Ecological Indicators Research Articles

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

The objective of this inquiry is to illuminate the attributes of heavy metal contamination and evaluate the potential ecological hazards inherent in the surface soil of Chenzhou City. A comprehensive analysis was conducted on 600 systematically collected soil samples within the study area, utilizing enrichment factors, geo-accumulation indices, comprehensive pollution indices, potential ecological hazard indices, and health risk assessment models to evaluate the degree of heavy metal contamination in the soil, potential ecological risks, and associated health hazards. The findings reveal that the average enrichment factor (EF) for each heavy metal is below 2, with the hierarchy from highest to lowest being Hg > Cd > Cu > Pb > Ni > Zn > Cr > As. Approximately 78.67% of soil samples exhibit no pollution to weak pollution levels based on heavy metal enrichment factors. Moreover, the comprehensive pollution index (IPIN) indicates that 95.17% of soil samples are within safe and pollution-free levels, indicating an overall environmentally secure setting. However, 2.67% of samples display heightened potential ecological risk levels, primarily concentrated in the southwestern region of the study area, influenced by nearby industrial activities. Additionally, it is noteworthy that both the non-carcinogenic and carcinogenic health hazards emanating from soil heavy metals to adult individuals lie within tolerable thresholds. Among these, arsenic (As), chromium (Cr), and lead (Pb) have been discerned as the principal non-carcinogenic agents. It is of particular significance that only a solitary soil specimen, located in the southwestern quadrant of the investigative region, manifests detectable health perils for children.

Combining Multi-View UAV Photogrammetry, Thermal Imaging, and Computer Vision Can Derive Cost-Effective Ecological Indicators for Habitat Assessment

Recent developments in Unmanned Aircraft Vehicles (UAVs), thermal imaging, and Auto-machine learning (AutoML) have shown high potential for precise wildlife surveys but have rarely been studied for habitat assessment. Here, we propose a framework that leverages these advanced techniques to achieve cost-effective habitat quality assessment from the perspective of actual wildlife community usage. The framework exploits vision intelligence hidden in the UAV thermal images and AutoML methods to achieve cost-effective wildlife distribution mapping, and then derives wildlife use indicators to imply habitat quality variance. We conducted UAV-based thermal wildlife surveys at three wetlands in the Rainwater Basin, Nebraska. Experiments were set to examine the optimal protocols, including various flight designs (61 and 122 m), feature types, and AutoML. The results showed that UAV images collected at 61 m with a spatial resolution of 7.5 cm, combined with Faster R-CNN, returned the optimal wildlife mapping (more than 90% accuracy). Results also indicated that the vision intelligence exploited can effectively transfer the redundant AutoML adaptation cycles into a fully automatic process (with around 33 times efficiency improvement for data labeling), facilitating cost-effective AutoML adaptation. Eventually, the derived ecological indicators can explain the wildlife use status well, reflecting potential within- and between-habitat quality variance.

Odonata Assemblages in Urban Semi-Natural Wetlands.

As the human population in urban areas is continuously growing, urbanization is one of the greatest threats to biodiversity. To mitigate the negative effects, the inclusion of blue zones (aquatic habitats) in modern urban development practices is strongly recommended, as they could be beneficial for the local biodiversity conservation. Odonata are a flagship group and are widely used in freshwater conservation as ecological indicators of habitat integrity and health. However, our understanding of their ecological requirements in urban landscapes is not yet complete. Therefore, we analyzed the taxonomic and functional diversity of Odonata in a semi-natural wetland in the Croatian capital. This study was conducted in the summers of 2020 and 2023. Most taxonomic and functional assemblage metrics were comparable between the two main habitat types, anthropogenically disturbed and natural oxbow lakes. However, significant differences were found in relation to the time scale, where most metrics were lower in 2023, indicating the negative impact of extreme climate events (including droughts) that occurred in this region after 2020. With 19 species recorded, our results indicate that semi-natural urban wetlands, especially natural oxbow lakes, have great potential to function as good habitats for Odonata, where even some species of conservation concern were detected. When developing landscape management plans in urban areas, it is essential to consider the importance of habitat heterogeneity in terms of good structure of aquatic macrophytes (presence of submerged, emergent and floating vegetation), which would ensure the most suitable habitat conditions for local Odonata species.

