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Environmental risk assessment (ERA) is critical for protecting life by predicting population responses to contaminants. However, routine toxicity testing often examines only one genotype from surrogate species, potentially leading to inaccurate risk assessments, as natural populations typically consist of genetically diverse individuals. To evaluate the importance of intraspecific variation in translating toxicity testing to natural populations, we quantified the magnitude of phenotypic variation between 20 Daphnia magna clones exposed to two levels of microcystins, a cosmopolitan cyanobacterial toxin. We observed significant genetic variation in survival, growth, and reproduction, which increased under microcystins exposure. Simulations of survival showed that using a single genotype for toxicity tolerance estimates on average failed to produce accurate predictions within the 95% confidence interval over half of the time. Whole genome sequencing of the 20 clones tested for correlations between toxicological responses and genomic divergence, including candidate loci from prior gene expression studies. We found no overall correlations, indicating that clonal variation, rather than variation at candidate genes, predicts population-level responses to toxins. These results highlight the importance of incorporating broad intraspecific genetic variation, without focusing specifically on variation in candidate genes, into ERAs to more reliably predict how local populations will respond to contaminants. [ABSTRACT FROM AUTHOR]

This paper describes the integration of geographic information system (GIS) technology in a high school environmental science classroom, specifically examining the impact of GIS technology on student engagement, critical thinking, and interdisciplinary learning for Education for Sustainability (EfS). This environmental science classroom utilized ArcGIS Online and StoryMaps to facilitate hands-on learning, enabling students to explore spatial relationships, analyze data, and communicate insights to foster engagement and critical thinking. This GIS technology promotes interdisciplinary learning by connecting essential environmental issues with location and other social factors. Students deepen their understanding of human-environment interactions by interpreting spatial data, empowering them to propose sustainable solutions to environmental challenges. Using ArcGIS Online and StoryMaps, students engaged in guided lessons, explored sustainability topics, and created their own StoryMaps based on the United Nations' (UN) Sustainable Development Goals (SDGs). The findings highlight positive engagement, critical thinking, and interdisciplinary learning impacts. Students demonstrated increased interest, understanding of complex issues, and developed analytical skills through spatial data analysis. The approach encouraged interdisciplinary thinking and expanded awareness of ongoing environmental challenges, supporting EfS goals. [ABSTRACT FROM AUTHOR]

Remote sensing of forests is a powerful tool for monitoring the biodiversity of ecosystems, maintaining general planning, and accounting for resources. Various sensors bring together heterogeneous data, and advanced machine learning methods enable their automatic handling in wide territories. Key forest properties usually under consideration in environmental studies include dominant species, tree age, height, basal area and timber stock. Being proxies of stand productivity, they can be utilized for forest carbon stock estimation to analyze forests' status and proper climate change mitigation measures on a global scale. In this study, we aim to develop an effective machine learning-based pipeline for automatic carbon stock estimation using solely freely available and regularly updated satellite observations. We employed multispectral Sentinel-2 remote sensing data to predict forest structure characteristics and produce their detailed spatial maps. Using the Extreme Gradient Boosting (XGBoost) algorithm in classification and regression settings and management-level inventory data as reference measurements, we achieved quality of predictions of species equal to 0.75 according to the F1-score, and for stand age, height, and basal area, we achieved an accuracy of 0.75, 0.58 and 0.56, respectively, according to the R2. We focused on the growing stock volume as the main proxy to estimate forest carbon stocks on the example of the stem pool. We explored two approaches: a direct approach and a hierarchical approach. The direct approach leverages the remote sensing data to create the target maps, and the hierarchical approach calculates the target forest properties using predicted inventory characteristics and conversion equations. We estimated stem carbon stock based on the same approach: from Earth observation imagery directly and using biomass and conversion factors developed for the northern regions. Thus, our study proposes an end-to-end solution for carbon stock estimations based on the complexation of inventory data at the forest stand level, Earth observation imagery, machine learning predictions and conversion equations for the region. The presented approach enables more robust and accurate large-scale assessments using limited annotated datasets. [ABSTRACT FROM AUTHOR]

