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This study assessed forest cover change from 1985 to 2016, analyzed community perception on forest cover change and its drivers, and suggested possible solutions in northern Ethiopia. Landsat images of 1985, 2000 and 2016, household interviews and focus group discussions were used. While dense forests and open forests increased by 8.2% and 32.3% respectively between 1985 and 2000, they decreased by 10.4% and 9.8% respectively from 2000 to 2016. Grasslands and cultivated land decreased in the first period by 37.3% and 5.5% but increased in the second period by 89.5% and 28.5% respectively. Fuel wood collection, cultivated land expansion, population growth; free grazing, logging for income generation and drought were the major drivers of the change reported by local communities. Soil erosion, reduction in honey bee production, flooding and drought were the most perceived impacts of the changes. Most of the farmers have a holistic understanding of forest cover change. Strengthening of forest protection, improving soil and water conservation, enrichment planting, awareness creation, payment for ecosystem services and zero grazing campaigns were mentioned as possible solutions to the current state of deforestation. In addition, concerted efforts of conservation will ensure that the forests’ ecosystems contribute to increased ecosystem services.

Big data analytics (BDA) enhances knowledge and decision-making. Despite its importance, the connection between technical progress and political change is neglected in the administrative process. Most studies focus on e-government, e-governance, and how technology can improve existing operations of the bureaucracy. However, this article aims to explore the potential of BDA for public policy systems and provide a linkage for the transformation toward digital and smart governance using preferred reported items for systematic review and meta-analysis (PRISMA) approach to reveal the relevant documents and narrative review approach to interpret the application of BDA at each step of the public policy system. In addition, this study identifies several common public policy-related big data sources and techniques that could be used at the various stages of the public policy process. This study argues that BDA has the potential to be used for policy formulation in the four main phases—planning, design, service delivery, and evaluation. Most studies confirm its potential in the policy process for taxation, health, education, transportation, law, economy, and social system. This study reveals that it is also suitable for public policy execution stages, such as public supervision, public regulation, service delivery, and policy feedback. Previous studies have indicated that the application of BDA can transform traditional or manual governance systems into digital and smart governance. We contend that the policy cycle should be seen as a dynamic and iterative process characterized by continuous evolution. Though each step of transformation has its unique challenges in handling BDA and maintaining the Information and Communication Technology (ICT) infrastructure, it can ensure an accurate, prompt, and context-oriented public policy system. These insights provide a novel outlook on effectively managing the interplay between innovation and traditional approaches in the realm of public policy development. Plain Language Summary Importance: Big data analytics (BDA) enhances knowledge and decision-making. Despite its importance, the connection between technical progress and political change is neglected in the administrative process. Most studies focus on e-government, e-governance, and how technology can improve existing operations of the bureaucracy. Aims: However, this article aims to explore the potential of BDA for public policy systems and provide a linkage for the transformation toward digital and smart governance using preferred reported items for systematic review and meta-analysis (PRISMA) approach to reveal the relevant documents and narrative review approach to interpret the application of BDA at each step of the public policy system. In addition, this study identifies several common public policy-related big data sources and techniques that could be used at the various stages of the public policy process. Findings: This study argues that BDA has the potential to be used for policy formulation in the four main phases—planning, design, service delivery, and evaluation. Most studies confirm its potential in the policy process for taxation, health, education, transportation, law, economy, and social system. This study reveals that it is also suitable for public policy execution stages, such as public supervision, public regulation, service delivery, and policy feedback. Implications: Previous studies have indicated that the application of BDA can transform traditional or manual governance systems into digital and smart governance. Though each step of transformation has its unique challenges in handling BDA and maintaining the Information and Communication Technology (ICT) infrastructure, it can ensure an accurate, prompt, and context-oriented public policy system.

