rainfed farming systems over Nigeria and Senegal using the Agricultural Production Systems Simulator (APSIM) model. The impact of climate change on millet yield was evaluated using a validated APSIM-millet module that utilized yield data collected through participatory research and extension approach (PREA) in contrasting environments. The climate model projections for the mid-century period (2040–2069) were compared against a baseline period of 1980–2009 for both locations. During the simulation, two millet varieties (improved local and dual-purpose) with two sowing regimes were considered comparing traditional farmers’ sowing window (dry sowing) and agronomic sowing window (planting based on the onset of the rainfall) at three different fertilizer levels [low (23 kg N ha−1), medium (40.5 kg N ha−1), and high (68.5 kg N ha−1) respectively]. The performance of the APSIM-millet module was found to be satisfactory as indicated by the low Root Means Square Error (RMSE) and Normalized Root Mean Square Error (NRMSE) values. The range for grain yield was between 17.7% and 25.8%, while for AGB it was between 18.6% and 21.4%. The results showed that farmers’ sowing window simulated slightly higher grain yield than the agronomic sowing window for improved local millet cultivar indicating yield increased by 8–12%. However, the projected changes in the mid-century (2040–2069) resulted in a decline in yield against baseline climate for both varieties and sowing windows, indicating the negative impact of climate change (CC) on yield productivity. The comparison between dual-purpose millet and improved local millet indicates that disseminating the improved millet variety and implementing early sowing could be an effective adaptation strategy in reducing risks and losses caused by climate change. Similarly, low magnitude impacts simulated on grain yield (< −8% in Nigeria compared to > −8% in Senegal) even though both locations are in the same agroecological zone.

Vocational and University Paramedicine Education

This paper highlights key research areas within paramedicine education in Australia. Firstly, it discusses the need for a comparative analysis of accreditation standards, focusing on the recent shift towards a pre-employment model and its impact on program content, particularly the balance between theoretical and practical components. Secondly, it addresses the importance of exploring the influence of ethics education on paramedic practice, investigating how a robust ethical foundation acquired during education translates into ethical practices in real-world scenarios. Additionally, it suggests conducting a comparative study of international models to understand different education approaches, emphasising the importance of identifying best practices to enhance paramedic education in Australia. Lastly, it emphasises the significance of assessing the impact of accreditation changes in 2018, specifically the shift in accreditation responsibilities from the Council of Ambulance Authorities to the Paramedicine Board of Australia, aiming to understand its implications on the quality and consistency of paramedicine education across various institutions. Overall, this paper highlight the critical research gaps and areas of investigation essential for advancing paramedicine education and improving the quality of paramedic training in Australia.

Will urban scale affect health services inequity? The empirical evidence from cities in China.

The equity of public resources triggered by city shrinkage is a global challenge. Significantly, the impact of city shrinkage on the allocation of health service resources needs to be better understood. This study explores the impact of population change on government investment and health service delivery in shrinking cities. Using data from China's Urban Statistical Yearbook (2010-2020), we employ regression discontinuity (RD) and fixed-effect models to examine the causal relationship between city shrinkage and health service provision. Shrinking cities show significant disparities in health resources, particularly in bed numbers (-1,167.58, p < 0.05) and doctor availability (-538.54, p < 0.05). Economic development (p < 0.01) and financial autonomy (p < 0.01) influence hospital bed distribution. Investments in public services (primary schools and teachers, p < 0.01) affect health resource delivery. Robustness tests support our results. This study reveals how city shrinkage disrupts health service provision and equity, establishing a causal relationship between city shrinkage/expansion and health resource allocation, emphasizing the imbalance caused by urban population changes. City expansion intensifies competition for health resources, while shrinking cities struggle to provide adequate resources due to government reluctance. Policymakers should adapt health resource allocation strategies to meet patient demands in changing urban landscapes.

Remote Sensing Assessment of Water Resources, Vegetation, and Land Surface Temperature in Eastern Saudi Arabia: Identification, Variability, and Trends

Saudi Arabia has one of the biggest water shortages and the least vegetation in the world, which is presumed to provoke this problem further due to climate change. Therefore, the present study investigates the water, vegetation, and temperature over Al-Asfar Lake region, Al Ahsa, Eastern province of Saudi Arabia using the Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST: °C) from Landsat-8 based operational land imager (OLI) measurements for the period 2013 to 2023. This study presented annual and seasonal (dry months: June–September and wet months: December–April) spatiotemporal distribution and variations, calculated their absolute change and trends, and examined their relationship. Results showed positive NDWI values over Al-Asfar Lake, indicating waterbodies; while positive NDVI values on the lake's bank, signifying vegetation. Notably, there were significant temporal variations in water and vegetation observed on annual, seasonal, and monthly scales. The study also found an overall decrease in vegetation areas of 5.36 km2 in 2023 compared to 2013, while waterbodies increased by 8.83 km2. The trend analysis using area-averaged data demonstrated that NDWI increased on annual (0.0075/year) and seasonal (dry: 0.0083/year and wet: 0.0049/year) scales, while NDVI decreased (annual: 0.0066/year, dry: 0.0083/year, and wet: 0.0009/year). Moreover, LST was recorded least amount over waterbodies (28.23 °C) and vegetation (32.45 °C) covered areas compared to the entire lake region (38.43 °C), respectively. Remark, LST displayed decreasing trends over waterbodies (−0.05/year), followed by vegetation (−0.17/year), and the entire lake region (−0.0001/year), signifying that water and vegetation are vital components to controlling land surface temperature in this region. Finally, the LST showed a positive correlation with NDVI and negative correlation with NDWI. There may be a direct and indirect impact of climate change upon NDVI, LST, and NDWI as shown by the decreases in NDVI and LST and an increase in NDWI. This study can be considered as a base document to monitor waterbodies, vegetation cover, and temperature changes using remote sensing measurements of NDWI, NDVI, and LST, which will assist policymakers in developing water resource management, irrigation planning, and environmental monitoring strategies.