Science classrooms are most engaging when students have the opportunity to engage in the practices of scientists. Unfortunately, many attempts to incorporate science into the classroom are disconnected from real scientific practice. When classroom science is divorced from genuine scientific research, collaboration also suffers. Students may sometimes collaborate with each other during traditional labs at school, but too often, the end goal is simply for students to see what the instructor wants them to see. Citizen science, however, gives students the opportunity to help scientists with real-world research projects. In a well-designed citizen science project, no one knows what the results will be! This creates the conditions for further collaboration: between students and teachers, between students and professional scientists, and even between students and the general public. Gung ho for Ginkgo (Enthusiastic for Ginkgo) is a citizen science project in which students help scientists by counting cells in online microscope images. Then students graph their data, analyze their graphs, and write about their results. Furthermore, the project could provide insight into the impacts of future climate change. [ABSTRACT FROM AUTHOR]

Geographic Information Systems (GISs) cover a wide range of Earth and environmental science disciplines that have become essential for spatial data management, easing the digital transformation needs of our society. Despite the usefulness of GISs, they remain underutilised in academia, and many students do not understand the possibilities that these tools offer. To familiarise university students with the potential of GISs, we designed 11 short clips (less than 5 min long) recorded by Earth scientists with diverse backgrounds who shared their work experience with GISs to solve real-world problems. Through these short clips, we emphasised not only the multidisciplinary uses of GISs but also provided professional references for undergraduate students, including societal aspects such as gender equality, national and international mobility, private-to-public-sector transitioning, and different family circumstances. As a result, the students expressed their interest in the applications of GISs, many of which were completely new to them, highlighting the potential of GISs in terms of entrepreneurship and their usefulness in mitigating global change. Thus, we were able to transfer knowledge from research to university education and foster spatial data management skills in Earth science. [ABSTRACT FROM AUTHOR]

Black environmental geographies scholarship has made significant strides in expanding the ways we understand ecologies and ecological relationships interweaving the lives of black communities across the black diaspora. In this article, I review the analytical interventions in this field that press the bounds of traditional environmental injustice framings of black ecological experiences and relations. Drawing on black studies, this literature, first, helps us to position present racial ecological landscapes within historical and long-standing logics of race, colonialism, and imperialism. Moreover, it breathes nuance and life into discourse that overrepresents black ecological relationships as lack, decay, and containers of pollution and death, with very little everyday living. Building on these interventions and understanding the dialectic relationship between death-dealing and life-affirming socio-ecological processes at work in black environmental geographies, I call attention to interdisciplinary methodological approaches that bring together black environmental geographies and critical environmental science to behold the complex enmeshment of social and biophysical relations and the entanglement of life and degradation that interweave the two. [ABSTRACT FROM AUTHOR]

Abstract Remote sensing of forests is a powerful tool for monitoring the biodiversity of ecosystems, maintaining general planning, and accounting for resources. Various sensors bring together heterogeneous data, and advanced machine learning methods enable their automatic handling in wide territories. Key forest properties usually under consideration in environmental studies include dominant species, tree age, height, basal area and timber stock. Being proxies of stand productivity, they can be utilized for forest carbon stock estimation to analyze forests’ status and proper climate change mitigation measures on a global scale. In this study, we aim to develop an effective machine learning-based pipeline for automatic carbon stock estimation using solely freely available and regularly updated satellite observations. We employed multispectral Sentinel-2 remote sensing data to predict forest structure characteristics and produce their detailed spatial maps. Using the Extreme Gradient Boosting (XGBoost) algorithm in classification and regression settings and management-level inventory data as reference measurements, we achieved quality of predictions of species equal to 0.75 according to the F1-score, and for stand age, height, and basal area, we achieved an accuracy of 0.75, 0.58 and 0.56, respectively, according to the R2. We focused on the growing stock volume as the main proxy to estimate forest carbon stocks on the example of the stem pool. We explored two approaches: a direct approach and a hierarchical approach. The direct approach leverages the remote sensing data to create the target maps, and the hierarchical approach calculates the target forest properties using predicted inventory characteristics and conversion equations. We estimated stem carbon stock based on the same approach: from Earth observation imagery directly and using biomass and conversion factors developed for the northern regions. Thus, our study proposes an end-to-end solution for carbon stock estimations based on the complexation of inventory data at the forest stand level, Earth observation imagery, machine learning predictions and conversion equations for the region. The presented approach enables more robust and accurate large-scale assessments using limited annotated datasets.

