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The coffee species Coffea arabica is facing numerous challenges regarding climate change, pests and disease pressure. Improved varieties will be part of the solution. Making optimal use of the scarce genetic diversity of the species is hence essential. In this paper, we present the first study of C. arabica genetic diversity covering its complete native habitat in Ethiopia together with its main domestication centers: Yemen and Hararghe region in Ethiopia. All in all, 555 samples were analyzed with a set of Single Sequence Repeat markers. Through admixture genetic analysis, six clusters were identified. A total of two "Core Ethiopian" clusters did not participate in the domestication of the species. There were four clusters that were part of the "Domestication Pathway" of C. arabica. The first one was named "Ethiopian Legacy" as it represents the genetic link between "Core Ethiopia" and the "Domestication Pathway" in Yemen and Hararghe. The geographic origin of this cluster in Ethiopia was the south of Ethiopia, namely Gedio, Guji and Sidama, which hence appears as the source of coffee seeds that led to the domestication of C. arabica. In Yemen, in addition to the "Ethiopian Legacy" cluster, we confirmed the "Typica/Bourbon" and "New-Yemen" clusters. In Hararghe, the "Harrar" cluster, never described before, likely originates from a re-introduction of domesticated coffee from Yemen into this region of Ethiopia. Cultivated varieties around the world today originate from the "Ethiopian Legacy" and "Typica/Bourbon" clusters and but none are related to the "new-Yemen" and "Harrar" clusters. Implications for breeding strategies are discussed. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to undertake a narrative review on climate change, institutional quality, and SDGs within the context of Yemen. The methodology is a broad study of past and recent academic works related to the topic's keywords. In essence, a narrative review has been undertaken to incorporate the three interlacing issues; climate change, institutional quality, and SDG in the context of Yemen. The present research work reinforces the evidence that climate change effects are particularly more catastrophic in regions already under political, socio-economic, and cultural pressures. Eventually, the attainment of SDGs become increasingly challenging in contexts with intense climate variability and native disturbances. Besides, the lack of quality institutions and strong governance put in peril the stability of the country, thereby making it more prone to conflicts. This eventually leads to the formation of a vicious circle where low institutional quality fecund more conflicts, which in turn further destabilizes state institutions. Overall, climate change is making matters worse for countries like Yemen, and hence this study provides an insight into the Yemenite society and economy. Since this is a narrative review with an interpretive approach, further studies should aim to engage in more econometric analysis covering the interference relationships between climate change, institutional quality, and SDGs, especially in countries facing the turmoils of war and conflict. [ABSTRACT FROM AUTHOR]

Heritage buildings are considered unique assets with a significant value for the country where they are situated that must be conserved or preserved for the coming generations. However, heritage sites, as any other site where a construction is present, experience tremendous risks that impact both the condition and the withstanding of the building or asset they include. Therefore, a risk management framework is essential for these sites and buildings, in particular to be able to decide how to respond and act upon foreseeable risks when they occur or even before experiencing them. This study starts with investigating the most dominant risks in the heritage buildings context with a focus on Yemeni sites, and consequently 38 Yemeni experts in the field of heritage building management were surveyed to examine the identified risks in three case study heritage sites in Yemen. The significance of the risks as well as their impact, likelihood, and detectability levels were measured using an analytic hierarchy process (AHP) basis that reduces the subjectivity of the expert opinions. After risks were analyzed, a suitable response action was therefore suggested to manage and minimize risk impacts as much as possible. In addition to the relative scoring for the priority of each identified risk, an overall risk proneness metric is presented in this paper that can be used to compare the vulnerability of different heritage buildings and/or sites for a strategic efficient budget allocation for the management and preservation of those areas. The preliminary results revealed that armed conflicts, climate change, and flooding are three of the most critical risk factors in Yemeni heritage buildings. This framework is expected to aid heritage building managers in identifying the correct course of actions to prevent or mitigate risks from disturbing the heritage sites and help preserve their value and significance. [ABSTRACT FROM AUTHOR]

