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.

Mapping China's reserved arable lands and its sustainable cropping layout.

BACKGROUND: Reserved arable lands in China is of great significance for rationally allocating crop planting structures, alleviating the pressure of grain imports, and protecting food security. Owing to data acquisition limitations, obtaining the spatial distribution of reserved arable lands at large spatial scales is relatively rare, and there is little information on predicting the suitability, production capacity, and ecological effects of crop cultivation in reserved arable lands. This study obtained the distribution of reserved arable lands in China by applying restrictive factors, and used the Food and Agriculture Organisation of the United Nations (FAO) suitability index for eight crops to obtain a spatial distribution map of suitable crops, proposed a cropland ecological efficiency index (CEEI) to analyse the ecological impact of crop cultivation in reserved arable lands. RESULTS: China possesses approximately 3.93 million hectares of viable reserved arable lands comprising primarily grasslands (67.68%), sandy land (8.11%), saline-alkali land (20.68%), and bare land (3.53%). The average CEEI for the eight crops under irrigation conditions ranges from 0.844 to 0.865, and that under rain-fed conditions (excluding rice) ranges from 0.609 to 0.779. CONCLUSION: We proposed the development of rain-fed agriculture with sorghum as the primary crop in the central part of Shanxi and Inner Mongolia, while promoting the cultivation of rapeseed and soybeans in the eastern parts of Heilongjiang, Jilin, and Inner Mongolia. Overall, the development of irrigation agriculture focusing on wheat and barley should be pursued only when water resources are guaranteed, particularly in north-western regions such as Gansu, Ningxia, Xinjiang, Qinghai, and Shaanxi. © 2024 Society of Chemical Industry.

Framework for mapping large-scale nature-based solutions for drought mitigation: Regional application in Flanders.

Droughts are classified as the most expensive climate disasters as they leave long-term and chronic impacts on the ecosystem, agriculture, and human society. The intensity, frequency, and duration of drought events have increased in the past and are expected to continue rising at global, continental, and regional scales. Nature-based solutions (NBS) are highlighted as effective solutions to cope with the future impacts of these events. Despite this, there has been limited comprehensive research on the effectiveness of NBS for drought mitigation, and existing suitability mapping frameworks often overlook drought-specific criteria. To address this gap, a new framework is proposed to identify areas suitable for two drought-coping NBS types at a regional scale: detention basins and managed aquifer recharge. Two multi-criteria decision-making techniques (MCDM), i.e. Boolean logic and Analytic- Hierarchy Process (AHP), were used to map suitable large-scale NBS. The new framework accounts for unique criteria to specifically address drought conditions. By incorporating climate change scenarios for both surface and groundwater, recharge, and different groundwater characteristics, it identifies suitable and sustainable locations capable of managing extreme drought events. Executed through Boolean logic at a regional scale in Flanders (Belgium), the framework's strict approach yields significant potential areas for detention basins (298.7 km²) and managed aquifer recharge (867.5 km²). Incorporating AHP with the same criteria introduces a higher degree of flexibility for decision-makers. This approach shows a notable expansion across Flanders, varying with the level of suitability. The results underscore the highly suitable potential for detention basins (2552.2 km²) and managed aquifer recharge (2538.7 km²), emphasizing the adaptability and scalability of the framework for addressing drought in the region. The comparison between potential recharge volume due to detention basin and groundwater use in the region indicated that the detention basins could partially compensate for the high water demand. Therefore, creating a framework targeting drought is vital for the sustainable management of water scarcity scenarios.

Effect of calcium sources on enzyme-induced carbonate precipitation to solidify desert aeolian sand.