Today’s data-driven world requires earth and environmental scientists to have skills at the intersection of domain and data science. These skills are imperative to harness information contained in a growing volume of complex data to solve the world’s most pressing environmental challenges. Despite the importance of these skills, Earth and Environmental Data Science (EDS) training is not equally accessible, contributing to a lack of diversity in the field. This creates a critical need for EDS training opportunities designed specifically for underrepresented groups. In response, we developed the Earth Data Science Corps (EDSC) which couples a paid internship for undergraduate students with faculty training to build capacity to teach and learn EDS using Python at smaller Minority Serving Institutions. EDSC faculty participants are further empowered to teach these skills at their home institutions which scales the program beyond the training lead by our team. Using a Rasch modeling approach, we found that participating in the EDSC program had a significant impact on undergraduate learners’ comfort and confidence with technical and nontechnical data science skills, as well as their science identity and sense of belonging in science, two critical aspects of recruiting and retaining members of underrepresented groups in STEM. Supplementary materials for this article are available online.

Tropospheric ozone is a significant air pollutant with severe adverse effects on human health. The complex dynamics of ozone formation, distribution, and health impacts underscore the need for a comprehensive understanding of this pollutant. Despite well-documented health risks, including an estimated 423,100 deaths annually due to ozone exposure, millions of people in major countries continue to be exposed to unhealthy levels. Notably, the epidemiological evidence linking long-term ozone exposure to health outcomes is limited compared to short-term exposure studies, leaving some findings incomplete. Regulatory standards vary globally, with the implementation of the World Health Organization recommendation for an 8-h average limit of 50 ppb to protect public health remaining heterogeneous, leading to significant disparities in adoption across countries, and often significantly higher. Emissions from diesel and gasoline vehicles are major sources of VOCs and NOx in urban areas, and their reduction is a key strategy. Additionally, climate change may exacerbate ozone pollution through increased natural precursor emissions, leading to higher ground-level ozone in polluted regions, like the eastern US, southern Europe, and parts of Asia. Addressing tropospheric ozone effectively requires an integrated approach that considers both natural and anthropogenic sources to reduce concentrations and mitigate health impacts. [ABSTRACT FROM AUTHOR]

The EAACI Guidelines on the impact of short‐term exposure to outdoor pollutants on asthma‐related outcomes provide recommendations for prevention, patient care and mitigation in a framework supporting rational decisions for healthcare professionals and patients to individualize and improve asthma management and for policymakers and regulators as an evidence‐informed reference to help setting legally binding standards and goals for outdoor air quality at international, national and local levels. The Guideline was developed using the GRADE approach and evaluated outdoor pollutants referenced in the current Air Quality Guideline of the World Health Organization as single or mixed pollutants and outdoor pesticides. Short‐term exposure to all pollutants evaluated increases the risk of asthma‐related adverse outcomes, especially hospital admissions and emergency department visits (moderate certainty of evidence at specific lag days). There is limited evidence for the impact of traffic‐related air pollution and outdoor pesticides exposure as well as for the interventions to reduce emissions. Due to the quality of evidence, conditional recommendations were formulated for all pollutants and for the interventions reducing outdoor air pollution. Asthma management counselled by the current EAACI guidelines can improve asthma‐related outcomes but global measures for clean air are needed to achieve significant impact. [ABSTRACT FROM AUTHOR]

Research integrated into higher education curricula has been shown by numerous studies to be beneficial to undergraduate students. Citizen science provides an alternative to research performed in a lab and is gaining traction as a good choice for integration into classes. The Undergraduate Student Experiences in Citizen Science (USE Cit Sci) research collaboration network is working to help more instructors in higher education adopt citizen science as part of their curriculum by providing training and educational materials. To date, the Network has identified areas of critical need for citizen science to be more readily used in higher education courses and created a clearinghouse of lessons for faculty to use freely. Forthcoming products of the USE Cit Sci network include direct partnerships between educators and citizen science projects in addition to a peer mentoring program. Given the preponderance of ecology citizen science projects available, bringing this educational opportunity to students opens new avenues of pedagogical experiences. [ABSTRACT FROM AUTHOR]

Demands to manage the risks of artificial intelligence (AI) are growing. These demands and the government standards arising from them both call for trustworthy AI. In response, we adopt a convergent approach to review, evaluate, and synthesize research on the trust and trustworthiness of AI in the environmental sciences and propose a research agenda. Evidential and conceptual histories of research on trust and trustworthiness reveal persisting ambiguities and measurement shortcomings related to inconsistent attention to the contextual and social dependencies and dynamics of trust. Potentially underappreciated in the development of trustworthy AI for environmental sciences is the importance of engaging AI users and other stakeholders, which human–AI teaming perspectives on AI development similarly underscore. Co‐development strategies may also help reconcile efforts to develop performance‐based trustworthiness standards with dynamic and contextual notions of trust. We illustrate the importance of these themes with applied examples and show how insights from research on trust and the communication of risk and uncertainty can help advance the understanding of trust and trustworthiness of AI in the environmental sciences. [ABSTRACT FROM AUTHOR]

