Current Climate Change Scenarios Research Articles

Trends and gaps in sweet potato (Ipomoea batatas L.) improvement in sub‐Saharan Africa: Drought tolerance breeding strategies

AbstractThe main challenge facing agricultural crop production in the current global climate change scenario is sustainability. Drought, as a yield‐limiting factor, has become a major threat to international food security. Tolerance to drought is a complex trait and its response is carried out by various genes, transcription factors, microRNAs, hormones, proteins, cofactors, ions and metabolites. The complexity of the trait has limited the development of drought‐tolerant sweet potato cultivars by traditional breeding. Advances in sweet potato breeding to exploit the full potential of the crop to contribute to improved and higher performing sweet potato cultivars, adapted to increasingly risky rainfed conditions, mainly drought, are key to making food production systems more efficient and more tolerant to pressure from drought and other stressors. Genetic gain for yield potential in sweet potato has improved mostly in African countries, mainly as a result of an accelerated breeding scheme. The focus on maximising the utilisation of molecular tools for sweet potato improvement and yield has been recently explored in breeding programmes in sub‐Saharan Africa (SSA). This article provides an update on the trends and gaps in sweet potato breeding in SSA, reviewing the relevant strategies used to improve sweet potato in the region. Finally, the perspectives of using new advanced tools including genetic engineering and genome editing, and the challenges associated with climate change for further improvement of the crop are highlighted. Collaborative efforts in African countries are driving advances in breeding methods through the incorporation of molecular tools to develop drought‐tolerant sweet potato varieties that are important to global food security despite challenges posed by the drastic change in climate.

Rhizospheric bacteria from the Atacama Desert hyper-arid core: cultured community dynamics and plant growth promotion.

The Atacama Desert is the oldest and driest desert on Earth, encompassing great temperature variations, high ultraviolet radiation, drought, and high salinity, making it ideal for studying the limits of life and resistance strategies. It is also known for harboring a great biodiversity of adapted life forms. While desertification is increasing as a result of climate change and human activities, it is necessary to optimize soil and water usage, where stress-resistant crops are possible solutions. As many studies have revealed the great impact of the rhizobiome on plant growth efficiency and resistance to abiotic stress, we set up to explore the rhizospheric soils of Suaeda foliosa and Distichlis spicata desert plants. By culturing these soils and using 16S rRNA amplicon sequencing, we address community taxonomy composition dynamics, stability through time, and the ability to promote lettuce plant growth. The rhizospheric soil communities were dominated by the families Pseudomonadaceae, Bacillaceae, and Planococcaceae for S. foliosa and Porphyromonadaceae and Haloferacaceae for D. spicata. Nonetheless, the cultures were completely dominated by the Enterobacteriaceae family (up to 98%). Effectively, lettuce plants supplemented with the cultures showed greater size and biomass accumulation. We identified 12 candidates that could be responsible for these outcomes, of which 5 (Enterococcus, Pseudomonas, Klebsiella, Paenisporosarcina, and Ammoniphilus) were part of the built co-occurrence network. We aim to contribute to the efforts to characterize the microbial communities as key for the plant's survival in extreme environments and as a possible source of consortia with plant growth promotion traits aimed at agricultural applications.IMPORTANCEThe current scenario of climate change and desertification represents a series of incoming challenges for all living organisms. As the human population grows rapidly, so does the rising demand for food and natural resources; thus, it is necessary to make agriculture more efficient by optimizing soil and water usage, thus ensuring future food supplies. Particularly, the Atacama Desert (northern Chile) is considered the most arid place on Earth as a consequence of geological and climatic characteristics, such as the naturally low precipitation patterns and high temperatures, which makes it an ideal place to carry out research that seeks to aid agriculture in future conditions that are predicted to resemble these scenarios. Our main interest lies in utilizing microorganism consortia from plants thriving under extreme conditions, aiming to promote plant growth, improve crops, and render "unsuitable" soils farmable.