We propose renin angiotensin system (RAS) peptides are critical in wound reparative processes such as in acute respiratory distress syndrome (ARDS). Their role in predicting clinical outcomes in ARDS has been unexplored; thus, we used a targeted metabolomics approach to investigate them as potential predictors of outcomes. Thirty-nine ARDS patients were enrolled within 24 hours of ARDS diagnosis. Plasma RAS peptide levels were quantified at study entry and 24, 48 and 72 hours using a liquid chromatography-mass spectrometry based metabolomics assay. RAS peptide concentrations were compared between survivors and non-survivors, and were correlated with clinical and pulmonary measures. Angiotensin I (Ang-I or A(1-10)) levels were significantly higher in non-survivors at study entry and 72 hours. ARDS survival was associated with lower A(1-10) concentration (OR 0.36, 95% CI 0.18-0.72, p = 0.004) but higher A(1-9) concentration (OR 2.24, 95% CI 1.15-4.39, p = 0.018), a biologically active metabolite of A(1-10) and an agonist of angiotensin II receptor type 2. Survivors had significantly higher median A(1-9)/A(1-10) and A(1-7)/A(1-10) ratios than the non-survivors (p = 0.001). Increased A(1-9)/A(1-10) ratio suggests that angiotensin converting enzyme II (ACE2) activity is higher in patients who survived their ARDS insult while an increase in A(1-7)/A(1-10) ratio suggests that ACE activity is also higher in survivors. A(1-10) accumulation and reduced A(1-9) concentration in the non-survivor group suggest that ACE2 activities may be reduced in patients succumbing to ARDS. Plasma levels of both A(1-10) and A(1-9) and their ratio may serve as useful biomarkers for prognosis in ARDS patients.

Optimizing sustainability among smallholder farms poses challenges due to inherent trade‐offs. In the study of organic and conventional cocoa smallholder farming in Ghana, 398 farms are assessed using the Food and Agriculture Organsation of the United Nations (FAO) Sustainability Assessment of Food and Agriculture systems (SAFA) Guidelines and Sustainability Monitoring and Assessment Routine (SMART)‐Farm Tool. Organic farming exhibited synergies in environmental aspects (e.g., soil quality, energy efficiency) and between biodiversity conservation and risk management. Conventional farming showed potential vulnerabilities, including trade‐offs with long‐range investments (e.g., chemical inputs) and species diversity. Both systems demand tailored approaches for short‐term economic and environmental sustainability, aligning with community‐wide long‐term goals. To mitigate trade‐offs in conventional farming, smallholders should adopt practices like material reuse, recycling, and recovery within their operations. Optimizing sustainability among smallholder farms poses challenges due to inherent trade‐offs. In the study of organic and conventional cocoa smallholder farming in Ghana, 398 farms are assessed using the FAO SAFA Guidelines and SMART‐Farm Tool. Organic farming exhibited synergies in environmental aspects (e.g., soil quality, energy efficiency) and between biodiversity conservation and risk management. Conventional farming showed potential vulnerabilities, including trade‐offs with long‐range investments (e.g., chemical inputs) and species diversity. Both systems demand tailored approaches for short‐term economic and environmental sustainability, aligning with community‐wide long‐term goals. To mitigate trade‐offs in conventional farming, smallholders should adopt practices like material reuse, recycling, and recovery within their operations.

BackgroundForests play an important role in mitigating global climate change by capturing and sequestering atmospheric carbon. Quantitative estimation of the temporal and spatial pattern of carbon storage in forest ecosystems is critical for formulating forest management policies to combat climate change. This study explored the effects of land cover change on carbon stock dynamics in the Wujig Mahgo Waren forest, a dry Afromontane forest that covers an area of 17,000 ha in northern Ethiopia.ResultsThe total carbon stocks of the Wujig Mahgo Waren forest ecosystems estimated using a multi-disciplinary approach that combined remote sensing with a ground survey were 1951, 1999, and 1955 GgC in 1985, 2000 and 2016 years respectively. The mean carbon stocks in the dense forests, open forests, grasslands, cultivated lands and bare lands were estimated at 181.78 ± 27.06, 104.83 ± 12.35, 108.77 ± 6.77, 76.54 ± 7.84 and 83.11 ± 8.53 MgC ha−1 respectively. The aboveground vegetation parameters (tree density, DBH and height) explain 59% of the variance in soil organic carbon.ConclusionsThe obtained estimates of mean carbon stocks in ecosystems representing the major land cover types are of importance in the development of forest management plan aimed at enhancing mitigation potential of dry Afromontane forests in northern Ethiopia.