Species diversity and distribution-pattern determinants of African rivulines (Cyprinodontiformes: Nothobranchiidae) in rainforest streams of southern Cameroon

Understanding the community structure and ecology of fish populations in rainforest streams is a prerequisite for any actions towards their exploitation, management or conservation. We examined the community structure and species diversity of nothobranchiids (African rivulines) in rainforest streams of Cameroon’s southern plateau and part of the coastal plain, using data on 19 environmental variables for ecological indices and multivariate analyses. In total, 1 019 individual cyprinodontiforms assigned to 14 species (largely species of Aphyosemion) were collected, for a global sampling effort of 78.6%. The presence of nothobranchiids in the study area was associated with several local environmental factors common to all sampling sites, mainly canopy cover above the watercourse and physicochemical characteristics of the stream habitat. Distribution of the species was strongly spatially structured, driven by the site’s elevation and the water temperature, and influenced primarily by the riparian vegetation, substrate type, water conductivity and flow velocity. However, fish species richness did not differ significantly between the five sectors sampled and by elevation. The nothobranchiid communities were highly diverse (Shannon’s H′ = 2.28 ± 0.05; Pielou’s J = 0.87) and the species evenly distributed. Seven species were exclusive to a single sector, others were prevalent in multiple sectors, and no species was common to all sectors. Affinities between species were relatively few, though there were exceptions, and most species tended to exclude each other. These findings highlight nothobranchiids as local fish assemblages having high biotic integrity and responsiveness to environmental degradation. In tropical Africa, these fishes often occupy fragile habitats influenced by anthropogenic activities. A better understanding of the unifying role of habitat in ecology will assist management efforts to promote biodiversity conservation.

Biodiversity and Carbon Sequestration in Chakra-Type Agroforestry Systems and Humid Tropical Forests of the Ecuadorian Amazon

Currently, there are several studies related to climate change, carbon sequestration, and floristic composition in different scenarios and land uses. In this context, the objective of this research is: (a) to characterize biodiversity based on ecological indicators and diversity indices and (b) to evaluate carbon sequestration in different components of chakra-type agroforestry systems and secondary tropical humid forests of the Ecuadorian Amazon. For this, temporary sampling plots of 1600 m2 are established on the properties to be investigated. The study found that the structural characteristics and floristic composition vary according to the forest arrangement and the management system. Secondary forests are the most diverse, according to the Shannon (3.49), Simpson (0.96), and Margaleft (9.34) diversity indices, in addition to having the largest carbon stores with 233 (Mg C ha−1), followed by agroforestry systems in association with timber trees (TAFS) and fruit trees (FAFS) with 97.8 and 95.1 (Mg C ha−1) respectively, and cocoa monoculture (CMC) with 90.4 (Mg C ha−1). These results demonstrate the importance of conserving the remnants of tropical forests that still remain, due to the diversity of species, ecosystem services, and the total carbon they contain, as well as the agroforestry systems (AFS), systems analogous to forests, which are gradually becoming important management systems, especially if they are associated with potential species to sequester carbon, such as those documented in this and several other studies that seek solutions to global climate change.

Ecological health assessment of Tibetan alpine grasslands in Gannan using remote sensed ecological indicators

ABSTRACT Ecosystem health assessments are crucial to protect the ecological environment and ensure the sustainable ecological functions of alpine ecoregions. At present, few studies evaluating the ecosystem health of the Gannan alpine grassland, China, an ecologically fragile area, based on a remote sensing theoretical framework exist. As such, this study assessed the ecosystem health of the Gannan alpine grassland based on the Remote Sensing-based Ecological Index (RSEI) and provided a comparative analysis of the RSEI and Gross Primary Productivity (GPP), extending the study of their spatiotemporal patterns and influencing factors. The results suggested that RSEI and GPP showed strong comparability in an ecological sense, with the RSEI better reflecting changes in ecosystem health of the Gannan alpine grassland than the GPP. Overall, the health of the Gannan alpine grassland ecosystem was good (RSEI of 0.61–0.76) and a slow, fluctuating upward trend was seen from 2000 (RSEI = 0.66) to 2020 (RSEI = 0.72). Notably, the RSEI was high in the south and low in the north of the region. Over the past 21 years, 43.92% of the ecologically healthy grassland in the southwest of Gannan has been degrading, while the poor ecological health of 39.04% of the grasslands in the southeast and northeast improved. The model test results show that RSEI could reasonably evaluate the ecosystem health of Gannan alpine grassland. Our assessment results provide important scientific data and information on health monitoring and targeted ecological restoration efforts in the Gannan region.

