Ecological Conservation Policies Research Articles

Assessment of eco‐environmental changes along roads in the Qinghai‐Tibetan Plateau based on remote sensing data: A case study of the Sino‐Nepalese Transport Corridor

AbstractUnderstanding the evolutionary patterns of ecological quality in transport corridor areas and their driving mechanisms is essential for maintaining regional sustainable development. However, an integrated assessment of the ecology of plateau transport corridors is still lacking. This study focuses on the Sino‐Nepalese Transport Corridor (SNTC) and comprehensively evaluates the spatio‐temporal patterns and evolution of eco‐environmental quality from 2000 to 2021 based on remote sensing data and quantifies and explores the potential driving factors. The results indicate significant spatial heterogeneity in the eco‐environmental quality of the SNTC, with an overall bipolar “northeast‐southwest” distribution pattern. The area of poor and worse quality is the largest (32,471.75 km2), accounting for about 47.20% of the total area of the SNTC, distributed in the plateau bare land and the Yarlung Tsangpo River valley. From 2000 to 2021, the eco‐environmental quality showed an initial decline and then an increase, with a relatively gentle overall trend. The increase in the remote sensing ecological index in Region (I) from 0.314 in the first 10 years to 0.334 in the second 10 years, an increase of 6.37%, was mainly attributed to afforestation projects in the “One River and two tributaries Nature Reserve” region. The eco‐environmental quality of the SNTC is influenced by multiple factors including human activities, climate, and topography. Grazing intensity, population density, and digital elevation model are the main negative disturbance factors, while temperature, precipitation, gross domestic product, and afforestation areas promote eco‐environmental quality. In particular, afforestation projects partially offset the negative impact of human activities. These results will provide useful information for understanding the complex effects of human activities and natural factors on the eco‐environmental quality in the plateau transport corridor region and for formulating ecological conservation policies.

Has the Establishment of National Key Ecological Function Zones Improved Eco-Environmental Quality?—Evidence from a Quasi-Natural Experiment in 130 Counties in Sichuan Province, China

China’s National Key Ecological Function Zones (NKEFZs) currently represent the largest and most extensive ecological conservation policy in China, with one of the core objectives of this policy being to improve eco-environmental quality (EEQ). This study regards the establishment of NKEFZs as a quasi-natural experiment. Based on panel data from 130 counties in Sichuan Province from 2001 to 2021, a multi-period difference-in-differences (DID) model was employed to evaluate the impact of NKEFZ establishment on EEQ. The findings indicate the following: ① The establishment of NKEFZs can significantly enhance the EEQ of the covered areas, albeit as a gradual long-term process. This conclusion not only meets the parallel-trends assumption but also holds true in a series of robustness tests such as placebo tests. ② Mechanism analysis reveals that NKEFZs can enhance EEQ through the effects of optimizing land spatial allocation and upgrading industrial structure. ③ Heterogeneity analysis demonstrates that the beneficial effect of NKEFZs on EEQ varies across different functional zone types, geographic spaces and ethnic regions. Our study not only contributes to the accumulation of empirical evidence and institutional refinement in the sustainable implementation of ecological policies in China but also offers valuable insights and references for other countries in formulating policies for eco-environmental protection.

Analyzing the Spatiotemporal Dynamics and Driving Forces of Ecological Environment Quality in the Qinling Mountains, China

The Qinling Mountains serve as a vital ecological barrier for China, needing regular monitoring for sustainable progress. The present study analyzed the Qinling Mountains (sections in Shaanxi province) via the Google Earth Engine (GEE) and Landsat images, constructing a Remote Sensing Ecological Index (RSEI) for quantitatively analyzing the spatiotemporal evolution of the ecological environment quality from 1990 to 2020. Additionally, this study integrated geodetector and multiscale geographically weighted regression (MGWR) to discern the driving factors influencing ecological quality. The results indicated the following: (1) over the 30 years, the RSEI in the study area initially declined (1990–2005) and then began to improve (2005–2020), demonstrating an overall upward trend; (2) RSEI varied with topography: lower values corresponded to lower elevations (<1200 m) and gentle slopes (<10°), whereas higher values were linked to higher elevations (>1600 m) and steeper slopes (>20°); and (3) NDVI, DEM, land use, and the presence of protected areas emerged as the main driving forces of ecological quality. The interaction between ecological conservation policies and socioeconomic factors enhanced the explanatory strength for the differentiation in ecological environment quality. In conclusion, factors like increased vegetation cover and the establishment of protected areas have significantly promoted the improvement of ecological environment quality in the Qinling region, making this study a scientific reference for providing ecological environment protection and promoting high-quality development.

