Ecological Risk Assessment Framework Research Articles

Construction of landscape eco-geological risk assessment framework in coal mining area using multi-source remote sensing data

High-intensity and large-scale mining activities have aggravated regional eco-geological risk. Therefore, it is significantly essential to conduct an assessment of the eco-geological risk of mining areas. Although some progress has been achieved in ecological risk assessment studies, existing approaches are not entirely suitable for coal bases with high landscape fragmentation and dense coal mining activities. Here, we developed a novel landscape ecological and geological risk (LEGR) assessment framework based on theories that include landscape ecological risk and eco-geological risk. The framework selected 10 indicators, including slope, fluctuation, lithological hardness, soil type, FVC, RSEI, precipitation, biological abundance, distance to road and subsidence rate, and calculated the weights of indicators by introducing the AHP-CRITIC coupled weighting model. Then, the impact of landscape disturbances on eco-geological risk is quantified by measuring landscape losses. This framework was applied to the Shenfu mining area (SFMA), a typical coal base in northwest China. The results indicated the LEGR was moderate in the SFMA whose spatial distribution exhibited an increasing trend from southwest to northeast. Besides, the high LEGR was mainly in the aggregated mining area with high subsidence. For the eco-geological environment monitoring at the mine scale, a multiscale geographically weighted regression (MGWR) model was utilized for analyzing the relationship between indicators and LEGR within the disturbed range of coal mining. It provided valuable insights for the formulation of environmental protection policies in the mining area.

Ecological risk of metals in Andean water resources: A framework for early environmental assessment of mining projects in Peru

Metallic contaminants in Andean water resources influenced by mining activities poses risks to aquatic ecosystems and a challenge to regulatory agencies responsible for environmental compliance. In this study, the Ecological Risk Assessment (ERA) framework was adapted to assess dissolved heavy metal concentrations at 283 surface water monitoring stations near to six mining projects during the dry and wet seasons. Reports from OEFA-Peru on Early Environmental Assessment (EEA) were used to apply various criteria and non-parametric statistical tests. They included ecological, ecotoxicological, chemical, and regulatory factors. The main goal of this research was to identify, analyze, characterize, and compare the risks present at different trophic levels. These levels were categorized as T1 (Microalgae), T2 (Zooplankton and Benthic invertebrates), and T3 (Fish). Individual risk (IR) was estimated using the quotient model, while total risk (TR) was assessed using the additive probability rule. Rainbow trout (Oncorhynchus mykiss), representing trophic level T3, showed the highest sensitivity to Fe and Cu. Statistical tests ranked the IR as Fe > Cu > Zn > Mn > Pb (p < 0.01). The TR was more prevalent during the wet season compared to the dry season (p < 0.01). Notably, around 50 % of the monitoring stations (n = 142) were classified as high risk, and 9 % (n = 13) showed extremely high-risk values for Cu and Fe. The adapted ERA framework demonstrated great effectiveness in identifying critical points of metal contamination in high Andean aquatic ecosystems under mining influence. However, specialized studies are suggested that allow the sources of pollution to be associated with specific regulatory actions.

Spatiotemporal distribution of ecological risk of antibiotics in seven major river basins of China: An optimized multilevel assessment approach.

Antibiotics have been recognized as emerging pollutants due to their ecological and human health risks. This paper aims to enhance the ecological risk assessment (ERA) framework for antibiotics, to illustrate the distribution of these risks across different locations and seasons, and to identify the antibiotics that pose high ecological risk. This paper focuses on 52 antibiotics in seven major basins of China. Relying on the optimized approach of ERA and antibiotic monitoring data published from 2017 to 2021, the results of ERA are presented in multilevel. Across the study area, there are marked variations in the spatial distribution of antibiotics' ecological risks. The Huaihe River Basin, the Haihe River Basin, and the Liaohe River Basin are the top three in the ranking of present ecological risks. The research results also reveal significant differences in temporal variation, underscoring the need for increased attention during certain seasons. Ten antibiotics with high contribution rates to ecological risk are identified, which is an important reference to formulate an antibiotic control list. The multilevel results provided both risk values and their ubiquities across a broad study region, which is a powerful support for developing ecological risk management of antibiotics.

