Climate change effects on biodiversity, ecosystems, ecosystem services, and natural resource management in the United States

Unravelling the eco-monitoring potential of phytoplankton towards a sustainable aquatic ecosystem

Phytoplankton play an integral role in primary production in aquatic ecosystems, thus butressing its function as an important tool for pollution indication and water quality assessment. Their response mechanism towards the changes in nutrient levels and environmental conditions makes them valuable indicators of ecosystem health. The driver of this response is a complex molecular mechanism involving gene expression and metabolic pathways that allow microalgae to adapt and thrive in varying conditions. The current study shows how phytoplankton population and functional trait dynamics can serve as early signs of potential environmental stressors impacting aquatic ecosystems. This study is highly significant because it highlights the role of phytoplankton as sensitive and reliable bioindicators of aquatic ecosystem health. Thus, providing valuable information for monitoring and managing water quality in marine environments. Also, the study will provide a unique insight into understanding the impact of pollution on phytoplankton, which can also help inform conservation efforts to protect vulnerable species and ecosystems. The study linked the bioindicator role of phytoplankton to a complex molecular mechanisms involving alterations in gene expression, activation of stress-related signalling pathways, and shifts in metabolic profiles. These responses are often characterised by the production of reactive oxygen species (ROS), the upregulation of antioxidant defence systems, and modifications in lipid, protein, and pigment synthesis. The progress of the application of phytoplankton for biomonitoring has been hindered by issues such as sensitivity to multiple environmental variables, diversity of phytoplankton species, and complexity of community interactions. This challenge can be averted through the development of advanced monitoring techniques that can accurately detect and quantify toxins in real time.

A comprehensive review of mycotoxins, their toxicity, and innovative detoxification methods

A comprehensive overview of food mycotoxins, their toxicity, and contemporary detoxification techniques is given in this article. Mycotoxins, which are harmful secondary metabolites generated by a variety of fungi, including Fusarium, Aspergillus, and Penicillium, provide serious health concerns to humans and animals. These include hepatotoxicity, neurotoxicity, and carcinogenicity. Mycotoxins are commonly found in basic food products, as evidenced by recent studies, raising worries about public health and food safety. The article discusses detection techniques such as enzyme-linked immunosorbent assays (ELISA), and quick strip tests. Moreover, the use of various control systems associated with the detoxification of mycotoxinis highlighted. In addition, novel detoxification strategies such as nanotechnology, plant extracts, and omics studies were also discussed. When taken as a whole, this analysis helps to clarify the pressing need for efficient management and monitoring techniques to prevent mycotoxin contamination in the food chain.

Conserving the critically endangered Hangul (Cervus hanglu hanglu)-future distribution and efficiency of protected areas under climate change

Climate change is impacting species distribution at a global scale, posing a significant threat to biodiversity. Special attention needs to be given to threatened species like the Kashmir Red Deer (Cervus hanglu hanglu). Despite being a symbol of global conservation, holistic management is necessary for decision-making and species recovery. A comprehensive study mapping of the potential habitat changes for Hangul in the Dachigam landscape is crucial to enhance conservation efforts. We examined the impacts of expected global warming on the distribution of Hangul by employing a maximum entropy approach to assess species range shift. Hangul was anticipated to be sensitive to upcoming worldwide warming, and it was expected that this would increase its risk of local extinction. In the model, the severity of repercussions from climate change grew as the time horizon increased and decreased the species' suitable habitat. By 2080, predictions indicated a gradual reduction in range or, in some scenarios, the complete loss of habitat, regardless of the potential for Hangul to disperse indefinitely. We estimated that the overall very highly suitable habitat in the protected region is currently 2220 ha, while its vast distribution area in the unprotected zone is 30,445 ha, emphasizing the necessity of establishing corridor connectivity between fragmented populations and promoting conservation efforts. Among various climate conditions, the core-to-edge ratio is at its highest level in the current conditions. Our study reveals two critical findings: Firstly, endangered species unique to a particular region are highly susceptible to the impacts of global warming. Secondly, when evaluating the outcomes of global warming, the highly suitable habitat is expected to shift under predicted climatic changes, with an average altitudinal migration of 700 m. Consequently, conservation strategies must consider the expected regional shifts and are designed with a clear understanding of the accuracy of projecting climate change effects.

Warming unsynchronised tree radial growth and regional vegetation canopy growth in semi-arid areas of north-eastern China--a case of Pinus sylvestris var. mongolica in plantation

Exploring the synchronisation between radial growth from a specific tree species and the regional vegetation canopy growth covering a certain area (obtained from remote sensing data) and their climate responses contributes towards clarifying the influence of climate change on aboveground forest biomass. We assessed the variation and correlation between the radial growth of Pinus sylvestris var. mongolica (PM) and regional vegetation canopy growth along with their climate responses in the semi-arid area of northeastern China, investigating the synchronisation and temperature limitation of the two growths. We also clarified the variation in the synchronisation of radial and canopy growth in a warming climate. The radial growth of PM and canopy growth of regional vegetation increased significantly. Positive correlations between tree-ring width index (RWI) and leaf area index (LAI) during May and June were higher than those during the rest of the months and month-combinations of a year. The synchronisation of the radial growth and the canopy growth significantly increased along increasing gradients of latitude, and significantly decreased along increasing gradients of temperature. Radial and canopy growth were limited in July by minimum temperatures in the northern high-latitude sample sites (cold and arid) of the study area. Warming induced the unsynchronised radial and canopy growth in the semi-arid area. The synchronous change of the two growth types will weak in the study area in the future; the decoupling of tree growth is expected to occur earlier in the cold, dry areas than in the warm, wet areas. Weakened or broken statistical linkages, such as the synchronisation between the radial growth of a tree species and the canopy growth of the regional vegetation, indicate that the decreased effectiveness of a specific tree radial growth as an indicator of regional vegetation growth complicates the up- or down-scale assessment of forest biomass dynamics and its carbon sequestration potential.

Modeling supports the implementation of urban greening as a response to the challenges of sustainable spatial planning

Urban greening is critical for sustainable urban development, climate change mitigation, and biodiversity conservation. However, the effectiveness of urban greening varies depending on the specific goals (e.g., enhancing biodiversity, reducing urban heat, or both) and their spatial implementation. To address the spatial variability in the effectiveness of greening, we propose a spatial decision support model based on the non-dominated sorting genetic algorithm-II (NSGA-II). This model aims to optimize urban greening locations to maximize biomass density, mitigate urban heat stress, and improve landscape connectivity. Applied to Suwon City, South Korea, the model's effectiveness was evaluated against a business-as-usual (BAU) scenario across four scenarios: connectivity-based, biomass density-based, heat stress-based, and an integrated-based scenario. The integrated approach, balancing trade-offs between ecological benefits and implementation costs, outperformed the BAU scenario by 8.84 %. Despite highlighting a weaker correlation with heat stress mitigation, this outcome indicates significant improvements in biomass density and landscape connectivity. Our findings underscore the necessity of an integrated planning approach to urban greening, as it can contribute toward attaining urban development goals. Additionally, by proposing an app-based model for policymakers, our outputs should enable the reconciliation of multiple environmental objectives in urban landscapes.

Insights into the linkages of forest structure dynamics with ecosystem services

Large-scale land cover changes leading to land degradation and deforestation in fragile ecosystems such as the Western Ghats have impaired ecosystem services, evident from the conversion of perennial water bodies to seasonal, which necessitates an understanding of forest structure dynamics with ecosystem services to evolve appropriate location-specific mitigation measures to arrest land degradation. The current study evaluates the extent and condition of forest ecosystems in Goa of the Central Western Ghats, a biodiversity hotspot. Land use dynamics is assessed through a supervised hierarchical classifier based on the Random Forest Machine Learning Algorithm, revealing that total forest cover declined by 3.75% during the post-1990s due to market forces associated with globalization. Likely land uses predicated through the CA-Markov-based Analytic Hierarchy Process (AHP) highlight a decline in evergreen forest cover of 10.98%. The carbon sequestration potential of forests in Goa assessed through the InVEST model highlights the storage of 56,131.16 Gg of carbon, which accounts for 373.47 billion INR (4.49 billion USD). The total ecosystem supply value (TESV) for forest ecosystems was computed by aggregating the provisioning, regulating, and cultural services, which accounts for 481.76 billion INR per year. TESV helps in accounting for the degradation cost of ecosystems towards the development of green GDP (Gross Domestic Product). Prioritization of Ecologically Sensitive Regions (ESR) considering bio-geo-climatic, ecological, and social characteristics at disaggregated levels reveals that 54.41% of the region is highly sensitive (ESR1 and ESR2). The outcome of the research offers invaluable insights for the formulation of strategic natural resource management approaches.

