The emergence of cloud computing, big data analytics, and machine learning has catalysed the use of remote sensing technologies to enable more timely land management of sustainability indicators such as ground cover and grassland biomass, given the uncertainty of future climate and drought conditions. Here, we examine the potential of “regenerative agriculture”, as an adaptive grazing management strategy to minimise bare ground exposure while maximising pasture biomass productivity. High-intensity sheep grazing treatments were conducted in small fields (less than 1 hectare) for short durations (typically less than 1 day). Paddocks were subsequently spelled to allow pasture biomass recovery (treatments comprising 3, 6, 9, 12, and 15 months) with each compared with control treatments with lighter stocking rates for longer periods (2,000 DSE). Pastures were composed of wallaby grass (Austrodanthonia species), kangaroo grass (Themeda triandra), Phalaris (Phalaris aquatica, and cocksfoot (Dactylis glomerata) were destructively sampled to estimate total standing dry matter (TSDM), standing green biomass, standing dry biomass and trampled biomass. We then invoked a machine learning model using Sentinel-2 imagery to quantify TSDM, standing green biomass and standing dry biomass. Faced with La Nina conditions, regenerative grazing did not significantly impact pasture productivity, with all treatments showing similar TSDM and green biomass. However, regenerative treatments significantly impacted litter fall and trampled material, with the high intensity grazing treatments causing more dry matter trampling, increasing litter, enhancing decomposition rates and surface organic matter. Pasture digestibility was greatest for treatments with minimal spelling (3 months), whereas both standing senescent and trampled material were significantly greater for the treatment with 15-month spell periods. Estimates of TSDM using machine learning with Sentinel-2 imagery underestimated TSDM in treatment plots but explained spatiotemporal variability associated within and across treatments. The root mean square error between the measured and modelled TSDM was 903 kg DM/ha, which was less than the variability measured in the field. We conclude that regenerative grazing with short recovery periods (3-6 months) are most conducive to increasing pasture production under high rainfall conditions, and we speculate that high intensity grazing is likely to positively impact on soil organic carbon through increased litterfall and trampling. Our study paves the way forward for using machine learning with satellite imagery to quantify pasture biomass at small scales, enabling management of pastures from afar.

We re-inventoried red wood ant nests (RWA) in 12 study sites (≈1281 ha) in the Westeifel Volcanic Field, Germany, in an area-wide and integrated ecosystem approach after 12 years. Combined with the re-identification of previously mapped nests using a photo database, this approach leads to more accurate nest counts in (re)inventories. A total increase of nests from 1144 (2009) to 1252 (2021), and a dramatic one for the Heidberg site by 52-fold (2009) and 85-fold (2021) compared to a 1984 inventory was observed, contrasting with earlier postulations of a decline in RWA. Early to medium mature (41-80 years) and mature (³81–140 years) spruce forests were the preferred habitat. Large increase in small nest sizes suggests an increase in new nest settlements also in clearings, despite climate-induced forest dieback over the past decade. A decline in biodiversity in the herbaceous layer was observed; highly proliferating blackberries had no negative impact on RWA nests. Monitoring of woodpecker cavities in RWA nests is suggested as an indirect indicator tool for evaluating populations in forests. Positive ground movement rates caused by the Eifel plume are suggested another factor favoring nest settlements. This study contributes to the urgent update of statistically valid data required to a) effectively substantiate the status-quo of RWA occurrences, b) protect RWA as ecosystem engineers, c) advance understanding of Geo-Bio-Interactions in the wake of climate change, and c) contribute to the German government's Insect Conservation Action Program.

Rainfall variability has resulted in extreme events like devastating floods and droughts which is the main cause of human vulnerability to precipitation in West Africa. Attempts have been made by previous studies to understand rainfall variability over Ghana but these have mostly focused on the major rainy season of April-July, leaving a gap in our understanding of the variability in the September-November season which is a very important aspect of the Ghanaian climate system. The current study seeks to close this knowledge gap by employing statistical tools to quantify variabilities in rainfall amounts, rain days, and extreme precipitation indices in the minor rainfall season over Ghana. We find extremely high variability in rainfall with a Coefficient of variation (CV) between 25.3% and 70.8%, and moderate to high variability in rain days (CV=14.0% - 48.8%). Rainfall amount was found to be higher over the middle sector (262.7 mm – 400.2 mm) but lowest over the east coast (125.2 mm – 181.8 mm). Analysis of the second rainfall season using the Mankandell Test presents a non-significant trend of rainfall amount and extreme indices (R10, R20, R99p, and R99p) for many places in southern Ghana. Rainfall Anomaly Indices show that the middle sector recorded above normal precipitation which is the opposite for areas in the transition zone. The result of this work provides a good understanding of rainfall in the minor rainfall season and may be used for planning purposes.

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Risks are increasing and conditions deteriorating. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached and understood. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory that is intended to serve as the foundation for the R&D program.