Enzyme-induced carbonate precipitation (EICP) is a promising technique for soil reinforcement. To select a suitable calcium source and a suitable solution amount for aeolian sand stabilization using EICP, specimens treated with different solution amounts (1.5, 2, 2.5, 3, and 3.5 L/m2). Surface strength, crust thickness, calcium carbonate content (CCC) and water vapor adsorption tests were performed to evaluate the effect of two calcium sources (calcium acetate and calcium chloride) on aeolian sand solidification. The plant suitability of solidified sand was investigated by the sea buckthorn growth test. The suitable calcium source was then used for the laboratory wind tunnel test and the field test to examine the erosion resistance of solidified sand. The results demonstrated that Ca(CH3COO)2-treated specimens exhibited higher strength than CaCl2-treated specimens at the same EICP solution amount, and the water vapor equilibrium adsorption mass of Ca(CH3COO)2-treated specimens was less, indicating that Ca(CH3COO)2-solidified sand was more effective and had better long-term stability. In addition, plants grown in Ca(CH3COO)2-treated sand had greater seedling emergence percentage and higher average height, which indicated that calcium acetate is a more suitable calcium source for EICP treatment. Furthermore, the surface strength and crust thickness of solidified sand increased with increasing the solution amount. For sand treated with 3 L/m2 of solution, the excessive strength and thickness of the crust made plants growth difficult, and the performance of sand treated with more than 2 L/m2 of solution significantly improved. Thus, the solution amount of 2-3 L/m2 is suggested for engineering applications. The sand solidified using EICP in the field could effectively mitigate wind erosion and facilitate the growth of native plants. Therefore, EICP can be combined with vegetative method to achieve long-term wind erosion control in the future.

Habitat suitability of biocrust communities in a cold desert ecosystem.

Drylands are unique among terrestrial ecosystems in that they have a significant proportion of primary production facilitated by non-vascular plants such as colonial cyanobacteria, moss, and lichens, i.e., biocrusts, which occur on and in the surface soil. Biocrusts inhabit all continents, including Antarctica, an increasingly dynamic continent on the precipice of change. Here, we describe in-situ field surveying and sampling, remote sensing, and modeling approaches to assess the habitat suitability of biocrusts in the Lake Fryxell basin of Taylor Valley, Antarctica, which is the main site of the McMurdo Dry Valleys Long-Term Ecological Research Program. Soils suitable for the development of biocrusts are typically wetter, less alkaline, and less saline compared to unvegetated soils. Using random forest models, we show that gravimetric water content, electrical conductivity, and snow frequency are the top predictors of biocrust presence and biomass. Areas most suitable for the growth of dense biocrusts are soils associated with seasonal snow patches. Using geospatial data to extrapolate our habitat suitability model to the whole basin predicts that biocrusts are present in 2.7 × 105 m2 and contain 11-72 Mg of aboveground carbon, based on the 90% probability of occurrence. Our study illustrates the synergistic effect of combining field and remote sensing data for understanding the distribution and biomass of biocrusts, a foundational community in the carbon balance of this region. Extreme weather events and changing climate conditions in this region, especially those influencing snow accumulation and persistence, could have significant effects on the future distribution and abundance of biocrusts and therefore soil organic carbon storage in the McMurdo Dry Valleys.

Global wheat planting suitability under the 1.5°C and 2°C warming targets.

The potential distribution of crops will be impacted by climate change, but there is limited research on potential wheat distributions under specific global warming targets. This study employed the Maxent model to predict the potential distribution of wheat under the 1.5°C and 2°C warming targets based on data from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) multimodel ensemble, and the effect of global warming on wheat planting suitability was analyzed. Our results indicated global warming would significantly change wheat planting suitability. Over half of the areas experienced changes in wheat planting suitability under two warming targets, and the effect became more pronounced with increasing temperatures. Additionally, global warming might promote wheat planting in more regions. The area with an increase in wheat planting suitability was observed to be 9% higher than those experiencing a decrease on average. Moreover, global warming could exacerbate the disparity between global wheat supply and demand in countries/regions. Traditional wheat-producing countries/regions are poised to benefit from the warming effects of climate change, while less developed and wheat import-dependent countries/regions may face greater challenges in achieving wheat self-sufficiency. To address this potential challenge, the promotion and inter-regional exchange of agronomic technologies, and the development of more rational trade standards are urgently needed. Since socioeconomic factors have a significant impact on wheat cultivation, further investigation is required to determine how the wheat planting distribution may change in the future under the combined impact of climate change, supply-demand relationship, and policy.

Geospatial insights into Alphonso mango cultivation: a comprehensive land suitability study in the coastal belt of Maharashtra, India.