Habitat Suitability of Ziziphus spina-christi and Ziziphus nummularia in a Changing Climate in the Khalijo-Omanian Zone, Iran

Climate change, a global threat of utmost significance, has the potential to trigger shifts in biodiversity distribution and the emergence of novel ecological communities. While considerable research has focused on predicting the impacts of climate change on the range shift of species, a critical yet often overlooked aspect is the role of changing climate on plants in hot, arid, and poorly known ecosystems. We employed an ensemble species distribution modeling framework to investigate how climate change might affect the spatial range of two significant indicator species, Ziziphus spina-christi and Ziziphus nummularia, within the hot and arid Khalijo-Omanian ecosystem of Iran. We ran the models for the current species distribution using climatic variables and then projected the models for two future periods (2041-2070 and 2071-2100) under different climate scenarios. These findings suggest that both species respond differently to climate change under different climatic scenarios. Some regions may undergo range expansion, whereas others may experience range contraction due to shifting environmental conditions. Overall, both species are projected to shift their range towards higher latitudes as climatic conditions evolve. Conservation and management measures, including the identification of priority areas, are crucial for protecting these species. The conclusions of this study are valuable to biodiversity conservation authorities, local stakeholders, and individuals dedicated to preserving Ziziphus habitats.

Ensemble predictions of high trophic-level fish distribution and species association in response to climate change in the coastal waters of China

As climate change shifts marine ecosystems, understanding distribution changes of high trophic-level fish is critical for ecological and fisheries management. This study examined the distribution changes of five high trophic-level fish species in China's coastal waters from 1990 to 2023, using species distribution models (SDMs) combined in an ensemble modeling framework to predict future trends under RCP26 and RCP85 scenarios. The ensemble approach integrated multiple SDM algorithms to reduce uncertainty and improve predictive accuracy. The analysis incorporated ecological metrics like niche breadth, niche overlap, and species association indices to assess habitat suitability and interspecies interactions. The ensemble model performed well, particularly for monkfish (Lophius litulon) and whitespotted conger (Conger myriaster), both of which are demersal species. Key environmental factors influencing habitat distribution included bottom water temperature and depth. Under climate change scenarios, the spatial niche breadth of only the largehead hairtail (Trichiurus lepturus) was expected to increase, while the niche breadth of the other species was projected to decrease, especially under high emissions. Fish habitats were predicted to shrink under future climate scenarios, especially under high emissions, with significant losses projected by 2100, ranging from -47 % for the Slender lizardfish (Saurida elongata) to -24 % for the Monkfish, although habitat suitability was expected to improve in southern coastal areas and near the Korean Peninsula. This study emphasizes the profound effects of climate change on the distribution and ecological niches of high trophic-level fish, offering insights for future fisheries management and climate adaptation strategies.

Future precipitation projections and model evaluation in the Hengduan Mountains based on CMIP6

The Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset was utilized to predict future precipitation changes in the Hengduan Mountains of China. This study evaluated the performance of 26 climate models in simulating historical precipitation based on three metrics: Pearson Correlation Coefficient (PCC), Root Mean Square Error (RMSE), and a ±3.0 Standard Deviation (STD) threshold. The top five performing model ensembles were selected to project precipitation changes for 2031-2050 and 2051-2070 under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Results indicate significant wet biases, with simulated precipitation deviations ranging from 70.7 % to 140.6 % relative to the National Tibetan Plateau Data Center dataset and 68.7 %-135.4 % compared to the Global Precipitation Climatology Centre dataset. Despite these biases, CMIP6 models effectively capture the temporal and spatial patterns of annual precipitation during the reference period. Future projections show marked spatial variability, with slight precipitation increases in central and northern regions across all scenarios. Northern areas experience pronounced rises (10.0 %-12.9 %), peaking at 16.2 % in the WNH region under SSP5-8.5 by 2070. In contrast, southern regions display varied trends: strong increases under SSP1-2.6 (>5 %), minimal changes under SSP2-4.5 (<2 %), and moderate increases under SSP5-8.5 (<5 %). These findings emphasize the need for targeted mitigation and adaptation strategies to address environmental and socioeconomic challenges, offering valuable insights for regional climate policy formulation.

Big Data-Driven Evolution of a Diagnostic Multiplex IgE-Test: Enhancing Accuracy and Efficacy in Allergy Diagnostics

The ALEX2-test (MacroArray Diagnostics, Vienna, Austria) is a diagnostic multiplex IgE-test for the simultaneous detection of IgE to 178 allergens and 117 extracts, in addition to total IgE. Test results from more than 90 countries are stored on a GDPR-compliant cloud server for backup, customer support, and continuous postmarket surveillance. To improve the coverage of exposomes on a global scale and to further increase the sensitivity of the test, the allergen panel was updated from ALEX2 to ALEX3. By mid-2023, when ALEX3 was designed, almost 400,000 real-world ALEX2 test results were available. Analysing prevalences and average sIgE-levels of individual allergen preparations, coverage of extracts by components, and co-reactivity of members of the same allergen family provided a rationale for updating the array. In parallel, based on the scientific literature and clinical studies, new allergens were selected. On ALEX3, 218 allergens and 82 extracts will be represented, including 52 new allergens. Allergen preparations with low prevalence and clinical relevance, as well as redundant allergens and extracts, were discontinued. New allergens encompass, e.g., cyclophilins, alpha-gal, and additional markers from respiratory and food allergen sources. Using a large dataset of ALEX2 test results exemplifies the targeted, data-driven improvement of a diagnostic IgE-macroarray.

A multiple computational spatial analysis of genetic, morphological, and anatomical diversity in Pteris cretica L. (Pteridaceae) geographical populations

The brake fern Pteris cretica is an evergreen, perennial plant known for its medicinal properties, particularly in treating hepatitis and jaundice. Despite previous genetic studies, little is known about the landscape genetics of P. cretica and the influence of spatial factors on its genetic structure. This study aimed to examine the effects of spatial and environmental variables on genetic variability and morphological differentiation in P. cretica populations. We analyzed 130 plants from 13 populations in northern Iran using multivariate statistical methods. This is the first study of landscape genetics in P. cretica in Iran and other regions. The study focused on identifying geographical variables that affect population formation and examining climatic factors influencing the species'distribution. SCoT genetic loci related to geographical variables and key morphological traits were identified. The climatic factors affecting the current and future distribution of this species were also examined. Results revealed significant associations between genetic diversity, differentiation (Fst), and environmental variables like longitude, latitude, and altitude. Genetic loci with adaptive potential to climate were identified through RDA, CCA, and FAMD analyses. sPCA analysis indicated significant spatial structuring and genetic cline formation in the populations. PLS-SEM analysis showed complex interactions among genetic factors, climate, resistance, morphology, and anatomy. These findings highlight the role of spatial and environmental factors in shaping the genetic structure of P. cretica populations. The study provides valuable insights for developing conservation strategies to preserve genetic diversity and adapt to environmental changes, contributing to the species' long-term survival and sustainable use.

Assessing the impact of global warming on the distributions of Allium stipitatum and Kelussia odoratissima in the Central Zagros using a MaxEnt model

Global warming is an undeniable fact occurring in different parts of the world. Climate changes can have irreversible effects on plant communities, particularly on endemic and endangered species. Therefore, it is important to predict the impact of climate change on the distribution of these species to help protect them. This study utilized the MaxEnt model to forecast the impact of climate change on the distributions of two medicinal, edible, and aromatic species, Kelussia odoratissima and Allium stipitatum, in Chaharmahal and Bakhtiari province. The study used the CCSM4 general circulation model along with two climate scenarios, RCP2.6 and RCP8.5, for the 2050s and 2070s to predict the potential impact of climate change on the distribution of the species studied. The research findings indicated that the model performed effectively for prediction (AUC≥0.9). The primary environmental variables influencing species distribution were found to be isothermality (Bio3), soil organic carbon, and pH for A. stipitatum, and soil organic carbon, precipitation seasonality (Bio15), and precipitation of the wettest month (Bio13) for K. odoratissima. The findings suggest that the distribution of the studied species is expected to decline in the 2050s and 2070s due to climate change, under both the RCP2.6 and RCP8.5 climate scenarios. The research indicates that climate change is likely to have a significantly negative effect on the habitats of these species, leading to important ecological and socio-economic impacts. Therefore, our study emphasizes the urgent need for conservation efforts to prevent their extinction and protect their habitats.