Heat stress adversely affects tomato production worldwide. Breeding thermotolerant varieties is critical to adapt to increased heat stress but tomato has a narrow genetic base for heat tolerance. Identification of new sources of heat-tolerant germplasm is important to understand physiological and molecular mechanisms of adaptation to heat stress and to broaden the genetic base of heat tolerance in tomato. Here, we screened a germplasm collection comprised of 42 tomato entries using 19 quantitative (physiological, reproductive, and morphological) and five qualitative traits. The plants were grown under long term mild heat stress with temperatures and relative humidities ranging from 23.3 to 37 °C, and 47 to 100%, respectively. The analysis of variance revealed significant differences among the entries for all the quantitative traits. Biologically significant associations were recorded for many traits. Proportion of viable pollen was not associated with fruit set percentage. The clustering analysis groups the germplasm into five clusters with a clear distinction between Solanum lycopersicum and Solanum pimpinellifolium entries. We also observed differences between the entries based on their origins. Known thermo-tolerant entries were found in Clusters 3 (eg.: LA2662, LA3317, LA3120) and 4 (e.g.: CL5915-93D4-1-0, CLN1621L, LA2661). Lines BJ01, BJ02 from Republic of Benin, and WAC1 and ATS020 from Ghana in Cluster 3 are potential new sources of thermo-tolerance in tomato. Generation of hybrids from parents belonging to the clusters 1 to 4 identified in this study would improve heterosis for heat tolerance traits in tomato. Useful traits like high pollen viability and high inflorescence numbers per plant could be introgressed from S. pimpinellifolium entries into the cultivated tomato. Our study provides important information to improve heat tolerance in tomato.

Heat stress is a major limiting factor for crop productivity. Tomato is highly sensitive to heat stress, which can result in a total yield loss. To adapt to current and future heat stress, there is a dire need to develop heat tolerant cultivars. Here, we review recent attempts to improve screening for heat tolerance and to exploit genetic and genomic resources in tomatoes. We provide key factors related to phenotyping environments and traits (morphological, physiological, and metabolic) to be considered to identify and breed thermo-tolerant genotypes. There is significant variability in tomato germplasm that can be harnessed to breed for thermo-tolerance. Based on our review, we propose that the use of advanced backcross populations and chromosome segments substitution lines is the best means to exploit variability for heat tolerance in non-cultivated tomato species. We applied a meta quantitative trait loci (MQTL) analysis on data from four mapping experiments to co-localize QTL associated with heat tolerance traits (e.g., pollen viability, number of pollen, number of flowers, style protrusion, style length). The analysis revealed 13 MQTL of which 11 were composed of a cluster of QTL. Overall, there was a reduction of about 1.5-fold in the confidence interval (CI) of the MQTL (31.82 cM) compared to the average CI of individual QTL (47.4 cM). This confidence interval is still large and additional mapping resolution approaches such as association mapping and multi-parent linkage mapping are needed. Further investigations are required to decipher the genetic architecture of heat tolerance surrogate traits in tomatoes. Genomic selection and new breeding techniques including genome editing and speed breeding hold promise to fast-track development of improved heat tolerance and other farmer- and consumer-preferred traits in tomatoes.