Land suitability assessment is integral to the advancement of precision agriculture. This inquiry is focused on identifying optimal regions for cultivating Alphonso mango in the coastal belt of Maharashtra, spanning across Palghar, Raigad, Thane, Ratnagiri, and Sindhudurg districts. Employing a GIS-based Analytic Hierarchy Process (AHP) methodology, 10 crucial parameters have been considered, encompassing climatic, physical, and chemical soil characteristics: cation exchange capacity, organic carbon, slope, rainfall, soil pH, soil texture, mean annual soil temperature, base saturation, soil drainage, and soil depth. Weights are assigned to these parameters based on expert opinions and existing literature to determine their significance in developing a soil suitability map. The study reveals distinct land suitability zones for Alphonso mango cultivation. The land suitability map designates 25.78% of the study area as highly suitable, while 9.18% is considered unsuitable for Alphonso mango cultivation. To validate the study, the Receiver Operating Characteristic (ROC) curve has been employed, indicating an 83% approval rate for the reliability and performance of the soil suitability. The results categorise soil suitability classes, providing valuable insights for farmers and agricultural planners to make informed decisions regarding Alphonso mango cultivation in similar geoenvironmental regions.

The role of coronary CT angiography in athletes.

The sudden death of a young or high-level athlete or adolescent during recreational sports is one of the events with the greatest impact on public opinion in modern society. Sudden cardiac death (SCD) is the principal medical cause of death in athletes and can be the first and last clinical presentation of underlying disease. To prevent such episodes, pre-participation screening has been introduced in many countries to guarantee cardiovascular safety during sports and has become a common target among medical sports/governing organizations. Different cardiac conditions may cause SCD, with incidence depending on definition, evaluation methods, and studied populations, and a prevalence and etiology changing according to the age of athletes, with CAD most frequent in master athletes, while coronary anomalies and non-ischemic causes prevalent in young. To detect silent underlying causes early would be of considerable clinical value. This review summarizes the pre-participation screening in athletes, the specialist agonistic suitability visit performed in Italy, the anatomical characteristics of malignant coronary anomalies, and finally, the role of coronary CT angiography in such arena. In particular, the anatomical conditions suggesting potential disqualification from sport, the post-treatment follow-up to reintegrate young athletes, the diagnostic workflow to rule-out CAD in master athletes, and their clinical management are analyzed.

The Spatial Shifts and Vulnerability Assessment of Ecological Niches under Climate Change Scenarios for Betula luminifera, a Fast-Growing Precious Tree in China.

The spatial shifts and vulnerability assessments of ecological niches for trees will offer fresh perspectives for sustainable development and preservation of forests, particularly within the framework of rapid climate change. Betula luminifera is a fast-growing native timber plantation species in China, but the natural resources have been severely damaged. Here, a comprehensive habitat suitability model (including ten niche-based GIS modeling algorithms) was developed that integrates three types of environmental factors, namely, climatic, soil, and ultraviolet variables, to assess the species contemporary and future distribution of suitable habitats across China. Our results suggest that the habitats of B. luminifera generally occur in subtropical areas (about 1.52 × 106 km2). However, the growth of B. luminifera is profoundly shaped by the nuances of its local environment, the most reasonable niche spaces are only 1.15 × 106 km2 when limiting ecological factors (soil and ultraviolet) are considered, generally considered as the core production region. Furthermore, it is anticipated that species-suitable habitats will decrease by 10 and 8% with climate change in the 2050s and 2070s, respectively. Our study provided a clear understanding of species-suitable habitat distribution and identified the reasons why other niche spaces are unsuitable in the future, which can warn against artificial cultivation and conservation planning.

Forecast the Habitat Sustainability of Schoenus ferrugineus L. (Cyperaceae) in the Southern Urals under Climate Change.