A benchmark analysis of feature selection and machine learning methods for environmental metabarcoding datasets

Next-Generation Sequencing methods like DNA metabarcoding enable the generation of large community composition datasets and have grown instrumental in many branches of ecology in recent years. However, the sparsity, compositionality, and high dimensionality of metabarcoding datasets pose challenges in data analysis. In theory, feature selection methods improve the analyzability of eDNA metabarcoding datasets by identifying a subset of informative taxa that are relevant for a certain task and discarding those that are redundant or irrelevant. However, general guidelines on selecting a feature selection method for application to a given setting are lacking. Here, we report a comparison of feature selection methods in a supervised machine learning setup across 13 environmental metabarcoding datasets with differing characteristics. We evaluate workflows that consist of data preprocessing, feature selection and a machine learning model by their ability to capture the ecological relationship between the microbial community composition and environmental parameters. Our results demonstrate that, while the optimal feature selection approach depends on dataset characteristics, feature selection is more likely to impair model performance than to improve it for tree ensemble models like Random Forests. Furthermore, our results show that calculating relative counts impairs model performance, which suggests that novel methods to combat the compositionality of metabarcoding data are required.

Climate influences broadly, landscape influences narrowly: Implications for agricultural beneficial insects

Insects provide critical ecosystem services, like pollination, in both natural and agricultural ecosystems. Delivery of these services depends on their ability to develop, survive, and move through their environment. Whether they can do this depends on the weather, climate, and landscape; but a changing climate means these systems are potentially vulnerable to disruption. Short-term fluctuations in weather can disrupt development, impede movement, and affect survival, while long-term climate norms influence environmental niches and influence species distribution. Landscape composition also influences beneficial insect distribution and has the potential to reduce the impacts of climate change. Here we use a database of >97,000 bee occurrence records, collected from 320 sampling sites across a 90,000+ km2 area in the North American Prairies to generate models of species occurrence for 50 species, sampling in and around crop fields. We use a tree-based machine learning method with extreme gradient boosting to create predictive classification models. These models are then used to analyze the relative importance of weather, climate, and landscape variables. The variables with the highest mean absolute importance are cumulative degree days, cumulative precipitation, and percent tree cover. When we analyzed individual species models, bee taxonomic groups responded most strongly to weather, and the direction of response corresponded to trait-grouping. The responses to landscape were weak and species-specific. The results indicate that pollination service supply is largely determined by heat and moisture, and that cavity nesters and ground-nesters have opposite responses to rising temperature, which could impact taxonomic and functional diversity.

Evaluation of Ecosystem Service Capacity Using the Integrated Ecosystem Services Index at Optimal Scale in Central Yunnan, China

Understanding and quantifying the dynamic features of local ecosystem services (ESs) and integrating diverse ecosystem assessment results form crucial foundations for regional ES management. However, existing methods for integrating and objectively evaluating multiple ESs remain limited. Consequently, this research evaluates four key services based on the InVEST and RUSLE models in the Central Yunnan Province (CYP)-from 2000 to 2020: water yield (WY), carbon storage (CS), habitat quality (HQ), and soil conservation (SC). It then constructs an Integrated Ecosystem Service Index (IESI) using principal component analysis (PCA). Additionally, this study explores the factors driving the spatial divergence of ESs by employing the optimal parameter-based geographical detector model (OPGD) at the optimal spatial scale. The results indicated that (1) the IESI was effectively applied in the CYP and could quantitatively and comprehensively integrate the assessment results of the four key ESs. (2) During the study period, the ESs in the CYP showed increasing trends for WY, HQ, and SC, while CS showed a decreasing trend. (3) The IESI during the study period exhibited a trend of initially decreasing and then increasing. The average IESI values for CYP were 0.7338 in 2000, 0.6981 in 2005, 0.6947 in 2010, 0.6650 in 2015, and 0.6992 in 2020. (4) A 4500 m × 4500 m grid was identified as the optimal spatial scale for detecting the spatial divergence of comprehensive ecosystem service (CES) in CYP, and relief degree of land surface (RDLS), slope, and the NDVI were the top three drivers based on q-values. This study offers a more scientific and effective method for evaluating regional CES. It also provides a comprehensive analytical tool for balancing land use competition and assessing the effectiveness of policy implementation.

Weak monsoon signals detected in growth chronologies of lake fish on the Qinghai-Tibetan Plateau

Understanding the variation in fish growth responses to climate change across regions is essential for predicting fish population dynamics and relevant ecological consequences on a large scale. Despite the demonstrated sensitivity of fish growth responses to climate change on the Qinghai-Tibetan Plateau (QTP), the geographical variations in these responses remain unclear. This study analyzed the growth responses of schizothoracine fish to environmental variables in four geographically distinct QTP lakes (Qinghai Lake, Yamdrok Lake, Pangong Tso, and Co Nag) using otolith biochronologies and hierarchical mixed-effects modeling and quantified the relative contributions of intrinsic and extrinsic factors to fish growth variations. Overall, we found that the optimal model accounted for 82% of the annual growth variability. Age variables were the intrinsic factors primarily influencing fish growth (significant and negative, accounting for 92% of the explained variability), followed by the influence of extrinsic environmental factors at the local (i.e., air temperature and precipitation, significant and positive, 5%), global (i.e., sea surface temperature [SST], significant and negative, 2%), and regional (i.e., monsoon intensity, nonsignificant and negative, 0.4%) scales. At the lake level, the influences of environmental factors on fish growth aligned with overall results but showed varied contributions. Therefore, local factors primarily influence fish growth responses, emphasizing that geographical variations in fish responses to climate change should be accounted for in relevant population predictions. This study provides valuable insights into the complex interactions between fish growth and multi-scale environmental changes and offers scientific support for ecosystem management under climate change on the QTP.

Mitigating global climate change and its environmental impact is a key social responsibility of scientists and should be part of research ethics policies and guidelines

Scientists have both epistemic and social responsibilities. Doing good science and reproducible research work would be a scientist's epistemic responsibility, but what might constitute social responsibility is perhaps broader and more subjective. Here, I posit that mitigation of global climate change (CC) and its environmental impact would be a key contemporary social responsibility of scientists. In their research, diligence in reducing the contribution of their work to greenhouse gas emissions and CC would be morally normative. Furthermore, contributing to tackling CC and its detrimental effects would be befitting of scientists' technical expertise, and is thus an appropriate reciprocative return for the training and resources afforded to them by society (and the environment). Scientists being responsible for tackling CC and its effects can be adequately described by the terms of dimensions of responsibility alluded to by de Melo-Martin and Intemann. As such, there would be no convincing reasons to reject these as important notions that should be incorporated into research ethics guidelines and policies.

Negative effects of nitrogen fertilization on herbivore fitness are exaggerated at warmer temperatures and in high-altitude populations

Biodiversity is currently under strong pressure due to anthropogenic global change. Different drivers of global change may exert direct and indirect effects on biodiversity, and may furthermore interact with one another, but our respective knowledge is still very limited. We investigated indirect and interactive effects of two important drivers of global change, eutrophication and climate change, in replicated low- and high-altitude populations of an insect herbivore, the butterfly Lycaena tityrus, in a laboratory setting. We found local adaptation in developmental traits, with low-altitude populations being adapted to warmer temperatures and longer seasons. Lycaena tityrus responded negatively to agriculturally relevant levels of fertilization of its host plant, showing reduced body mass and prolonged development time. Negative effects were particularly pronounced at warmer temperatures and in high-altitude populations. Our study adds to the increasing knowledge that different drivers of global change may interact and thereby increase the overall level of threat to biodiversity. We suggest that populations inhabiting naturally nutrient-poor environments might be even more vulnerable to agricultural intensification than others, potentially applicable to many species. These findings may have important implications for protecting numerous vulnerable species in the face of rapid environmental change.

Adaptive Distribution and Priority Protection of Endangered Species Cycas balansae

As an endangered species, the habitat of Cycas balansae (C. balansae) is subject to a variety of impacts, including climate change and human activities, and exploring its adaptive distribution and conservation areas under such conditions is crucial to protecting the ecological security of endangered species. In this study, we used the MaxEnt model and Marxan v4.0.6 to systematically evaluate the adaptive distribution and priority protection areas of the endangered species C. balansae. The results showed that the endangered species C. balansae is concentrated in Xishuangbanna and its surrounding zones in the southern Yunnan Province. The main factors affecting the distribution of C. balansae were temperature seasonality, mean temperature of the coldest quarter, isothermality, and precipitation of the warmest quarter, among which temperature was the dominant factor. Under different climate scenarios in the future, the adaptive distribution area of C. balansae showed a slight decrease, and the adaptive distribution showed a northward migration trend. The future climate distribution pattern is closely related to temperature seasonality and the mean temperature of the coldest quarter. In addition, the influence of anthropogenic disturbances on the distribution of C. balansae cannot be ignored. Currently, there is a large range of conservation vacancies for C. balansae, and it is recommended that Simao City be used as a priority conservation area. This study provides new insights for determining the priority conservation areas and conservation strategies for the endangered species C. balansae.