Grazing alters the soil nematode communities in grasslands: A meta-analysis

Grazing causes great disturbances in grassland ecosystems and may change the abundance, diversity, and ecological function of soil biota. Because of their important role in nutrient cycling and as good environmental indicators, nematodes are very representative soil organisms. However, the mechanisms by which grazing intensity, livestock type, duration, and environmental factors (e.g., climate and edaphic factors) affect soil nematodes remain poorly understood. In this study, we collected 1964 paired observations all over the world from 53 studies to clarify the grazing response patterns of soil nematodes and their potential mechanisms. Overall, grazing significantly decreased the abundance of bacterial-feeding (BF) nematodes (−16.54%) and omnivorous-predatory (OP) nematodes (−36.81%), and decreased nematode community diversity indices (Shannon–Weiner index: −4.33%, evenness index: −9.22%, species richness: −5.35%), but had no effect on ecological indices under a global regional scale. The response of soil nematodes to grazing varied by grazing intensity, animals, and duration. Heavy grazing decreased OP nematode abundance, but had no effect on the abundance of other trophic groups, or on diversity or ecological indices. Grazing by small animals had stronger effects than that by large animals and mixed-size animals on BF, fungal-feeding (FF), plant-feeding (PF) and OP nematodes, the Shannon–Wiener index, and the species richness index. The abundance of FF and OP nematodes influenced significantly under short-term grazing. The evenness index decreased significantly under long-term grazing (>10 years). Climate and edaphic factors impacted the effects of grazing on nematode abundance, diversity, and ecological indices. When resources (i.e., rain, heat, and soil nutrients) were abundant, the negative effects of grazing on nematodes were reduced; under sufficiently abundant resources, grazing even had positive effects on soil nematode communities. Thus, the influence of grazing on soil nematode communities is resource-dependent. Our study provides decision makers with grazing strategies based on the resource abundance. Resource-poor areas should have less grazing, while resource-rich areas should have more grazing to conserve soil biodiversity and maintain soil health.

Distribution of Macrozoobenthos of Flowing Water Bodies by Altitudinal Belts of the Nakhchivan Autonomous Republic

Spatial distribution, species structure and ecological indicators of macrozoobenthos of flowing water bodies by altitude belts of Nakhchivan Autonomous Republic were studied. Macrobenthos fauna of the rivers of the region is formed in psammoreophilic, phytoreophilic and peloreophilic biocenoses with a great advantage of lithoreophilic biocenosis. The lithoreophilic biocenosis of rivers of the mountain and high-mountain belts is characterized by extensive area and abundance of species diversity. The core of the lithoreophilic biocenosis is composed of populations of rheophilic organisms such as moths, mayflies, vernal pools and simulids; its usual inhabitants are also rheophilic larvae of chironomids of the genus Polypedilum, Endochironomus, Eukiefferiella, Cricotopus and Orthocladius. The family composition of the fauna was found to be relatively stable along the rivers. Differences in the species composition of macrobenthos fauna, change of dominant species in biocenoses are related to biological features of the main species, anthropic and anthropogenic impacts, as well as different time of research. The species composition of macrozoobenthos of the rivers of the autonomous republic decreases from the source to the mouth.

