The effects of climate change and human pollution on ecosystems worldwide are becoming increasingly apparent and are expected to increase disease susceptibility, which could have devastating impacts when keystone species are affected. Habitat-forming kelps are vital ecosystem engineers in marine ecosystems. In the Southern Hemisphere, bull kelps (Durvillaea) shape shallow marine ecosystems, providing habitat, food and shelter for numerous marine organisms. Despite their ecological importance, little is known about kelp diseases and their drivers. Here, we survey various blemishes, potentially indicative of disease, in New Zealand Durvillaea poha populations. Generalized linear mixed modelling was used to explore which environmental and anthropogenic factors might affect blemish prevalence. Our analysis indicated that blemish prevalence may be influenced by combinations of external factors, such as the distance to sewage and river outlets and predominant land use. Our study lays the groundwork for mapping blemishes and their drivers in large, brown macroalgae, an essential step in exploring kelp diseases, improving predictions and protection of marine ecosystems.

Increasing agrobiodiversity is a widely supported idea and prevalent topic in academic discussion recently as a means to combat the effects of climate change. However, there is a lack of connection between academic discussion and application. Our study aims to create a high-throughput MaxEnt workflow design that can be used to predict which neglected and underutilized crops (NUS) to use in any regional area with limited occurrence data. Our study reveals possible candidates for highly resilient NUS and that geospatial effects of climate change on these NUS were not homogenous. This tool can be deployed to help smallholders decide the most appropriate NUS to develop in any area based on crop suitability of current and future conditions.

High-efficiency restoration of stone cultural relics via immobilized carbonic anhydrase on magnetic graphite oxide.

Climate change effects, such as rising temperature, carbon dioxide levels and extreme weather events, impact agriculture directly by reduction of crop yields and indirectly by increasing damage of crop pests. Therefore, preventive methods of plant protection, like cover cropping in integrated weed management, gain in importance. Their performance, however, depends on soil moisture and temperature in late summer. This study examined the effects of elevated temperature (+5°C) and increasing drought levels (no, mild and severe drought) on four commercial and two self-composed cover crop mixtures and their weed suppression performance in a split-plot greenhouse experiment from 2020-2022. Cover crop (CC) and weed biomass were assessed, along with weed control efficacy (WCE) and soil coverage. A canonical correspondence analysis (CCA) was performed to identify drought and temperature tolerant species. Both, elevated temperature and increasing drought level, reduced CC biomass and soil cover by 50%, severe drought even by more than 80%. Weed biomass was affected similarly, only severe drought reduced it by more than 90%. Nevertheless, CC mixtures, and the self-composed mixtures in particular, reduced weed biomass further and showed consistently WCE of more than 80% and up to 98%. The CCA revealed that Sorghum bicolor , Brassica carinata and Camelina sativa are promising species for future CC mixtures. Even though their biomass and soil coverage were reduced drastically by the examined climate change effects, CC mixtures still showed a high weed control ability. This resilience might be improved further by adjusted sowing dates and establishment methods and in turn improve CC performance under adverse climate change conditions. • The influence of drought and heat stress on cover crop mixtures was examined • Cover crop and weed biomass was reduced by each stress level by approx. 25-50% • Cover crop biomass was reduced, but weed control efficacy was still at 80-98% • Sorghum bicolor , Brassica carinata and Camelina sativa are promising species • Species diversity in mixtures did not contribute to stress resilience

A systematic review of climate change impacts on sewer overflow.

Climate change and brain health, a risk management approach focusing on the European region: A narrative review.