Understanding habitat isolation in the context of construction land expansion using an ecological network approach

ContextThe impact of construction land expansion on regional landscape sustainability received significant attention, but the habitat isolation caused by such expansion across the urban-rural continuum calls for a closer examination.ObjectiveThis study aims to use the ecological network approach to assess the isolation effect imposed by urban areas and rural settlements on habitat patches in the Nanjing Metropolitan Area during 2000, 2010, and 2020.MethodsWe first extracted the habitat patches by applying morphological spatial pattern analysis (MSPA), then identified the ecological networks based on the comprehensive resistance surface and circuit theory. Finally, we constructed two indices, the isolation effect index (IEI) and isolation degree (ID), and evaluated the differential contributions of urban areas and rural settlements to habitat isolation.ResultsOur results showed a total of 129 habitat patches within our study area. These patches were linked by 188, 186, and 183 ecological corridors in the years 2000, 2010, and 2020, respectively. Further analysis revealed that habitat patches were strongly isolated by the expansion of construction land and increasing human activities. Remarkably, both urban areas and rural settlements played pivotal roles in exacerbating this isolation, with urban areas showing a striking surge in their isolation impact, while rural settlements continued to be the predominant driver of habitat isolation.ConclusionsSustainable landscape planning should consider how land uses may cause habitat isolation. Our study utilizes the ecological network approach to evaluate habitat isolation and introduces applicable indicators for estimating the isolation effects attributed to construction land expansion. Our findings hold significant implications for informing landscape planning and shaping ecological conservation policies.

Scale effects and spatial heterogeneity of driving factors in ecosystem services value interactions within the Tibet autonomous region

Widespread land development, deforestation, and wetland degradation have disrupted the physical integrity and functional capacity of ecosystems, leading to a reduction in ecosystem service values (ESV). However, comprehensive research addressing ESV interactions that represent various ecosystem services from multifaceted angles is limited. Moreover, the relative significance and spatiotemporal diversity of natural and socio-economic variables influencing ESV demand further investigation. This study conducts both quantitative and qualitative assessments of the spatiotemporal dynamics and interrelationships of ESV in the Tibet autonomous region from 2000 to 2020. Geographical detector and geographically weighted regression models are applied to ascertain the relative importance and spatial heterogeneity of diverse ESV determinants. The findings reveal the following key insights: (1) Barren lands experienced the most substantial expansion from 2000 to 2020, indicating an exacerbation of desertification in the Tibet autonomous region. (2) Over the two decades, ESV exhibited an overall upward trajectory, with regulation of water flows, water bodies, and forests making the most significant contributions to ESV and its growth. (3) The quantitative and qualitative assessment of ESV interrelations has identified the number of trade-offs and synergies, along with spatial occurrences, offering a detailed foundation for the scientific management of ecosystems. Specifically, quantitative results portray ESV correlations as positive or negative, qualitative spatial mapping elucidates intricate local interactions among ESV. (4) The primary driver of ESV in the Tibet autonomous region is NDVI (0.072), with elevation following closely behind, underscoring the predominant influence of natural factors relative to socio-economic variables. This research serves as a scientific underpinning for the development of ecological conservation policies and the execution of ecological restoration initiatives.