MEASURING SUSTAINABILITY IN SUPPLY CHAIN MANAGEMENT IN CONSTRUCTION COMPANIES

This paper provides an analysis of the most important sustainability indicators for SSCM in construction and gives a detailed overview of what has been scientifically accomplished in the field to date, and identifies areas for further research. The most important sustainability indicators were also grouped and presented in the literature review into the main seven assessment groups of the SSCM construction industry and ranked by experts from Northern Italy and Lithuania in several different ways. Based on the data from the Table 3, it can be inferred that a harmonious work environment among ecological sustainability indicators appeared as the most crucial indicator for respondents. Environmental education was among the most important social indicators. In the legal group, work efficiency emerged as the most significant indicator, while in the physical group, sustainable resource use was crucial. In the political realm, economic and political stability was the most important, and among technological indicators, innovation stood out. Among economic indicators, profit was the most significant sustainability indicator for respondents. A general indicator importance method combined results obtained from expert surveys using various methods. The ranking of sustainability indicators in each group was not included in the calculation of the overall indicator importance, but the results were similar in both cases. The determined importance of indicator values could be adapted for further analysis, specifically for multicriteria evaluation, as per the conceptual model shown in Figure 1. This article provides members of the construction industry with detailed calculations and results of the evaluation of key sustainability indicators related to supply chain groups. This study explores several possible ways to measure the importance of sustainability indicators, which could provide further theoretical insights into SSCM in the construction industry and help develop an accurate sustainability index model.

Assessing the spatial distribution of elemental concentrations in surface sediments of Lake Victoria, Kenya: implications for ecological health and management.

Lacustrine sediment quality indicates the effects of both natural and anthropogenic activities on the ecosystem and communities. Despite its ecological importance, myriad complexities, and potential contaminant sources, the spatial distribution of surficial sediments in Lake Victoria's Winam Gulf has never been comprehensively documented. The purpose of this study was to assess the spatial distribution, pathways, and ecological risk of metal elements in the lake using a sediment matrix. Sediment samples were collected throughout the gulf in November 2022. The concentrations of Al, As, Cd, Co, Cr, Cu, Fe, K, Mn, Mo, Ni, P, Pb, Sb, Sn, Ti, Tl, U, and Zn were compared to different contamination metrics and ecological risk assessment indices. The average concentrations were in the following decreasing order: Zn >  >  > Cr >  > Cu > Ni > Pb > Co > As > Cd with mean (± SD) of 185 ± 45mgkg-1, 56 ± 15mgkg-1, 45 ± 16mgkg-1, 37 ± 11mgkg-1, 24 ± 5mgkg-1, 20 ± 7mgkg-1, 3.9 ± 1.3mgkg-1, 0.30 ± 0.09mgkg-1, respectively, with strong indications of anthropogenic sources. Average concentrations were in the following decreasing order: Zn >  >  > Cr, Cu, Ni, Pb, Co, As, and Cd levels (mean ± SD) were 185 ± 45mgkg-1, 56 ± 15mgkg-1, 45 ± 16mgkg-1, 37 ± 11mgkg-1, 24 ± 5mgkg-1, 20 ± 7mgkg-1, 3.9 ± 1.3mgkg-1 and 0.30 ± 0.09mgkg-1 with strong indications of anthropogenic sources. The geo-accumulation index (Igeo) and enrichment factor categorisation schemes, respectively, classified these as uncontaminated (level 0) and depletion to minimal enrichment (level 1), while the ecological risk analysis classified them as "low risk". The mouth of the Nyando River, as well as Kisumu, Kendu, and Homa bays, were the most element-enriched and should be prioritised for focused monitoring and remediation. As a result, targeted land management of urban, industrial, transportation, and agricultural areas offers the opportunity to reduce sediment inputs into the lake ecosystem.

Geochemical baseline establishment, pollution level and health risk assessment of soil heavy metals in the upper Xiaowen River Basin, Shandong Province, China.

This study analyzed the distribution and content of eight heavy metals (Cu, Pb, Zn, Ni, Cr, As, Cd, and Hg) in 221 surface soil samples from the upper reaches of the Xiaowen River. Environmental geochemical baselines were established for the eight heavy metals, and the pollution status was assessed on the basis of these baselines and the soil background value of Weifang City. The calculation results of Nemerow pollution index and the potential ecological hazard index (PEHI)-Ri showed that the overall pollution degree and ecological hazard in the study area were at a slight level. 49% (calculated by baseline value) and 24% (calculated by background value of Weifang City) samples were at moderate or above pollution level. 9% (calculated by baseline value) and 42% (calculated by background value) samples were at the level of moderate potential ecological hazards or above. According to the calculation results of Igeo and PEHI-Ei, the main pollutant in the study area was Hg, followed by Cd. 3% (calculated by baseline value) and 12% (calculated by background value) of Hg samples were at moderate or above contamination levels. 5% (calculated by baseline value) and 38% (calculated by background value) of Hg samples were at the level of strong potential ecological hazard or above. The western, central, and eastern parts of the study area were mainly the primary areas of pollution and ecological hazards. The non-carcinogenic risk was at an acceptable level, the carcinogenic risk was at a tolerable level, and the main risk pathway was oral intake, with Cr being the main contributor. Source apportionment indicated that soil heavy metals primarily originate from soil parent material, transportation, agricultural fertilization, and industrial emissions (waste gas, waste water and solid waste).