Distribution characteristics and ecological risk assessment of microplastics in intertidal sediments near coastal water

Plastic products are widely distributed worldwide and continue to have a negative impact on the environment and organisms. Intertidal regions, which interface between upland and marine ecosystems, are regions of high ecological importance and serve as repositories for a variety of plastic wastes. However, ecological risk assessments of microplastics (MPs) in these transitional environments are still scarce. In this study, the morphological characteristics and spatial distribution of MPs in the intertidal surface sediments of Haizhou Bay were analyzed, and an ecological risk assessment framework for MPs was developed. Overall, the average abundance of MPs in the sediments was 2.31 ± 1.35 pieces/g dw. The size of the MPs was mainly less than 1 mm, and the main shape, color and polymer type of the MPs were mainly fibrous (58%), blue (30%), and PVC (22%), respectively. Cluster analyses showed that the sites could be well distinguished by size and polymer type but not by MP shape and color. According to the hazard scores, most of the sites in this area belonged to a risk level of IV, while the pollution loading index (PLI) showed that most of the sites belonged to a risk level of II. The ecological toxicity risk from the species–sensitive distribution (SSD) model showed that one–third of the sites had ecological MPs toxicity risks to marine organisms. We believe that normalized and standardized assessment methods should be implemented to monitor and manage the risk of MPs in the intertidal sediments. Particularly, the multiple dimensions, standard abundance of MPs, as well as MPs ingestion in the intertidal organisms, should be fully considered in the next step.

Analyzing species sensitivity distribution of evidently edible microplastics for freshwater biota

Assessing the ecological risks of microplastics is difficult because of the limited availability of reliable ecotoxicity data. Although freshwater is a valuable sink for microplastics, the current framework for ecological risk assessment using traditional toxicity data is not applicable to freshwater ecosystems. Herein, species sensitivity distribution (SSD) curves were compared for edible and all microplastics exposed to aquatic organisms based on traditional endpoint-based and all-endpoint-based databases. Freshwater toxicity data for microplastics were screened after verifying microplastic presence in test species (56 toxicity datapoints for one microalga, three water fleas, one fish, and one crab; 0.02–100 µm-sized microplastics). SSD and curve parameters were compared with or without non-traditional toxicity endpoints. The HC50 in all endpoint databases was more sensitive than that in the traditional endpoint database and showed a good fit. SSD curves derived from the database for all microplastics were compared and analyzed with edible microplastics. HCx increased for edible microplastics (0.02–100 µm-sized) than for all microplastics (0.02–200 µm-sized), and the size of edible microplastics was lower than of all microplastics. Thus, using non-traditional toxicity data, the SSD approach compensates for the limited ecotoxicity data on microplastics while considering the internalization of microplastics in biota.

Exploring watershed ecological risk bundles based on ecosystem services: A case study of Shanxi Province, China

Humans are having an increasingly profound impact on the environment along with the advent of the Anthropocene. Ecological risk assessment (ERA) as a method to quantify ecological problems can provide support for decision-makers, and it is one of key issues to integrate ecosystem services into ERA. In this study, an ERA framework was proposed under the loss-probability paradigm from the perspective of ecosystem services risk bundles. The results showed that initiatives aimed at ecological protection in Shanxi Province had been effective, the number of watersheds with low-risk bundles increased significantly (from 16.09% to 34.49%) and the watersheds basically overlapped with key forestation areas. However, the effects of forestation activities may no longer be as significant as they once were, as the relationship between forestation and water supply was becoming increasingly contradictory. Meanwhile, the conflict between urban expansion and natural ecosystem protection was intensifying, habitat degradation risks were gradually polarized, and the risk bundles dominated by high carbon emission and habitat degradation were increasing significantly (from 15.88% to 33.54%). Strengthening the construction of urban green space and controlling the expansion of human activities may be the next focus of ecological conservation in Shanxi Province. This study enriched the ERA framework with an ecosystem services risk bundle approach.