Applying deep-learning enhanced fusion methods for improved NDVI reconstruction and long-term vegetation cover study: A case of the Danjiang River Basin

The Normalized Difference Vegetation Index (NDVI) is an essential metric in vegetation monitoring for remote sensing applications. While there are numerous long-term low-resolution NDVI datasets available there remains an unmet need for high-resolution NDVI reconstructions over extended time frames. Existing research has not comprehensively assessed the efficacy of various temporal fusion techniques for NDVI reconstruction at large regional scales. Traditional Spatiotemporal Image Fusion (TSTIF) methods often suffer from limited fusion accuracy due to input data quality constraints. To address these limitations this study introduces an innovative Deep Learning-Enhanced Spatiotemporal Fusion Method. Deep learning algorithms are employed to refine the spatial resolution of input data thereby facilitating the separation of complex image elements located at feature boundaries. This improved approach significantly enhances fusion accuracy as validated against five established TSTIF techniques through empirical analysis. As a case study we generate long-term Fractional Vegetation Cover (FVC) datasets to investigate the ecological dynamics of the Danjiang River Basin. Our findings reveal substantial gains in NDVI reconstruction accuracy through the incorporation of deep learning into traditional fusion techniques. Among the methods tested the STRUM algorithm showed the greatest improvement with its R2 value increasing from 0.872 to 0.894 and a consistent reduction in Root Mean Square Error (RMSE). The FSDAF technique emerged as the most effective boasting an R2 value of 0.953 and an RMSE of 0.012. These enhanced NDVI datasets provide more accurate representations of the basin's vegetation cover thus enriching long-term observational archives and facilitating further quantitative remote sensing analyses. Moreover we report a 21-year mean FVC of 0.702 for the Danjiang River Basin characterized by a “north-high south-low” distribution that varies seasonally. Improvements in vegetation cover were observed in Xichuan and Neixiang counties while environmental degradation is evident in the broader Danjiang River watershed. Key factors influencing these spatial variations include elevation and soil composition in addition to climate variables such as rainfall and temperature. Infrastructure projects like the South-to-North Water Diversion Project and targeted ecological conservation policies have also positively impacted vegetation within the basin.

Impact of grassland storage balance management policies on ecological vulnerability: Evidence from ecological vulnerability assessments in the Selinco region of China

The Selinco region is a highland grassland ecosystem with a unique lake system and diverse flora and fauna. However, it is highly vulnerable to degradation due to its high altitude and harsh climate. In recent years, the region has been subjected to increasing external pressures, including climate change, human activities, and natural disasters. Therefore, conducting an ecological vulnerability assessment is essential to ensure the sustainable development of the region. To achieve this, we performed a comprehensive integrated spatial principal component analysis (SPCA) of 12 representative ecological vulnerability indicators to assess the ecosystem of the region. This approach facilitated a comprehensive assessment of the ecological status of the region. Our study indicated that population and livestock density are the most important factors influencing environmental vulnerability. While the region has shown a trend of ecological recovery and stability over the past 20 years, some areas still experience ecological deterioration, emphasizing the importance of increasing efforts for to ecological conservation and restoration. Furthermore, we observed that different ecologically fragile areas have experienced varying degrees of transformation, underscoring the importance of more precise ecological conservation policies. At the county level, Nima and Shuanghu counties require focused attention and remedial measures to address severe ecological degradation, while other counties have demonstrated a trend towards ecological restoration, which could be attributed to the implementation of a balanced grass storage management policy that mitigates the impact of human activities. Therefore, further research is essential to determine the persistence of ecological trends and to identify long-term conservation and sustainable use solutions.

Discussion. Has the human population become a sentinel for the adverse effects of PFAS contamination on wildlife health and endangered species?

Global contamination with per- and polyfluoroalkyl substances (PFAS) poses a threat to both human health and the environment, with significant implications for ecological conservation policies. A growing list of peer-reviewed publications indicates that PFAS can harm wildlife health and that the adverse effects associated with PFAS exposure in wildlife are in concordance with human epidemiological studies. The correlation of cross-species data supports a unique perspective that humans can be regarded as a sentinel for PFAS effects in other species. The health harms due to PFAS are potentially most concerning for populations of endangered and threatened species that are simultaneously exposed to PFAS and other toxic pollutants, and also face threats to their survival due to habitat loss, degradation of ecosystems, and over-harvesting. Human epidemiological studies on the PFAS doses associated with health harm present a rich source of information about potential impacts on wildlife health due to PFAS. Our analysis suggests that national and international efforts to restrict the discharges of PFAS into the environment and to clean up PFAS-contaminated sites present an opportunity to protect wildlife from chemical pollution and to advance species conservation worldwide.