Tree-Related Microhabitats and Multi-Taxon Biodiversity Quantification Exploiting ALS Data

The quantification of tree-related microhabitats (TreMs) and multi-taxon biodiversity is pivotal to the implementation of forest conservation policies, which are crucial under the current climate change scenarios. We assessed the capacity of Airborne Laser Scanning (ALS) data to quantify biodiversity indices related to both forest beetle and bird communities and TreMs, calculating the species richness and types of saproxylic and epixylic TreMs using the Shannon index. As biodiversity predictors, 240 ALS-derived metrics were calculated: 214 were point-cloud based, 14 were pixel-level from the canopy height model, and 12 were RGB spectral statistics. We used the random forests algorithm to predict species richness and the Shannon diversity index, using the field plot measures as dependent variables and the ALS-derived metrics as predictors for each taxon and TreMs type. The final models were used to produce wall-to-wall maps of biodiversity indices. The Shannon index produced the best performance for each group considered, with a mean difference of −6.7%. Likewise, the highest R2 was for the Shannon index (0.17, against 0.14 for richness). Our results confirm the importance of ALS data in assessing forest biodiversity indicators that are relevant for monitoring forest habitats. The proposed method supports the quantification and monitoring of the measures needed to implement better forest stands and multi-taxon biodiversity conservation.

Building energy savings by green roofs and cool roofs in current and future climates

The global energy demand has greatly impacted greenhouse gas emissions and climate change. Since buildings are responsible for a large portion of global energy consumption, this study investigates the energy-saving potential of green roofs and cool roofs in reducing building energy consumption. Using an integrated approach that combines climate change modeling and building energy simulation, the study evaluates these strategies in six global cities (Cairo, Hong Kong, Seoul, London, Los Angeles, and Sao Paulo) under current and future climate change scenarios. The results show that in future climates, the implementation of green and cool roofs at the city level can lead to substantial annual energy reductions, with up to 65.51% and 71.72% reduction in HVAC consumption, respectively, by 2100. These findings can guide the implementation of these strategies in different climatic zones worldwide, informing the selection and design of suitable roof mitigation strategies for specific urban contexts.

Sex-dependent resilience to extreme drought events: implications for climate change adaptation of a South American endangered tree species

BackgroundRecent changes in climatic trends are resulting in an increased frequency and intensity of extreme events, with unknown effect on ecosystem dynamics in the near future. Extreme drought episodes are recognized as disturbance factors capable of modifying forest dynamics and tree growth. Within this context, dioecious tree species may be impacted by climatic extremes, affecting male/female proportions and, consequently, reproductive processes and species persistence. Therefore, there is an urgent need for species-specific assessments of growth tolerance to extreme dry spells in dioecious tree species, to establish effective conservation strategies for these particular natural resources. Araucaria araucana (araucaria), an endangered dioecious Patagonian tree species, has recently undergone decay and mortality episodes in response to increasing dry climatic conditions. While sex-dependent tolerance to extreme drought episodes has been assessed in the species’ humid distribution range, there is still a lack of information on the gender-based resilience of trees growing in the drier environments of the species’ distribution.MethodsWe reconstructed, through dendrochronological methods, the sex-dependent response of 105 araucaria individuals (55 female and 50 male trees) to five regional extreme dry spells employing a set of different indices. Resistance, recovery period, and average growth reduction of standardized tree-ring growth were examined, analysing the effect of biotic (sex, pre-drought stem tree growth) and abiotic (local climatic conditions before, during, and after extreme climatic episodes) factors on tree resilience.ResultsSex influences only the species resistance to climatic disturbance, with male individuals showing lower tolerance to extreme drought events. Pre-drought radial growth rates and local meteorological conditions preceding, during, and following extreme dry spells strongly modulated araucaria radial growth resilience regardless of tree sex, influencing the species resistance, recovery period, and average growth reduction.ConclusionsWe provide novel and crucial information for the species conservation and management in the current climate change scenario, and contribute to the debate regarding the role of tree sex as a factor influencing woody species growth under particularly adverse climatic conditions. In the face of climate change, an increase in extreme drought events is expected in the easternmost araucaria xeric end distribution area, which will likely decrease the species resilience.