Remote sensing perspective in exploring the spatiotemporal variation characteristics and post-disaster recovery of ecological environment quality, a case study of the 2010 Ms7.1 Yushu earthquake

Natural hazards usually cause heavy casualties and vast economic losses, as well as severe damage to the ecological environment. Quantitative and scientific evaluations of the ecological environment quality (EEQ) and its recovery trend after hazards can provide valuable insights for disaster risk reductions. This study takes the 2010 Ms7.1 Yushu earthquake as an example to explore the spatiotemporal changes and driving mechanisms of EEQ before and after the earthquake using remote sensing and GIScience. First, the Moderate-resolution Imaging Spectroradiometer (MODIS) data was selected to establish the remote sensing based ecological index (RSEI). Then, we analyzed the spatiotemporal characteristics of Yushu’s EEQ from 2001 to 2020 and explored spatial autocorrelation relationships. Last, the driving mechanism of EEQ recovery in Yushu was analyzed using the GeoDetector model. The main conclusions are as follows: (1) From the perspective of the RSEI time series, the EEQ in Yushu County was strongly negatively affected during the earthquake and recovered well after the earthquake. (2) Based on a spatial distribution analysis, it can be observed that the regions in Yushu with relatively high EEQ are primarily concentrated in the central and southern areas. Conversely, the northwestern and southeastern areas display relatively lower quality. Moreover, the EEQ in Yushu County has a strong correlation and clustering, as evidenced by Moran’s I value exceeding 0.7 over the years. (3) Based on the GeoDetector results, elevation and population were found to be the key driving factors affecting changes in post-disaster EEQ. The interaction between elevation and slope plays the most critical role in the process of ecological recovery. This study provides a theoretical basis for the evolution of the post-disaster ecological environment in Yushu County and helps decision-makers better balance the relationship between social development and environmental protection in disaster management and urban planning. It also provides useful reference and guidance for future ecological protection and recovery under similar disasters.

Long-Term Dynamic Monitoring and Driving Force Analysis of Eco-Environmental Quality in China

Accurate assessments of the historical and current status of eco-environmental quality (EEQ) are essential for governments to have a comprehensive understanding of regional ecological conditions, formulate scientific policies, and achieve the United Nations Sustainable Development Goals (SDGs). While various approaches to EEQ monitoring exist, they each have limitations and cannot be used universally. Moreover, previous studies lack detailed examinations of EEQ dynamics and its driving factors at national and local levels. Therefore, this study utilized a remote sensing ecological index (RSEI) to assess the EEQ of China from 2001 to 2021. Additionally, an emerging hot-spot analysis was conducted to study the spatial and temporal dynamics of the EEQ of China. The degree of influence of eight major drivers affecting EEQ was evaluated by a GeoDetector model. The results show that from 2001 to 2021, the mean RSEI values in China showed a fluctuating upward trend; the EEQ varied significantly in different regions of China, with a lower EEQ in the north and west and a higher EEQ in the northeast, east, and south in general. The spatio-temporal patterns of hot/cold spots in China were dominated by intensifying hot spots, persistent cold spots, and diminishing cold spots, with an area coverage of over 90%. The hot spots were concentrated to the east of the Hu Huanyong Line, while the cold spots were concentrated to its west. The oscillating hot/cold spots were located in the ecologically fragile agro-pastoral zone, next to the upper part of the Hu Huanyong Line. Natural forces have become the main driving force for changes in China’s EEQ, and precipitation and soil sand content were key variables affecting the EEQ. The interaction between these factors had a greater impact on the EEQ than individual factors.