Seasonal effects of extreme climate events and sea surface temperature indicators on the vulnerability of marine pelagic fisheries in the Bay of Bengal region

The study highlights the vulnerability of the eastern coast to tropical cyclones and the unique characteristics of the Bay of Bengal region. Seasonality, driven by global climatic events and geography, significantly affects the marine ecosystem. Furthermore, it underscores the effects of extreme climate events on marine pelagic fisheries and advocates for a state-based approach to raise awareness among government institutions and fishing communities. Findings reveal a significant negative relationship between Sea Surface Temperature (SST) and fish-catch (coefficient = -0.09, p < 0.01), indicating that rising SST adversely affects pelagic fish populations. Moreover, increased frequency of extreme events (-0.12 to -2.06, p < 0.05 to p < 0.01) and disturbances (-0.149 to -0.679, p < 0.05) exhibits detrimental impacts across various models. Notably, seasonal variations play a crucial role, with quarters 1, 3, and 4 demonstrating positive associations (0.186-0.604, p < 0.1 to p < 0.05) with fish-catch, signifying potentially favourable conditions during specific seasons. State-specific analysis highlights diverse impacts, wherein West Bengal experiences substantial negative effects from extreme events (-2.056, p < 0.01), emphasizing regional disparities. These findings underscore the need for regionalized mitigation strategies and sustainable fishing practices to ensure the future of the Bay of Bengal's marine ecosystem.

Environmental conditions influence host-parasite interactions and host fitness in a migratory passerine

The study of host-parasite co-evolution is a central topic in evolutionary ecology. However, research is still fragmented and the extent to which parasites influence host life history is debated. One reason for this incomplete picture is the frequent omission of environmental conditions in studies analyzing host-parasite dynamics, which may influence the exposure to or effects of parasitism. To contribute to elucidating the largely unresolved question of how environmental conditions are related to the prevalence and intensity of infestation and their impact on hosts, we took advantage of 25 years of monitoring of a breeding population of pied flycatchers, Ficedula hypoleuca, in a Mediterranean area of central Spain. We investigated the influence of temperature and precipitation during the nestling stage at a local scale on the intensity of blowfly (Protocalliphora azurea) parasitism during the nestling stage. In addition, we explored the mediating effect of extrinsic and intrinsic factors and blowfly parasitism on breeding success (production of fledglings) and offspring quality (nestling mass on day 13). The prevalence and intensity of blowfly parasitism were associated with different intrinsic (host breeding date, brood size) and extrinsic (breeding habitat, mean temperature) factors. Specifically, higher average temperatures during the nestling phase were associated with lower intensities of parasitism, which may be explained by changes in blowflies' activity or larval developmental success. In contrast, no relationship was found between the prevalence of parasitism and any of the environmental variables evaluated. Hosts that experienced high parasitism intensities in their broods produced more fledglings as temperature increased, suggesting that physiological responses to severe parasitism during nestling development might be enhanced in warmer conditions. The weight of fledglings was, however, unrelated to the interactive effect of parasitism intensity and environmental conditions. Overall, our results highlight the temperature dependence of parasite-host interactions and the importance of considering multiple fitness indicators and climate-mediated effects to understand their complex implications for avian fitness and population dynamics.

Bionanotechnology: A Paradigm for Advancing Environmental Sustainability

The urgent need for innovative solutions to global environmental challenges has driven the convergence of biology and nanotechnology, resulting in the emergence of bionanotechnology as a transformative force. This comprehensive review paper explores the fundamental principles, applications, benefits, and potential risks associated with harnessing bionanotechnology to advance environmental sustainability. Beginning with an elucidation of the fundamental concepts underlying bionanotechnology, this paper establishes the synergy between biological systems and nanomaterials. The unique properties of nanomaterials, coupled with the adaptability of biological processes, form the foundation for a diverse array of real-world applications. Focusing on applications, the paper highlights how bionanotechnology addresses critical environmental issues. It showcases case studies that exemplify its impact on water purification, air quality improvement, waste management, renewable energy production, and more. These case studies underscore the tangible benefits and efficacy of bionanotechnology in tackling complex challenges. However, as the potential of bionanotechnology is harnessed, it is crucial to navigate potential ecological risks. The paper emphasizes the importance of ecotoxicological considerations, discussing how nanomaterials interact with ecosystems and organisms. Ethical and responsible development of bionanotechnology, informed by these considerations, ensures that its benefits are maximized while minimizing potential harm. In conclusion, this review paper underscores bionanotechnology's potential to revolutionize environmental sustainability. By fusing the power of nanomaterials and biology, bionanotechnology offers a holistic approach to address pressing global challenges. While celebrating its transformative promise, the paper emphasizes the need for a balanced approach that safeguards environmental health. As society looks towards a more sustainable future, bionanotechnology stands as a pivotal paradigm for shaping an environmentally conscious world.

Stress-Induced Response and Adaptation Mechanisms in Bacillus licheniformis PSKA1 Exposed With Abiotic and Antibiotic Stresses

Soil ecosystems consist of diverse microbial communities with great potential for ecological and biotechnological applications. These communities encounter various abiotic stresses, which expedite the activation of transient overexpression of heat shock proteins (HSPs). In the present study, a soil bacterium was isolated and identified as Bacillus licheniformis strain PSK.A1, and its growth parameters were optimized before exposing it to heat, salt, pH, and antibiotic stress conditions. Comparative protein expression was analyzed using SDS-PAGE, protein stabilization via protein aggregation assays, and survival through single spot dilution and colony-counting methods under various stress conditions. The pre-treatment of short stress dosage showed endured overall tolerance of bacterium to lethal conditions, as evidenced by moderately enhanced total soluble intracellular protein content, better protein stabilization, comparatively over-expressed HSPs, and relatively enhanced cell survival. The findings highlighted that cells grown under optimal conditions were more susceptible to lethal environments than stressed cells, with their enhanced tolerance linked to the overexpression of 20 distinct HSPs of 17-91 kD. These insights offer the potential for developing strategies to enhance microbial resilience for various applications including bacterial bioprocessing, bio-remediation, and infectious disease management.

MaxEnt Modeling and Effects of Climate Change on Shifts in Habitat Suitability for Sorbus alnifolia in China

Anthropogenic climate change stands out as one of the primary forces expected to reshape Earth's ecosystems and global biodiversity in the coming decades. Sorbus alnifolia, which occurs in deciduous forests, is valued for its ornamental appeal and practical uses but is reported to be declining in the wild. Nevertheless, the distribution of this species' suitable range, along with the key ecological and environmental drivers that shape its habitat suitability, remains largely unknown. By analyzing 198 occurrence records and 54 environmental factors, we employed MaxEnt to project S. alnifolia's current and future habitat suitability. Our results showed that annual precipitation (37.4%), normalized difference vegetation index (30.0%), August water vapor pressure (20.8%), and temperature annual range (3.4%) were the most significant variables explaining S. alnifolia's environmental requirements. The suitable habitats were primarily scattered across eastern and central China. Under projected future climatic conditions, the total expanse of potential habitat is expected to increase. However, most of this expansion involves low-suitability habitats, whereas moderately and highly suitable habitats are likely to shrink, especially in southern and lower-altitude regions of China. Based on these findings, we propose several conservation strategies to support the long-term sustainability of S. alnifolia.

Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl

Introduction

Climate change poses significant challenges to the distribution of endemics in the Mediterranean region. Assessing the impact of climate change on the distribution patterns of Mediterranean endemics is of critical importance for understanding the dynamics of these terrestrial ecosystems under the uncertainty of future changes. The population size of the Cynara cornigera has declined significantly over the previous century across its geographical region. This decline is linked to how ongoing climate change is affecting natural resources like water and the capacity of foraging sites. In fact, it is distributed in 3 fragmented locations in Egypt (Wadi Hashem (5 individuals), Wadi Um Rakham (20 individuals), Burg El-Arab (4 individuals)).