Ecological risk assessment of a coastal area using multi-source remote sensing images and in-situ sample data

Healthy coastal area have high ecological service value. However, because of the uncontrolled utilization of marine resources and the discharge of pollutants, the ecological environments of many coastal areas are faced with ecological risks, such as oil spills and Enteromorpha blooms. Therefore, it is of great significance to monitor and assess the ecological risks in coastal areas. The remote sensing technique can be used to obtain frequent and wide-coverage images of the areas of interest, and has become an effective tool to monitor the ecological risks occurring in coastal areas. In this study, taking Jiaozhou Bay in China as the study area, an innovative ecological risk assessment framework was established using multi-source remote sensing images and in-situ sample data, which fully considers the potential harm of oil spills and Enteromorpha blooms on the ecology of the bay. Specifically, the oil spill risk for Jiaozhou Bay from 2017 to 2019 was identified by a deep learning based method from synthetic aperture radar (SAR) images, and the Enteromorpha bloom risk for the corresponding years was identified by a floating algae index (FAI) threshold method from multi-source optical images. Then, using habitat information and ground observation data about the marine species in the bay, environmental vulnerability maps were generated. Finally, a disaster-causing factors and disaster-bearing factors weighted risk assessment model was developed. The risk source monitoring results show that the occurrence frequency of oil spills in Jiaozhou Bay decreased from 2017 to 2019, while the outbreak intensity of Enteromorpha blooms generally became higher. The ecological risk assessment results reveal that the high risk areas of Jiaozhou Bay are mainly around the transportation regions and the ports, with a higher risk degree in the eastern and southern parts. To support our work, the well-trained oil spill detection network model and some information about the oil spill events that have occurred in Jiaozhou Bay are provided in this paper.

Evaluating the effects of climate change and chemical, physical, and biological stressors on nearshore coral reefs: A case study in the Great Barrier Reef, Australia.

An understanding of the combined effects of climate change (CC) and other anthropogenic stressors, such as chemical exposures, is essential for improving ecological risk assessments of vulnerable ecosystems. In the Great Barrier Reef, coral reefs are under increasingly severe duress from increasing ocean temperatures, acidification, and cyclone intensities associated with CC. In addition to these stressors, inshore reef systems, such as the Mackay-Whitsunday coastal zone, are being impacted by other anthropogenic stressors, including chemical, nutrient, and sediment exposures related to more intense rainfall events that increase the catchment runoff of contaminated waters. To illustrate an approach for incorporating CC into ecological risk assessment frameworks, we developed an adverse outcome pathway network to conceptually delineate the effects of climate variables and photosystem II herbicide (diuron) exposures on scleractinian corals. This informed the development of a Bayesian network (BN) to quantitatively compare the effects of historical (1975-2005) and future projected climate on inshore hard coral bleaching, mortality, and cover. This BN demonstrated how risk may be predicted for multiple physical and biological stressors, including temperature, ocean acidification, cyclones, sediments, macroalgae competition, and crown of thorns starfish predation, as well as chemical stressors such as nitrogen and herbicides. Climate scenarios included an ensemble of 16 downscaled models encompassing current and future conditions based on multiple emission scenarios for two 30-year periods. It was found that both climate-related and catchment-related stressors pose a risk to these inshore reef systems, with projected increases in coral bleaching and coral mortality under all future climate scenarios. This modeling exercise can support the identification of risk drivers for the prioritization of management interventions to build future resilient reefs. Integr Environ Assess Manag 2024;20:401-418. © 2023 Norwegian Institute for Water Research and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Bioavailability (BA)-based risk assessment of soil heavy metals in provinces of China through the predictive BA-models

The real biological effect is not generated by the total content of heavy metals (HMs), but rather by bioavailable content. A new bioavailability-based ecological risk assessment (BA-based ERA) framework was developed for deriving bioavailability-based soil quality criteria (BA-based SQC) and accurately assessing the ecological risk of soil HMs at a multi-regional scale in this study. Through the random forest (RF) models and BA-based ERA framework, the 217 BA-based SQC for HMs in 31 Chinese provinces were derived and the BA-based ERA was comprehensively assessed. This study found that bioavailable HMs extraction methods (BHEMs) and total HMs content play the predominant role in affecting HMs (As, Cd, Cr, Cu, Ni, Pb, and Zn) bioavailability by explaining 27.55–56.11% and 9.20–62.09% of the variation, respectively. The RF model had accurate and stable prediction ability for the bioavailability of soil HMs with the mean R2 and RMSE of 0.83 and 0.43 for the test set, respectively. The results of BA-based ERA showed that bioavailability could avoid the overestimation of ecological risks to some extent after reducing the uncertainty of soil differences. This study confirmed the feasibility of using bioavailability for ERA and will utilised to revise the soil environmental standards based on bioavailability for HMs.