Summary: China, holding nearly half of the global coal-fired power capacity, must shift from its coal-centric energy system to meet climate and air quality goals. This study explores the optimal utilization of natural gas by evaluating the environmental and economic costs of gas- and coal-fired power using plant-level data and a multidisciplinary modeling approach. We find that gas power has substantially lower air pollution costs (0.77 versus 12.2 cents/kWh) and moderately lower GHG costs (2.8 versus 4.5 cents/kWh), with an average environmental advantage of 12.1 cents/kWh and a social benefit of 10.4 cents/kWh when considering LCOE. The benefits vary spatially with the highest benefits in east-central China. Prioritizing substitution in regions with high environmental benefits could reduce SO2, NOx, and PM emissions by 28%, 15%, and 56%, respectively, offering a 52% higher environmental benefit than existing gas power plans. This study provides quantitative support for gas power development in China.

Summary: China’s pursuit of photovoltaic (PV) power, particularly rooftop installations, addresses energy and ecological challenges, aiming to reduce basic energy consumption by 50% by 2030. The northwest region, with its solar potential, is a focal point for distributed PV growth, which has already exceeded 50% of the energy mix by 2021. This study assesses the rooftop PV potential in five northwestern capitals, finding favorable conditions such as ample space, dense populations, and high sunlight exposure. Cities like Yinchuan and Xining are highlighted for their high projected annual PV yields. Although there is a negative correlation between surface temperature and vegetation coverage, the Weather Research and Forecasting (WRF) numerical simulation found that large-scale deployment of rooftop photovoltaics will not have a significant impact on the vegetation ecology of the area. The research underscores the significant role of rooftop PV in achieving China’s energy and climate goals in its northwestern urban centers.

Summary: Rooftop photovoltaics (RPVs) are crucial for decarbonizing the power sector and achieving carbon neutrality, with expected future capacity increases. The growth of RPVs necessitates substantial aluminum (Al) resources, contributing significantly to carbon dioxide (CO2) emissions from Al production. Given China’s bauxite shortage, recycling Al from waste RPV panels presents an effective solution to enhance resource security and mitigate CO2 emissions. We developed a framework to project waste RPV quantities and assess the recycling potential of Al and its impact on CO2 emissions from 2020 to 2060. Our findings indicate potential waste flows of 95–221 million tonnes (Mt) and recycled Al ranging from 5 to 28 Mt, with a primary Al supply gap of 25–43 Mt. Recycling could reduce CO2 emissions by 35–207 Mt over the period. This research underscores the importance of Al resource security and sustainable RPV industry development in China’s pursuit of carbon neutrality.

Summary: The wide and continuous usage of glyphosate in the environment poses a serious threat to biological systems. Besides the accumulation of glyphosate in vivo, a growing body of research has revealed that aminomethylphosphonic acid (AMPA), the main degradation intermediate of glyphosate, has significant environmental and biological influences by inducing chromosome aberration of fish and canceration of human erythrocyte. Therefore, the development of new strategies avoiding the generation of the toxic AMPA intermediate during the full degradation of glyphosate is becoming of high importance. Herein, we provide a mini-review that includes the most recent advances in the selective degradation of glyphosate avoiding the generation of AMPA in the last several years from 2018. The developments of the selective degradation of glyphosate, highlighting its synthesis and selective degradation mechanism, are summarized here. This review intends to attract more attention from researchers toward this area and to emphasize the recent developments of selective degradation of glyphosate in highlighting future challenges.

Summary: A recurring trend in evidence scrutinized over the past few decades is that disease outbreaks will become more frequent, intense, and widespread on land and in water, due to climate change. Pathogens and the diseases they inflict represent a major constraint on seafood production and yield, and by extension, food security. The risk(s) for fish and shellfish from disease is a function of pathogen characteristics, biological species identity, and the ambient environmental conditions. A changing climate can adversely influence the host and environment, while augmenting pathogen characteristics simultaneously, thereby favoring disease outbreaks. Herein, we use a series of case studies covering some of the world’s most cultured aquatic species (e.g., salmonids, penaeid shrimp, and oysters), and the pathogens (viral, fungal, bacterial, and parasitic) that afflict them, to illustrate the magnitude of disease-related problems linked to climate change.