Methods

In this study, we examined C. cornigera's response to predicted climate change over the next few decades (2020-2040 and 2061-2080) using species distribution models (SDMs). Our analysis involved inclusion of bioclimatic variables, in the SDM modeling process that incorporated five algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), Support Vector Machines (SVM), and Generalized Additive Model (GAM).

Results and discussion

The ensemble model obtained high accuracy and performance model outcomes with a mean AUC of 0.95 and TSS of 0.85 for the overall model. Notably, RF and GLM algorithms outperformed the other algorithms, underscoring their efficacy in predicting the distribution of endemics in the Mediterranean region. Analysis of the relative importance of bioclimatic variables revealed Precipitation of wettest month (Bio13) (88.3%), Precipitation of warmest quarter (Bio18) (30%), and Precipitation of driest month (Bio14) (22%) as the primary drivers shaping the potential distribution of C. cornigera. The findings revealed spatial variations in habitat suitability, with the highest potential distribution observed in Egypt, (especially the Arishian sub sector), Palestine, Morocco, Northern Cyprus, and different islands in the Sea of Crete. Furthermore, our models predicted that the distribution range of C. cornigera would drop by more than 25% during the next few decades. Surprisingly, the future potential distribution area of C. cornigera (SSP 126 scenario) for 2061 and 2080 showed that there is increase in the suitable habitats area. It showed high habitat suitability along the Mediterranean coastal strip of Spain, Sardinia, Morocco, Algeria, Tunisia, Libya, Egypt, (especially the Arishian sub sector), Palestine, Lebanon, Northern Cyprus, and different Aegean islands.

Atmospheric nitrogen oxides (NOx), hydrogen sulphide (H2S) and carbon monoxide (CO): Boon or Bane for plant metabolism and development?

Urban air pollution has been a global challenge world-wide. While urban vegetation or forest modelling can be useful in reducing the toxicities of the atmospheric gases by their absorption, the surge in gaseous pollutants negatively affects plant growth, thereby altering photosynthetic efficiency and harvest index. The present review analyses our current understanding of the toxic and beneficial effects of atmospheric nitrogen oxides (NOx), hydrogen sulphide (H2S) and carbon monoxide (CO) on plant growth and metabolism. The atmospheric levels of these gases vary considerably due to urbanization, automobile emission, volcanic eruptions, agricultural practices and other anthropological activities. These gaseous pollutants prevalent in the atmosphere are known for their dual action (toxic or beneficiary) on plant growth, development and metabolism. NO seems to exert a specialized impact by upregulating nitrogen metabolism and reducing tropospheric ozone. High H2S emission in specific areas of geothermal plants, fumarolic soils and wetlands can be a limitation to air quality control. Certain shortcomings associated with the designing of field experiments, sensitivity of detection methods and simulation development are yet to be overcome to analyze the precise levels of NO, H2S and CO in the rhizosphere of diverse agro-climatic regions. Several laboratory-based investigations have been undertaken to assess the roles of atmospheric gases, namely NOx, CO, H2S, and particulate matter (PM). However, in order to enable natural and sustainable mitigation, it is essential to increase the number of field experiments in order to identify the pollutant-tolerant plants and study their interactive impact on plant growth and agriculture.

Climate change effects on ecosystem services: Disentangling drivers of mixed responses

Climate change is a pervasive hazard that impacts the supply and demand of ecosystem goods and services (EGS) that maintain human well-being. A recent review found that the impacts of climate change on EGS are sometimes mixed, posing challenges for managers who need to adapt to these changes. We expand on earlier work by exploring drivers of varying responses of EGS to climate within studies. We conducted a systematic review of English-language papers directly assessing climate change impacts on the supply, demand, or monetary value of 'provisioning EGS', 'regulating EGS', or 'cultural EGS'. Ultimately, 44 papers published from December 2014 to March 2018 were analyzed. Nearly 66% of EGS were assessed for higher-income countries despite how lower-income countries disproportionately face negative climate impacts. Around 59% of observations or projections were mixed responses of EGS to climate change. Differences in climate impacts to EGS across space or climate scenarios were the most common causes of mixed responses, followed by mixed responses across time periods assessed. Disaggregating findings by drivers is valuable because mixed responses were often due to multiple drivers of variation. Carefully considering the decision context and desired outcome of a study will help select appropriate methodology to detect EGS variation. Although studies have often assessed relevant drivers of variation, assessing interactions of other sources of uncertainty and both climate and non-climate drivers may support more effective management decisions that holistically account for different values in the face of uncertainty.

Effects of Climate Change on Health and Health Systems: A Systematic Review of Preparedness, Resilience, and Challenges

Climate change has a significant impact on the population's health and negatively affects the functioning of healthcare systems. Health systems must be operationally prepared to handle the challenges posed by environmental change. Resilience is required to adapt quickly to critical environmental conditions and reduce carbon emissions. In this systematic review strategies, for health system preparedness and resilience are examined to address the impacts of climate change, and the barriers and challenges faced when implementing them. To identify studies, the Scopus, PubMed and Google Scholar databases were searched three times (from April to October 2024, 21 April, 15 June, and 9 September) for the years 2018 to 2024, using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. Specifically, the search identified 471 articles, of which the specified inclusion and exclusion criteria (secondary studies with inclusion criteria, being in English, etc.) were met by sixteen (16) studies. According to the findings of the studies reviewed, adaptation strategies focus on structural changes, the development of training programs, the development of surveillance systems, and appropriate operational plans. The leader's ability to motivate employees to achieve defined goals, continuous evaluation of goals and interventions, and learning from previous disasters play an important role in their implementation. Similarly, key policies and strategies for mitigation include the adoption of sustainable practices, such as recycling and cultural change. However, lack of resources (human, material, financial) and increased demand for health services make it difficult to implement adaptation and mitigation strategies. The findings of the review are mainly theoretical in nature and are confirmed by other studies. It is suggested that further research on resilience and preparedness of health systems should be pursued, leading to their sustainability and the formulation of appropriate policies.

A novel GIS-based modified multivariate drought index for modeling and management of the hydrogeological drought (Case study: Hashtgerd Aquifer, Iran)

The importance of a comprehensive drought evaluation due to the influence of various parameters has led to an expansion of the use of multivariate indicators in drought assessment. On the other hand, the lack of a specific index for the hydrogeological conditions of the aquifer has led to the presentation of a novel index based on these characteristics within the Geographic Information Systems (GIS) environment in this study. Accordingly, the Modified Standardized Electrical Conductivity Index (MSECI), which is based on the Electrical Conductivity (EC) data of groundwater in quality wells, was used as an indicator of the qualitative status of the aquifer. In addition, the Groundwater Resource Index (GRI), Standardized Well Discharge Index (SWDI), and Standardized Transmissivity Index (STI), which are based on the fluctuations of groundwater level in piezometric wells, the flow rate of pumping wells, and the transmissivity of the aquifer, respectively, were used as indicators of the quantitative condition of the aquifer to construct the novel hydrogeological drought index called Modified Hydrogeological Drought Management Index (MHDMI). Results showed that, when taking into account the impacts of drought, 78% of the study area is in the "Moderate" class, 4.53% in the "Very" class, 0.07% in the "Extreme" class, 17% in the "Low" class, and 0.05% in the "No effect" class, according to the descriptive maps of the MHDMI. Concerning management, the assessed area is divided into four classes: "Exploitation with limited constraints" (53.4%), "Limited exploitation" (24.8%), "Exploitation without limitation" (17%), and "No exploitation" (4.6%). The findings of the descriptive maps of MHDMI indicate that management scenarios must be applied to the most vulnerable area, the southwest boundary of the Hashtgerd Aquifer. According to the results, the method developed in this research can identify and manage areas sensitive to hydrogeological drought stress.

Optimizing nature-based solutions for urban flood risk mitigation: A multi-objective genetic algorithm approach in Gdańsk, Poland

Nature-based Solutions (NbS) have emerged as a sustainable approach to managing flood risks by enhancing natural water retention and reducing surface runoff in urban areas. As climate change and rapid urbanization exacerbate flood hazards, optimizing the spatial deployment of NbS is crucial for improving urban resilience and mitigating flood impacts. This study presents a comprehensive optimization framework for the spatial allocation of fourteen different NbS types aimed at mitigating urban flood risks in Gdańsk, Poland. Leveraging a genetic algorithm alongside the Urban Flood Risk Mitigation (UFRM) model of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) software suite, we identified areas of the city most vulnerable to pluvial flooding and optimized NbS placement to maximize water retention and reduce runoff. The optimization process balanced multiple objectives, including minimizing implementation costs and maximizing water retention capacity, ensuring that the solutions are both economically feasible and environmentally effective. Three distinct scenarios were proposed: a cost-effective solution, a high-retention solution, and a balanced solution, offering urban planners a range of strategies to address flood risks based on their specific priorities and constraints. Results demonstrated considerable variations in water retention effectiveness across different NbS configurations, with denser urban regions showing the most significant improvements from targeted interventions. The optimized placement of NbS resulted in estimated total water retention improvement of approximately 15.5 % for the best solution considered. These findings provide valuable insights for integrating NbS into urban flood management strategies, enhancing citywide resilience, sustainability, and long-term flood mitigation.