Assessing the effects of climate change on the streamflow of the major river basins of central India

Climate change is silently reshaping childhood, especially in the world's most vulnerable regions. This scoping review explores how environmental stressors-such as rising temperatures, altered rainfall patterns, droughts, and floods-affect the nutritional status of children under 5 years of age. A systematic search of four major databases yielded 1586 studies, of which 37 met the inclusion criteria. Our findings reveal that climate change impacts child malnutrition primarily through indirect pathways influenced by food insecurity, disruptions in agricultural production, and deep-rooted socioeconomic inequalities. Stunting emerged as the most frequently and severely affected outcome, while overweight and obesity were rarely addressed-highlighting important gaps in the current evidence. Socioeconomic factors such as caregiver education, rural residence, and household income were consistently identified as key variables, shaping the extent to which climate risks translate into nutritional harm. Most studies focused on countries in Sub-Saharan Africa and South Asia, where the burden of vulnerability is greatest. Beyond documenting associations, this review draws attention to a broader reality: that child nutrition today is threatened not by a single crisis but by a web of interconnected challenges. As the global polycrisis unfolds, early childhood nutrition demands urgent, coordinated responses that are evidence-based, socially just, and future-oriented.

Natural hazards such as earthquakes, floods, and tropical cyclones pose significant threats to the operation of critical infrastructure systems (CISs) in urban environments. Rapid recovery of post-disaster CISs is essential not only for mitigating immediate socio-economic impacts but also for strengthening urban resilience against future shocks. A key challenge in this recovery process is the efficient scheduling of resources to repair damaged infrastructure, a task complicated by the dynamic and uncertain post-disaster environment, the interdependencies within infrastructure networks, and the diverse priorities and demands of various stakeholders. Given the multifaceted nature of these challenges, numerous repair resource scheduling models have been developed, each incorporating distinct algorithmic strategies tailored to different disaster types and infrastructure systems. Despite a growing body of literature on optimization problems in disaster recovery, a comprehensive understanding of the variations in these models and methods remains lacking. This review aims to systematically explore and synthesize the landscape of repair resource scheduling models, highlighting model variants and their solution algorithms. In particular, it addresses the emerging challenges in post-disaster recovery, exacerbated by the coupled effects of climate change and rapid urbanization. By categorizing the variants and extensions of existing models, this study seeks to refine current frameworks and inspire the development of more comprehensive models, ultimately contributing to more informed restoration decisions and enhanced resilience of urban infrastructure systems.

Multiple stressors rewire trophic cascades and ecosystem processes in freshwater systems.

Data-driven Approaches based on Cross-scale Dense Convolutional Network for Detecting Climate Change Effects on Crop Yield and Farming Patterns

Anoplophora horsfieldii (Hope, 1843) (Coleoptera: Cerambycidae) is a destructive wood-boring pest that causes extensive damage to forestry resources and threatens the health of forest ecosystems. With the accelerating effects of climate change, its spread and potential invasion could severely affect forest ecosystems and threaten the timber industry. In this study, we constructed ensemble models to predict suitable areas for A. horsfieldii in China under current and future climate change, and analyzed the effects of bioclimatic factors on its habitat distribution. The results indicate that the AUC and TSS values of the ensemble model were 0.982 and 0.865, respectively, and the bioclimatic factors affecting the distribution of A. horsfieldii were the mean diurnal range (Bio2), mean temperature of the wettest quarter (Bio8), and mean temperature of the driest quarter (Bio9). In the current period, the suitable habitat of A. horsfieldii is concentrated in central and southern China, and it is expected that climate change in the future will significantly change its distribution pattern, with an increase of 16.09% to 74.74% in suitable habitat and shifting towards higher latitudes. Additionally, the analysis of the multivariate environmental similarity surfaces and most dissimilar variables confirmed that the bioclimatic conditions of future expansion areas closely resemble those of the current distribution. These findings elucidate the response patterns of A. horsfieldii to climate change and provide a scientific basis for regional prevention and control strategies. The study provides crucial insights into mitigating the potential threats posed by this invasive pest to forest ecosystem stability and economic sustainability.

ABSTRACT Negative effects of anthropogenic climate change are accelerating. The threat climate change poses has prompted research into radical technological responses, including forms of solar radiation management (SRM). While there has been some consideration of the ethical challenges SRM technologies present, to date, these have almost exclusively concerned humans. Here, we take one leading form of SRM, stratospheric aerosol injection (SAI), and examine the ethical questions its deployment might present for wild animals. We map this terrain by investigating two overarching ethical questions: a) whether deploying stratospheric aerosol injection should be seen as in-principle wrong from animal ethics perspectives, and b) if not, or where it is not, what ethicists need to consider to morally evaluate SAI in the context of wild animals. To address the second question, we explore existing research gaps regarding empirical information on the effects of SAI on animals, the possible impacts of SAI on animal welfare, and its potential implications for justice issues when animals are included in theories of justice.