Summary: Global warming significantly impacts amphibian populations globally, and modeling helps understand these effects. Here, we used MaxEnt and MigClim models to predict the impact of climate change on habitat suitability for Hoplobatrachus chinensis. Our results indicate that temperature is a key factor affecting H. chinensis distribution. Increasing temperatures positively correlated with habitat suitability, with suitable habitat expanding northward by 2060 while maintaining suitability in the southern parts of the range. We found a 25.18% overlap between the current potential suitable habitat of H. chinensis and agricultural wetlands. Our model indicated that H. chinensis might be able to track shifts in suitable habitats under climate change given a 15 km dispersal ability per generation. Climate change will likely expand suitable habitat for H. chinensis. Our predictions offer important guidance for the conservation of the species, especially for the integrated role of natural and agricultural wetlands such as rice paddies.

Summary: There are anywhere from 5 to 8 priority antibiotics in typical wastewater treatment plants (WWTPs) whose concentrations exceed the maximum allowed, out of 12 priority antibiotics designated by the World Health Organization as the species to pose severe health hazard than others. If the priority antibiotics to deal with could be reduced to just one or two, such reduction would greatly simplify the construction and operation of the treatment plants. Introduced here is a concept of ‘primary’ antibiotic, the abatement of which ensures mitigation of all the other priority antibiotics in the wastewater. A criterion for determining primary antibiotic is developed. For a demonstration of the approach, the wastewater systems treated with solar-based photocatalysts are considered. The criterion reveals that the primary antibiotic in the typical European WWTP as well as in the typical municipal and hospital wastewater is ciprofloxacin, whereas the typical industrial wastewater contains ciprofloxacin and oxytetracycline.

Summary: Identifying the main threats to soil biodiversity is crucial as soils harbor ∼60% of global biodiversity. Many previous meta-analyses investigating the impact of different global changes (GCs) on biodiversity have omitted soil fauna or are limited by the GCs studied. We conducted a broad-scale meta-analysis focused on soil fauna communities, analyzing 3,161 effect sizes from 624 publications studying climate change, land-use intensification, pollution, nutrient enrichment, invasive species and habitat fragmentation. Land-use intensification resulted in large reductions in soil fauna communities, especially for the larger-bodied groups. Unexpectedly, pollution caused the largest negative impact on soil biodiversity - particularly worrying due to continually increasing levels of pollution and poor mechanistic understanding of impacts relative to other GCs. Not all GCs and stressors were detrimental; organic-based nutrient enrichment often resulted in positive responses. Including soil biodiversity in large-scale analyses is vital to fully understand the impact of GCs across the different realms.

Summary: Optimizing water allocation is a crucial strategy for water planning in large basins, such as the Yellow River basin. The transforming water supply pattern, triggered by inter-basin water transfer, urges the optimization and refinement of water allocation. Here, we predict the future water demand for different sectors at the provincial level and carry out future water allocation based on a multi-objective allocation model. The results imply that “demand increases in midstream and water deficits in downstream” would persist by 2050, and the demand structure highlights potential sectoral rivalry for water resources in each province. Water transfer will be the “antidote” to water disputes and will account for 19.8% and 34.5% of the water demand in 2030 and 2050, respectively. This study provides a basis for the policymaking of water management and establishes the future allocation pattern from water resources to sectors in each province in the Yellow River basin.

This article explores the importance of integration in systems biology and medicine research, highlighting the need to address fragmentation and biases in the field. It emphasizes the significance of considering the exposome, which encompasses cognitive, behavioral, and environmental factors, in research. The article identifies challenges in implementing systems biology and medicine approaches, such as cost, participant burden, imprecise measures, limited cross-disciplinary implementation of analytical tools, and regulatory barriers. It concludes by emphasizing the need for a paradigm shift in healthcare and the translation of scientific discoveries into clinical care. The document also includes references and acknowledgments related to systems biology and systems medicine, covering topics such as social environments and health, wearable devices, bias in research, stress management, and the impact of genetics and the environment on health. [Extracted from the article]

This paper addresses the crucial question of the structuring of scientific Notions for the purpose of their proper teaching/acquisition. It aims to demonstrate that non-taxonomic structures, derived from the systematic lexicographic definition of terminological lexical units, can be rigorously constructed and are adequate for implementing a non-isolationist approach to terminology modeling: one that embeds the description of terminological units within a more global model of the general lexicon. Using theoretical and descriptive principles of Explanatory Combinatorial Lexicology and the lexicography of lexical networks known as Lexical Systems, we apply our approach to the core terminology of chemistry and chemistry-related environmental terminology. This allows us to propose Notion building road maps for three languages—English, French and Russian—that can be used as guides for the teaching/acquisition of chemistry Notions. Additionally, exploiting the special case of the noun carbon—which pertains to chemistry, environmental science and, even, general language—we demonstrate the potential of our non-isolationist approach for interfacing distinct sectors of terminological knowledge. [ABSTRACT FROM AUTHOR]