Haplotype breeding: fast-track the crop improvements

MAIN CONCLUSION

Haplotype-based breeding unleashed the genetic variations of unexplored germplasms and integration with recent genomics tools accelerated the genetic gain and address the present challenges of food security by climate change. Climate change is linked to unforeseen abiotic stresses and changes in the patterns of pests and diseases. Hence, it is necessary to use novel methods to detect genetic variations to mitigate the adverse effects on crops by climate change. Genomic-assisted breeding methods are strategies that improve the efficiency of breeding cereal crops in a dynamic environment. These methods detect differences in the structure of single nucleotide polymorphisms (SNPs) throughout the population. The decrease in sequencing costs has enabled the thorough sequencing of crop genomes, resulting in the discovery of millions of SNPs. By using statistical tests, it is possible to integrate these SNPs into a limited number of haplotype blocks. This allows for a more comprehensive analysis of how variation is distributed and segregated within a population. Therefore, the use of haplotype-based breeding shows great potential as a tool for creating tailored crop varieties. The process entails the identification of superior haplotypes and their use in breeding operations. The haplotype-based breeding (HBB) technique utilizes genome sequence data to identify specific allelic variations that accelerate the breeding cycle and overcome linkage drag difficulties. This study aims to present the idea of HBB, examine the connection between haplotype breeding and conventional breeding, and analyze the benefits and current advancements of HBB, with a specific focus on cereal crops.

Perceptions of cultural and provisioning ecosystem services and human wellbeing indicators amongst indigenous communities neighbouring the greater limpopo transfrontier conservation area

Nature plays a crucial role in providing ecosystem services (ESs) essential for human wellbeing and biodiversity conservation in rural areas. However, existing paradigms often lack an integrative approach towards rural livelihoods and wellbeing, highlighting the need for a comprehensive understanding of the relationship between human wellbeing (HWB) and ESs. The area around the Greater Limpopo Transfrontier Conservation Area (GLTFCA) offers such ESs to indigenous people who rely heavily on these natural resources. Thus, this study aimed to quantify indigenous people's perceptions of cultural and provisioning ESs and their link to human wellbeing in villages adjacent to the GLTFCA. Key informant interviews were initially conducted to identify ESs as perceived by the participants. Subsequently, face-to-face surveys were carried out in 9 wards across South Africa and Zimbabwe, involving 350 participants. Respondents were asked about the availability of ESs, their levels of degradation, drivers of change, and the impact on their wellbeing. Responses were captured using Likert scales, and multiple regression models analysed the relationships between socio-demographic characteristics and ESs. Results indicated that indigenous people perceived both cultural and provisioning ESs to be available but degrading, with provisioning services degrading more rapidly. Climate change, legislation/policies, and poverty were identified as key drivers of this change. Socio-demographic factors such as gender, nativeness, and employment level influenced perceptions of both ESs. Overall, participants reported that both ESs contribute to their human wellbeing and livelihoods through life satisfaction, happiness, living standards, safety, security, and good health. Finally, this study's findings uniquely offer a baseline for these ESs accounting, demonstrating their direct and indirect benefits to indigenous communities' livelihoods and well-being.

Distribution of Vegetation and Soil Seed Banks Across Habitat Types in Paddy Fields Under Different Farming Practices

Paddy field ecosystems are crucial for crop production, biodiversity conservation, and ecosystem services. Although previous studies have examined paddy field biodiversity, few have addressed how the distribution and species richness of vegetation and soil seed banks are regulated. This study investigated the distribution of wetland plants and soil seed banks in paddy fields across diverse habitat types and identified factors influencing their patterns. Surveys revealed that conventional paddy field habitats contained only a few herbicide-tolerant species (e.g., Portulaca oleracea L., Cardamine flexuosa With., and Rorippa palustris (L.) Besser). In contrast, organic paddy field habitats exhibited higher species richness and abundance. Cluster analysis and nonmetric multidimensional scaling demonstrated that soil seed bank distribution differed markedly in paddy field habitats with different farming practices and was influenced by distinct soil factors. These findings highlight the importance of understanding vegetation and soil seed bank dynamics in paddy field ecosystems to support biodiversity conservation and sustainable agriculture.

The Role of Artificial Lakes Located in Forests in the Context of Small Retention, Biodiversity and Climatic Changes-Evidence From Southern Poland

Drought has an effect on hydrologic conditions and water quality under climate change. Small water retention in forests is one of the priority investment programs implemented in recent years, supported by the European Union. This study aimed to assess the ecological conditions of forest lakes using macrophytes and benthos organisms diversity as an ecological indicator of ecosystem conditions under climatic changes. The study was carried out in forest artificial lakes serving as surface water retention in the context of biodiversity in climatic changes and its role in the retention of water. Despite systematic maintenance activities, a long period of lake existence significantly determines the natural biological processes occurring in lakes and riparian habitats. The analysis showed low values of salinity indicators and the concentration of nitrogen and phosphorus. The pH ranged from 6.2 to 7.6; showing slightly acidic conditions or within the limits of neutral. The model of plant associations showed the occurrence of 24 species of plants within nine plant assemblages in the Phragmitetea and Potametea classes of associations (Biocenotic index 1.007-1.692). Despite human activities, lake condition, as assessed by the ESMI index or the biocenotic diversity indices, is good (0.416-0.648). Climate change, expressed by an increase in the frequency of dry years, creates a situation of changes in filling lakes with water, which, taking into account their small depth, results in dynamically changing conditions for the development of phytolittoral. Along with the phytolittoral changes, benthos communities change, their density and the number of taxa also fluctuate. It should be assumed that with ongoing climate change, these phenomena will probably intensify, which will lead to changes in entire ecosystems at plant and animal levels.

Predicting the Potential Distribution of Cheirotonus jansoni (Coleoptera: Scarabaeidae) Under Climate Change

Cheirotonus jansoni (Jordan, 1898), a beetle species of ecological and ornamental significance, is predominantly found in southern China. With limited dispersal ability, it is classified as a Class 2 protected species in China. In this study, the widely employed maximum entropy (MaxEnt) model and the ensemble Biomod2 model were applied to simulate C. jansoni habitat suitability in China under current environmental conditions based on available distribution data and multiple environmental variables. The optimized MaxEnt model demonstrated improved accuracy and robust predictive capabilities, making it the preferred choice for simulating dynamic changes in potentially suitable habitats for C. jansoni under future climate scenarios. Protection gaps were further identified through analyses of the overlap between nature reserves and highly suitable areas for C. jansoni. The established models indicated that this species primarily resides in southeastern mountainous regions of China below 2000 m, with a preferred altitude of 1000-2000 m. Future climate scenarios suggest a reduction in the overall suitable habitat for C. jansoni with an increase in temperature, underscoring the urgent need for enhanced conservation efforts for this beetle species.

Investigating the biodiversity conservation capability of technological innovation and FinTech

Human activities, primarily economic growth, and technological innovation, threaten global biodiversity. This study utilizes 22-year panel data from 87 developing countries and a novel cross-sectional heterogeneous factor analysis-based financial technology index to investigate how economic growth, renewable energy consumption, technological innovation, natural resources, and financial technology affect biodiversity. To account for cross-sectional dependency, this study employed a Panel Autoregressive Distributive Lagged with Pooled Mean Group specifications within the Driscoll and Kraay standard error estimator. The findings revealed that the log of Gross Domestic Product (GDP) had an inverted U-shaped effect. Moreover, economic growth, renewable energy, and FinTech can improve biodiversity conservation. Traditionally, technological innovation and unregulated resource exploitation have posed threats to biodiversity. This study focused on responsible economic development and practical solutions to biodiversity threats posed by technological innovation and unrestrained resource use. FinTech can promote sustainable behaviors and divert funds from ecosystem-harming projects to biodiversity-friendly ones. Innovative financial instruments enable stakeholders to balance nature. This study demonstrates that FinTech, renewable energy, and responsible economic growth can help reverse biodiversity loss. We provide the policy implications of our research.