An analysis of the current potential range of the Pleistocene relict plant species Schoenus ferrugineus and modeling of changes in its future range under moderate (RCP4.5) and strong (RCP8.5) climate change in the middle and second half of the 21st century were carried out. The MaxEnt program was used for modeling. Climate variables from CHELSA Bioclim, the global digital soil mapping system SoilGrids, and a digital elevation model were used as predictors. Modeling has shown that climate change will lead to a significant reduction in the suitability of S. ferrugineus habitat conditions by the mid-21st century. The predicted changes in the distribution of habitats of S. ferrugineus, a diagnostic species of calcareous mires and an indicator of their ecological state, indicate a possible strong transformation of wetland complexes in the Southern Urals region even under moderate climate change. A reduction in the distribution of S. ferrugineus at the eastern limit of its range will also be facilitated by more frequent extreme droughts. To maintain the distribution of S. ferrugineus on the eastern border of its range, a number of measures are proposed to mitigate the negative consequences of climate change, contributing to the preservation of the hydrological regime of calcareous mires.

Predicting suitable habitats for foraging and migration in Eastern Indian Ocean pygmy blue whales from satellite tracking data.

BACKGROUND: Accurate predictions of animal occurrence in time and space are crucial for informing and implementing science-based management strategies for threatened species. METHODS: We compiled known, available satellite tracking data for pygmy blue whales in the Eastern Indian Ocean (n = 38), applied movement models to define low (foraging and reproduction) and high (migratory) move persistence underlying location estimates and matched these with environmental data. We then used machine learning models to identify the relationship between whale occurrence and environment, and predict foraging and migration habitat suitability in Australia and Southeast Asia. RESULTS: Our model predictions were validated by producing spatially varying accuracy metrics. We identified the shelf off the Bonney Coast, Great Australian Bight, and southern Western Australia as well as the slope off the Western Australian coast as suitable habitat for migration, with predicted foraging/reproduction suitable habitat in Southeast Asia region occurring on slope and in deep ocean waters. Suitable foraging habitat occurred primarily on slope and shelf break throughout most of Australia, with use of the continental shelf also occurring, predominanly in South West and Southern Australia. Depth of the water column (bathymetry) was consistently a top predictor of suitable habitat for most regions, however, dynamic environmental variables (sea surface temperature, surface height anomaly) influenced the probability of whale occurrence. CONCLUSIONS: Our results indicate suitable habitat is related to dynamic, localised oceanic processes that may occur at fine temporal scales or seasonally. An increase in the sample size of tagged whales is required to move towards developing more dynamic distribution models at seasonal and monthly temporal scales. Our validation metrics also indicated areas where further data collection is needed to improve model accuracy. This is of particular importance for pygmy blue whale management, since threats (e.g., shipping, underwater noise and artificial structures) from the offshore energy and shipping industries will persist or may increase with the onset of an offshore renewable energy sector in Australia.

A GIS-based approach to determining optimal location for decentralized inner city smart filters: Toward net zero cities.

Climate change has already begun to take visible effect globally in recent years. Given the climate change paradox and urbanization trends, cities' success would not only depend on smartness and sustainability, but also resilience to all forthcoming economic, environmental, or behavioral changes. Numerous technologies have surfaced and proved effective in CO2 removal from the local environment. However, the optimal placement of these smart filters is a complex task and require logical and strategic decision-making. Determining the optimal location is one of the key factors for establishing a network of smart air filters. This study used a GIS-based suitability analysis for identifying optimal locations for smart filters based on pollution hotspots (population and spatial proximity to industry, commercial centers, roads, high-traffic areas, and intersections). The spatial analysis involves the determination and preparation of input layers, ranking layers, assigning weights to each criterion, and generation of a suitability map. The sites with a higher suitability score (7 or above) are optimum sites for air filters. The sites are spatially distributed over different regions. The findings revealed that GIS-based suitability analysis can be an effective technique for placing smart filters within an urban environment. These findings can help decision-makers to prioritize the location considering environmental constraints. The proposed solution aims to pave the way for fostering resilient, smart, and sustainable cities through a community sensing platform targeting hotspots within spatial variations.

The role of donor hypertension and angiotensin II in the occurrence of early pancreas allograft thrombosis.