Understanding climate extremes and indices is crucial for addressing climate change impacts, including the increased variability in local weather patterns and extreme events. Previous studies on the Arabian Peninsula (AP) have been limited by sparse station data and restricted spatial coverage. To overcome this limitation, this paper aims to assess the spatial distribution and temporal trends of temperature and precipitation indices suggested by the Expert Team on Climate Change Detection and Indices (ETCCDI) using ERA5 reanalysis data from 1951 to 2020 for the AP. Additionally, this study investigated the changes relative to the reference period (1951–1980). The modified Mann-Kendall test and Sen's Slope estimator are utilized to detect significant trends and estimate their magnitude. Results revealed that ERA5 was consistent with previous studies that utilized in-situ station data, which offers a more detailed picture of the affected areas. The findings indicated a significant warming trend in temperature indices, with an increase of over 1 °C per decade observed across several areas, including the northern AP, and certain regions experiencing a discrepant change of 3 °C increase compared to the reference period. Changes in rainfall indices indicate a shift in rainfall patterns from the AP's fertile southwest regions towards more intense patterns in specific eastern regions, including Oman, Kuwait, Saudi Arabia, and Yemen. However, the precipitation temporal trends are weak in magnitude and variable spatially, with dominant decreases in both intensity (-10 mm per decade) and frequency indices (-5 days per decade). Some locations are subject to the combined effects of most heatwave indicators simultaneously, while flood indicators and yet others by drought indicators influence others. All these locations have been accurately identified in this study. The findings provide valuable information regarding the region's climate change vulnerability and adaptation needs. [Display omitted] • Prior studies relied on limited station data, short period, and MK trend test. • Extremes are assessed using ERA5, ETCCDI, Modified-MK, and Sen's Slope. • Affected areas are identified, and valuable insights for policymakers are set. • Significant warming trend: >1 °C/decade and > 2 °C change from reference period. • Spatiotemporal trends of precipitation are weak in magnitude and variable spatially. [ABSTRACT FROM AUTHOR]

The critical impacts of climate change have imposed an imperative for accelerated global actions to curb the greenhouse gas (GHG) emission. The “historic Paris agreement” on climate change as well as the Sustainable Energy for All (SE4All) initiative are among the well-known foundations to restrict GHG emission by promoting renewable energy (RE) across the globe. In Yemen, a country with abundant RE resources, feasibility studies to explore RE potentiality are scarce. This paper first reviews the historical development of RE technologies as well as the RE prospects in Yemen. This is followed by a comprehensive feasibility study of an off-grid renewable-based power system for rural electrification in Yemen. Shafar, a key district in Hajjah province, is considered as a case study. Five different cases (various combination of energy resources) of power system have been investigated with a key objective to find out the most suitable hybrid system that yields the minimal system cost as well as environmental impact. In this work, the hybrid optimization model for electric renewables (HOMER) is employed to perform the optimization and sensitivity analysis. The simulation results indicate that combination of photovoltaic and wind energy system achieves potential reduction of 100% in the CO 2 emission, along with 30% decrement in the cost of energy (COE). Comparatively, the photovoltaic/wind/diesel energy system could only achieve 70% reduction in the CO 2 emission but 45% decrement in the COE. Furthermore, the latter case exhibits a superior system robustness to RE variability in comparison with the former case. Finally, the study recommends the deployment of the proposed hybrid system (photovoltaic/wind/diesel) as the means for Yemen (and other similar context countries) to sustainably achieve Paris agreement targets and the SE4All initiatives, simultaneously. [ABSTRACT FROM AUTHOR]

This paper outlines the methodology followed in the study of climate change impact on water resources in Yemen and presents initial results on the vulnerability of the water resources system. The selected modeling strategy is used for the first time in climate change assessment studies and is briefly discussed. This strategy comprised 4 interacting models: a Rainfall-Runoff Model (RRM), an Irrigation Simulation Model (ISM), a Groundwater Simulation Model (GSM), and an Economic Policy Model (EPM). Adequate indication of the water system's sensitivity to climate change in arid and semiarid regions can only be achieved when appropriate temporal and spatial scales of the assessment are used. For instance, only hourly or daily time step models can capture climate impacts on floods of ephemeral wadis. The degree of accuracy required should also be determined by the scarcity/availability of the resources. [ABSTRACT FROM AUTHOR]

The sensitivity of tropical cyclone (TC) projection results to different models and the detection and tracking scheme used is well established. In this study, future climate projections of TC activity in the North Indian Ocean (NIO) are assessed with a model‐ and basin‐independent detection and tracking scheme. The scheme is applied to selected models from the coupled model intercomparison project phase 5 (CMIP5) experiments forced under the historical and representative concentration pathway 8.5 (RCP8.5) conditions. Most models underestimated the frequency of early season (April–June) TCs and contained genesis biases equatorward of ~7.5°N in comparison to the historical records. TC tracks detected in reanalysis and model data were input to a clustering algorithm simultaneously, with two clusters in the Arabian Sea and two in the Bay of Bengal (k = 4). Projection results indicated a slight decrease of overall TC genesis frequency in the NIO, with an increase of TC genesis frequency in the Arabian Sea (30–64%) and a decrease in the Bay of Bengal (22–43%), consistent between clusters in each of these sub‐regions. These changes were largely due to changes in the pre‐monsoon season (April–June) where Bay of Bengal TCs significantly decreased, consistent with changes in vertical ascent. Northern Arabian Sea TCs significantly increased during the pre‐monsoon season, consistent with changes in vertical wind shear and relative humidity. There was a projected increase of TC frequency in the post‐monsoon season (October–December), consistent with changes in relative humidity and vertical ascent, although not all clusters followed this trend; noting a different response in the southern Bay of Bengal. In turn, these projections caused changes to the climate averaged TC track density, including a decrease (up to 2 TCs per decade) affecting the eastern coast of India and a small increase (up to 0.5 TCs per decade) affecting eastern Africa, Oman and Yemen. [ABSTRACT FROM AUTHOR]