Screening of Key Biogeochemical Indicators of the Environment of Large Industrial Agglomerations (on the Example of the Moskovsky District of St. Petersburg)

The ecological and biogeochemical indicators of the state of the environment on the territory of a large urban agglomeration on the example of the Moskovsky district of St. Petersburg are considers. In 2009–2015–2021, the pH, chemical composition of soils and bark of Populus balsamifera were studied, biotesting of soils using Daphnia magna and Chlorella vulgaris was carried out. An integral indicator of LTP (Landscape Total Pollution) pollution based on the Harrington desirability function was used. An analysis of changes in the state of the environment over the specified period, depending on the functional use of the territory, was given. The aggravation of long-term pollution of environmental components in conditions of increasing emissions from motor vehicles, which is induced by increasing concentrations of Pb, Cd, Zn, Cu, Ni, Fe, Mn in soils and plants, is noted.

Landsat series images for evaluating ecological restoration effect from multi-time scale based on an ideal reference

Multi-time scale assessment of ecological restoration effects based on objective and scientific approaches can provide crucial information for implementing environmental protection policies and ensuring sustainable regional development. This study evaluated the effect of ecological restoration based on a natural evolution as a reference frame, using yearly Landsat time series. Southern Ningxia in China was selected as the study area. The remote sensing ecological index (RSEI) was calculated. The features of natural evolution were derived from the time series of the RSEI in the natural reserve areas (NRAs). LandTrendr was employed to characterize the disturbance–recovery processes. Furthermore, we adopted the dynamic time-warping method for the entire study period, along with the relative variation ratio (during the disturbance–recovery cycle) to capture the long-term and short-term ecological restoration effects, respectively. The following conclusions were drawn: First, a time-series RSEI based on LandTrendr was used to successfully monitor disturbance–recovery processes. Second, the majority of RSEI disturbances (i.e., >60%) occurred between 2000 and 2005. It is characterized by fewer disturbance times and obvious spatial heterogeneity in disturbance duration. Notably, from 2000 to 2022, the RSEI improved. Additionally, approximately 40% of the study area portrayed a strong similarity to the RSEI of the NRAs. We conclude that quantifying the ecological restoration effect at multi-time scales is a practical operational approach for policymakers and environmental protection. Our study presents novel insights for assessing regional ecological quality, by capturing the processes of natural evolution features in NRAs.

Ecological Vulnerability Assessment and Spatiotemporal Characteristics Analysis of Urban Green-Space Systems in Beijing–Tianjin–Hebei Region

The evaluation and analysis of the ecological vulnerability of urban green-space systems are conducive to the sustainable development of urban green-space systems. Taking the urban green-space system in the Beijing–Tianjin–Hebei region in 2010, 2015, and 2020 as the research object, an ESSR model was first constructed, and a total of ten types of impact factors were integrated into the four dimensions of “Exposure, Sensitivity, State and Response”. The weight of the impact factors was objectively determined via spatial principal component analysis, and the ecological vulnerability of the urban green-space system was evaluated via superposition analysis; the evaluation’s results were graded. Moreover, the transfer matrix, center-of-gravity migration model, standard deviation ellipse, and spatial autocorrelation analysis were used to study the temporal and spatial variation characteristics of the evaluation results; then, the driving force of impact factors was analyzed based on a geographical detector. Finally, the rationality of the evaluation results was verified using the changing trend of the remote sensing ecological index (RSEI). The results show that the ecological vulnerability of the urban green-space system in the Beijing–Tianjin–Hebei region has decreased year by year for the past ten years. The distribution law of “Hebei surrounds Beijing and Tianjin” is presented in this space, and 2015 is the mutation node. In 2010, the moderately and severely vulnerable areas of Hebei surrounded the mildly vulnerability areas of Beijing and Tianjin. Moreover, in 2015 and 2020, the mildly vulnerable areas of Hebei surrounded the severely vulnerable areas of Beijing and Tianjin. Vulnerability expands slightly in the east–west direction and shrinks slightly in the north–south direction, and the center of gravity shifts towards Beijing year by year along the northeast direction. Moreover, the spatial distribution of vulnerability shows significant positive spatial autocorrelations and exhibits very obvious agglomeration. In addition, vulnerability is the result of the combined effect of various factors, and education degree, human disturbance index, and annual average precipitation are the dominant factors. The analysis results provide a reference for the effective application and sustainable development of urban green-space ecological functions.

[Ecological Environment Assessment and Driving Mechanism Analysis of Nagqu and Amdo Sections of Qinghai-Xizang Highway Based on Improved Remote Sensing Ecological Index].

