Ecosystem Health Index Research Articles

Improvement of water quality through coordinated multi-trophic level biomanipulations: Application to a subtropical emergency water supply lake

Artificial emergency water source lakes have been built in most cities in the middle and lower reaches of the Yangtze River, China, to ensure water safety for residents. However, these new ecosystems are prone to algal blooms or other degraded water quality conditions. A newly built water supply lake in the lower reaches of the Yangtze River was selected as a model system to test whether the coordinated manipulation of fish and submerged macrophyte communities could enhance ecosystem function and quality. The coordinated manipulations spanned a five-year period, aiming to enhance both top-down and bottom-up control of phytoplankton. As a result of these manipulations, the catch per unit effort of small-bodied zooplanktivorous fishes decreased by >95 % from year two and remained low. The coverage and biomass of submerged macrophytes increased year by year. Water transparency increased from 1.07 to 3.33 m. Total phosphorus and total nitrogen showed a decreasing trend (not significant though). The annual mean biomass of Cyanophyta, Chlorophyta and Bacillariophyta decreased from 2.99 to 0.03 mg/L, 3.90 to 0.16 mg/L, and 3.50 to 0.3 mg/L, respectively. The biomass of phytoplankton in different groups decreased in all four seasons. The annual mean biomass of Cladocera and Copepoda remained low. The biomass of Cladocera and Copepoda decreased in summer, fall, and winter. The Ecosystem Health Index - increased from 15.9 to 32.0. The pros and cons of the various top-down and bottom-up control measures employed are discussed. This research presents a valuable case study on the enhancement of ecosystem structure and function in newly constructed emergency water supply lakes and offers insights into the restoration of other subtropical shallow lakes.

Integrating ecosystem stress into the assessment of ecosystem health in karst areas and exploring its driving factors

Accurately evaluating the degree of ecosystem health and comprehending its drivers are of crucial importance for ecosystem management and restoration in fragile ecoregions. Adopting an ecosystem stress perspective, this investigation scientifically diagnosed ecosystem health in Guizhou Province, a typical karst fragile ecological area, by developing a “Vigor-Organization-Resilience-Stress” (VORS) regional ecosystem health assessment framework. The principal driving factors and their spatio-temporal heterogeneity influencing ecosystem health in karst regions were investigated using geographic detectors and geographically and temporally weighted regression. Our findings indicated that: (1) The ecosystem health in Guizhou province presents a spatial distribution pattern of lower in the western region and higher in the eastern region, and the average ecosystem health index (EHI) in 2000, 2010 and 2020 is 0.194, 0.246 and 0.254 respectively, indicating that the overall ecosystem health level in Guizhou province has improved with the passage of time. (2) The spatiotemporal variation of ecosystem stress in Guizhou Province is substantial; the pressure associated with land use is projected to increase, whereas the intensity of stress attributed to rocky desertification and soil erosion is anticipated to diminish over time. (3) The primary determinants influencing the health of ecosystems in karst environments are the social and economic elements. These factors progressively amplify their effect on ecosystem health as time passes. The new assessment framework we have established includes ecosystem integrity and ecological threats faced by the ecosystem, which provides a new perspective for understanding the complex internal characteristics of karst areas and the coupling relationship between human and natural ecosystems. The results of this study can provide scientific reference for land use and ecological management policies in fragile ecological areas.

Ecosystem health assessment of East Kolkata Wetlands, India: Implications for environmental sustainability