Background: About 10-20% of pancreas allografts are still lost in the early postoperative period despite the identification of numerous detrimental risk factors that correlate with graft thrombosis. Methods: We conducted a multicenter study including 899 pancreas transplant recipients between 2000 and 2018. Early pancreas failure due to complete thrombosis, long-term pancreas, kidney and patient survivals were analyzed and adjusted to donor, recipient and perioperative variables using a multivariate cause-specific Cox model stratified to transplant centers. Results: Pancreas from donors with history of hypertension (6.7%), as well as with high body mass index (BMI), were independently associated with an increased risk of pancreas failure within the first 30 post-operative days (respectively, HR= 2.57, 95% CI from 1.35 to 4.89 and HR= 1.11, 95% CI from 1.04 to 1.19). Interaction term between hypertension and BMI was negative. Donor hypertension also impacted long-term pancreas survival (HR= 1.88, 95% CI from 1.13 to 3.12). However, when pancreas survival was calculated after the postoperative day 30, donor hypertension was no longer a significant risk factor (HR= 1.22, 95% CI from 0.47 to 3.15). A lower pancreas survival was observed in patients receiving a pancreas from a hypertensive donor without RAAS (Renin Angiotensin Aldosterone System) blockers compared to others (50% vs 14%, p < 0.001). Pancreas survival was similar among non-hypertensive donors and hypertensive ones under RAAS blockers. Conclusion: Donor hypertension was a significant and independent risk factor of pancreas failure. The well-known pathogenic role of renin-angiotensin-aldosterone system seems to be involved in the genesis of this immediate graft failure.

Development and application of an urban solar photovoltaic opportunity mapping tool.

A Geospatial Opportunity Mapping (GOMap) tool was created to identify policy unconstrained land in urban cities that is technically feasible for the deployment of solar photovoltaic power stations; and identify buildings with north- or south-facing orientation for the installation of building integrated PV (BIPV). Collaboration with a local Governing authority and a local electricity provider enabled the process to elicit comprehensive policy and technical aspect information respectively that would impact the site selection process. Five policy and four technical aspects are comprised of a total of 36 individual factors displayable by GOMap on a high-resolution city grid with a scoring system implemented to distinguish between factors that encourage or inhibits solar PV deployment. Weightings can be applied, and different scenarios explored including alternative policy changes and infrastructure upgrades. GOMap generates opportunity maps in the form of available land estimates which can be extrapolated by an in-built solar PV model to quantify annual energy generation based on local weather data, array spacing, panel type and array tilt angle. Three scenarios were devised to identify unconstrained land for solar PV deployment with varying levels of policy and technical factor relaxation, and a fourth scenario to identify dwellings for potential BIPV. These scenarios aim to tackle Glasgow City's growing energy demand and fuel poverty issue, the latter of which can supply energy to dwellings categorised as 'hard-to-heat' once heating is electrified due to the Scottish Government's Energy Strategy commitment.

Water temperature and microenvironmental factors predict the presence and detection of the snail host of Fasciola hepatica in Andean Patagonia.

The transmission of Fasciola hepatica occurs only where there are -or recently were- aquatic or amphibious snails of the Lymnaeidae family, the intermediate host of this parasite. Direct detection of these snails is time-consuming and imprecise, hindering accurate and detailed mapping of transmission risk. To identify which microenvironmental factors could be used as proxies for the occurrence of the lymnaeid snail Galba viator, a major intermediate host in South America, a total of 183 1-m2 quadrants across diverse water bodies in an endemic area in Andean Patagonia were manually timed-searched for snails and microenvironmental variables were registered. Data was analyzed using a Bayesian hierarchical occupancy model that assessed the effects of the microenvironmental variables on the presence of snails while considering imperfect snail detection. The model estimated that G. viator predominantly inhabits shallow aquatic environments, in the presence of grasses, where snails of the genus Biomphalaria are also detected, and with scarce tree canopy cover. Physical factors affecting occupancy presumably act as proxies for the average water temperature, while the temperature at the time of sampling was found to affect snail detectability. The identified variables are easy, fast, and inexpensive to measure, and can complement management decisions and risk maps based on coarser remote-sensing data, particularly relevant in a context of growing resistance to anthelminthic drugs.

Rotation Culture of Macroalgae Based on Photosynthetic Physiological Characteristics of Algae.