This article introduces the Data Puzzles instructional framework as a means to engage middle school students in the exploration of wind energy and its potential for future wind farm locations across the United States. By eliciting and leveraging student resources through an opening scenario that prompts personal experiences with wind, teachers can effectively connect students to abstract science phenomena and facilitate sensemaking. The Data Puzzles framework combines authentic scientific data sets with the Ambitious Science Teaching pedagogical practices to support students in constructing knowledge and addressing contemporary phenomena. [ABSTRACT FROM AUTHOR]

Rather than stressful, an assessment should feel like a celebration of learning for students. Performance-based assessments allow students to demonstrate their understanding of one or more standards by accomplishing tasks that are engaging and flexible in how students approach them. In addition to seeing students' scientific knowledge, teachers get a better sense of their students' interests and strengths that they bring to each open-ended assignment. Three examples of performance-based assessments are provided, as well as an explanation of the challenges and successes that come with this assessment approach. [ABSTRACT FROM AUTHOR]

Transdisciplinarity — the inclusion of both the public and scientific community in knowledge construction and policy formation — is increasingly called upon to ameliorate wicked problems associated with social-ecological systems. Informed by previous scholarship, we propose that there is a spectrum from superficial to meaningful ways that public perception and knowledge are incorporated in transdisciplinary approaches to constructing knowledge and developing policy. Further, we argue that students in environmental science graduate programs hold beliefs not compatible with current recommendations related to transdisciplinary research and practice. Thus, the primary purpose of this paper is to describe how students imagine the ways in which transdisciplinarity ought to unfold, which can then serve as the foundation for the development of transdisciplinary curricula that meet them where they are. In this study, we used qualitative interviews to explore environmental science graduate students' perceptions of how public stakeholders and scientists ought to work together across four phases of transdisciplinary research: (1) conceptualizing the problem, (2) data collection, (3) analyzing and interpreting information, and (4) participating in decision-making. Our findings suggest that students generally believed that public stakeholders should be superficially included differentially across these phases. Using these findings, we suggest that university environmental science programs should utilize curricula that promote more participatory and meaningful transdisciplinarity across all four phases of transdisciplinary processes to train students to address fractious social-ecological issues. [ABSTRACT FROM AUTHOR]

Environmental heat stress is implicated in various animal health issues in ruminants, including reproduction rates, mortality rates, and animal physical quality. During extremely hot weather, there is often no overnight equilibration of animal temperature with its cooling effect, and the accumulated heat load becomes an important factor in animal health for ruminants such as sheep. Using the heat load index (HLI), a heat load model is used as an indicator of heat stress on an hourly basis and annually, using downscaling models for temperature, humidity, solar radiation, and wind speed, in both spatial and temporal cases, across several example sites in regional Victoria. Analysis is provided on the performance of the downscaling models and various adaptation and mitigation options are discussed and tested. These options include using different tree planting patterns to modify solar radiation exposure and wind effects, with mixed results because adding shading structures may also diminish the effect of wind-based cooling. The modelling experiments indicated that (1) heat stress is likely to increase under future climate conditions and could represent a serious threat to the health of small ruminants; (2) adaptation measures by means of tree planting to provide shade may not be sufficient to alleviate projected heat stress; and (3) other adaptation measures will need to be considered. Indicative results for heat stress under potential future environments are provided for 2030, 2050, and 2070. Also discussed is the performance of wind speed modelling, and the effect of heat stress on animal growth and ram fertility. [ABSTRACT FROM AUTHOR]

Summary: The phytoplankton Phaeocystis globosa plays an important role in sulfur cycling and climate control, and can develop harmful algal blooms (HABs). Here we report a chromosome-scale reference genome assembly of P. globosa, which enable in-depth analysis of molecular underpinnings of important ecological characteristics. Comparative genomic analyses detected two-rounds of genome duplications that may have fueled evolutionary innovations. The genome duplication may have resulted in the formation of dual HiDP and LoDP dimethylsulphoniopropionate (DMSP) biosynthesis pathways in P. globosa. Selective gene family expansions may have strengthened biological pathways critical for colonial formation that is often associated with the development of algal blooms. The copy numbers of rhodopsin genes are variable in different strains, suggesting that rhodopsin genes may play a role in strain-specific adaptation to ecological factors. The successful reconstruction of the P. globosa genome sets up an excellent platform that facilitates in-depth research on bloom development and DMSP metabolism.