Long-term assessment of ecological risk dynamics in Wuhan, China: Multi-perspective spatiotemporal variation analysis

Ecological Risk Assessment (ERA) is a critical component of ecosystem management aimed at identifying potential harms caused by human activities. However, previous studies have been limited by short periods, narrow perspectives, and a focus on single-risk factors, making it difficult to comprehensively assess ecological risk. To address these issues, our study investigates ecological risk changes in Wuhan from 1996 to 2020, adopting a multi-perspective method. We then employed a unified scalar overlay approach that fuses the Landscape Ecological Risk Index (LERI) and Habitat Degradation Index (HDI) to conduct an in-depth analysis of comprehensive ecological risk. It considers the interrelationships between threat sources and receptors, as well as the morphological structure of patches, to extract spatial information of ecological risks. Our results reveal that: (1) Wuhan's cropland decreased by 1760.98km2 (−38.95%), mainly converting to construction land and woodland. Simultaneously, construction land expanded outwards from the city center (+895.72km2). At the landscape level, Wuhan's landscape patches are becoming progressively more fragmented. (2) Total Ecological Risk Index (SERI) retains the “Low-High-Low” pattern of both LERI and HDI from the inside out, with high ecological risks radiating from the central urban boundary towards the surrounding regions. The lower-risk areas of the SERI converted mainly to the low-risk areas, whereas the area of higher-risk experienced a larger increase (+1083.45km2), mainly from high-risk areas. Overall, the SERI of Wuhan tends to move towards the north and east. (3) Spatially, hot-spots of risk are predominantly concentrated in the north of Wuhan, while cold-spots are primarily located in the city center. Confidence degrees of both hot and cold spots decrease from their center to the external areas. Additionally, ecological risk showed significant spatial dependency in its distribution. Given the current global environmental crisis, ecological risk research is more important than ever, and our new ERA framework is developed to provide valuable insights for urban planners to mitigate ecological risk.

Landscape Ecological Risk Assessment and Zoning Control Based on Ecosystem Service Value: Taking Sichuan Province as an Example

The escalation of urbanization in Sichuan Province has resulted in irrational land use and excessive resource exploitation. These developments have consequently diminished the functionality of ecosystem services and exacerbated landscape fragmentation in the region. These challenges pose significant threats to the ecological security of the area. In this study, we computed the ecosystem service value and the landscape ecological risk index of Sichuan Province from 2005 to 2018. We analyzed the spatial autocorrelation between the ecosystem service value and the landscape ecological risk index, constructing a framework for landscape ecological risk assessment and zoning control based on ecosystem service value. The results show the following: (1) Between 2005 and 2018, the total value of ecosystem services in Sichuan Province increased from CNY 10,261.17 × 108 to CNY 10,310.43 × 108, with forest land and grassland being the primary contributors to the ESV. (2) High- and higher-risk areas within the landscape ecology of Sichuan Province are expanding, forming a pattern of high-level risk concentration from west to east. (3) There exists a negative correlation between the ecosystem service value and the landscape ecological risk index in Sichuan Province. (4) In the ecological conservation zone, the principle of low-impact development must be upheld. In the ecological cultivation zone, adjusting the proportion of land use types is necessary to enhance the rationality of the land use structure. The ecological agricultural zone should fully utilize the advantages of agriculture, while the ecological improvement zone requires focused attention to ecological restoration and land remediation.

Multi-dimensional landscape ecological risk assessment and its drivers in coastal areas