Seaweed farming has made outstanding contributions to food supply and the restoration of the ecological environment despite the limitations in production and ecological effects due to the current intensive farming of single algae species. These limitations can be overcome by selecting suitable algal species based on their physiological characteristics and by constructing a large-scale seaweed rotation model. This study carried out a trial culture in aquaculture sea areas, and performed in situ monitoring of the environmental conditions and physiological characteristics of Saccharina japonica, Hizikia fusiformis, and Gracilariopsis lemaneiformis. Additionally, a comparative analysis of the three macroalgae at different times was conducted to determine their response characteristics to environmental factors. The results showed that: (1) The three macroalgae had varying light tolerance. The effective quantum yield of Hizikia fusiformis and Gracilariopsis lemaneiformis remained unchanged during the changes in light environment, while that of Saccharina japonica first decreased and then recovered. (2) The relative electron transport rates of the three macroalgae were significantly different under different temperature conditions. Hizikia fusiformis and Saccharina japonica exhibited the highest relative electron transport rates (70.45 and 106.75, respectively) in May (20.3 °C). Notably, Gracilariopsis lemaneiformis demonstrated good growth and exhibited the highest relative electron transport rate (93.07) in September (27.5 °C). These findings collectively support the feasibility of establishing a macroalgae rotation model. Based on the combined environmental conditions of the seas in Shandong, Zhejiang, and Fujian, a macroalgae rotation model was proposed. The application of this model in the construction of artificial seaweed farms in marine ranches can provide a stable output of large-scale seaweed production and ecological benefits.

The consistent fuzzy suitability assessment of forest land resources with multi-source heterogeneous data.

In view of the suitability assessment of forest land resources, a consistent fuzzy assessment method with heterogeneous information is proposed. Firstly, some formulas for transforming large-scale real data and interval data into fuzzy numbers are provided. To derive the unified representation of multi-granularity linguistic assessment information, a fuzzy quantitative transformation for multi-granularity uncertain linguistic information is proposed. The proofs of the desirable properties and some normalized formulas for the trapezoidal fuzzy numbers are presented simultaneously. Next, the objective weight of each assessment indicator is further determined by calculating the Jaccard-Cosine similarity between the trapezoidal fuzzy numbers. Moreover, the trapezoidal fuzzy numbers corresponding to the comprehensive assessment values of each alternative are obtained. The alternatives are effectively ranked according to the distance from the centroid of the trapezoidal fuzzy number to the origin. Finally, based on the proposed consistent fuzzy assessment method, the suitability assessment of forest land resources is achieved under a multi-source heterogeneous data setting.

Distribution and extent of suitable habitats of Ruspoli's Turaco (Tauraco ruspolii) and White-cheeked Turaco (Tauraco leucotis) under a changing climate in Ethiopia.

BACKGROUND: Understanding the distribution pattern of species and their suitable habitat is key to focus conservation efforts. Climate change has had notable impact on the distribution and extent of suitable habitats, and the long-term survival of various species. We aim to determine the distribution and extent of suitable habitats for Tauraco ruspolii and T. leucotis in Ethiopia and predict their range in the 2050s and 2070s using MaxEnt algorithm. We used 25 and 29 rarified occurrence points for T. ruspolii and T. leucotis, respectively, and 13 environmental variables. Three regularization multipliers and two cut-off thresholds were used to map the potential suitable habitats for each species under current and future climates. Maps were assembled from these techniques to produce final composite tertiary maps and investigated the habitat suitability overlap between the two species using the UNION tool in the geographical information system. RESULT: All model run performances were highly accurate for both species. Precipitation of the driest month and vegetation cover are the most influential variables for the habitat suitability of T. ruspolii. The habitat suitability of T. leucotis is also mainly influenced by mean temperature of the driest quarter and vegetation cover. Under the current climate, the suitable habitat predicted for T. ruspolii covered about 24,639.19 km2, but its range size change shows a gain and increase by 156.00% and 142.68% in 2050 and 2070, respectively. The T. leucotis's current suitable habitat ranges about 204,397.62 km², but this is reduced by 40.84% and 68.67% in 2050 and 2070, respectively. Our modeling also showed that there was suitable habitat overlap between them at the margin of their respective habitat types in time series. CONCLUSION: We concluded that there is a direct or indirect impact of climate change on the suitable habitat range expansion for T. ruspolii and contraction for T. leucotis as well as overlapping of these turaco species in different regions of Ethiopia. Therefore, understanding the distribution of current and future suitable habitats of the two turaco species can provide valuable information to implement conservation practices for the species and the regions as well.