Africa was the only continent not to achieve the 2015 Millennium Development Goal of 50% poverty reduction. This paper asks whether Africa will fare better in meeting Sustainable Development Goals (SDGs) addressing poverty and hunger by 2030. To answer this question we examine literature, including our field research published over the last thirteen years. We find that ‘sustainable development’ is a failed concept immersed in the contemporary global economic system that favors growth over ecosystem stability and patriarchal systems of governance that undervalue women’s capacity for sustainability in their care-work as food providers. We examine barriers to women’s farming (climate change, gender bias, limited access to land, technology, finance) and provide examples of women’s innovative strategies for overcoming these barriers in their care practices toward family and community well-being and ecosystem health. We conclude that sustainability is only possible through transformation of thinking away from approaches that value profit over people and ecosystems and toward gender-based approaches for achieving the goals laid out in the SDGs through holistic, integrative systems of ecosystem fit.

For water-stressed regions like Iran improving the effectiveness and productivity of agricultural water-use is of utmost importance due to climate change and unsustainable demands. Therefore, a hydro-economic model has been developed here for the Zarrine River Basin with the central concept of that demands are value-sensitive functions, where quantities of water-uses at different locations and times have a changeable economic benefits. To do this, the potential crop yields and the surface and groundwater resources, especially Boukan Dam inflow are simulated using the hydrologic model, SWAT, based on predicted climatic scenarios i.e. quantile mapping-downscaled projections. Then, to allocate the agricultural water based on the agro- economic crop water productivity (AEWP) of crops, a basin-wide water management tool, MODSIM, is customized. Next, a simulation- optimization model has been developed using a coupled CSPSO-MODSIM, to optimize the total AEWP, considering climatic impact and crop pattern scenarios, for 2020-2038, 2050-2068 and 2080-2098 periods. Finally, the optimum crop pattern and crop water irrigation depths are presented for different RCPs and periods. The results indicated that this approach will improve considerably the AEWPs and decrease the agricultural water-use up to 40%. Thus, this integrated model is able to support water authorities and other stakeholder in a water-scarce basin, as is the study area.

The Blue Economy represents a sustainable development model emphasizing the responsible use of ocean resources to foster economic growth while preserving marine ecosystems. This approach aims to balance economic prosperity with environmental conservation, recognizing the oceans' crucial role in supporting life on Earth. Key sectors within the Blue Economy include fisheries, tourism, renewable energy, maritime transportation, and aquaculture. As global populations rise and climate change impacts intensify, the Blue Economy is increasingly seen as essential for addressing global challenges and promoting sustainable development. Responsible fisheries management, such as implementing fishing quotas and creating marine protected areas, is crucial to combat overfishing and ensure food security. Sustainable aquaculture practices further alleviate pressure on wild fish stocks. Marine tourism, or ecotourism, promotes responsible practices that benefit local communities and the marine environment. Activities like beach clean-ups, wildlife conservation, and responsible diving practices are integral to this sector, supporting local economies and conservation initiatives. The Blue Economy significantly impacts the global economy, with the potential to double its contribution to the world's GDP by 2030. Sustainable marine sectors create jobs, drive economic growth, and contribute to energy security by harnessing renewable ocean-based energy sources. Additionally, the Blue Economy fosters innovation and technological advancements, enhancing competitiveness across various industries. Despite its potential, the Blue Economy faces challenges like overfishing, pollution, and climate change, which threaten marine biodiversity and ecosystems. Addressing these issues requires international cooperation, effective governance, and public awareness to promote sustainable practices and protect marine resource.

Retrospective information about the climate system and plant ecophysiology are key inputs in climate and Earth system modelling. Dendrochronology provides such information with large spatiotemporal coverage, and stable carbon isotope (¹³C/¹²C) analysis across tree-ring series is among the most advanced dendrochronological tools. For the past seventy years, this analysis was performed on whole molecules, and, to this day, ¹³C/¹²C variation is attributed to ¹³C discrimination during CO₂ diffusion into leaves and assimilation by rubisco. By contrast, ¹³C discrimination by post-rubisco processes is presumed constant. Here, recently reported results on the first dataset of intramolecular ¹³C discrimination in tree rings were synthesised by variance component analysis. The emerging picture is not consistent with the classical (DR-discrimination-centred) concepts and practices of carbon-isotope dendrochronology. Specifically, leaf and stem post-rubisco discrimination each account for more variation in the data than diffusion-rubisco discrimination, i.e., post-rubisco discrimination is not constant. Furthermore, diffusion-rubisco discrimination is used widely as proxy of leaf intrinsic water-use efficiency (iWUE), a key determinant in the responses of global biogeochemical cycles to climate change. However, since diffusion-rubisco discrimination is a small component of the total data variance, whole-molecule analysis yields confounded iWUE estimates, yet intramolecular analysis will likely offer solutions. Lastly, all currently observed ¹³C/¹²C-climate relationships are attributed to diffusion-rubisco discrimination. However, here, relationships with temperature and radiation derive from leaf-level post-rubisco discrimination while relationships with precipitation derive from stem-level post-rubisco discrimination. That said, advances in mass spectrometry may soon make intramolecular ¹³C/¹²C analysis broadly available taking carbon-isotope dendrochronology to the next level.

Rapid increase in urbanization and industrialization due to increase in human population has led to increase in global warming resulting to climate change that affects the ecosystem. Unusual natural disasters such as cyclones, storms, floods, weather fluctuations, rising seal levels, transitional ecosystems and coastal disruptions are major adverse effects of climate change. There are huge worrisome concerns and uncertainties about the future of the planet earth due to climate change caused by high carbon emissions. Global aggressive policies in control of Carbon-dioxide (CO2) emissions from several combustion mechanisms have paved way for alternative/ clean energy sources. Green hydrogen is a promising means of clean energy sources for commercial power generation stations and other crucial systems such as hydrogen fuel cell vehicles (HFCVs) , motors, drives, backup power for buildings, and also serving as a source of electrical energy for remote locations. The goal of this study is to review the current level of Sub-Saharan African nations’ preparedness to adopt green hydrogen as a way to mitigate local energy supply issues and strengthen their individual economies.