The East Kolkata Wetlands (EKW) in Kolkata, India, span 12,500 ha and are a vital ecological zone providing several benefits, including water purification, flood control, and biodiversity support. This study investigated land use and land cover (LULC) alterations in the EKW from 1991 to 2023, using a random forest (RF) machine learning model. Significant LULC changes were observed over the 32 years, with wetland areas decreasing from 91.2 km2 in 1991 to 33.4 km2 in 2023, reflecting substantial habitat loss and reduced ecosystem services. Conversely, agricultural land expanded from 27.8 km2 to 58.7 km2, driven by economic and food production needs, and built-up areas increased dramatically from 0.2 km2 to 10.5 km2, indicating rapid urbanization. This study evaluated the health, resilience, and ecosystem functionality of EKW by analysing human-induced land use changes and using ecological indicators and landscape metrics. Landscape and class level metrics such as PLAND, largest patch index (LPI), total edge (TE), edge density (ED), number of patches (NP), and patch density (PD) were used to analyse the spatiotemporal dynamics of the wetlands. This study revealed a significant increase in fragmentation, with the number of patches increasing from 2689 in 1991 to 4532 in 2023, despite a consistent decrease in core wetland areas. Ecosystem health indicators, such as the ecosystem structure index (ESI) and landscape deviation degree (LDD), were used to assess landscape metrics and fragmentation changes. The ESI and other metrics revealed significant temporal fluctuations, providing insights into landscape structure, connectivity, and heterogeneity. The ESI improved from 0.87 in 1991 to 1.03 in 2023, indicating enhanced connectivity and diversity. Conversely, the LDD increased from 20.6% to 56.85%, indicating a shift towards impervious surfaces. The vegetation productivity and ecosystem health index (EHI) decreased, indicating biodiversity loss and reduced carbon sequestration. The EHI also dropped from 0.67 to 0.55, signifying ongoing environmental stress. This study emphasizes the need for conservation efforts to maintain the ecological integrity of the EKW amidst urbanization and land use changes and recommends a balanced approach for sustainable urban development and enhanced wetland resilience.

Integrating key ecosystem services to study the spatio-temporal dynamics and determinants of ecosystem health in Wuhan’s central urban area

The central areas of many Chinese cities have experienced large-scale urbanization in recent decades, a trend that is affecting the quality of life of residents and posing challenges to the sustainable development of urban ecosystems. Hence, it is vital to conduct assessments of urban ecosystems’ health conditions to ensure their sustainability. In this study, the spatial and temporal dynamics of ecosystem health in the central city of Wuhan were analyzed using the Vigor-Organization-Resilience-Service (VORS) model. The sensitivity of ecosystem health at different scales was also investigated using hierarchical health assessment delineation and random forest regression methods. The results showed that the composite index of ecosystem health has been declining since 2000, highlighting the negative impacts of shrinking ecological space, declining service capacity and urban expansion. Health zoning divides areas into five categories. Meanwhile, the health zones are located in areas of dense shrubs, cropland and water bodies on the edge of the central city, while the weak zones are mainly in the core of the city, which is 99.33 % impervious surface. The main factors influencing ecosystem health, including impervious surface area, water bodies and topography, vary from region to region. The study proposes targeted ecological management strategies for different health zones in Wuhan, emphasizing ecosystem protection and providing guidance for sustainable urban development.

The dominant role of human activity intensity in spatial pattern of ecosystem health in the Poyang Lake ecological economic zone

Human activities are the main factors threatening ecosystems, and ecological management should place a strong emphasis on guiding their positive development. More targeted and differentiated ecological preservation strategies can be proposed with research on the regional variability of the interaction between ecosystems and human activities. Utilizing the Vigor-Organization-Resilience-Services (VORS) model and the land surface human activity intensity model, the ecosystem health index (EHI) and human activity intensity (HAI) of the Poyang Lake Ecological Economic Zone (PLEEZ) were evaluated, respectively. Furthermore, their spatial association was investigated using spatial autocorrelation analysis, and the effect of HAI on EHI was analyzed using Geographic Detector and Geographic Weighted Regress. The results revealed that in the PLEEZ, (1) The zones of intensified human activity were highly consistent with the expansion of built-up land, and the EHI here has always been the lowest; (2) The HAI and EHI showed a significant and increasing spatial negative correlation, manifested as high HAI with low EHI clustering in the central plains and the adverse in the peripheral mountainous areas. (3) The HAI has the highest explanatory power on the spatial pattern of EHI, and its influence was greatest at the lower EHI. (4) Natural ecosystems with high EHI were highly sensitive to HAI, while areas with low EHI were less sensitive. The research can offer theoretical guidance for ecological construction in the future. The adverse effects of human activities in PLEEZ can be reduced through strict regulation of natural ecological sources, intensive utilization of human gathering areas, and promotion of green production and lifestyle.