Application of graph neural networks to forecast urban flood events: the case study of the 2013 flood of the Bow River, Calgary, Canada

ABSTRACT Mitigating the harmful effects of flooding is essential in the current climate change and urban growth scenario, where these natural phenomena are expected to occur more often. Addressing this problem, we present a novel graph-based forecasting model for predicting urban flooding and showcase its application in the Bow River in the City of Calgary, Alberta, Canada. The proposed model is based on graph theory and deep learning paradigms and was used to forecast flooding occurrences up to 24 h ahead. Our new approach developed the SAGE algorithm, a hybrid learning and planning approach that accurately predicted floodings for various analyzed forecasting horizons, increasing the forecasting performance by up to 44% compared to the persistence model. The SAGE model also returned superior or competitive results compared to other models in the literature. The superiority of the SAGE model was highlighted for longer forecast horizons of 24 h ahead, where it reached a maximum improvement of 79%, suggesting its superiority in capturing spatiotemporal information in the dataset. These results indicate that the SAGE approach is a cutting-edge tool for flooding forecasting, and it could be used to develop early flood warning systems to reduce potential flooding impacts.

Agroindustrial By-Products as a Source of Biostimulants Enhancing Responses to Abiotic Stress of Horticultural Crops.

Together with other abiotic stresses such as drought and high temperatures, salt stress is one of the most deleterious environmental factors affecting plant development and productivity, causing significant crop yield reductions. The progressive secondary salinisation of irrigated farmland is a problem as old as agriculture but is aggravated and accelerated in the current climate change scenario. Plant biostimulants, developed commercially during the last decade, are now recognised as innovative, sustainable agronomic tools for improving crop growth, yield, plant health and tolerance to abiotic stress factors such as water and soil salinity. Biostimulants are a disparate collection of biological extracts, natural and synthetic organic compounds or mixtures of compounds, inorganic molecules and microorganisms, defined by the positive effects of their application to crops. The growing interest in biostimulants is reflected in the increasing number of scientific reports published on this topic in recent years. However, the processes triggered by the biostimulants and, therefore, their mechanisms of action remain elusive and represent an exciting research field. In this review, we will mainly focus on one specific group of biostimulants, protein hydrolysates, generally produced from agricultural wastes and agroindustrial by-products-contributing, therefore, to more sustainable use of resources and circular economy-and primarily on the consequences of their application on the abiotic stress resistance of horticultural crops. We will summarise data in the scientific literature describing the biostimulants' effects on basic, conserved mechanisms activated in response to elevated salinity and other abiotic stress conditions, such as the control of ion transport and ion homeostasis, the accumulation of osmolytes for osmotic adjustment, or the activation of enzymatic and non-enzymatic antioxidant systems to counteract the induced secondary oxidative stress. The collected information confirms the positive effects of biostimulants on crop tolerance to abiotic stress by enhancing morphological, physiological and biochemical responses, but also highlights that more work is needed to further establish the molecular mechanisms underlying biostimulants' effects.

Hydro-sediment responses to management options under current and future climate change scenarios in Maybar watershed, South Wollo Zone, Ethiopia

Climate change coupled with inappropriate land use management is a serious environmental challenge in the highland part of Ethiopia. The aim of this study was to investigate hydro-sediment responses to management options under current and future climate change scenarios in Maybar watershed, Northern Ethiopia. We employed soil and water assessment tool (ArcSWAT 2012.10_7.24) for hydrologic modeling and CORDEX-climate data under RCP 4.5 and RCP 8.5 emission scenarios for climate projections. Soil map was prepared by digitizing soil characterization map of the watershed generated by Weigel in 1986. DEM data with 2 m spatial resolution was obtained from water and land resource center and land use classification was done through digitization of google earth images. Better agreement between calibrated SWAT simulation and observed variables was achieved. Delta change bias correction method was employed to improve the climate simulation in reproducing the observed climate variables. We found a considerable increase in annual precipitation by 18.71 % and 22.33 % for RCP 4.5 and RCP 8.5, respectively compared with the current climate conditions. Climate change induced hydro-sediment results were observed to be consistent with predicted precipitation. Under the current climatic conditions, average sediment yield at the sub-basin scale varies from negligible (under terrace complementation) to approximately more than 50 t ha−1 yr−1 with a basin average of 32 t ha−1 yr−1 (under no-terrace conditions). The implementation of management alternatives gets the dry season's hydrological behavior of the catchment improved and climate change induced sediment yield reduction. Generally, the information could possibly support decision makers and planners to implement best-fitted management options and thereby reduce current and expected aggressive sediment loss situations.