The manifestations of climate change take a multitude of forms in different regional contexts. For a large part of the world, it goes beyond the extreme weather events and affects their lives to the core, leading to social, economic, and cultural conflicts. The present research studies the representation of effects of climate change in the context of the Indian subcontinent, as discussed on a podcast named ‘Climate Brides’. Starting its inquiry from the issue of ‘marriages of survival’ done to cope with climate change, the podcast explores the intersectional nature of climate change. This study uses Thematic Analysis combined with Discourse Analysis to examine the portrayal of climate change and its relationship with other issues like gender, ethnicity, slow violence, and human dignity. The discourse here, however, transcends the conflict-centric portrayal of the climate crisis and also discusses possible ways to handle it. By doing this, the podcast aligns itself well with the solutions journalism framework. The article not only makes a contribution to the scarcely studied media portrayal of climate change in the Global South but also advocates for an intersectional framing of the climate crisis, necessary to foster climate justice.

The identification of viticultural strategies capable of mitigating the effects of climate change, including increased temperatures and reduced water availability, has prompted renewed interest in minor grapevine varieties adapted to specific growing areas. The enological suitability of these cultivars depends, in part, on the characterization of their glycosylated aroma precursors. In this study (2022 harvest), two recovered white grape varieties from Castilla-La Mancha, Pintada and Jarrosuelto, were evaluated. Their adaptability to two water stress regimes (moderate/deficit and severe/survival) was evaluated through the composition of intact aroma precursors compared with the predominant regional cultivar, Airén. The results revealed cultivar-dependent responses to water stress. Aroma precursor biosynthesis in Airén was only marginally affected, whereas Pintada exhibited enhanced accumulation under severe water deficit. Additionally, a C13-norisoprenoid hexose-hexose derivative and an isopropyl alcohol pentosyl-hexoside isomer were detected exclusively in Airén and Jarrosuelto, respectively, indicating their potential as varietal markers.

ABSTRACT In remote Canada, sparse meteorological stations hinder reliable snow data collection, especially for assessing historical records. Yet, these data are crucial to evaluate the effect of climate change on ecosystems and species. Changes in snow cover influence wildlife ecology and can impact body condition, survival, or reproduction. This study validated the SNOWPACK model, forced with North American Regional Reanalysis (NARR) data, to estimate snow cover data for Ram Mountain, Alberta. We used snow depth data from five stations covering the 2022–2023 and 2023–2024 snow seasons for validation. We adjusted NARR radiation and precipitation data and SNOWPACK phase change temperature to improve model fit with snow depth and end date observations. The simulation, after bias calibration, showed an average error of less than 6 cm for snow depth and plus or minus sixteen days for the snow cover end date over the two winters. This parameterized model was then used to reconstruct snow cover data from 1979 to 2024. Though no clear trend in snow cover duration or start/end dates emerged, snow depth increased by an average of 5 mm/year. Our findings suggest that SNOWPACK can estimate snow cover characteristics in remote areas, making them valuable for reconstructing long-term snow cover trends in alpine environments.