Evaluating and diagnosing ecosystem health of the “three-lake” watershed in Yuxi, Yunnan, China from 2010 to 2020 by PSR-KDE

To carry out the diagnosis and evaluation of the ecosystem health in Yuxi three-lake watershed, this paper presents the changing trend of its health state, and predicts the future development. This also provides ideas for maintaining the regional ecosystem health, and then gradually improves the ecological environment quality. Taking Fuxian Lake, Qilu Lake and Xingyun Lake (the three-lake watershed) in Yuxi City, Yunnan Province, Southwest China as the research object, a model combining pressure-state-response and kernel density estimation (PSR-KDE) adopts to diagnose and evaluate the ecosystem health of the "three lake" watershed from 2010 to 2020, and the distribution map of ecosystem health index has obtained by the evaluation indexes integration based on GIS spatial analysis. Hence, the evaluation results have visualized on the map. The results show that: The distribution of ecosystem health index in the study area was 0.1530–0.7045 in 2010, 0.2056–0.7512 in 2015, and 0.2248–0.7662 in 2020. 0.12% was in the pathological area in 2010. After 2015, the pathological condition of ecosystem health has completely solved, and the proportion of unhealthy ecosystems was 11.95% in 2010, 7.38% in 2015, and 5.97% in 2020. The ecosystem health index of the study region was 0.5523 in 2010, 0.5807 in 2015, and 0.5815 in 2020, it indicates that the ecosystem was in a sub-health state. From 2010 to 2020, the ecosystem health around Qilu Lake was the most worrying, followed by the northwest of Fuxian Lake and the northern and southern regions of Xingyun Lake. The ecosystem health of the three-lake watershed showed significant improvement from 2010 to 2020. The study ecosystem health assessment and early warning in the three-lake watershed is significant to the ecological environment protection and management of the plateau lake basin, the restoration of the territorial space ecology and the economic development of the surrounding area.

Estimation of aquatic ecosystem health using deep neural network with nonlinear data mapping

Estimation of aquatic ecosystem health indices can assist in reducing the burden of time-consuming, labor-intensive, and cost-effective fieldwork for the sustainable evaluation of freshwater ecosystem status. In this study, we developed a deep neural network to estimate the trophic diatom index (TDI), benthic macroinvertebrate index (BMI), and fish assessment index (FAI) using water quality and hydraulic and hydrological data. A convolutional neural network (CNN) model was built to estimate health indices. In addition, an autoencoder was adopted to produce manifold features that were used as inputs for the CNN model. Conventional machine learning models, including artificial neural networks, support vector machines, random forests, and extreme gradient boosting, have been developed to estimate the TDI, BMI, and FAI. The results showed that the CNN with an autoencoder exhibited the best performance, with validation accuracies of Nash Sutcliffe Efficiency (NSE) and root mean squared error (RMSE) values of 0.592 and 17.249 for TDI, 0.669 and 12.282 for BMI, and 0.638 and 13.897 for FAI, respectively. The autoencoder enhanced the nonlinear feature learning of the time series and static input data, which contributed to improving the CNN feature extraction for accurate estimation of aquatic ecosystem health indices compared to other data-driven approaches. Therefore, deep learning techniques can be used to investigate aquatic ecosystem health by successfully reflecting the quantitative and qualitative features of health indices.

Ecosystem health assessment using multi-criteria approach in a forested ecotone area in northwest Iran

Assessing and monitoring ecosystem health are critical components of ecosystem management as they provide information on natural resource destruction and the causes and factors leading to it. The need for comprehensive and multidimensional indices for assessing and predicting the status of ecosystems has become increasingly important. The ecosystem health index (EHI) was calculated by assessing multiple criteria, including vigor, organization, and resilience criteria, in an ecotone ecosystem in Ardabil province. Different weighting approaches were used to evaluate the index value, and sub-watersheds were prioritized based on the index weighting. The EHI values varied among the studied sub-watersheds, ranging from 0.32 to 0.79, depending on the weighting method. Sub-watershed SW1 had a higher health status with a value of 0.77 compared to other studied sub-watersheds in the Iril watershed, while SW5 had a lower health status with a value of 0.34 in the equal weighting approach. The average value of the EHI for all studied sub-watersheds in the Iril watershed was found to be 0.50, indicating a relatively undesirable ecosystem health status. The EHI is a useful tool for prioritizing areas and an effective step in ecosystem management, considering the multidimensional nature of the index and the factors affecting ecosystem restoration or destruction. Assessing the extent of ecosystem degradation across various regions depends on the health status of the studied ecosystem, the feasibility of index calculation, and may involve different selection criteria.