This paper provides an in-depth exploration of the role of Big Data and Artificial Intelligence (AI) in advancing dairy farming towards net zero emissions, a critical goal in the face of the global climate crisis. The study emphasizes how these technologies significantly enhance the management of greenhouse gas (GHG) emissions and optimize resource use, thereby contributing to environmental sustainability in agriculture. A key aspect of this transition is the alignment with international climate commitments, such as the Paris Agreement, which are instrumental in steering global efforts toward emission reduction and mitigating climate change. The integration of Big Data and AI in dairy farming emerges as a powerful tool to reduce the sector's environmental impact while sustaining economic growth. The paper delves into the specific applications of these technologies in emission management, including predictive analytics for feed optimization, manure management, and energy efficiency enhancements. It also addresses the broader implications of technological integration in dairy farming, considering aspects like benchmarking standards, data privacy, and the role of policy in fostering sustainable practices. The study underscores the challenges inherent in adopting these advanced technologies, including the need for improved farmer training, data quality, and compatibility with existing systems. It also advocates for enhanced policy frameworks that support sustainable practices, encourage technological adoption, and balance economic viability with environmental responsibility. This comprehensive analysis offers valuable insights into harnessing digital technologies for climate change mitigation and delineates a path for the dairy industry towards achieving net zero emissions, thereby contributing significantly to global environmental sustainability efforts.

The amendment or removal of superfluous government support policies is typically difficult, yet in the ever more important debate on low-carbon (i.e. clean) marine energy policy under the international law of climate action, the law of the sea, and international investment protection, there are additional dimensions of legal or economic peril. Coastal states enact policies subsidising clean energy investments, such as offshore wind energy generation, in their exclusive economic zones or continental shelves. Investors are attracted to the prospect that policies granting subsidies for ostensibly new industries are sufficiently durable. Are such subsidy policies salient or stale? In principle, the purpose of regulatory policy is the promotion of social welfare, and hence there is an optimal incidence, magnitude, and duration of the subsidy, in essence, an ideal strategy for starting, altering, or exiting such policy. We aim to introduce the concept of optimisation to the design and implementation of regulatory policy in this context. Our contribution is to offer three maxims of optimal clean marine energy law and policy: the efficiency and equity of alternative regulatory arrangements; the continuous optimisation of such arrangements; and the recognition of linguistic entanglements in the law. We test these maxims against the case of clean marine energy policy on offshore wind energy generation. One legal implication for international investment protection is that coastal states should establish a policy exit clause in their investment contracts. Our analysis of policy optimisation is generalisable across policies supporting the transition to sustainable energy forms.

We reviewed various physical and biological manifestations of an unprecedented large-scale water temperature anomaly that emerged in the Northeast Pacific in late 2013. The anomaly dubbed “The Blob” persisted through 2014-2016, with some signs of its persistence through 2017-2018 and a possible reemergence in 2019. The tentative timeline of The Blob’s successive appearances around the Northeast Pacific is suggestive of its advection by currents around the Gulf of Alaska, along the Aleutians, into the Bering Sea, and eventually to the Bering Strait. During the initial phase of The Blob’s development in 2013-2014, advection along the Polar Front might have played a certain role. The extreme persistence and magnitude of The Blob resulted in numerous and sometimes dramatic ecosystem responses in the eastern Bering Sea. The multi-year duration of The Blob might have preconditioned the Bering Sea for the record low seasonal sea ice extent during the winter of 2017-2018 and disappearance of the cold pool in 2016 and 2018 that profoundly affected zooplankton, invertebrates, fishes, sea birds, and marine mammals. Comparison of time-series of population responses across trophic levels suggests that The Blob lowered primary production during spring, increasing small copepod production and jellyfish, and reducing energy transfer efficiently to higher trophic levels. While the Bering Sea’s water temperature, seasonal sea ice, and cold pool seem to return to the long-term mean state in 2022, it remains to be seen if the Bering Sea ecosystem will completely recover. The two most likely alternative scenarios envision either irreversible changes or hysteresis recovery.

Arctic sea ice characteristics have been changing rapidly and significantly in the last few decades. Using a long-term time series of sea ice products from satellite observations - the extended AVHRR Polar Pathfinder (APP-x), trends in sea ice concentration, ice extent, ice thickness, and ice volume in the Arctic from 1982 to 2020 are investigated. Results show that the Arctic has become less ice-covered in all seasons, especially in summer and autumn. Arctic sea ice thickness has been decreasing at the rate of -3.24 cm per year, resulting in about a 52% reduction in thickness from 2.35 m in 1982 to 1.13 m in 2020. Arctic sea ice volume has been decreasing at the rate of -467.7 km³ per year, resulting in about a 63% reduction in volume, from 27590.4 km³ in 1982 to 10305.5 km³ in 2020. These trends are further examined from a new perspective, where the Arctic Ocean is classified into open water, perennial, and seasonal sea ice-covered areas based on the sea ice persistence. The loss of the perennial sea ice-covered area is the major factor in the total sea ice loss in all seasons. If the current rates of sea ice changes in extent, concentration, and thickness continue, the Arctic is expected to have ice-free summer by the early 2060s.