The eastern coastal areas of Japan are threatened by multiple ecological risks due to frequent natural disasters, climate changes, human activities, etc. Identification spatio-temporal variations and driving mechanisms of landscape ecological risk could be used as significant basis for policymakers. In this study, taking the eastern coastal areas of Japan affected by the 2011 Great East Japan Earthquake and Tsunami Disaster as the study area, the “Nature-Landscape Pattern-Human Society” (NA-LP-HS) multi-dimensional ecological risk assessment framework was established to analyze the spatio-temporal patterns, and identity driving factors using spatial cluster analysis and spatial principal component analysis (SPCA) based on ArcGIS from 2009 to 2021. The findings revealed the distinct geographic patterns in landscape ecological risk, with a noticeable decline from the southwest to the northeast. During the period from 2009 to 2015, the driving factors leading to a sharp risk increase were natural disasters and vegetation coverage. These high-risk areas were concentrated in Sendai Bay and its surroundings. From 2015 to 2021, ecological instability was primarily attributed to a reduction in vegetation coverage, the occurrence of natural disasters, and heightened rainfall erosion. These high-risk areas were mainly clustered within the Tokyo-centered urban agglomeration. Spatial clustering of ecological risks was obvious across all time periods. The key factors contributing to the clustering of high ecological landscape risks focused on the “landscape pattern” criterion, specifically including vegetation coverage, land use land cover. This study demonstrated the ability of multi-dimensional ecological risk assessment to identify high-risk areas and driving factors, and these results could provide a visual analysis and decision-making basis for sustainable development of coastal areas.

Deriving aquatic PNECs of endocrine disruption effects for PFOS and PFOA by combining species sensitivity weighted distributions and adverse outcome pathway networks

Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), as emerging endocrine-disrupting chemicals (EDCs), pose adverse effects on aquatic organisms. Conventional ecological risk assessment (ERA) not fully considering the mode of toxicity action of PFOS and PFOA, may result in an underestimation of risks and confuse decision-makers. In the study, we developed species sensitivity weighted distribution (SSWD) models based on adverse outcome pathway (AOP) networks for deriving predicted no-effect concentrations (PNECs). Three kinds of weighting criteria (intraspecies variation, trophic level abundance, and data quality) and weighted log-normal distribution methods were adopted. The developed models considered the inter/intraspecies variation and integrated nontraditional endpoints of endocrine-disrupting effects. The PNECs of endocrine disruption effects were derived as 2.52 μg/L (95% confidence intervals 0.667–9.85 μg/L) for PFOS and 18.7 μg/L (5.40–71.0 μg/L) for PFOA, which were more conservative than those derived from the SSD method and were comparable with the values in the literature based on the chronic toxicity data. For PFOS, the effect of growth and development was the most sensitive; however, for PFOA, the effect of reproduction was the most sensitive in the effects of growth and development, reproduction, biochemistry and genetics, and survival. The endocrine-disrupting effects of PFOS and PFOA are significant and need to be fully recognized in the ERA. This study provided an ERA framework that can improve the ecological relevance and reduce the uncertainty of PNECs of EDCs.

Regional ecological risk assessment based on multi-scenario simulation of land use changes and ecosystem service values in Inner Mongolia, China

Regional ecological risk assessment (ERA) is an important means towards sustainable regional development. Yet, existing ERA approaches often fall short of characterizing ecological processes as dynamic processes involving uncertainty. Using Inner Mongolia, a high ecological risk area in China, this study employed a framework for regional ERA that considers ecosystem service value (ESV) and four scenarios of future land use patterns to understand its regional ecological risk. The spatially explicit risk assessment method was implemented by a model combining multi-criteria evaluation (MCE), cellular automata (CA), and Markov chain to predict future land use/cover of 2030, an adjustment-based equivalence factor method to assess the ESV in each scenario, and Sharpe Index to assess regional ecological risk. The results show the following. First, the overall ESV increases from 2020 to 2030 under all but the socio-economic development (SED) scenarios considered in this study. Second, the overall regional ecological risk of Inner Mongolia is high in the central region and low in the east, north, and west regions. The low ecological risk areas account for the largest areal proportion in the ecosystem services protection (ESP) and natural development (ND) scenarios, while the medium ecological risk areas are the largest under SED. However, some low ecological risk areas are converted into medium ecological risk in ecological and socioeconomic balance scenario (ESB) scenario. Third, NDVI is the driving factor with the strongest explanatory power for the regional ecological risk in Inner Mongolia, followed by mean annual precipitation and temperature. The present study applied a framework for regional ERA that explicitly considers spatial heterogeneity and uncertainty, which can be useful for guiding decision-making for ecological risk control and the planning of the land use of ecosystems.

Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects.

Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically based risk assessments to enhance the "eco" component of ERAs. Regulatory and logistical challenges often relegate such nonstandard endpoints and indirect effects to postregistration evaluations of pesticides and industrial chemicals and contaminated site evaluations. While NAMs are being developed, to date, their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory- and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole-animal data and simple hazard ratios. Integr Environ Assess Manag 2024;20:725-748. © 2023 His Majesty the King in Right of Canada and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Towards a management strategy for microplastic pollution in the Laurentian Great Lakes—ecological risk assessment and management (part 2)

Over the past decade, plastic pollution has been documented throughout the Laurentian Great Lakes basin. Here, we demonstrate the application of a published ecological risk assessment and management framework for microplastics in aquatic environments by comparing proposed thresholds for risk to monitoring data from the Great Lakes region. Our results suggest that there may be measurable risks from microplastics to aquatic communities in parts of the Great Lakes where current concentrations are relatively high. For example, 89% of surface water samples collected across the region exceed the proposed risk thresholds for food dilution toxicity. However, all sediment samples remain below the proposed risk thresholds. Accordingly, we suggest that an appropriate and necessary next step for management may include convening a working group of local experts to develop an ecological risk assessment and management framework for the region comprising thresholds of concern for microplastics in surface water and sediment. Ultimately, microplastic pollution should be addressed in the Great Lakes Water Quality Agreement to ensure coordinated and sustained efforts are taken by the governments of Canada and the United States to reduce their release and impact.

Ecological risk of geohazards and its combination patterns: A case study of an ecologically fragile region, NW China

Our comprehension of ecological risk in the Upper Yellow River region in China remains limited due to the prevailing focus of current studies on urbanized areas, with insufficient attention given to the mountainous regions. Luqu County is widely recognized as an important regional ecological barrier and ecologically fragile area, susceptible to geohazard effects. However, the relationship between ecological risk and geohazard remains unclear. To address this gap, we conducted an assessment of ecological risk and analyzed its combination patterns using the available geohazard inventory of Luqu. We established a framework for ecological risk assessment, employing the MaxEnt, Fragstats, and InVEST models to evaluate the degree of hazard, ecological vulnerability, and potential ecological loss. The evaluation results consider the significance of the geoenvironmental and climatic context in Luqu. Among the selected conditioning factors, elevation, distance to the river, average precipitation from May to September, gully density, and stratigraphic age exhibit the highest relative contribution values to the geohazards, with values of 0.861, 0.789, 0.764, 0.67, and 0.636, respectively. The Northern Taohe River Basin has been identified as a high ecological risk area characterized by highly fragmented landscapes. Furthermore, ecological risk exhibits a gradual decline trend from the northeast to the southwest. The combination pattern characterized by high ecological fragility-predominated, low hazard and low ecological loss-supplemented exhibits the highest ecological risk. This pattern covers over 60% of Luqu. The township-level ranking of medium-high and high ecological risk proportions is as follows: Ala (33.59%), Xicang (19.52%), Shuangcha (14.38%), Ma'ai (6.96%), Larenguan (4.49%), Langmusi (1.06%), and Gahai (0.13%). Compared with hazard and ecological loss, ecological fragility has generally maintained a relatively stable level during current period. Considering the positive correlation between ecological risk and geohazards found in this study, we recommend that local communities prioritize high-risk areas for effective risk management.

Insights into the mechanisms of within-species variation in sensitivity to chemicals: A case study using daphnids exposed to CMIT/MIT biocide

Living organisms adapt to their environment, and this adaptive response to environmental changes is influenced by both genomic and epigenomic components. As adaptation underpins tolerance to stressors, it is crucial to consider biological adaptation in evaluating the adverse outcomes of environmental chemicals, such as biocides. Daphnid studies have revealed differences in sensitivity to environmental chemicals between conspecific populations or clones, as well as between species. This study aimed to identify whether sensitivity to chemicals is subject to intraspecific variation, and whether this sensitivity depends on the genetic and epigenetic backgrounds of the daphnid population. We used an integrative approach to assess the comparative toxicity of a mixture of 5-chloro-2-methyl-4-isothiazoline-3-one and 2-methyl-4-isothiazolin-3-one (CMIT/MIT), a commonly used isothiazolinone biocide, by measuring mortality, reproduction, physiological traits, global DNA methylation, and proteomic expression at the species and strain levels. The results showed that the variation in sensitivity to CMIT/MIT between conspecific strains (Daphnia pulex; DPR vs. DPA strains) could exceed that observed between congeneric species (D. magna vs. D. pulex DPR strain). Under the control conditions, DPR (the strain most sensitive to CMIT/MIT) was characterized by a larger body size, a higher heart rate, and a higher level of global DNA methylation compared to its counterpart (DPA), and proteome profiles differed between the two strains. Particularly, the study identified strain-specific epigenetic and proteomic responses to LC20 of CMIT/MIT, demonstrating putative critical proteins and biological pathways associated with the observed differences in phenotype and sensitivity to CMIT/MIT. Downregulation of certain proteins (e.g., SAM synthase, GSTs, hemoglobin, and cuticle proteins) and DNA hypomethylation can be proposed as key events (KEs) of adverse outcome pathway (AOP) for isothiazolinone toxicity. Our findings indicate that both genetic variations and epigenetic modifications can lead to intraspecific variation in sensitivity to chemicals, and this variation should be considered in the ecological risk assessment framework for chemical substances. We suggest conducting further analysis on methylated gene regions and observing transgenerational effects to verify the role of crosstalk between genetic and epigenetic factors in phenotypic and protein expressions. Data availabilityProteomic data is available in supplementary materials.