Evaluating climate change scenarios on global pea aphid habitat suitability using species distribution models

The global threat of invasive alien species (IAS) being introduced into new habitats is concerning, particularly in agricultural crops as invasive insect species are continuing to expand their distribution through anthropogenic activities and climate changes. Pea aphids (Acyrthosiphon pisum Harris) are an economic threat to numerous legume crops as they can reproduce parthenogenetically, damage crops directly, and vector over 30 plant viruses as the insect's distribution continues to spread. There are no existing pea aphid-specific risk maps that identify the habitat suitability of pea aphids at either a regional or global scale. Here, we used Species Distribution Models (SDMs) to evaluate which climatic variables influence pea aphid distribution, identify regions of potential distribution, and analyze the global distribution of pea aphids under current and future climate change scenarios (SSP 126, 245, and 370) by utilizing presence-only SDMs based on Maximum Entropy (MaxEnt). The modeling results indicate suitable conditions are relevant for pea aphid establishment in six out of seven continents, with significant range expansion in western Canada, the United States of America, and across Europe. We identified human influence to be the most prominent predictor in determining the distribution of pea aphids, supporting the fact that invasive species distributions are heavily impacted by human activities.

Shoals in troubled waters? The impact of rising temperatures on metabolism, foraging, and shoaling behavior in mixed-species shoals.

Rising water temperatures across aquatic habitats, in the current global climate change scenario, can directly affect metabolism and food intake in fish species. This can potentially alter their physiological, behavioral, and shoaling properties. In the current study, we examined the effects of high temperatures on metabolism, foraging, and shoaling in tropical fish. Mixed-species (comprising flying barbs, zebrafish, and gambusia) and single-species (flying barbs and zebrafish) shoals were conditioned for 45 days to three kinds of temperature regimes: the current temperature regime (CTR), in which shoals were maintained at water temperature of 24°C (i.e., the current mean temperature of their habitat), the predicted temperature regime (PTR) at 31°C (i.e., simulating conditions projected for their habitat in 2100), and the dynamic temperature regime (DTR), which experienced daily temperature fluctuations between 24 and 31°C (i.e., resembling rapid temperature changes expected in their natural environments). We found species-specific responses to these temperature regimes. Flying barbs exhibited significantly lower body weight at PTR but maintained consistent muscle glycogen content across all temperature regimes. In contrast, zebrafish and gambusia displayed significantly elevated muscle glycogen content at PTR, with similar body weights across all three temperature regimes. Cohesion within flying barb shoals and cohesion/polarization in mixed-species shoals decreased significantly at PTR. Shoals exposed to DTR exhibited intermediate characteristics between those conditioned to CTR and PTR, suggesting that shoals may be less impacted by dynamic temperatures compared to prolonged high temperatures. This study highlights species-specific metabolic responses to temperature changes and their potential implications for larger-scale shoal properties.

Methyl Jasmonate Improves Antioxidants, Protecting Photosynthetic Apparatus in Blueberry Plants under Water Deficit

The plant water status is crucial for growth and production, but the current climate change scenario makes it challenging to match the water plant demand. Blueberries are an economically important crop and play an acknowledged role in human health due to their antioxidant compounds. This research aimed to determine whether the exogenous application of methyl jasmonate (MeJA) improves the antioxidant defense mechanisms for protecting the photosynthetic performance in the blueberry plant cultivar ‘Brigitta’ under the stress condition of a water deficit (WD). A greenhouse experiment was carried out under a 16-h light period, at 20 °C, and 60–80% relative humidity for two weeks before the application of MeJA to the blueberry plants (Vaccinium corymbosum, cultivar ‘Brigitta’). The following treatments were maintained for 7-days: (i) 80% field capacity (NoWD), (ii) 80% field capacity plus MeJA application (NoWD + MeJA), (iii) 20% field capacity (WD), and (iv) 20% field capacity plus MeJA application (WD + MeJA). The MeJA was sprayed as an aqueous solution of 10 µM MeJA over the plant’s foliar system. At the end of the assay, the blueberry leaves were analyzed for their relative water content, specific leaf area, lipid peroxidation, total antioxidant activity, total phenols, total anthocyanins, anthocyanidin compounds, and photosynthetic performance. The ‘Brigitta’ cultivar showed a significant decrease in the oxidative stress at leaf levels, with an increase in antioxidant activity, phenolic compounds, total anthocyanins, delphinidin, petunidin, antheraxanthin, zeaxanthin, and an improvement in photosynthetic performance parameters. The ‘Brigitta’ blueberry cultivar was shown to be susceptible to WD, which mainly decreased photosynthesis. However, the application of MeJA to the leaves induced metabolic changes through an increase of the antioxidant strategy within the plant to counteract the negative effects of WD and protect the photosynthetic apparatus, which allowed the ‘Brigitta’ cultivar to withstand the period of a WD.