Post-Restoration Monitoring of Wetland Restored from Farmland Indicated That Its Effectiveness Barely Measured Up

In the context of wetland restoration, the reconstruction of an ecosystem’s structure typically manifests within a relatively short timeframe, while the restoration of its function often necessitates an extended period of time following the implementation of restoration measures. Consequently, it becomes imperative to engage in the comprehensive, long-term dynamic monitoring of restored wetlands to capture timely information regarding the ecological health status of wetland restoration. In this paper, we aimed to precisely assess the ecosystem health of a typical wetland that had been converted from farmland to wetland in Fujin National Wetland Park in 2022. We selected 18 ecological, social, and economic indicators to establish a wetland ecological health evaluation model, and then used the method of an analytic hierarchy process (AHP) to calculate the weights for each indicator and acquire the ecological health index (EHI) score. The results of our study revealed that the ecosystem health index was 3.68, indicating that the FNWP wetland ecosystem was in “good” condition; this result was mainly affected by wetland water quality (0.382). The ecological health assessment of restored wetlands can monitor wetland ecological resources and provide a scientific basis for the management and protection of restored wetlands.

Chinese urbanization promoted terrestrial ecosystem health by implementing high‐quality development and ecological management

AbstractHigh‐quality urbanization and a healthy ecosystem are both the material basis for sustainable social development. However, the tie between terrestrial ecosystem health (TEH) and urbanization is still unclear. Therefore, we assessed the spatial and temporal dynamics of urbanization and TEH at 368 cities in China from 2000 to 2020, then explored their spatial interaction and driving mechanisms by spatial autocorrelation analysis and structural equation modeling. The results showed: (1) China's comprehensive urbanization index (UI) improved from 0.08 in 2000 to 0.10 in 2020, contributing by some national urban agglomerations such as Beijing‐Tianjin‐Hebei, Yangtze River Delta, and Pearl River Delta. (2) China's terrestrial ecosystem health index (EHI) also increased from 0.67 to 0.68. Ecosystem vigor improved significantly, while ecosystem organization and resilience both decreased. (3) EHI and UI appeared to be locally spatially dependent, and path dependence was presented at municipal scales. (4) At the national scale, urbanization positively relates to EHI, which was enhanced by social, economic, and topography factors. The dominant drivers on EHI varied among regions, and urbanization improved EHI in all regions except for the southwest. Our study demonstrated that urbanization would promote TEH by implementing high‐quality development and ecological management simultaneously, providing theoretical support for urban sustainable development and ecological management.

Exploring coordinated development and its driving factors between carbon emission and ecosystem health in the southern hilly and mountainous region of China

Achieving “carbon neutrality” is an inevitable requirement for tackling global warming. As one of the national ecological barriers, the southern hilly and mountainous region (SHMR) shoulder the important mission of taking the lead in achieving “carbon peak” and “carbon neutrality”. Thus, it has important scientific significance to explore and analyze how to coordinate ecological development under the background of “double carbon action”, and it is a key step to ensure that the region achieves synergistic development of promoting economic development and improving ecosystem health. Therefore, in this study, we aimed to address these gaps by adopting a refined grid scale of 10 km × 10 km to explore the spatial-temporal distribution characteristics of carbon emissions and ecosystem health. Additionally, we established a coupling coordination model of carbon emissions intensity (CEI) and ecosystem health index (EHI) to assess the impact of natural and socio-economic factors on the coupling coordination degree (CCD) in different regions. Our findings are as follows: 1) In the SHMR region, the EHI exhibited a progressive development trend, with spatially increasing values from the south to the north. 2) The spatial discrepancy in CEI has been on the rise, which assumed an increase of 4.69 times, and with an increasingly pronounced pattern of spatial imbalance. Carbon emissions tend to concentrate more in the eastern and northern areas, while they are comparatively lower in the western and southern regions. 3) The R2 of geographical weighted regression model (GWR) is all above 0.8, and the CCD between CEI and EHI demonstrated a positive developmental state. However, most regions still displayed an imbalanced development, albeit with a slight increase in areas exhibiting a more balanced development state. 4) The driving forces of natural and socio-economic factors had a dual-factor and non-linear enhancement effect on the CCD. The influence of natural factors on CCD has gradually diminished, whereas the influence of socio-economic factors has progressively strengthened.