A study of irrigation conflict in Khageri irrigation project

While Nepal is rich in water resources, there are also plenty of water related problems. Issues like water scarcity; improper water allocation, distribution, collection of water fees, farmers’ cooperation, performance of water users association etc give rise to water-induced conflict. As there is a wide range of such issues, this article examines only the conflict of water in the sector of irrigation and its management practices. This article assesses the major dimensions of irrigation management and how these dimensions give rise to conflict using a case study of the Khageri irrigation project (KIP). This study is based on the qualitative design including key informant interviews (KII), focus group discussion (FGD) and participant observation. The informants cover key stakeholders like members of water users associations, elderly farmers, local government officials, etc. Some of the major issues concern to conflict is the denial of riparian rights, repair and maintenance activities related to the canal, resource rights dilemmas, human encroachment to the canal, park control and legal restrictions etc. In addition, impact of climate change is one of the major factors that escalate conflict in the study area. Theory of co-management, Hardin’s tragedy of commons -position, interest, and needs (PIN), the best alternative to a negotiated agreement (BATNA), etc. were used as a theoretical lenses to analyze the findings. Analysis through these theories has further given rise to some other new theoretical models like neo-liberal socioeconomic resource management.

Future changes in soil salinization across Central Asia under CMIP6 forcing scenarios

AbstractSoil salinization is a critical environmental and socio‐economic concern with global implications, and its severity is expected to amplify under changing climate. The impact of climate change on salinization in Central Asia is still not fully understood. This study addresses this gap by employing a digital soil mapping (DSM) framework. Cubist, random forest (RF), and quantile regression forests (QRF) are utilized to project variations in soil surface salinity (0‐10 cm) in Central Asia from 2025 to 2100 under two shared socio‐economic pathways (SSPs): SSP2‐4.5 and SSP5‐8.5. These models are developed using data from 20 global climate models (GCMs) obtained from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results reveal that the RF model exhibits superior predictive capability in estimating soil salinity. RF performed on the calibration set with a coefficient of determination (R2) of 0.86, root mean square error (RMSE) of 9.84 and 9.90 dS m−1, ratio of performance to interquartile distance (RPIQ) of 3.09 and 3.07, and a Nash–Sutcliffe efficiency (NSE) of 0.86. The multi‐GCM ensemble means revealed the potential for varying degrees of salinization in Central Asia, with higher levels predominantly observed in the southeast and southwest of the study area, particularly downstream of the river and in the lakeside areas. Temporal analysis of soil salinity evolution reveals an overall increase in salinity across the region, with more notable changes projected under SSP5‐8.5. Specifically, the projected increase rate in soil salinity for Central Asia was 0.0005 dS m−1/year under SSP2‐4.5 and 0.01 dS m−1/year under SSP5‐8.5. Turkmenistan is notable for possessing the highest regional average of soil salinity, with the exception of a declining trend observed within this area. The remaining regions of Central Asia exhibit an upward trend in average soil salinity, particularly noteworthy under the SSP5‐8.5 scenario, where variations in soil salinity are more obvious. These findings hold significant potential in enhancing our understanding of how Central Asia responds to global change, advances toward sustainable development, and enhances comprehension of the dynamics within the region.

Archaeology, climate change and human adaptation in southern Africa: Evidence from Mapela and Little Mapela, southern Africa

In Africa south of the Zambezi River, archaeologists and other experts have long explored the impact of climate and environmental changes to the development of ancient civilizations during the Iron Age (CE 200–1900). Some of the prevailing thought is however still rooted in environmental deterministic models informed by selected ethnographies, stable isotopes and archaeological evidence. For instance, the drought brought by the medieval Little Ice Age is assumed to have collapsed the civilisation at Mapungubwe in the Shashi-Limpopo valley around 1300 CE. And yet, within the wider region, and in similar ecological settings, upstream (Shashi and Upper Limpopo) and downstream civilisations (Lower Limpopo), persisted and thrived through the same climatic challenges. We draw on African cosmologies, resilience theory and archaeological evidence from Mapela and Little Mapela to spotlight adaptation strategies utilised by their inhabitants to build resilience through time. The main conclusion is that even in cases of climatic extremes, humans responded to opportunities and constraints in context specific ways.