A MaxEnt Model of Citrus Black Fly Aleurocanthus woglumi Ashby (Hemiptera: Aleyrodidae) under Different Climate Change Scenarios.

The citrus blackfly (CBF), Aleurocanthus woglumi Ashby, is an exotic pest native to Southeast Asia that has spread rapidly to the world's main centers of citrus production, having been recently introduced to Brazil. In this study, a maximum entropy niche model (MaxEnt) was used to predict the potential worldwide distribution of CBF under current and future climate change scenarios for 2030 and 2050. These future scenarios came from the Coupled Model Intercomparison Project Phase 6 (CMIP6), SSP1-2.6, and SSP5-8.5. The MaxEnt model predicted the potential distribution of CBF with area under receiver operator curve (AUC) values of 0.953 and 0.930 in the initial and final models, respectively. The average temperature of the coldest quarter months, precipitation of the rainiest month, isothermality, and precipitation of the driest month were the strongest predictors of CBF distribution, with contributions of 36.7%, 14.7%, 13.2%, and 10.2%, respectively. The model based on the current time conditions predicted that suitable areas for the potential occurrence of CBF, including countries such as Brazil, China, the European Union, the USA, Egypt, Turkey, and Morocco, are located in tropical and subtropical regions. Models from SSP1-2.6 (2030 and 2050) and SSP5-8.5 (2030) predicted that suitable habitats for CBF are increasing dramatically worldwide under future climate change scenarios, particularly in areas located in the southern US, southern Europe, North Africa, South China, and part of Australia. On the other hand, the SSP5-8.5 model of 2050 indicated a great retraction of the areas suitable for CBF located in the tropical region, with an emphasis on countries such as Brazil, Colombia, Venezuela, and India. In general, the CMIP6 models predicted greater risks of invasion and dissemination of CBF until 2030 and 2050 in the southern regions of the USA, European Union, and China, which are some of the world's largest orange producers. Knowledge of the current situation and future propagation paths of the pest serve as tools to improve the strategic government policies employed in CBF's regulation, commercialization, inspection, combat, and phytosanitary management.

ShetlandsUAVmetry: unmanned aerial vehicle-based photogrammetric dataset for Antarctic environmental research

The study of the functioning and responses of Antarctica to the current climate change scenario is a priority and a challenge for the scientific community aiming to predict and mitigate impacts at a regional and global scale. Due to the difficulty of obtaining aerial data in such extreme, remote, and difficult-to-reach region of the planet, the development of remote sensing techniques with Unmanned Aerial Vehicles (UAVs) has revolutionized polar research. ShetlandsUAVmetry comprises original datasets collected by UAVs during the Spanish Antarctic Campaign 2021–2022 (January to March 2022), along with the photogrammetric products resulting from their processing. It includes data recorded during twenty-eight distinct UAV flights at various study sites on Deception and Livingston islands (South Shetland Islands, Antarctica) and consists of a total of 15,691 high-resolution optical RGB captures. In addition, this dataset is accompanied by additional associated files that facilitate its use and accessibility. It is publicly accessible and can be downloaded from the figshare data repository.

Current and Future Distribution of Camellia sinensis in China Estimated by MaxEnt

Tea (Camellia sinensis L.) is an important cash crop. In the context of climate change, analyzing the current distribution of tea trees and climate change environmental variables to predict the potential distribution area of tea trees in the future can help decision-makers make appropriate planting decisions and promote sustainable management. In this study, an optimized MaxEnt model was used to predict the limiting factors of tea tree growth and distribution under current and future climate change scenarios. The climate soil mixing model [area under the curve (AUC) = 0.934] performed excellently. The results showed that precipitation, temperature, slope, and soil factors all affected the distribution of suitable habitats for tea trees. Compared with the current distribution area of tea trees, under three shared socioeconomic pathways (SSP126, SSP245, and SSP585), the area of highly suitable habitats for tea trees will expand, especially in 2061–2080 and 2081–2100 years, and the suitable area will extend overall to the north of China, indicating that future climate change may create more new suitable habitats for tea production, especially in Shandong, Shaanxi, Guizhou, and Yunnan provinces. This study will provide important scientific insights for tea production decision-making, tea garden location selection, and future adaptation methods, and will help in the cultivation and transplantation of tea trees in the future.