Ecosystem health risk assessment of lakes in the Inner Mongolian Plateau based on the coupled AHP-SOM-CGT model

The ecosystem health risk assessment of lake basins can provide a crucial foundation and support for the sustainable development of ecosystems in the arid regions of northern China. This study adopts the Driver-Pressure-State-Impact-Response (DPSIR) framework to select evaluation indicators, and utilizes a coupled model of the Analytic Hierarchy Process (AHP)-Self-Organizing Mapping Neural Network Algorithm (SOM)-Combinatorial Game Theory Algorithm (CGT) to determine the weight values of each indicator, and ultimately calculate the Ecosystem Health Index (EHI) of a typical lake basin from 1990 to 2020. AHP and SOM are employed to determine the subjective and objective weights of the evaluation indicators, respectively. While, the CGT is used to establish a balance between these two weights. This ensures that the final weight values embody both the subjective preferences of the decision-makers and the objective characteristics inherent in the data. The calculations show that the EHI of the basin fluctuated from a healthy state (69.8) in 1990 to a sub-healthy state (47.0) in 2020, although the dominant factors influencing EHI varied across different stages, the decline in the Driver and Impact health indices emerged as the primary reason for the decrease in EHI. Before 2009, driven by socio-economic development, the area of irrigated land and water withdrawals in the basin increased significantly, which led to an increase in ecosystem pressures, resulting in a rapid decrease in EHI. After 2009, the increase in per capita water resources and water-saving irrigation facilities reduced the pressure on the ecological system. the increased ecological water use and afforestation area improved the ecosystem’s status, leading to an increase in the vegetation cover within the basin and a gradual upward trend in EHI.

Trophic functioning of a small, anthropogenically disturbed, tropical estuary

A trophic model was constructed for the Poonthura Estuary, a small, anthropogenically impacted estuary along the south-western coast of India. An Ecopath with Ecosim based trophic modelling approach, based on observations made between 2016 and 2020, revealed that the Poonthura Estuary had a low total system throughput (3044.2 t km-2 year-1), low ascendancy (15%), high Finn’s cycling index (17.9%), low primary production/total biomass (5.2 t km-2 year-1), high mean transfer efficiency (12.4%), and low eco-exergy (14,455.46 gm detritus equivalent m-2). These values indicated that the estuary is an immature, less organized, and unhealthy system. The evaluation of Ecological Network Analysis, and ecosystem health indices revealed that the ecological structure and functioning of the estuary are impaired to a large extent from multiple anthropogenic stressors. The Poonthura Estuary trophic model revealed the total primary production/respiration value as 0.46, indicative of the massive pollution that the system is subjected to, particularly from organic sources. Small benthic carnivores were the most important keystone groups recorded from the Poonthura Estuary, despite their low biomass. The comparison of ecological indices of Poonthura Estuary, with those recorded for other small estuaries from various geographical locations, suggested dissimilar trophic functioning and food web structures from estuaries with similar physical features. Our study is a pioneering step to reveal the ecosystem status and functioning of small, anthropogenically disturbed estuaries, besides offering theoretical and scientific basis for the management, supervision and restoration of the Poonthura Estuary as well as other small estuaries, around the world.

Ecosystem health assessment and approaches to improve Sichuan Province based on an improved vigor organization resilience model

Ecological degradation is a global issue that seriously threatens sustainable human development, and the evaluation of ecosystem health (EH) is the primary condition for regional ecological restoration work. In this study, we optimized the classic vigor organization resilience (VOR) model and analyzed the spatial distribution pattern of the ecosystem health index (EHI) in Sichuan Province in 2020 and 2005. We determined the land spatial ecosystem restoration zone (ESZ), ecological degradation zone (EDZ), and ecological improvement zone (EIZ) in Sichuan Province. The results indicate that (1) the kappa values of the VOR models for 2020 and 2005 were 33.84 and 32.74, respectively, which were below 100. (2) The ranges of EHI values in Sichuan Province in 2020 and 2005 were 0.238–0.892 and 0.218–0.896, respectively. (3) The areas of EDZ and EIZ were 41781.84 and 26032 km2, accounting for 8.58 and 5.35% of the total area of Sichuan Province, respectively. (4) The total area of the ESZ accounts for 36.46% of that of Sichuan Province. This study is beneficial for eco-environmental management departments to develop ecological restoration strategies based on local ESZ, EDZ, and EIZ.