Climate change has significantly disrupted the food systems and livelihoods of low-resource rural communities, particularly in Southern Zambia's Agroecological Region I. Agroecological Region I, receives mean annual rainfall of less than 800 mm with an increasing reliance on rain-fed agriculture. This study evaluates the vulnerability of food system livelihoods to climate change in Kazungula, Gwembe, Chirundu, and Siavonga districts using the LVI-IPCC framework outlined in the sixth assessment report (IPCC-AR6) of the Intergovernmental Panel on Climate Change. The LVI-IPCC for the respondents was formed by combining its three components; exposure, sensitivity, and adaptive capacity from 195 rural households, who were selected using a stratified random sampling method. LVI was employed to identify the differential vulnerability of the four districts to climate change effects. An explanatory sequential mixed-methods design was employed, in which quantitative household survey data ( n = 195) were first used to construct the Livelihood Vulnerability Index (LVI) and LVI-IPCC metrics, followed by focus group discussions and key-informant interviews to contextualise and interpret observed vulnerability patterns. Results show that households across all districts perceived climate change primarily through erratic rainfall, droughts, rising temperatures, and shifting rainfall seasonality, with perceived climate risk intensity varying significantly by district due to differences in livelihood sensitivity and adaptive capacity rather than hazard exposure. With regards to vulnerability, Siavonga had the highest vulnerability (LVI-IPCC = 0.0711) due to high exposure and limited adaptive capacity, while Kazungula had the lowest vulnerability (0.022). Dependence on rain-fed crop production was the main factor affecting sensitivity across districts. Farmers perceived rising temperatures, erratic rainfall, and reduced yields, confirming the consistency between the measured and perceived risks. These findings indicate that the impacts of climate on food systems stem from interconnected biophysical and socioeconomic pressures. It is crucial to strengthen the adaptive capacity of smallholder farmers in this region through irrigation interventions, livelihood diversification, and integrating early warning systems and climate-information services. The study provides evidence to guide district-level adaptation planning and facilitates the development of context-specific strategies that increase the resilience of food systems in Agroecological Region I and similar regions in Southern Zambia.

Abstract Apex predators play a crucial role in maintaining ecosystem functioning and biodiversity, and studying their diet is key to understanding habitat dynamics. In the context of global change, predators must adapt to both natural ecological gradients such as elevation and human‐driven impacts, including climate and land‐use changes. Using camera traps, we assessed the diet of Mediterranean golden eagles ( Aquila chrysaetos homeyeri ) across the Iberian Peninsula. We reviewed 520 282 images collected over 1365 monitoring days, spanning 50 distinct reproductive events over four breeding seasons (2017–2020). We analyzed the frequency and biomass of each prey species in relation to elevation and land use, which have recently experienced significant anthropogenic changes, mostly due to climate change and rural abandonment. Elevation rather than land use emerged as the primary driver of dietary variation. Lagomorphs and Columbiformes dominated their diet at lower elevations, while wild ungulates and reptiles increased at higher elevations. Despite lagomorphs being the most frequently consumed prey, wild ungulates (mostly roe deer) and reptiles represented a higher proportion than previous studies. This pattern may reflect the combined effect of rural abandonment and climate change which are reshaping prey communities in the Iberian Peninsula, as well as improved detection of small prey such as squamates through camera trapping. Overall, our findings highlight the high adaptability of golden eagles to changes in prey availability under ongoing anthropogenic global change.

Pericopsis elata (Afrormosia), a valuable and threatened species, is experiencing a sharp decline in suitable habitats in the Democratic Republic of the Congo due to the combined effects of climate change and increasing human pressures. This study modeled its current and future spatial distribution using the MaxEnt algorithm, based on 72 occurrence points from national forest inventories conducted by the DIAF, filtered to reduce sampling bias. The model showed excellent performance, with AUC values of 0.95 (training) and 0.952 (testing). Out of 19 initial environmental variables, seven were retained after correlation analysis, notably the precipitation of the driest month (Bio_14), isothermality (Bio_3), and altitude as the main explanatory factors. Results reveal that only 2.8% of the national territory (66,039 km²), mainly located in the provinces of Mongala, Équateur, and Tshopo, currently provide highly suitable habitats, while 94.9% are less suitable. The distribution strongly depends on water availability during periods of hydric stress and moderate climatic conditions.Under two climate scenarios (SSP2-4.5, optimistic, and SSP5-8.5, pessimistic), suitable habitats are expected to shrink significantly by 2070. SSP2-4.5 predicts a slight increase to 4.25% of suitable areas in 2050 before declining to 1.94% in 2070. Under SSP5-8.5, 99.6% of the territory will become unsuitable, leaving only 0.11% of highly suitable habitat. These findings underscore the urgent need to develop conservation strategies integrating key climate variables. Considering multiple climate models is recommended to reduce uncertainty. This study informs sustainable management and protection of P. elata in the face of climate change.

Holistic assessment of India's water security using coupled climate-human intervention models.