The relative importance of nitrogen deposition and climate change in driving plant diversity decline in roadside grasslands

Nitrogen deposition and climate change have been identified as major threats to the biodiversity of semi-natural grasslands. Their relative contribution to recent biodiversity loss is however not fully understood, and may depend on local site conditions such as soil type, which hampers efforts to prevent further decline. We used data from >900 permanent plots in semi-natural grasslands in Dutch roadsides to investigate whether trends in plant diversity and community composition (2004-2020) could be explained by: (1) nitrogen deposition (NHx and NOy) and climate change (winter degree days and summer drought), (2) the interactive effect of nitrogen deposition and climate change, and (3) the interactive effect of nitrogen deposition and climate change with soil type. Overall we observed a decline in plant diversity and an increased dominance of tall species and grasses. These changes were linked to winter warming, but not to changes in summer drought and nitrogen deposition. The effect of winter warming was more pronounced in areas with higher NOy deposition, but was consistent across different soil types. Our results suggest that winter warming will become an important driver of plant diversity loss by altering competitive interactions, which could have major repercussions for other trophic levels and ecosystem services. Future conservation and restoration of grassland biodiversity therefore requires management regimes that are adapted to winter warming.

Responses of fisheries ecosystems to marine heatwaves and other extreme events

Marine ecosystems and their living marine resources (LMRs) continue to respond to the effects of global change, with environmental factors impacting marine fisheries biomass, distribution, harvest, and associated economic performance. Extreme events such as high-category hurricanes, harmful algal blooms, marine heatwaves, and large-scale hypoxia affect major regions and subregions of United States waters, with their frequency expected to increase over the next decades. The impacts of extreme events on fisheries biomass, harvest, and economic performance have not been examined as closely as a system (i.e., cumulatively), or in terms of their differential effects on particular functional groups of a given system. Among several U.S. subregions, we examined responses of fisheries biomass, landings, and revenue for particular functional groups to large-scale environmental perturbations (i.e., marine heatwaves, Hurricane Katrina, Deepwater Horizon oil spill). Distinct negative short-term consequences to annual fisheries biomass, landings, and revenue were observed in all regions, including at the system-level scale for several ecosystems which have higher proportions of pelagic species composition and variable shellfish-based revenue. In addition, shifts in species composition often were associated with environmental perturbations. Recovery to pre-perturbation levels (both in the immediate years following the event and over the post-event period of study) and resilience at the system level was observed in several cases, although post-event declines in biomass and landings occurred in the California ecosystem. Certain extreme events are expected to become more common in marine environments, with resulting perturbations throughout multiple components of U.S. socioecological systems. The recognition and understanding of the consequences of extreme events throughout marine ecosystems is necessary for effective, holistic, and sustainable management practices.

New York State Climate Impacts Assessment Chapter 03: Agriculture

Agriculture is a vital industry in New York State, which ranks among the top-producing states for dairy, fruits, and several other commodities. As agriculture depends on the weather and specific climatic conditions, this sector faces extraordinary challenges as New York's climate changes. This chapter explores the many impacts of a changing climate on agriculture, the ways these impacts interact with other challenges that New York farmers and farmworkers face, and opportunities for the agriculture industry to adapt and build resilience.

New York State Climate Impacts Assessment Chapter 05: Ecosystems

The people of New York have long benefited from the state's diversity of ecosystems, which range from coastal shorelines and wetlands to extensive forests and mountaintop alpine habitat, and from lakes and rivers to greenspaces in heavily populated urban areas. These ecosystems provide key services such as food, water, forest products, flood prevention, carbon storage, climate moderation, recreational opportunities, and other cultural services. This chapter examines how changes in climatic conditions across the state are affecting different types of ecosystems and the services they provide, and considers likely future impacts of projected climate change. The chapter emphasizes how climate change is increasing the vulnerability of ecosystems to existing stressors, such as habitat fragmentation and invasive species, and highlights opportunities for New Yorkers to adapt and build resilience.

Occurrence and potential diffusion of pine wilt disease mediated by insect vectors in China under climate change

BACKGROUND

Pine wilt disease (PWD), a major international quarantined forest pest, causes serious ecological and economic damage to Pinus species in Asia and Europe. In China, PWD has spread northeasterly and northwesterly beyond its original northern limits. Consequently, an evaluation of the insect vector-mediated occurrence and potential diffusion of PWD is needed to identify important transmission routes and control the spread of disease.

RESULTS

An optimized MaxEnt model was used to assess the current and future geographical distribution of Bursaphelenchus xylophilus and its insect vectors in China. The predicted suitable area for B. xylophilus colonization is currently 212.32 × 104 km2 and mainly concentrated in Central, East, Southwest and South China, although is anticipated to include the northwestern regions of China in the future. As for the insect vectors, Monochamus alternatus and M. saltuarius are expected to spread toward the northwest and southwest, respectively. The maximum predicted dispersion area of PWD mediated by M. alternatus, M. saltuarius and both species was 91.85 × 104, 218.76 × 104 and 29.99 × 104 km2, respectively, with potential diffusion areas being anticipated to increase in the future. Both the suitable probabilities and areas of B. xylophilus and its insect vectors were found to vary substantially along the latitudinal gradient, with the latitudinal range of these species being predicted to expand in the future.

CONCLUSION

This is the first study to investigate the potential diffusion areas of PWD mediated by insect vectors in China, and our finding will provide a vital theoretical reference and empirical basis for developing more effective management strategies for the control of PWD in China. © 2024 Society of Chemical Industry.

Effect of pH on Development of the Zebrafish Inner Ear and Lateral Line: Comparisons between High School and University Settings

Increasing carbon dioxide levels associated with climate change will likely have a devastating effect on aquatic ecosystems. Aquatic environments sequester carbon dioxide, resulting in acidic conditions that can negatively affect fish development. Increasing climate change impacts in the coming decades will have an outsized effect on younger generations. Therefore, our research had two interconnected goals: 1) understand how aquatic acidification affects the development of zebrafish, and 2) support a high school scientist's ability to address environmental questions of increasing importance to her generation. Working with teachers and other mentors, the first author designed and conducted the research, first in her high school, then in a university research laboratory. Zebrafish embryos were reared in varying pH conditions (6.7-8.2) for up to 7 days. We assessed fish length and development of the inner ear, including the otoliths; structures that depend on calcium carbonate for proper development. Although pH did not affect fish length, fish reared in pH 7.75 had smaller anterior otoliths, showing that pH can impact zebrafish ear development. Furthermore, we demonstrate how zebrafish may be used for high school students to pursue open-ended questions using different levels of available resources.

Machining performance, economic and environmental analyses and multi-criteria optimization of electric discharge machining for SS310 alloy

With the expansion of the manufacturing sector, it has become crucial to incorporate sustainable production methods in order to remain competitive in the market. This study focuses on addressing the needs of the manufacturing industry by conducting a sustainability analysis of electric discharge machining for SS310 alloy. The analysis explores the impact of various electrode materials, for instance, copper and brass, as well as different machining variables, including discharge current (I = 4-12 A), spark gap (SG = 6-12 mu), pulse duration (Pon = 15-45 μs), and duty cycle (DC = 75-85%) using Taguchi method. The objective is to optimize the machining performance measures, which includes material removal rate (MRR), surface roughness (Ra), electrode wear (EW), and energy consumption (EC). In addition, the economic analysis of the machining process takes into account factors such as energy cost, dielectric consumption cost, EW cost, labor cost, and machine depreciation cost for both types of electrodes. Furthermore, the study investigates the carbon emissions resulting from EC, dielectric consumption, and EW to assess the environmental impact of the machining process. Multi-criteria decision-making approach is employed to assess the sustainability of the machining process by taking into account several performance, cost and environmental factors simultaneously. From empirical analysis, it has been observed that the copper electrode outperformed the brass electrode in terms of MRR (2.67 mm3/min), Ra (3.36 µm), EW (0.272 g), and EC (145.08 kJ) due to its superior electrical and thermal characteristics. In the cost analysis, copper offered lower costs for EC (2.02 PKR) attributed to its higher electrical conductivity while higher costs in terms of EW (5.5 PKR) and dielectric consumption (5.2 PKR) than brass. However, the analysis of labor and machine depreciation costs revealed that the application of copper electrode results in lower costs (80.1 and 99.3 PKR, respectively) than the brass electrode primarily due to its shorter machining time. The analysis of the environmental impact showed that the utilization of a copper electrode leads to reduced carbon emissions of 9.8 g CO2 due to its lower EC during the machining process. However, the copper electrode results in higher emissions from EW (5.07 g CO2) and dielectric consumption (54.58 g CO2) compared to the brass electrode. Based on the multi-criteria decision-making using the composite desirability function approach, it is evident that the copper electrode exhibits superior performance in terms of MRR, Ra, and total machining cost. Conversely, the brass electrode demonstrates better performance in terms of overall carbon emissions.