Summary: Urban centers located on the coast expose some of the most vulnerable populations to the effects of climate change. In addition to the challenges faced by high population densities and interdependent social-ecological systems, there is an increasing demand for resources. Exposing the pinch points that are already sensitive to extreme weather, highlights the urban systems that will be least resilient in the face of climate change. We map the projected changes in water availability onto the components of the food-water-energy Nexus at several spatial scales. Resilience thinking acknowledges the different spatial scales at which governance operates, resilience occurs, and Nexus systems function. We use a case study to illustrate how the effects of climate change at locations remote from the city could impact resilience of urban communities in multiple ways through cascading effects from the Nexus. This article underscores the need to examine resilience from multiple spatial and governance angles.

Summary: The nexus between environmental pollution (EP) and technological innovation is crucial for achieving sustainable development. However, existing literature has paid less attention to the new form of high-quality innovation (HI) in environmental management. This paper uses panel data from 31 Chinese provinces from 2008 to 2020, employing the two-stage least squares method to investigate the relationship between HI and EP. The empirical results reveal that HI can effectively reduce the EP, which holds after multiple robustness tests, and this effect is more obvious in southern China. Meanwhile, HI drives clean and efficient energy transition and decreases EP. Moreover, increased environmental regulation weakens the influence of HI on EP. The major contributions of this study are constructing an HI index including innovation, human capital, and government support and examining its influence on EP in China. The findings encourage government to implement policies of innovation-driven transformation, energy conservation and emissions reduction.

Summary: Bioenergy development is critical for achieving carbon neutrality. Biomass residues from agriculture, forest, and livestock manure provide substantial bioenergy resources in China, but their availability, climate, and economic impacts have not been evaluated systematically. Here we assess biomass sustainability, bioenergy potential, greenhouse gas emissions (GHG) reduction, and cost-effectiveness using an integrated data-modeling approach. Nationally, only 27% of biomass can be used for sustainable bioenergy production, but can contribute to significant climate change mitigation with optimized regional utilization. The annual GHG reduction can reach 1.0 Gt CO2e for bioenergy, or 1.4 Gt CO2e for bioenergy with carbon capture and storage (BECCS), which is comparable to total terrestrial ecosystem carbon sinks in China. The abatement cost varies regionally but is lower than many other carbon removal technologies. Our findings reveal region-specific bioenergy pathways that contribute to carbon neutrality, and encourage future assessments to explore factors including technological advances and carbon markets.

Summary: Cleaner heating policies aim to reduce air pollution and may bring about health benefits to individuals. Based on a fixed-effect model focusing on Beijing, this study found that after the onset of air pollution, daily clinic visits, hospitalization days, and hospitalization expenses increased several days after the occurrence of air pollution. These hospitalization changes were observed in males and females and three different age groups. A difference-in-differences (DID) model was constructed to identify the influences of cleaner heating policies on health consequences. The study revealed that the policy positively affects health outcomes, with an average decrease of 3.28 thousand clinic visits for all diseases. The total hospitalization days and expenses tend to decrease by 0.22 thousand days and 0.34 million CNY (Chinese Yuan), respectively. Furthermore, implementing the policy significantly reduced the number of daily clinic visits for respiratory diseases, asthma, stroke, diabetes, and chronic obstructive pulmonary diseases (COPDs).

Summary: Climate change carries important effects on human wellbeing and performance, and increasingly research is documenting the negative impacts of out-of-comfort temperatures on workplace performance. In this study, we investigate the plausibly causal effect of extreme temperatures, i.e., out-of-comfort, on language complexity among politicians, leveraging a fixed effects strategy. We analyze language complexity in over seven million parliamentary speeches across eight countries, connecting them with precise daily meteorological information. We find hot days reduce politicians’ language complexity, but not cold days. Focusing on one country, we explore marginal effects by age and gender, suggesting high temperatures significantly impact older politicians at lower thresholds. The findings propose that political rhetoric is not only driven by political circumstances and strategic concerns but also by physiological responses to external environmental factors. Overall, the study holds important implications on how climate change could affect human cognitive performance and the quality of political discourse.