How much is religion quantitatively involved in global climate politics? After assessing the role of the Conference of Parties to the United Nations Framework Convention on Climate Change from a normative perspective, this descriptive, transdisciplinary and unconventional study offers the first comprehensive quantitative examination of religious nongovernmental organizations that formally participate in its annual meetings, the largest attempts to solve the climate crisis through global governance. This study finds that although their numbers are growing, only about 3 percent of registered nongovernmental organizations accredited to participate in the conference are overtly religious in nature — and that more than 80 percent of those faith-based groups are Christian. Additionally, this study finds that religious nongovernmental organizations that participate in the conference are mostly from the Global North. The results call for greater participation of religious institutions in the international climate negotiations in order for society to address the planetary emergency of climate change.

The present paper reviews evidence for ecological evolution of Montiaceae. Montiaceae (Portulacineae) comprise a family of ca. 275 species and ca. 25 subspecific taxa of flowering plants distributed mainly in extreme western America, with additional endemism elsewhere, including other continents and islands. They have diversified repeatedly across steep ecological gradients. Based on narrative analysis, I argue that phylogenetic transitions from annual to perennial life history have been more frequent than suggested by computational phylogenetic reconstructions. I suggest that a reported phylogenetic correlation between the evolution of life history and temperature niche is coincidental and not causal. I demonstrate how statistical phylogenetic comparative analysis (PhCA) missed evidence for marked moisture niche diversification among Montiaceae. I discount PhCA evidence for the relation between Montiaceae genome duplication and ecological diversification. Based on the present analysis of Montiaceae evolution, I criticize the premise of the prevalent statistical approach to PhCA, which tests Darwinian deterministic hypotheses against stochastic evolutionary null models. I discuss theoretical/empirical evidence that evolution is neither stochastic, nor Darwinistically-determined, but idiosyncratic. Idiosyncraticity describes the outcome of a stochastically perturbed nonlinear chaos-like process. The Principle of Evolutionary Idiosyncraticity (PEI) is based on the evolutionary theory of Natural Drift, which maintains that determinism in evolution is a property of the organism and not, as maintained by the theory of Natural Selection, its traits or its milieu. This determinism is characteristic of chaotic functions, which are absolutely determinate, generate self-similarity, but remain absolutely unpredictable. PEI explains precisely observations that evolution proceeds not linearly, but chaotically, producing both quasi-linear fractal-like patterns and non-linear jumps. PEI has ramifications for all areas of macroevolutionary research. In particular, it demonstrates both the fallacy and futility of the statistical PhCA approach that interprets evolutionary causes in terms of evolutionary correlations. However, statistical methods of PhCA can be applied heuristically and fruitfully to reveal idiosyncraticity and discover evolutionary novelty. This, in turn, is demonstrated by the emergence of statistical anomalies in evolutionary analyses of Montiaceae.

Climate change has emerged as a crucial global issue that significantly threatens the survival of plants. In particular, low temperature (LT) is one of the critical environmental factors that influence plant morphological, physiological, and biochemical changes during both the vegetative and reproductive growth stages. LT, including abrupt drops in temperature, as well as winter conditions, can cause detrimental effects on the growth and development of tomato plants, ranging from sowing, transplanting, truss appearance, flowering, fertilization, flowering, fruit ripening, and yields. Therefore, it is imperative to understand the comprehensive mechanisms underlying the adaptation and acclimation of tomato plants to LT at the morphological and the molecular levels. In this review, we discuss the previous and current knowledge of morphological and physiological changes, which contains major factors and traits associated with the LT stress response during the period of the vegetative and reproductive growth and development in tomato plants. Moreover, we highlight recent advances in the understanding of physiological and biochemical responses, and molecular mechanisms, including LT perception, signaling transduction, gene regulation, and fruit ripening and epigenetic regulation. The comprehensive understanding of LT response provides a solid basis to develop the LT-resistant varieties for sustainable tomato production under the ever-changing temperature fluctuations.

Ecological Society is based on socioeconomic systems directed to the equilibrium of inter-relationships between environment, climate, production systems, technologies and human communities to promote the overall well-being of people and the Earth planet. It has a main goal for supporting sustainable development and equitable societies and achieving optimal health outcomes recognizing the interconnection between people, technologies, animals, plants, and their shared environment for the one health. Using data of scientific publications and patents until the year 2024, this study shows new technologies that can support the energy transition with the shift from fossil fuels to renewable energy sources in an effort to reduce CO₂ emissions for an ecological society having, whenever possible, zero-carbon economies to reduce environmental pollution and climate change and foster health and wellbeing of people. Results reveal that sustainable technologies supporting the transformation of the energy sector, economies and societies, and having a rapid growth, are blue hydrogen, floating photovoltaic systems, carbon capture and utilization, green hydrogen and liquid metal batteries. These findings can guide decisions of policymakers and stakeholders towards fruitful investments driving the transition from fossil-based to zero-carbon socioeconomic systems to have a long-run sustainable development of overall world system that has to direct towards an ecological society associated with one health.