The ecological environment along the Qinghai-Xizang highway is an important part of the construction of the ecological civilization in the Xizang region, and current research generally suffers from difficulties in data acquisition, low timeliness, and failure to consider the unique "alpine saline" environmental conditions in the study area due to the unique geographical environment of the Qinghai-Xizang plateau. Based on the GEE platform and the unique geographical environment of the study area, the remote sensing ecological index (RSEI) was improved, and a new saline remote sensing ecological index (SRSEI) applicable to the alpine saline region was constructed by using principal component analysis as an ecological environment quality evaluation index. The spatial distribution pattern and temporal variation trend of ecological environment quality along the Qinghai-Xizang Highway Nagqu-Amdo section were analyzed at multiple spatial and temporal scales using the ArcGIS 10.3 platform and geographic probes, and the driving mechanisms of eight control factors, including natural and human-made, on the spatial and temporal changes in SRSEI were investigated. The results showed that:① compared with RSEI, SRSEI was more sensitive to vegetation and had a stronger discriminatory ability in areas with sparse vegetation and severe salinization, which is suitable for ecological quality evaluation in alpine saline areas. ② The spatial scale of ecological environment quality in the study area had obvious geographical differentiation, and the areas with poor ecological quality were mainly concentrated in the northern Amdo County, whereas the areas with excellent and good quality grades were mainly distributed in the central-western and southeastern Nagqu areas. On the temporal scale, the ecological environment of the study area as a whole showed an improvement trend over 32 years, and the vegetation cover in the central-western and southeastern areas increased significantly, which had a strong improvement effect on the ecological environment. The improvement area was 1 425.98 km2, accounting for 99.82%. The mean value of SRSEI was 0.49, with an overall fluctuating upward trend and an average increase of 0.015 7 a-1. ③ The land use pattern was the most driving influence factor in the change of ecological environment quality in the study area, with an average q value of 0.157 6 over multiple years, and the influence of environmental factors was low. The multi-factor interaction results showed that the ecological environment in the study area was the result of multiple factors acting together, all factors had synergistic enhancement under the interaction, the influence of human factors was gradually increasing, and the interaction of the net primary productivity (NPP) of vegetation and land use pattern was the main interactive control factor of ecological environment quality in the study area. This study can provide a theoretical basis for ecological environmental protection and sustainable development along the Nagqu to Amdo section.

Spatially Explicit climate change vulnerability assessment of ecological systems along altitudinal gradients in the Indian Himalayan region

Spatial ecological vulnerability assessments are important for devising management plans for ecological systems to maintain the flow of ecosystem services, especially in the mountains. Himalayan mountains, being a fragile ecosystem, have considerable ecological value, however, information on ecological vulnerability is lacking. The present evaluation attempts to prioritize ecosensitive zones by assessing the altitudinal ecological vulnerability of Garhwal Himalaya, India by devising a framework using a mix of bio-physical parameters. Eight bio-physical parameters, viz., Land Use and Land Cover (LULC), slope, aspect, landscape fragmentation, temperature, precipitation, soil moisture, and Normalized Difference Vegetation Index (NDVI)) were identified and considered to assess vulnerability. Spatial Principal Component Analysis (SPCA) results in five Principal Components (PCs), which were integrated and weighted for the calculation of the Ecological Vulnerability Index (EVI). The analysis results differential vulnerability across the altitudes with above 2000m altitude showed severe vulnerability and classified as potential vulnerability (36.25 %), slight vulnerability (35.25 %), medium vulnerability (20.25 %), high vulnerability (8.25 %) and severe vulnerability (0.25 %). The vulnerable regions were prioritized based on their ecological vulnerability as per the classes viz., region of strict protection (24.70 %), region of focal protection (60.41%) and region of composite development (14.89 %). The study suggetsed priority conservation and management actions for addressing the vulnerable areas for sustainable development of the region. The study provides valuable insights of vulnerability and associated protection measures leading to devising the most suitable management strategies for the sustainability of the ecological systems.

[Spatial-temporal Evolution and Driving Factors Analysis of Ecological Environment Quality in Daihai Basin based on AWRSEI].