The devil is in the detail: Environmental variables frequently used for habitat suitability modeling lack information for forest-dwelling bats in Germany.

In response to the pressing challenges of the ongoing biodiversity crisis, the protection of endangered species and their habitats, as well as the monitoring of invasive species are crucial. Habitat suitability modeling (HSM) is often treated as the silver bullet to address these challenges, commonly relying on generic variables sourced from widely available datasets. However, for species with high habitat requirements, or for modeling the suitability of habitats within the geographic range of a species, variables at a coarse level of detail may fall short. Consequently, there is potential value in considering the incorporation of more targeted data, which may extend beyond readily available land cover and climate datasets. In this study, we investigate the impact of incorporating targeted land cover variables (specifically tree species composition) and vertical structure information (derived from LiDAR data) on HSM outcomes for three forest specialist bat species (Barbastella barbastellus, Myotis bechsteinii, and Plecotus auritus) in Rhineland-Palatinate, Germany, compared to commonly utilized environmental variables, such as generic land-cover classifications (e.g., Corine Land Cover) and climate variables (e.g., Bioclim). The integration of targeted variables enhanced the performance of habitat suitability models for all three bat species. Furthermore, our results showed a high difference in the distribution maps that resulted from using different levels of detail in environmental variables. This underscores the importance of making the effort to generate the appropriate variables, rather than simply relying on commonly used ones, and the necessity of exercising caution when using habitat models as a tool to inform conservation strategies and spatial planning efforts.

Suitability of agronomic water saving in karst areas and its enlightenment in the karst desertification control.

The special "dual" hydrogeological structure in karst areas causes rainfall easily "leaking" into the ground, resulting a unique "karst drought". In these areas, drought and insufficient water resources seriously restrict the sustainable development of agriculture. In order to restore the ecology of karst desertification, develop ecological industries, improve the utilization efficiency of water resources, and advance water-saving agriculture in such areas, literature review method was applied to discuss the suitability of agronomic water-saving measures in karst areas. The results are as follows. (1) Agronomic water-saving measures including tillage, mulching, water-fertilizer coupling, chemical regulation, crop allocation and deficit irrigation can all enhance the crop WUE. For example, deep tillage and deep loosening increased the WUE by 15.1 % and 15.9 % respectively. The WUE of spring wheat under straw mulching increased by 17.17 %-43.01 % compared with that under mulching film. Increased density of intercropping corn and wheat saved 9.85 % of water. (2) The cultural or natural particularity of karst areas limits the application of all agronomic water-saving measures in karst areas, and therefore choices and adjustments are necessary according to local conditions: ① No tillage should be adopted because of the high output of labor force; ② straw mulching need to be crushed; ③ the coupling of water and fertilizer reaches better effect when applied to crops several hours before rainfall; ④ the shallow soil layer and the complexity of preparing water retaining agent make it unsuitable to use water retaining agent; ⑤ agroforestry with dwarf and dense planting is more suitable; ⑥ crop deficit irrigation can be carried out by using ecological small pools. Based on the above results, proposes are offered in the following. First, it is necessary to construct the optimal model of regional water and fertilizer coupling in karst areas, and apply composite agronomic water-saving measures. Second, it is suggested to establish a model of coordinating forest, grain and grass, and vigorously develop ecologically derivative agroforestry. Third, there is a necessity to strengthen the research and development of technology about soil and water leakage monitoring and resistance, and intensify studies on "five waters" transformation at the basin scale. The research results and implication are an important reference for developing water-saving agriculture, solving the shortage of agricultural water resources, ensuring the sustainability of agriculture and improving farmers' living standards. Rational use of agronomic water-saving measures is of great significance to enhance the utilization efficiency of water resources and boost regional economy in karst desertification areas.