Appropriate governance structures are extremely important for the fishery dependent communities to develop integrated territorial development strategies and adaptive capacity to change, including the climate one. This paper assesses to what extent fisheries co-management schemes (e.g Fisheries LAGs, being regional/local governance instruments in fishing communities) are strengthening sustainability. The latter includes improving energy efficiency, promoting renewable energy sources (RES), coping with climate crisis, minimizing environmental impacts, and promoting sustainable blue economy. For detecting policy aspects of aligning climate neutrality and sustainable blue economy, the research lens focuses on the Greek Fisheries Local Action Groups (FLAGs) given that these are mostly located in coastal/marine and insular territories with significant blue growth potential. To map and assess their capacity and efficiency in pursuing Green Deal objectives, a co-development process with FLAG managers was put in place. The results and findings of this process reveal the scarcity of sustainability and blue economy related strategies. Key conclusion is that transition to a post-carbon blue economy on a local level, requires the understanding of the evolutionary dynamics of fisheries co-management schemes. The latter, being multi-sectoral structures, may boost dialogue and cooperation to harmonize local development strategies and EU policies. Maritime Spatial Planning (MSP) as an evolutionary governance process itself, can be a driver for making FLAGs evolve, and strengthen commonization and blue justice and equity for fishers.

Individuals with low health literacy (HL) are known to have poorer health outcomes and to have higher mortality rates compared to individuals with higher HL: hence, the improvement of HL is a key outcome in modern healthcare systems. Healthcare providers are therefore asked to support patients’ literacy skills by encouraging the implementation of autonomy-supportive patient centered communication (PCC), which in turn requires the enhancement of patient engagement. Our main hypothesis is that the well-known relationship between autonomy-supportive PCC and HL is mediated by patient engagement which is known to play a role in HL promotion and that is related to PCC as well. The purpose of this study was to formulate a hypothetical structural equation model (SEM) linking PCC to patient engagement and HL. A cross-sectional survey design was employed involving 1007 Italian chronic patients. The hypothetical model was tested using SEM to verify the hypothesized mediation of patient engagement between PCC and HL. Results show that the theoretical model has a good fit indexes and that patient engagement fully mediates the relationship between PCC and HL. This finding suggests healthcare systems to implement a new paradigm where patients are supported to play an autonomous role in their own healthcare.

Globalization and industrialization have significantly disturbed the environmental ecosystem, leading to critical challenges such as global warming, extreme weather events, and water scarcity. Forecasting temperature trends is crucial for enhancing the resilience and quality of life in smart sustainable cities, enabling informed decision-making and proactive urban planning. This research specifically targets Ahmedabad city in India and employs the Seasonal Auto Regressive Integrated Moving Average with eXogenous factors (SARIMAX) model to forecast temperatures over a ten-year horizon using two decades of real-time temperature data. The stationarity of the dataset was confirmed using the Augmented Dickey-Fuller test, and the Akaike Information Criterion (AIC) method helped identify the optimal seasonal parameters of the model, ensuring a balance between fidelity and predictive accuracy. The model achieved an RMSE of 1.0265, indicating high accuracy within the typical range for urban temperature forecasting. This robust measure of error underscores the model’s precision in predicting temperature deviations, which is particularly relevant for urban planning and environmental management. The findings provide city planners and policymakers with valuable insights and tools for preempting adverse environmental impacts, marking a significant step towards operational efficiency and enhanced governance in future smart urban ecosystems. Future work may extend the model's applicability to broader geographical areas and incorporate additional environmental variables to refine predictive accuracy further.

There is a growing concern about climate change being a serious threat to insurance business sustainability. Knowing if climate warming is a cause for claims and losses increase, and how this cause-effect relationship will develop in the future are two open major questions. In this article, we answer both questions by particularizing the geographical area of Spain, and a precise risk, hailstorm in crop insurance in the line of business of wine grapes. We measure climate change thanks to the Spanish Actuarial Climate Index (SACI). We use a database containing all the claims caused by hail risk in Spain from 1990 to 2022. With homogenized data, we consider as dependent variables the monthly number of claims, monthly number of loss costs equal to one, and monthly total losses. The independent variable is the monthly Spanish Actuarial Climate Index (SACI). We try to explain the former through the latter using regression and quantile regression models. Our main finding is that climate change as measured by SACI explains these three dependent variables. We also give an estimation of the increase of the monthly total losses Value at Risk, corresponding to a future increase in climate change measured in units of SACI. Spanish crop insurance managers should carefully incorporate these conclusions into their decision-making process to keep this line of business sustainable in the future.

Coastal resources in Lian, Batangas, have undergone significant degradation due to a combination of human activities and natural factors, including sea-level rise, changes in sea-surface temperature, fluctuations in rainfall, increased storm frequency, and sedimentation. This has led to adverse effects on key ecosystems such as corals, mangroves, and seagrasses. To assess the extent of climate change hazards on these coastal resources, a Vulnerability Assessment was conducted in the municipality of Lian, Batangas. The assessment employed a combination of the Coastal Integrity Vulnerability Assessment Toolkit (CIVAT) and Integrated Coastal Sensitivity, Exposure, and Adaptive Capacity to Climate Change (ICSEA-C) guidelines. Additionally, the analysis incorporated detailed mapping using Light Detection and Ranging (LiDAR) data for mangroves and LandSat 8 imagery for corals and seagrasses. The findings at the municipal scale revealed that a staggering 90% of mangroves in Lian, Batangas, were highly vulnerable. This vulnerability was attributed to a high score in intrinsic characteristics and a low adaptive capacity. Similarly, a majority of seagrasses in the area were classified as medium and highly vulnerable at the municipal level. Only 10–20% of seagrasses received low to medium vulnerability scores. Shockingly, almost 100% of the coral reefs in Lian, Batangas, were deemed highly vulnerable, indicating a critical threat to this crucial marine ecosystem.