Sustaining agricultural productivity by increasing seed replacement rate: Current challenges and the way forward

India is an agriculture-based Nation with a majority of the workforce involved in it. Agriculture in India contributes about 19% to the gross value added to the Indian economy. Seeds are considered to be the heart of agriculture and play about 15-20% role in determining productivity. In order to sustain productivity to feed the growing population, the use of certified seeds determined by the seed replacement rate can give good yields in the current scenario of climate change. The current constraints affecting the seed replacement rate and strategies that may be implemented for tackling them, have been discussed. In the Indian context, an integrated solution through digital intervention is of utmost importance and a platform as such has been proposed. Improved agricultural extension, reachability, inclusive policies and a competitive seed market are the key highlights of such a platform. A balanced and coordinated approach between private and public sectors is key to improving seed replacement rates and sustaining productivity to feed the huge Indian population.

Height increment patterns in Pinus pinaster seedlings emerging in naturally regenerated gaps

Abstract The group selection cutting system provides a promising technique for transforming monospecific even-aged stands into uneven-aged, mixed stands. However, this system has scarcely been used to regenerate Mediterranean shade-intolerant species. In this study, we analyze the height increment patterns of Pinus pinaster seedlings emerging in naturally regenerated gaps. P. pinaster is a shade-intolerant pine species distributed throughout the Mediterranean basin. An experimental trial was established in a 50-year-old P. pinaster (maritime pine) plantation located in the mountains of central Spain. Gaps of two different sizes (diameter equal to 1.5 and 2.5 times the dominant height of the stand, 26 and 44 m, respectively) were opened during winter 2017–18. A total of 531 subplots with a 1-m radius were installed in spring 2018, distributed within the gaps as well as in control plots adjacent to the gaps. Seedlings were tagged individually and variables including height, along with other ecological variables, were collected twice a year (in spring and autumn), providing six time intervals for the development of our models. We applied seemingly unrelated regression to analyze the height growth in this polycyclic species, allowing us to model spring and autumn height increments at the same time. Our results showed that seedling height growth depended on the silvicultural treatment, meteorological conditions during the spring growth season, inter-specific scrub competition, position within the gap, and seedling characteristics, such as the ontogenetic development or the size of the seedling itself. This work, along with germination and survival analysis, aims to provide a holistic perspective on the suitability of the group selection cutting system to regenerate maritime pine stands, taking into account current and future climate change scenarios.

Predicted shifts in suitable habitat of interacting benthic species in a warmer and invaded Canadian Arctic

Climate change and related expanding shipping activity are predicted to increase the risk of aquatic invasive species arriving in the Arctic. The goal of this study was to predict the distribution of an interconnected set of native and non-native primary producers and primary and secondary consumers in this changing context. Groups of species were selected to represent a benthic coastal Arctic food web in Hudson Bay, including kelps and eelgrass as primary producers (Alaria esculenta, Agarum clathratum, Saccharina latissima, Laminaria solidungula, and Zostera marina), amphipods as primary consumers (Gammarus oceanicus and G. setosus), and fish as secondary consumers (sculpins Gymnacanthus tricuspis, Myoxocephalus scorpius, M. scorpioides, and M. quadricornis). Ensemble models were used to predict the distribution of these native and several analogue non-native species (species known to be invasive elsewhere that can be considered analogues to Hudson Bay species): Dumontia contorta, Undaria pinnatifida, Sargassum muticum, and Codium fragile (primary producers); Gammarus tigrinus (primary consumer); and Artediellus atlanticus and A. uncinatus (secondary consumers). Predicted habitat suitability of trophic groups and analogue non-native species were overlaid under current and future climate change scenarios to assess areas of change through time. The predicted direction of potential distribution shifts varies by species identity (species composition) but not trophic group. Overall trophic relationships and roles in the ecosystem are likely to be maintained over time because while some species are predicted to decrease their potential ranges (e.g., M. quadricornis), others in the same trophic groups are predicted to increase (e.g., M. scorpius). Overlap (or lack thereof) between native and analogue non-native species pairs are expected to vary through time enabling novel interactions (e.g., competition) in space and time. This approach will help to identify current and future high-risk areas for trophic level changes and interactions with invasive species in response to global warming.