Spatiotemporal Relationships between Ecosystem Health and Urbanization on the Tibetan Plateau from a Coupling Coordination Perspective

A complex relationship exists between natural environmental and urban systems. This study focuses on the province of Qinghai, which is a major part of the Tibetan Plateau. For the period 1995–2020, we explore the relationships between ecosystem health and urbanization. We established an indicator system for ecosystem health and urbanization and quantitatively analyzed the spatiotemporal pattern of coupling coordination between the two. It shows that between 1995 and 2020, the urbanization level in Qinghai showed a continuous upward trend, with the urbanization index in 2020 increasing by 147.20% compared to 1995. The level of ecosystem health also showed an upward trend, with the ecosystem health index (EHI) value in 2020 increasing by 3.31% compared to 1995. The coupling coordination degree between ecosystem health and urbanization in Qinghai increased year-on-year. Areas with high coupling coordination between ecosystem health and urbanization basically overlapped with areas with high urbanization, and the area gradually increased during the study period. Locations with slightly unbalanced development were located on the periphery of high coupling-coordination areas, and that area expanded in the years covered in this study. The low coupling-coordination areas were located in the northwest and southwest of Qinghai, bounded by the Qinghai-Tibet Highway. These results can support the evaluation of ecosystem health and urbanization on the Tibetan Plateau and high-altitude river source areas similar to Qinghai in China and elsewhere, contributing to sustainable land use policy.

Effects of landscape patterns and their changes on ecosystem health under different topographic gradients: A case study of the Miaoling Mountains in southern China

Ecosystem health is an essential characterization of landscape pattern ecological effects, and refined analysis of the variability of landscape pattern changes on ecosystem health in mountainous areas is of great significance for the synergistic development of the mountainous Man-Earth systems. This study constructed a research framework for the ecological effects of landscape patterns based on the theory of landscape ecology and topographic gradient. Taking the Miaoling Mountains in China as an example, used spatial analysis techniques to analyze the process of landscape pattern changes from 2000 to 2020 and detected the response of ecosystem health to the changes in the landscape pattern by using rank correlation analysis. The study showed that: (1) The landscape pattern of the study area changed significantly during the study period, especially in the geographically disadvantaged areas, mainly showing an expansion of the landscape scale of the forestland and a shift of the landscape dominance of the farmland to the gently sloping lowland areas. (2) The ecosystem was at an average health level (mean ecosystem health index (EHI) = 0.58), and the EHI showed a “V” shape dynamic since 2000. (3) The changes in landscape patterns significantly impacted ecosystem health, and the effect varies considerably across topographic gradients, with the landscape shape index (LSI) and Shannon diversity index (SHDI) being the main factors influencing ecosystem health. This study emphasizes the importance of implementing regional and systemic landscape management strategies in the Miaoling Mountains according to local conditions and suggests four rational strategies, including zoning controls around the forestland and farmland. The study's results provide a valuable reference for defining key conservation areas and control indicators for regional ecological restoration in the Miaoling Mountains and for landscape management in mountainous regions worldwide.

Spatiotemporal Variation in Ecosystem Health and Its Driving Factors in Guizhou Province

Healthy ecosystems are crucial for sustainable regional development. The lack of spatial distribution patterns and driving factors of ecosystem health limited ecosystem management and urban planning. Understanding the spatiotemporal variation characteristics of ecosystem health and its driving factors can contribute to ecosystem management. Based on the “vigor–organization–resilience” (VOR) framework, this paper focuses on increasing ESs and forming an improved “vigor–organization–resilience–ecosystem services (VORS)” framework to evaluate the ecosystem health of Guizhou Province in 2010 and 2020. At the same time, we used the geographic detector model to investigate the driving factors of ecosystem health in the region. The results revealed the following: (1) The areas of forest land accounted for more than 52%. Simultaneously, farmland and forest land decreased, while construction land increased from 2010 to 2020. Construction land was mainly converted from forest land, grassland and farmland. (2) The level of ecosystem health in Guizhou Province spatially increased from northwest to southeast, with the central part exhibiting the lowest health level. The ecosystem health index (EHI) was mainly moderate, accounting for 78.32% and 83.80% in 2010 and 2020, respectively. (3) Among the 11 selected driving factors, the gross domestic product (GDP), general public budget revenue, annual average temperature, average annual precipitation, and night light index significantly affected ecosystem health. Our research refines ecosystem health research and the results will contribute to effective and precise decision-making in ecosystem management and the implementation of land use policies.

Use of remote sensing-based pressure-state-response framework for the spatial ecosystem health assessment in Langfang, China.