Background: Physical and mental health of corporate employees is equally important, especially in international salespeople in the in vitro diagnostic (IVD) medical device industry. The rapid growth of the IVD market is driven by the increasing prevalence of chronic and infectious diseases. This study aims to identify the association of socio-demographic, occupational, organizational, and psychosocial factors with mental health outcomes for depression, anxiety, and somatic symptoms in Chinese IVD international salespeople. Methods: The study was a cross-sectional survey of ISs in IVD companies officially registered in China. An online survey was designed to collect data through email contact with IVD companies and social media between August 2022 and March 2023. Measured factors included effort-reward imbalance (ERI), health-promoting leadership (HPL), health climate (HC), inner strength (IS), and perceived social support (PSS). Mental health outcomes assessed using the Core Symptom Index (CSI) were depression, anxiety, and somatic symptoms. Results: A total of 244 salespeople responded to the survey. CSI scores indicated that 18.4% (n = 45) and 10.2% (n = 25) of the respondents had symptoms of major depression and anxiety, respectively. ERI was positively correlated, while the IS and PSS were negatively correlated with major depression, anxiety, and somatic symptoms (p < .01). Health climate was negatively correlated with major depression (p < .05). Education background was associated with somatic symptoms (p < .05). ERI, IS, and gender were significant predictors of major depression, anxiety, and somatic symptoms (p < .05). Conclusion: The prevalence of depression and anxiety in China’s IVD international salespeople was considered low compared with prevalence in Chinese populations during COVID-19, but higher than those before the pandemic. Effort–reward imbalance, inner strength, and gender were significant factors in major depression, anxiety, and somatic symptoms among IVD international salespeople.

The need to address climate change and establish sustainable urban environments has driven increased efforts in Europe to develop climate-neutral cities. This study highlights the importance of integrating solar energy technologies and nature-based solutions as key strategies to achieve climate neutrality. By examining current practices, emerging trends, and case examples, it explores the benefits, challenges, and prospects associated with the integration of solar energy and nature-based solutions in urban contexts. The study presents a pioneering approach to assess the urban heat and climate change mitigation benefits of combining building-integrated photovoltaics and nature-based solutions specifically within the European context. The results emphasize the synergistic relationship between nature-based components and solar conversion technology, identifying effective combinations for different climatic zones. In warmer regions of Southern Europe, strategies like rooftop photovoltaics on cool roofs, photovoltaics shadings, green walls, and urban trees have demonstrated effectiveness. Conversely, mid- and high-latitude European cities have seen positive impacts through the integration of rooftop photovoltaics and photovoltaics facades with green roofs and green spaces. As solar cell conversion efficiency improves, the environmental impact of photovoltaics is expected to decrease, facilitating their integration into urban environments. The study emphasizes the importance of incorporating water bodies, cool pavements, spaces with high sky-view factors, and effective planning in urban design to maximize resilience benefits. It also highlights the significance of prioritizing mitigation actions in low-income regions and engaging citizens in the development of social photovoltaics positive energy houses, resilient neighbourhoods, and green spaces. By adopting these recommendations, European cities can lead the way in creating climate-neutral urban environments that prioritize clean energy, nature-based solutions, and the overall well-being of residents. The findings underscore the need for a multidisciplinary approach that combines technological innovation, urban planning strategies, and policy frameworks to effectively achieve climate neutrality in European cities.

Historical analysis of Australian bushfire data spanning 170 years addresses whether the strength of recent fire events has been exacerbated by human-induced climate change. The question of “cause” looks at the characteristics of a wider range of natural hazards. Fire characteristics are compared with earthquake hazard characteristics: (1) energy – termed “magnitude”; (2) severity – termed “intensity”; and (3) resultant damage to people and structures – termed “impact”.Published global, Northern and Southern hemisphere temperature data are shown to vary consistently in phase over 170 years, but vary in amplitude with statistical significance. CO₂ levels north and south of the Equator have tracked quite consistently. Thus, Southern Hemisphere bushfire magnitude and intensity is compared with the Southern Hemisphere climate record, rather than a global data set.28 major bushfires and associated droughts since 1850 show neither apparent drought extent, nor area burned, nor bushfire intensity, correlates with changes in Southern Hemisphere climate. Average rainfall from 1900 shows a wetter, rather than drier trend. Cyclone energy shows no significant trend with climate. Planet-wide “greening”, through CO₂ fertilisation, is an insignificant contributor to bushfire magnitude. Combustion theory shows recorded “global warming” could have had no significant influence on bushfire magnitude or intensity. Any increase in Australian bushfire impact, as judged by lives lost, similarly, shows no correlation with bushfire magnitude, nor indeed, any observed Southern Hemisphere global warming.Thus, bushfire magnitude seems much more likely driven by fuel load and any anomalous bushfire intensity is likely driven by anomalous ground level fuel load. The evidence suggests that any CO₂ emissions reduction will have no impact on future bushfire “severity.