The study examined the perception of undergraduate students towards choosing the broiler value chain (BVC) business as a vocation after graduation. A questionnaire was used to collect cross-sectional data from 728 students in 4 universities. The findings show that the overall perception index of students somewhat agrees that there were sociocultural, economic, government policy, and resource availability factors that constrained their ability to engage in the BVC. Students also agreed that government policies were inimical to BVC businesses, which could affect their decision to engage in the BVC after graduation. The results of the three-way factorial MANOVA did not show any statistically significant difference. Hence, any policy aimed at increasing the participation of students in BVC business after graduation can be designed without exception. The components extracted following the PCA were sociocultural, economic, and production resource. This implies that the three factors are influencing students’ decisions to engage in the BVC after graduation. Available literature on the engagement of young people in agriculture in Ghana has predominantly focussed on agriculture in general and a few on cocoa, but not the livestock or broiler industry. This study, therefore, highlights the role perception plays in the decision-making process of students in choosing to engage in the BVC as a vocation. It is recommended that the government implement policies that create an enabling business environment for BVC businesses to be profitable, ensure national macroeconomic stability, and increase access to land and productive resources to shape positively the perception of students.

Background Cassava is a crucial food security crop in Togo and the most significant root crop in terms of area under cultivation and production volume. However, its production is predominantly carried out by subsistence farmers using low-yielding landraces. Several constraints impede cassava production, threatening its sustainability in the country. The low adoption of improved varieties developed by the International Institute of Tropical Agriculture (IITA) underscores the need for a participatory approach to research and development. This study aimed to identify the cassava varieties grown, major production constraints, farmers' trait preferences, and perceptions of Cassava Mosaic Disease (CMD) through Participatory Rural Appraisal (PRA). Methods The study employed a multistage random sampling procedure to select regions, districts, and villages based on cassava production levels. The survey involved 83 men and 57 women in group interviews and 600 farmers in individual interviews: 200 in the forest–savanna transition, 180 in the rainforest, 120 in the wet savanna, and 100 in the dry savanna. Content analysis was used for qualitative data, and quantitative data were analyzed using descriptive statistics and comparative analyses, including Chi-square tests to assess differences in perceptions and preferences. Results The PRA revealed key constraints to cassava production, including inadequate capital, CMD, post-harvest physiological deterioration (PPD), and the non-availability of clean planting materials. Traits such as high yield, pest and disease resistance, early maturity, high dry matter content, delayed root deterioration, poundability, and taste were highly valued by farmers. CMD was identified as a significant disease, causing yield losses, with various causes and management practices reported. The study highlighted the necessity for a sustainable cassava seed system, as farmers pointed out the lack of improved varieties and clean planting materials. Conclusion This study provides essential insights into cassava farming practices, production constraints, and farmers' preferred traits, laying the groundwork for a participatory breeding program in Togo. Addressing low-yielding varieties and diseases, particularly CMD, is critical for enhancing cassava production and ensuring food security.

Although cocoa production addresses the livelihoods of several rural households, there is a global concern about its negative impact on the physical environment. How does this trade-off play out in different farming systems? This paper examined the social and environmental trade-offs and synergies of organic and conventional cocoa farming systems. Using the ‘SMART Farm-tool’ and principal component analysis approach, data collected from 398 cocoa farmers in five communities in the Atwima Mponua District of Ghana were analysed. We found that social and environmental trade-offs in the organic cocoa farming system are labour-related (EV = −0.38). The social and environmental trade-offs in the conventional cocoa farming system are health and safety and biodiversity-related (EV = −0.64). The organic farming system recognises indigenous knowledge in promoting biodiversity conservation and land degradation reduction (EV = −0.57). There can be more synergy than trade-off in both systems if support for capacity building and credit is provided and indigenous knowledge sharing is prioritised among low-income and vulnerable farmers. In this way, the labour conditions, biodiversity conservation, and health and safety-related concerns will be addressed. Addressing labour concerns in organic cocoa farming involves improving efficiency and working conditions. Strategies include training programs for organic techniques, introducing technology for tasks, and adhering to fair labour standards. This ensures labour concerns are addressed across the supply chain.