Summary: Air pollution is a challenge for many cities. The digital economy enhances support for environmental pollution management, while the mechanisms and scaling heterogeneity remain unclear. This study explored the contribution of digital economy development to PM2.5 concentrations control in China and driving mechanisms in different economic subregions and urban agglomerations. Results show that the spillover transfer effect on air pollution mitigation far exceeded the direct effect at different scales. At the national scale, the air pollution mitigation effect of digital economy was mainly through empowering industrial structure optimization and green technology innovation, while it also affected economic subregions and urban agglomerations through varying scenario combinations of pathways with structural optimization, green production, resource allocation, and technology innovation. Research findings provide support for cross-regional joint management strategies of digital economy and air quality and designing regionally differentiated pollution control pathways in the digital economy dimension.

Summary: The aviation industry’s emissions have had a significant impact on global climate change. This study focuses on carbon emission trading schemes, sustainable aviation fuels (SAFs), and hydrogen energy, as vital means for the aviation industry to reduce emissions. To evaluate the climate effects of global routes under four scenarios (24 sub-scenarios) until 2100, this study proposes the Aviation-FAIR (Aviation-Finite Amplitude Impulse Response) method. The findings reveal that while CO2 emissions and concentrations are significant, other emissions, such as N2O and CH4, have a greater effective radiative forcing (ERF) and contribute significantly to climate change. Moreover, SAFs are more effective in mitigating airline pollutant emissions than relying solely on carbon trading schemes. The effectiveness of hydrogen fuel cells may be hindered by technical limitations compared to hydrogen turbine engines. The findings of this study provide reference for the global aviation industry to adopt emission reduction measures.

Summary: Many insect pests are long-distance migrants, moving from lower latitudes where they overwinter to higher latitudes in spring to exploit superabundant, but seasonally ephemeral, host crops. These seasonal long-distance migration events are relatively easy to recognize, and justifiably garner much research attention. Evidence indicates several pest species that overwinter in diapause, and thus inhabit a year-round range, also engage in migratory flight, which is somewhat ''invisible'' because displacement is nondirectional and terminates among conspecifics. Support for aseasonal, undirected migration is related to recognizing true migratory flight behavior, which differs fundamentally from most other kinds of flight in that it is nonappetitive. Migrating adults are not searching for resources and migratory flight is not arrested by encounters with potential resources. The population-level consequence of aseasonal, undirected migration is spatial mixing of individuals within the larger metapopulation, which has important implications for population dynamics, gene flow, pest management, and insect resistance management.

Summary: The abnormal reproduction of algae in water worldwide is prominent in the context of human interference and global climate change. This study first thoroughly analyzed the effects of physical factors, such as light, temperature, hydrodynamics, and operational strategies, on algal growth and their mechanisms. Physical control techniques are safe and have great potential for preventing abnormal algal blooms in the absence of chemical reagents. The focus was on the principles and possible engineering applications of physical shading, ultrasound, micro-current, and ultraviolet (UV) technologies, in controlling abnormal algal reproduction. Physical shading can inhibit or weaken photosynthesis in algae, thereby inhibiting their growth. Ultrasound mainly affects the physiological and biochemical activities of cells by destroying the cell walls, air cells, and active enzymes. Micro-currents destroy the algal cell structure through direct and indirect oxidation, leading to algal cell death. UV irradiation can damage DNA, causing organisms to be unable to reproduce or algal cells to die directly. This article comprehensively summarizes and analyzes the advantages of physical prevention and control technologies for the abnormal reproduction of algae, providing a scientific basis for future research. In the future, attempts will be made toward appropriately and comprehensively utilizing various physical technologies to control algal blooms. The establishment of an intelligent, comprehensive physical prevention and control system to achieve environmentally friendly, economical, and effective physical prevention and control of algae, such as the South-to-North Water Diversion Project in China, is of great importance for specific waters.

Summary: While artificial intelligence (AI) offers promising solutions to address climate change impacts, it also raises many application limitations and challenges. A risk governance perspective is used to analyze the role of AI in supporting decision-making for climate adaptation, spanning risk assessment, policy analysis, and implementation. This comprehensive review combines expert insights and systematic literature review. The study’s findings indicate a large emphasis on applying AI to climate “risk assessments,” particularly regarding hazard and exposure assessment, but a lack of innovative approaches and tools to evaluate resilience and vulnerability as well as prioritization and implementation process, all of which involve subjective, qualitative, and context-specific elements. Additionally, the study points out challenges such as difficulty of simulating complex long-term changes, and evolving policies and human behavior, reliance on data quality and computational resources, and the need for improved interpretability of results as areas requiring further development.