Major Role of Natural Wetland Loss in the Decline of Wetland Habitat Quality—Spatio-Temporal Monitoring and Predictive Analysis

Land use change significantly affects habitat quality, and the long time series exploration of dynamic variations in wetland habitat quality is of great significance to wetland conservation and management practices. Jingxin Wetland is located in the lower reaches of the Tumen River Basin, an important ecological function area in China. In recent years, under the influence of human activities and climate change, Jingxin Wetland has faced the threat of degradation and reclamation. This study investigated the dynamic evolution of habitat quality in Jingxin Wetland based on the CA-Markov model and the InVEST model at a long time scale and analyzed the drivers of habitat quality changes. Furthermore, habitat statuses under different policy orientations were explored using a multi-scenario development model. The results show that the total area of Jingxin Wetland exhibited a shrinking trend from 1964 to 2019, the wetland landscape was more fragmented, and the loss of natural wetland (marsh wetland) was serious. Consequently, wetland habitat quality has declined. According to scenario analysis, the study area should firmly follow the ecological conservation route in the future, through which the encroachment of human activities on wetlands can be effectively reduced and habitat conditions can be effectively improved. Both natural and economic development scenarios would result in the shrinkage of wetlands, which will extend the trend of declining habitat quality. It is noteworthy that the loss of wetland can be effectively reduced by implementing ecological conservation policies, which would reduce the degradation of wetland habitat quality. The results of this study can provide valuable references for wetland ecological conservation and ecological management practices.

Spatio-Temporal Variation and Prediction of Carbon Storage in Terrestrial Ecosystems in the Yellow River Basin

The accurate estimation of a regional ecosystem’s carbon storage and the exploration of its spatial distribution and influencing factors are of great significance for ecosystem carbon sink function enhancements and management. Using the Yellow River Basin as the study area, we assessed the changes in regional terrestrial ecosystem carbon storage through geographically weighted regression modeling based on a large number of measured sample sites, explored the main influencing factors through geographic probe analysis, and predicted the carbon sequestration potentials under different scenarios from 2030 to 2050. The results showed that (1) the total carbon storage in the Yellow River Basin in 2020 was about 8.84 × 109 t. Above-ground biological carbon storage, below-ground biological carbon storage, and soil carbon storage accounted for 6.39%, 5.07%, and 89.70% of the total ecosystem carbon storage, respectively. From 2000 to 2020, the carbon storage in the basin showed a trend in decreasing and then increasing, and the carbon storage in the west was larger than in the east and larger in the south than in the north. (2) Forest ecosystem was the main contributor to the increase in carbon storage in the Yellow River Basin. Elevation, temperature, and precipitation were the main factors influencing the spatial pattern of carbon storage. (3) The ecological conservation scenario had the best carbon gain effect among the four future development scenarios, and appropriate ecological conservation policies could be formulated based on this scenario in the future to help achieve the goals of carbon sequestration and sink increase.

Impact of ecological conservation policies on land use and carbon stock in megacities at different stages of development