Assessment and Prediction of Landscape Ecological Risk from Land Use Change in Xinjiang, China

Land use change has significant impacts on the regional and global environment; thus, in-depth research on the associated ecological risks is necessary for promoting ecological restoration and sustainable development. Xinjiang, China, is characterized by a fragile ecological environment, and this study aimed to predict the land use change in the region in 2030 under different scenarios, including natural development, ecological conservation, and urban development, by using the PLUS model based on land use data from 2000, 2010, and 2020. Based on the landscape structure of regional ecosystems, we developed a comprehensive ecological risk assessment framework by utilizing a combination of landscape disturbance index, vulnerability index, and loss index. This framework allowed us to evaluate the spatiotemporal patterns and variations of landscape ecological risks under different scenarios in 2030. The study results indicate the following: (1) During the period from 2000 to 2020, the primary landscape type in Xinjiang was unused land. However, significant changes were observed in the area of cultivated land, mainly due to the conversion of grassland and construction land. The expansion of construction land during the urbanization process resulted in a decline in ecological landscapes, such as grassland, thereby weakening the ecosystem’s stability. (2) Under different simulation scenarios, the urban development scenario primarily led to the conversion of unused land into construction land, which is beneficial for economic development. On the other hand, the ecological conservation scenario resulted in a modest increase in construction land and a transformation of unused land into forest and grassland, which aligns with the principles of sustainable development. (3) Different scenarios in 2030 result in varying degrees of changes in each landscape type in Xinjiang, with the spatial distribution characteristics of landscape ecological risks remaining similar to those observed in 2020. Notably, under the urban development scenario, the area of lowest and medium risk areas decreases significantly while the area of higher and highest risk areas increases substantially. Conversely, under the ecological conservation scenario, the area of the lowest risk areas experiences a more significant increase. (4) Overall, the spatial differences in the ecological risk of Xinjiang’s landscape are significant, with HH and LL clustering types predominating and presenting a polarization pattern. The distribution pattern is low in the north and high in the central and southern parts of the study area.

A framework for systematic microplastic ecological risk assessment at a national scale

Microplastic pollution is widespread in terrestrial and aquatic environments; however, a systematic assessment of the ecological risks of microplastics is lacking. This study collected research studies on microplastics in soil, aquatic and sediment environments, and screened 128 articles including 3459 sites to assess the ecological risks posed by microplastics in China following a literature quality assessment. We developed a systematic ecological risk assessment framework for microplastics in terms of spatial characterization, biotoxicity and anthropogenic impacts. The results of the pollution load index indicated that 74% and 47% of the soil and aquatic environments studied, respectively, faced a medium or higher level of pollution. Comparing predicted no effect concentrations (PNEC) and measured environmental concentrations (MECs), revealed that soil (97.70%) and aquatic (50.77%) environmental studies were at serious ecological risk from microplastics. The results of the pressure-state-response model showed that the microplastic pollution in Pearl River Delta was in a high-risk state. In addition, we found that ultraviolet radiation and rainfall exacerbate soil microplastic pollution, and higher river runoff may carry large amounts of microplastic from the source. The framework developed in this study will help assess the ecological risks of microplastics in the region to promote the mitigation of plastic pollution.