Evaluating the influence of human disturbance on the ecosystem service scarcity value: an insightful exploration in Guangxi region

Investigating how human disturbance affects the ecosystem service scarcity value (ESSV) is crucial for maintaining ecosystem stability and achieving sustainable development goals (SDGs). This study separately assessed ESSV and human disturbance in Guangxi from 1990 to 2020, revealing their spatiotemporal distribution differences over time. The environmental Kuznets curve (EKC) is used to analyze the interrelationship between the two, with the purpose of filling the gap in current research. The main results are as follows: (1) From 1990 to 2020, ESSV in Guangxi increased significantly and reached its highest value in 2020. Under the four scenarios, ESSV increased significantly in Scenarios 2 and 4. Spatially, high ESSV was mainly distributed in some cities in central, southern, western and northeastern Guangxi. (2) The index of human disturbance in Guangxi continued to increase during the study period, with a high level of human disturbance in the central urban area and a low level of human disturbance in the peripheral areas, which were distributed in a radial pattern. (3) According to the EKC, the relationship between ESSV and human disturbance in Guangxi followed an inverted N-shaped curve. In addition, after 2010, the coupling and coordination level was dominated by "slightly balanced development", and the area of "ESSV significantly lagged" gradually increased. This study provides a new perspective for understanding ESSV and its relationship with human disturbances, and provides an important reference for the sustainable management of ecosystems and the formulation of ecological conservation policies.

Where did they come from, where did they go? Niche conservatism in woody and herbaceous plants and implications for plant-based paleoclimatic reconstructions

PREMISE

The ecological conditions that constrain plants to an environmental niche are assumed to be constant through time. While the fossil record has been used previously to test for niche conservatism of woody flowering plants, additional studies are needed in other plant groups especially since they can provide insight with paleoclimatic reconstructions, high biodiversity in modern terrestrial ecosystems, and significant contributions to agriculture.

METHODS

We tested climatic niche conservatism across time by characterizing the climatic niches of living herbaceous ginger plants (Zingiberaceae) and woody dawn redwood (Metasequoia) against paleoniches reconstructed based on fossil distribution data and paleoclimatic models.

RESULTS

Despite few fossil Zingiberaceae occurrences in the latitudinal tropics, unlike living Zingiberaceae, extinct Zingiberaceae likely experienced paratropical conditions in the higher latitudes, especially in the Cretaceous and Paleogene. The living and fossil distributions of Metasequoia largely remain in the upper latitudes of the northern hemisphere. The Zingiberaceae shifted from an initial subtropical climatic paleoniche in the Cretaceous, toward a temperate regime in the late Cenozoic; Metasequoia occupied a more consistent climatic niche over the same time intervals.

CONCLUSIONS

Because of the inconsistent climatic niches of Zingiberaceae over geologic time, we are less confident of using them for taxonomic-based paleoclimatic reconstruction methods like nearest living relative, which assume a consistent climatic niche between extant and extinct relatives; we argue that the consistent climatic niche of Metasequoia is more appropriate for these reconstructions. Niche conservatism cannot be assumed between extant and extinct plants and should be tested further in groups used for paleoclimatic reconstructions.

Great Gerbils (Rhombomys opimus) in Central Asia Are Spreading to Higher Latitudes and Altitudes

The great gerbil (Rhombomys opimus) is a gregarious rodent in Central Asia and is one of the major pests found in desert forest and grassland areas. The distribution changes and migration routes of R. opimus in Central Asia under climate change remain unexplored. This study employed multi-model ensemble, correlation analysis, jackknife method, and minimum cumulative resistance (MCR) model to simulate the potential habitat of R. opimus under current and future (2030 and 2050) climate scenarios and estimate its possible migration routes. The results indicate that the ensemble model integrating Random Forest (RF), Gradient Boosting Machine (GBM), and Maximum Entropy Model (MaxEnt) performed best within the present climate context. The model predicted the potential distribution of R. opimus in Central Asia with an area under the curve (AUC) of 0.986 and a True Skill Statistic (TSS) of 0.899, demonstrating excellent statistical accuracy and spatial performance. Under future climate scenarios, northern Xinjiang and southeastern Kazakhstan will remain the core areas of R. opimus distribution. However, the optimal habitat region will expand relative to the current one. This expansion will increase with the rising CO2 emission levels and over time, potentially enlarging the suitable area by up to 39.49 × 104 km2. In terms of spatial distribution, the suitable habitat for R. opimus is shifting toward higher latitudes and elevations. For specific migration routes, R. opimus tends to favor paths through farmland and grassland. This study can provide guidance for managing and controlling R. opimus under future climate change scenarios.

A wide range of abiotic habitat factors and genetic diversity facilitate expansion of Trapa natans within its native range

Climate change and intense human activity are exacerbating changes in species' ranges. While the rapid spread of invasive alien species is well documented worldwide, the phenomenon of the spread of native species is poorly understood. To explain the problem of rapidly spreading species in the changing world, it is necessary to understand their ecology, genetic diversity and habitat limitation. The aim of our study was to analyze the ecological requirements and genetic diversity in the population of the macrophyte Trapa natans s. l., an invasive alien species in North America but native in Europe and Asia. We investigated the populations in its native range (Central and Northeastern Europe), where the species is defined as rare or extinct. We found the occurrence of T. natans in Northeastern Europe aquatic habitats where, up to now, it was described as an extinct species. The results of our environmental studies showed that the species has a wide range of tolerance to habitat conditions and lives in medium to highly nutrient-rich water with low and high salinity. Using Amplified Fragment Length Polymorphism (AFLP) analysis, we revealed high genetic variability within populations with relatively limited differentiation between populations. We showed that some populations are highly diverse (possibly refugia; Central Europe) and others are homogeneous (new sites, commercial reintroduction; Northeastern Europe). Conservation status of T. natans in its native range should be reconsidered, as the species has spread rapidly in recent decades and could be detrimental to aquatic habitats. The conclusion is that expansion/invasion can start from small populations, but under favorable conditions these populations spread rapidly. The introduction of species (even native) should be done carefully, if at all, as uncontrolled introduction to new locations, e.g. private ponds, could be the start of dispersal (native habitats) or invasion (non-native area).

Vegetation Succession for 12 Years in a Pond Created Restoratively

The Najeoer Pond was created in a rice paddy as a part of a plan to build the National Institute of Ecology. To induce the establishment of various plants, the maximum depth of the pond was 2.0 m, and diverse depths were created with a gentle slope on the pond bed. When introducing vegetation, littoral and emergent vegetation were first introduced to stabilize the space secured for the creation of the pond, whereas the introduction of other vegetation was allowed to develop naturally. In this pond, floating, emergent, wetland, and littoral plants have been established to various degrees, reflecting the water depth and water table. As a result of stand ordination, based on vegetation data obtained from the created Najeoer Pond and a natural lagoon selected as the reference site, the species' composition resembled that of the reference site. Diversity, based on vegetation type, community, and species, tended to be higher than that of the reference site. The proportion of exotic species increased due to the disturbance that occurred during the pond creation process but continued to decrease as the vegetation introduced during the creation of the pond became established. Considering these results comprehensively, the restorative treatment served to increase both the biological integrity and ecological stability of the pond and, thus, achieved the creation goal from the viewpoint of the pond structure.

Acclimation Unifies the Scaling of Carbon Assimilation Across Climate Gradients and Levels of Organisation

The temperature dependence of carbon assimilation-from leaf photosynthesis to ecosystem productivity-is hypothesised to be driven by the kinetics of Rubisco-catalysed carboxylation and electron transport. However, photosynthetic physiology acclimates to changes in temperature, which may decouple temperature dependencies at higher levels of organisation from the acute temperature sensitivity of photosynthesis. Here, we integrate relative growth rate theory, metabolic theory and biochemical photosynthesis theory to develop a carbon budget model of plant growth that accounts for photosynthetic acclimation to temperature. We test its predictions using a novel experimental approach enabling concurrent measurement of the temperature sensitivity of acute photosynthesis, acclimated photosynthesis and growth rate. We demonstrate for the first time that photosynthetic acclimation mediates how carbon assimilation kinetics 'scale up' from leaf photosynthesis to whole-plant growth. We also find that existing models of photosynthetic acclimation are unable to predict features of growth rate responses to temperature in our system.