Land use/land cover changes are occurring at an unprecedented rate and scale because of the economic development that has jeopardized the ecosystem's health. Ecosystem health should be studied and monitored at spatiotemporal scale to promote sustainable development and ecological civilization. The goal of this study was to assess the spatial ecosystem health of Langfang at the city and administrative levels using city's regional characteristics. Remote sensing-based pressure-state-response (PSR) framework, analytical hierarchy process (AHP), and principal component analysis (PCA) were utilized for spatial ecosystem health index (SEHI) formulation, indicator weighting, and indicator selection in several epochs (1990, 2003, 2013, and 2021), respectively. SEHI was formulated by combining subindices of pressure, state and response. The spatial ecosystem pressure index (SEIP) identified that the pressure was increasing on the ecosystem. In contrast, the spatial ecosystem state index (SEIS) pointed out an improvement in the state of the ecosystem since 1990. The worst state of the ecosystem was observed for the year 2013. The spatial ecosystem response index (SEIR) indicated that the response of the ecosystem towards the exerted pressures and states remained variable; however, it was reasonably good in 1990. All the administrative units of Langfang were associated with a healthy score for the spatial ecosystem health index (SEHI) for 1990 (pre-industrialization epoch), while the SEHI significantly reduced in 2013 (industrialization epoch) however improved for the later epochs (circular economy and ecological civilization epoch). The SEHI was moderately healthy for Dachang, Dacheng, Guan, Guangyang, and Yongqing while relatively healthy for the remaining administrative units in 2021. SEHI identified that spatial health has been improving since 2003 though not reaching the 1990's level for Langfang. Therefore, efforts should be focused on minimizing pressure and stabilizing the state to improve the spatial ecosystem health of Langfang. The developed SEHI can assist policymakers in analyzing regional health, identifying development strategies, driving environmental restoration, and quantifying needed changes.

Effects of Long-Term (17 Years) Nitrogen Input on Soil Bacterial Community in Sanjiang Plain: The Largest Marsh Wetland in China.

Increased nitrogen (N) input from natural factors and human activities may negatively impact the health of marsh wetlands. However, the understanding of how exogenous N affects the ecosystem remains limited. We selected the soil bacterial community as the index of ecosystem health and performed a long-term N input experiment, including four N levels of 0, 6, 12, and 24 gN·m-2·a-1 (denoted as CK, C1, C2, and C3, respectively). The results showed that a high-level N (24 gN·m-2·a-1) input could significantly reduce the Chao index and ACE index for the bacterial community and inhibit some dominant microorganisms. The RDA results indicated that TN and NH4+ were the critical factors influencing the soil microbial community under the long-term N input. Moreover, the long-term N input was found to significantly reduce the abundance of Azospirillum and Desulfovibrio, which were typical N-fixing microorganisms. Conversely, the long-term N input was found to significantly increase the abundance of Nitrosospira and Clostridium_sensu_stricto_1, which were typical nitrifying and denitrifying microorganisms. Increased soil N content has been suggested to inhibit the N fixation function of the wetland and exert a positive effect on the processes of nitrification and denitrification in the wetland ecosystem. Our research can be used to improve strategies to protect wetland health.

A study on the dynamic evaluation of ecosystem health in the Yangtze river Basin of China

Healthy basin ecosystems are a key factor for guaranteeing the sustainable growth of regional economies and societies. Basin health assessments results are crucial for identifying the ecological environment’s current state and fostering the basin’s long-term development. This study includes the “management” aspect to the traditional “driving force-pressure-state-impact-response” model to develop the “driving force-pressure-state-impact-response-management” model. In this study, the health status of the ecosystem of the Yangtze River Basin was investigated from six different perspectives and multiple dimensions. Results show: (1) From 2010 to 2020, the ecosystem health index of the Yangtze River Basin exhibits a fluctuating upward trend with a level 3 ecological health status, which falls under the sub-health category. (2) Obvious spatial differences exist in the ecological health level of the upper, middle, and lower reaches of the Yangtze River Basin. Among them, the ecological health index in the downstream area increased from 0.4662 to 0.5546, showing a clear recovery trend. The ecological health index in the middle reaches decreased from 0.5338 to 0.4633 and then increased to 0.5304. The ecological health of the watershed first deteriorated and is now recovering. The ecological health index in the upstream area decreased from 0.5004 to 0.4822, showing a deteriorating trend. (3) Indicators of status and impact are the primary factors affecting the ecosystem health of the Yangtze River Basin, whereas indicators of management are declining. The findings provide a theoretical framework for government departments to create watershed management policies.