Yemen faces formidable freshwater management challenges. Devising policies for sustainable use and allocation of limited water resources is made difficult by substantial population growth, degrading environmental quality and uncertainty regarding possible changes in water availability due to climate change. We use the Water Resources Evaluation and Planning software to evaluate water needs and scarcity for three case study areas in Yemen representing different ecological conditions (Sana'a, Sadah, and Aden City) under a range of scenarios that include potential climate change and adaptation strategies. These management strategies, identified by stakeholder processes, have the potential to reduce vulnerability and build resilience. The modelled results suggest that current and predicted patterns of water consumption will soon fully deplete available supplies, and are a bigger driver of vulnerability than potential climate change for the region. In the absence of new strategies to bring into balance water supply and demand patterns, results for all three case studies suggest the pressing water crisis will only worsen. Timely interventions, designed to build resilience to scarcity, are urgently needed. [ABSTRACT FROM AUTHOR]

Management of water resources under climate change is one of the most challenging tasks in many arid and semiarid regions. A major challenge in countries, such as Yemen, is the lack of sufficient and long-term climate data required to drive hydrological models for better management of water resources. In this study, we evaluated the accuracy of accessible satellite and reanalysis-based precipitation products against observed data from Al Mahwit governorate (highland region, Yemen) during 1998–2007. Here, we evaluated the accuracy of the Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data, National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Tropical Rainfall Measuring Mission (TRMM 3B42), Unified Gauge-Based Analysis of Global Daily Precipitation (CPC), and European Atmospheric Reanalysis (ERA-5). The evaluation was performed on daily, monthly, and annual time steps by directly comparing the data from each single station with the data from the nearest grid box for each product. At a daily timescale, CHIRPS captures the daily rainfall characteristics best, such as the number of wet days, with average deviation from wet durations around 11.53%. TRMM 3B42 is the second-best performing product for a daily estimate with an average deviation of around 34.7%. However, CFSR (85.3%) and PERSIANN-CDR (103%) and ERA-5 (−81.13%) show an overestimation and underestimation of wet days and do not reflect rainfall variability of the study area. Moreover, CHIRPS is the most accurate gridded product on a monthly basis with high correlation and lower bias. The average monthly correlation between the observed and CHIRPS, TRMM 3B42, PERSIANN-CDR, CPC, ERA-5, and CFSR is 0.78, 0.56, 0.53, 0.15, 0.20, and 0.51, respectively. The average monthly bias is −2.9, −5.25, 7.35, −25.29, −24.96, and 16.68 mm for CHIRPS, TRMM 3B42, PERSIANN-CDR, CPC, ERA-5, and CFSR, respectively. CHIRPS displays the spatial distribution of annual rainfall pattern well with percent bias (Pbias) of around −8.68% at the five validation points, whereas TRMM 3B42, PERSIANN-CDR, and CFSR show a deviation of greater than 15.30, 22.90, and 66.21%, respectively. CPC and ERA-5 show Pbias of about −88.6% from observed data. Overall, in absence of better data, CHIRPS data can be used for hydrological and climate change studies on the highland region of Yemen where precipitation is often episodical and measurement records are spatially and temporally limited. [ABSTRACT FROM AUTHOR]

Various nontimber forest products (NTFPs) are produced from the forests and woodlands of Yemen. Dragon's blood tree resin is one of the commercial NTFPs in Yemen and is produced by tapping Dracaena cinnabari trees, which are listed as vulnerable by the IUCN (International Union for Conservation of Nature) Red List. By applying a forest resource assessment, the present study inventoried the D. cinnabari forest with the aim of identifying and evaluating its structure, the harvesting status of the resin, and the current management system. The study was conducted in the Firmihin forest, Socotra Island, Yemen Republic. The forest resource assessment was carried out through a forest inventory by measuring trees from 12 plots following stratified random sampling. The relevant parameters of a total of 819 trees were measured, including the tree height, stem height of lowest branches, height of the highest wound, diameter at breast height (DBH), and presence of wounds. The wounds were measured on a total of 401 trees. Value chain analysis (VCA) was used to clarify the flow of dragon's blood tree resin from the producers to the local, national, and international markets. Traditional management was examined using questionnaires in the case study area and surrounding villages. There are two tapping techniques: (1) collecting the pure dragon's blood tree resin and (2) cutting part of the bark along with the pure resin. The second technique resulted in 84% of the trees having wounds. The tappers were mostly from the community in and around the forest. The study found that the traditional management system of tapping dragon's blood tree resin is not sustainable. [ABSTRACT FROM AUTHOR]