Watersheds are an important ecological security barrier and social and economic development area. In order to evaluate the ecological environment quality of arid and semi-arid watersheds more objectively and accurately, based on the remote sensing ecological index (RSEI), the salinity index was introduced to construct a remote sensing ecological index (AWRSEI) suitable for arid and semi-arid watersheds, and the Daihai watershed was taken as an example to analyze its applicability. Based on the AWRSEI model, four phases of Landsat TM/OLI composite images were used to quantitatively evaluate the ecological and environmental quality of the Daihai Basin from 2001 to 2020. The spatio-temporal evolution of the ecological and environmental quality of the Daihai Basin was analyzed using the coefficient of variation and spatial autocorrelation, and the cause analysis and driving factor explanation power analysis were carried out using geographic detectors. The results showed that:① the average correlation coefficient between AWRSEI and various ecological factors was 0.860, which was more representative than that of a single index component. The load positive and negative values and ranking of the first principal component were consistent with those of RSEI, the contribution rate of eigenvalues was 3.69% higher than those of RSEI, and the evaluation results were closer to the real surface conditions, which is suitable for the ecological environment quality assessment of arid watersheds. ② The annual average of the AWRSEI index in the Daihai Basin from 2001 to 2020 was 0.427, which indicated a poor ecological environment quality basis. During the study period, the average of AWRSEI showed a fluctuating trend and reached the highest value of 0.502 in 2020. The overall ecological environment quality improved significantly, the deterioration area decreased by 20.51%, and the improvement area increased by 12.71%. In terms of spatial distribution, the ecological environment quality of forest land in the southern and northwestern high-altitude areas of the Daihai Basin was good, whereas that in the northern and southern mid-altitude areas was poor, and that in the northern area was better than that in the southern area. ③ The average variation coefficient of AWRSEI in the Daihai Basin was 0.280, the ecological environment quality was stable, and the overall change fluctuation was small; the high fluctuation was mainly concentrated in the southern part of the lake and the residential area. There was a significant spatial autocorrelation in the ecological environment quality of the Daihai Basin, and the high-high agglomeration area was mainly distributed in the forest area at high altitude and the cultivated land area at low altitude. Low-low concentration areas were scattered in the middle altitude area. ④ The improvement of the ecological environment in Daihai Basin from 2001 to 2020 was mainly due to the increase in NDVI and the decrease in NDBSI and NDSI. NDVI and NDBSI were the combination with the strongest interaction and the strongest interpretation of the ecological environment. Land use was the dominant factor of AWRSEI and had the strongest explanatory power. The combination of land use and meteorological factors was the strongest interaction, and the relationship between each driving factor was enhanced.

Spatiotemporal Changes and Driving Analysis of Ecological Environmental Quality along the Qinghai–Tibet Railway Using Google Earth Engine—A Case Study Covering Xining to Jianghe Stations

The Qinghai–Tibet Railway is located in the most fragile and sensitive terrestrial ecosystem of the Qinghai–Tibet Plateau in China, and once the ecological environment is damaged, it is difficult to restore. This study, based on the Google Earth Engine platform, focuses on the section of the Qinghai–Tibet Railway from Xining to Jianghe. It utilizes Landsat series satellite imagery data from 1986 to 2020 to calculate the Remote Sensing Ecological Index (RSEI). This approach enables large-scale and long-term dynamic monitoring, analysis, and assessment of the ecological changes along the Qinghai–Tibet Railway corridor. The results indicate that (1) the average RSEI of the study area increased from 0.37 in 1986 to 0.53 in 2020, showing an overall trend of improvement. The ecological environment quality is mainly categorized as medium and good. (2) The quality of the ecological environment in the areas along the railway experienced fluctuations during different periods of railway construction and operation. From 1986 to 1994, after the first phase of the railway opened, the overall ecological environment showed a relative decline in quality. From 1994 to 2002, the ecological quality of 60% of the region saw slight improvements. During the extension construction of the second phase of the railway from 2002 to 2007, the regional ecology fluctuated again. However, from 2013 to 2020, during the operational period, a stable recovery trend was observed in the ecological environment. (3) The ecological environment in the study area is influenced by multiple factors. Different railway station areas exhibit strong spatial heterogeneity. The impact of single factors is significant, with the existence of spatial stratification and enhanced interactions among multiple factors. The strongest interactive effects are observed between land use types, the intensity of human activities, and temperature.