Grass pea (Lathyrus sativus) interesting panoply of mechanisms to cope with contrasting water stress conditions – a controlled study of sub populational differences in a worldwide collection of accessions

The grain legume Lathyrus sativus L. (grass pea) is of high economic importance for food and feed in Asian and African developing countries and is part of cultural heritage of marginal areas in the Mediterranean region. Its outstanding robustness under adverse environmental conditions, when compared with other legume species, raises particular interest under the current climate change scenario. The aim of this work was to study the range, extent and mechanisms underlying this species’ reported tolerance to water stress. To achieve this, a worldwide representative collection of 194 grass pea accessions was subjected to specific well-watered, water deficit and waterlogging conditions. These conditions were defined previously to elicit differential physiologic responses among the collection on 21 days old plants as continuously kept at 95% field capacity, at 5 days without irrigation reaching 55% field capacity, and at 14 days of partial submergence, respectively. The assessment encompassed a comprehensive set of 20 traits, including gas exchange, chlorophyll a fluorescence, leaf photosynthetic pigments, leaf water status and biomass partitioning. This detailed phenotypic analysis demonstrated that leaf relative water content and gas-exchange related traits are particularly useful to differentiate accessions’ response to water treatments. We discovered that accessions with light and large seeds mostly of Mediterranean and East European origins produce plants with high total dry biomass, a trait that is mostly genetically determined and less affected by the water treatment. On the other hand, it is mainly dark and small seeded accessions that show advantageous physiological responses to water deficit and/or waterlogging, according to pigment contents, root to shoot ratio and water use efficiency traits. This integrative screening also allowed the identification of accessions displaying contrasting levels of tolerance and susceptibility to each stress (five tolerant and five susceptible to each stress), plus one multi-tolerant (PI283546) and one multi-susceptible (PTLS1001) accession. A comprehensive and deep understanding of grass pea’s water stress tolerance mechanisms is the first step for a more efficient exploitation of this grain legume as a model crop for multiple abiotic stress resistance studies and opens doors for further progresses on crop breeding efforts towards securing food and feed supplies.

The potential range and future distribution of the endangered lizard Darevskia clarkorum in the Caucasus Biodiversity Hotspot under climate change scenarios

The Clarks’ Lizard, Darevskia clarkorum is endemic to the Caucasian biodiversity hotspot, remarkable in terms of biogeography and evolutionary history in the Palearctic Realm. The purpose of this study is to evaluate the current distribution pattern of this species as well as its possible changes under various future climate scenarios. Fieldwork was conducted in Northeastern Anatolia and the Caucasus between 2019 and 2022, and 64 occurrence records and five bioclimatic variables were analysed using Ecological Niche Modeling (ENM) software. The annual temperature range is the most important variable influencing the distribution of this lizard species. The results showed that potential habitats for the Clarks’ Lizard are wider than its present distribution. It is predicted that under current climate change scenarios, this species’ range will be much more restricted than it is now. With rising greenhouse gas levels and solar radiation rates, the range of this species is expected to shift from northern Anatolia to the Caucasus mountainous areas, and would likely shrink in future. The remaining habitats of this lizard species may be significantly impacted by climate change and human-induced habitat modification.

An overview of the efficiency of anti-graffiti products in the context of climate change

Especially in urban environments, existing buildings are prone to anthropic hazards, such as unauthorized graffiti. Anti-graffiti products may protect surfaces against unwanted paints by acting as sacrificial, semi-permanent or permanent coatings. In addition, under the current climate change scenario, the preservation of the existing buildings is seeking sustainability and reducing maintenance energy and efforts. Therefore, the present study aims to discuss how anti-graffiti products and their related efficiency may be affected by the changing climate and how their performance and durability can present different scenarios. An overview is reported based on existing literature. Concerning the application of protective coatings on polluted environments, distinct anti-graffiti products can be differently affected by atmospheric pollutants, and the cleaning effectiveness of paints may be harmed. Furthermore, the cleaning and protective efficacy of anti-graffiti products may be affected by ageing, highlighting the importance of practical maintenance. The protective solutions’ choice is also fundamental within sustainable practices, pointing to the relevance of environmentally sustainable and low-invasive removal methods. The environmental and economic impacts of anti-graffiti products are closely related to their number of required cleaning cycles.