Nicotiana benthamiana plants infected with a potato virus Y isolate (PVYO) under ambient conditions of 25 °C and ~405 parts-per-million (ppm) ambient CO2 display symptoms of chlorosis, leaf curling, and stunting. However, under elevated temperature and CO2 levels (30 °C, 970 ppm), systemic viral titers decrease several-fold, and plants appear asymptomatic. Under the latter conditions we have studied how infection, drought, or both combined affect infection, drought-driven loss of leaf turgor, plant water content, stomatal conductance, metabolome, and hormone (ABA, SA, and JA) levels. We found that drought did not affect viral titers. As expected, drought decreased plant water content and stomatal conductance. Under drought conditions, infection did not alter significantly final water content or loss of leaf turgor progression, but it increased the levels of some sugars and other osmo-protectants. Infection and drought altered the levels of many components of the metabolome. Some components altered by infection were not altered by drought, but most of those altered by drought were also altered by infection. Drought increased the levels of ABA, infection increased the levels of ABA, SA, and JA, and altered their relative balance. The effects of drought and of infection on hormone levels were cumulative when combined. Thus, under ambient conditions that turn a severe infection into an asymptomatic one both, plant physiology parameters and the interplay with drought are affected.

Air pollution, climate change and global warming show direct linkage. Introduction - Background: Research in the field has proposed and demonstrated their link to increased allergenicity in plants, leading to increased allergic diseases. Allergen patterns are changing in response to climate change. Across Europe, up to 12% of the population suffers from allergic diseases (bronchial asthma and allergic rhinitis) caused by the pollen grains. The medical costs of these types of allergies are enormous and are increasing with the spread of common ragweed - Ambrosia artemisiifolia* in Europe. In practice, more and more patients are turning to allergists. Methods: Based on these data, the research aims to identify safety measures and specific legislation to control and eradicate common ragweed in the countries most affected by the spread of this plant in Europe, increase in population exposure in countries affected by the presence of common ragweed and the socio-economic impact of allergic rhinitis and bronchial asthma at European level.[1][2] Our database search did not reveal any other research that has addressed this topic to date. Results: This research identifies specific legislation to the countries most affected by the spread of this plant pollen grains at European level, changes in allergen patterns and monitoring/safety eradication measures decided by local authorities, and data on the spread of common ragweed over the last two decades, costs per treatment, increased allergic rhinitis and bronchial asthma morbidity in the most affected areas. Conclusions: At European level, there are no universally valid models for eradicating this weed. Various methods can be used to limit the spread of common ragweed and its pollen production (e.g. mowing once or twice a year of overgrown land, ploughing, chemical control, public information, etc.). Local and regional cooperation should be considered essential to promote phytosanitary &amp; safety measures and exchange of information on methods to identify and manage the spread of common ragweed. Unified legislation at European level would help all affected countries; reduce morbidity from respiratory allergic diseases and the costs of treating these diseases.

This study introduces a technique to uncover concealed patterns in satellite altimetry data, reflecting sea level variations in inland water bodies. We applied the methodology to the Caspian Sea, using altimetry data from four satellite missions over 27 years (1993-2020): TOPEX/Poseidon, Jason1, Jason2, and Jason3. The approach involves two steps: estimating sea level trends and identifying breakpoints that indicate trend shifts; and leveraging time lags between breakpoints at various locations to classify water drainage areas according to their degree of influence on each period. By revealing concealed patterns in the altimetry data, this technique can provide insights to understand the impacts of global warming and local climate changes on sea level fluctuations in the Caspian Sea. We hope that our study can facilitate subsequent interdisciplinary research on the intricate interplay between climate change and hydrological processes in inland water bodies.

Forest carbon sequestration is a widely accepted natural climate solution, however, methods to determine net carbon offsets are limited to commercial carbon proxies and CO2 eddy covariance research. Non-CO2 greenhouse gases (GHG) (e.g., CH4, N2O) receive less attention in the context of forests, in part, due to emphasis on CO2 and the operational requirements and cost for three-gas eddy covariance platforms. In this study, Howland forest flux tower (CO2, CH4) and soil flux data (CO2, CH4, N2O), representing net emission reductions, are linked to their respective social costs to estimate commercial revenue if sold as a GHG social cost forest offset product (GHG-SCF). Estimated annual revenue for GHG-SCF products, applicable to realization of a Green New Deal, range from 120,000 covering the site area of 557 acres in 2021, to 12,000,000 for extrapolation to 40,000 acres in 2040, assuming a 3% discount rate. The Howland Forest CO2 flux record for two adjacent towers is compared to California Air Resources Board forest carbon proxy data for compliance sequestration offsets, the only project site where these approaches overlap. Overcrediting, incomplete carbon accounting with annual errors of up to 2,256%, inadequate third-party verification, and limited application to non-CO2 GHG’s are established. In contrast, direct measurement of one or more GHG’s offers new forest products and revenue incentives to restore and conserve forests worldwide.

Species distribution models (SDMs) are usually used to predict current species’ geographic distributions and to forecast the impact of climate change, with different aims, such as conservation, and biodiversity management. SDMs use has been increasing in the last decades, however, they are vulnerable to parametrization and data quality input. Thus, inappropriate input can lead to potential unreliability in results. In this context, the most used data and methodologies in SDM, and putative deviations from the consensual best practices, were identified, by analysing recent literature (2018 to 2022). Results show that the parameters presented more consistently are the chosen algorithm (MaxEnt was used in 98% of the studies), the accuracy measures, and the time windows. Many papers fail to specify other parameters, limiting the reproducibility of the studies. Some papers also fail to provide information about the target species: only a fraction of the species' range is considered, or no justification for including specific variables in the model is provided. These options can decrease reliability in predictions under future scenarios since data provided to the model is inaccurate from the start or there is insufficient information for outputs discussion.

Advances in biological sciences have been applied in medicine, agriculture and industry with great benefit. Some recent trends in society, governance structures and communications, however, appear to be hampering the use of new scientific findings for controlling infectious diseases. These limitations are illustrated with examples related to (i) the adaptation of fresh water mosquito vectors of major arboviral diseases to salinity in coastal areas with consequences for disease transmission, (ii) understanding the implications of reduced dengue transmission during the COVID-19 lockdown for dengue control, (iii) causes underlying the rapid spread of the malaria vector Anopheles stephensi in South Asia and Africa, (iv) the application of serodiagnostic techniques for Lyme disease and tick-borne relapsing fever caused by tick-borne bacteria of the genus Borrelia, and (v) COVID-19 prevention.

High-resolution forecasting of vegetation type shifts may prove essential for anticipating and mitigating the impacts of future climate change on bird populations. Here, we used the US Forest Service Ecological Response Unit (ERU) classification to develop and assess vegetation-based breeding habitat profiles for eight owl species occurring in foothills and mountains of the southwestern US. Shifts in mapped habitat were forecast using an ecosystem vulnerability model based on the pre-1990 climate envelopes of ERUs and the A1B moderate IPCC emission scenario of future climate. For five of the eight owl species, regional breeding habitat extent was projected to decline by at least 60% by 2090. Three species, the boreal owl (Aegolius funereus; at the trailing edge of its distribution), flammulated owl (Psiloscops flammeolus), and northern pygmy-owl (Glaucidium gnoma) were projected to experience the steepest habitat-loss rates, or 85%, 85%, and 76%, respectively. Projected vegetation shifts overlaid with well-documented flammulated owl breeding populations showed complete or near complete loss of habitat by 2090 in areas of montane forest currently supporting dense aggregations of owl territories. Generalist or lower-elevation owl species were predicted to be less impacted, while for the whiskered screech-owl (Megascops trichopsis), the contraction of current habitat was nearly offset by a projected northward expansion. In general, the results of this study suggest high exposure to climate change impacts for upper-elevation forest owls of semi-arid southwestern North America. Long distance migration and low natal philopatry may prove important to some montane owl populations for adapting to regional loss of habitat.

The objective of this study was to identify the factors determining a company’s corporate governance related to climate change. We analyzed the effect of various sustainability corporate governance variables on the disclosure level of climate change governance. These variables included facts such as having a dedicated sustainability executive and board committee, the mediating effect of female representation on the board of directors, number of reporting years according to TCFD, membership in a sustainability index, MSCI ESG rating, the existence of a corporate climate transition plan, a mention of the UN Global Compact and GRI, company location, as well as company size and profitability. By adopting a multi-theoretical framework that included stakeholder theory as well the legitimacy and agency theory, the underlying research study used a sample of 100 of the largest global companies by market capitalization and their reporting for the year 2020. Based on 1,400 observations for fiscal year 2020 and using correlation analysis, univariate and linear multiple regressions, we find a positive association between having a climate transition plan in place, being a leader in sustainability according to MSCI ratings, and being a DJSI constituent and the propensity to disclose information on governance for climate change. In addition, we find a company with a dedicated sustainability executive show an increased tendency to be transparent on climate governance issues. Furthermore, having a company location in a developed country is significantly and positively associated with climate change governance. Surprisingly, gender diversity in the corporate board or having a sustainability board committee did not show any significant correlation between a higher climate change governance level. The same was true for companies being active in either the extractive or non-extractive sector. Companies referring to the Global Reporting Initiative (GRI) or UN Global Compact also did not score higher in climate change governance. Neither did corporate profitability or size play a significant role. Our results are robust to variations and provide valuable insights for researchers, academics, executives, practitioners as well as regulators. As more and more companies are shifting towards a climate change reporting framework, it is of paramount importance that we are able to determine the contributing variables that lead to effective climate change corporate governance. Our results are inconsistent with stakeholder theory and are strongly suggesting that a diversified board and the existence of a sustainability committee that meets often/sufficiently may not necessarily lead to a higher level of transparency/quality regarding climate change. While more research is needed, knowing that a dedicated sustainability executive as well as having a climate plan in place can make a difference in climate change reporting, can be very beneficial to many corporate stakeholders. Given the current urgent climate change situation and the crucial role that corporation play in it, dedicated sustainability positions and committees need to be established. The findings could be useful for managers as well as governmental standards setter and regulators who are interested in improving corporate practices dealing with climate change. This study applies STATA software with various regression models to empirically test the relationship between CG and other variables and corporate climate change reporting.