Urban expansion, especially the construction of megacities, increases carbon emissions and adversely affects the carbon storage of terrestrial ecosystems. However, scientific land-use management policies can increase carbon storage. This study takes two megacities at different stages of development, Beijing and Tianjin, as examples to explore the impact of different ecological conservation scenarios on both urban land use and carbon storage to provide recommendations for the construction planning of large cities with low-carbon development as the goal. Furthermore, we coupled the patch-generating land use simulation (PLUS) model with the integrated valuation of ecosystem services and tradeoffs (InVEST) model to simulate land use and carbon storage under a natural development scenario, a planned ecological protection scenario (PEPS), and a policy-based ecological restoration scenario (PERS). From 2000 to 2020, both cities had different degrees of construction land expansion and carbon loss, and Tianjin's dynamic degree of construction land was 0.94% higher than Beijing's, with a carbon loss 183,536.19 Mg higher than Beijing's; this trend of reducing carbon reserves will continue under the natural development scenario (NDS). Under the PEPS and PERS, the carbon stock of both cities increases, and the impact on Tianjin is greater, with an increase of 4.51% and 8.04%, respectively. Under PERS, the carbon stock increases the most, but the dynamic degree of construction land use is negative for both cities. Beijing's carbon stock is 0.40% lower than Tianjin's, which deviates slightly from the trend of urban economic development. Megacities in the rapid development stage can refer to Tianjin, strictly following the ecological protection land planning scope and vigorously implementing ecological restoration policies to effectively increase regional carbon stock. Megacities in the mature stage of development can refer to Beijing, and flexibly implement ecological restoration policies to increase regional carbon stock without affecting the city's economic development.

Analysis of Spatial and Temporal Variations in Ecosystem Service Functions and Drivers in Anxi County Based on the InVEST Model

Background: Exploring the spatial and temporal evolution patterns of regional ecosystem service functions and their main drivers can provide effective support for formulating regional ecological conservation policies and coordinating sustainable economic–ecological development. Methods: This study quantifies the service functions of the water production, soil conservation, carbon storage, habitat quality, and net primary productivity (NPP) in the study area based on the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and the Carnegie–Ames–Stanford Approach (CASA) model and constructs a comprehensive index for ecosystem services (CES) based on the analytic hierarchy process (AHP) to reflect the total supply of various ecosystem services spatially and explore the main driving mechanisms of their spatial variation. The main driving mechanisms of the spatial variation were investigated. Results: (1) Water production in the study area from 2010 to 2020 showed a trend of increasing before decreasing, soil retention showed a trend of continuously decreasing, carbon storage and biotope quality showed a trend of decreasing before increasing, and the NPP showed a trend of continuously increasing. (2) The mean CES of the study area from 2010 to 2020 (0.5398, 0.5763, 0.5456) showed a trend of increasing before decreasing. The improvement areas were mainly concentrated in the western, southwestern, and northeastern parts of the study area, and the degraded areas were mainly distributed in the southeast and northwest. (3) The fit of the geographically weighted regression (GWR) was higher than that of the ordinary least squares (OLS) in all the periods, and the main driving factors affecting the spatial variation in the CES were the NDVI and tea plantation area (T-Area). Conclusion: This study constructed the CES model, explored the regional CES spatiotemporal evolution pattern and its main driving mechanism, and provided a reference basis for promoting the high-quality development of specialized tea regions.

Place-based policy and green innovation: Evidence from the national pilot zone for ecological conservation in China

This study examines the impact of the National Pilot Zone for Ecological Conservation (NPZEC) policy in China on green innovation (GI) using panel data from 282 Chinese cities during the period 2011-2019. Employing a difference-in-differences (DID) model, we find that the NPZEC policy positively influences GI, leading to a significant increase of approximately 23.98% in the number of green patents in cities where the policy is implemented. Mechanism tests reveal that the NPZEC policy enhances fiscal support and promotes economic agglomeration, thereby fostering GI. Heterogeneity analyses indicate that the NPZEC policy prioritizes quantity over quality, with a stronger impact observed in western cities, low administrative level cities, and cities with lower economic development. Additionally, our findings highlight that higher public environmental attention and stronger intellectual property (IP) protection enhance the promotion effect of the NPZEC policy on GI. Lastly, the findings indicate that the NPZEC policy has a negative impact on GI in neighboring cities. Our study provides empirical references for policymakers to scientifically implement place-based policies and effectively promote GI in the future.

Will short-term constraints affect long-term growth? Empirical analysis from the Beibu Gulf Mangrove National Natural Reserve of China

The capability approach has long been confined to a static, short-term framework, preventing it from truly providing normative guidance for enhancing multidimensional well-being and sustainable development. Human well-being cannot be seen as fixed, so there is an urgent need to assess the capability approach from a dynamic and long-term perspective. In this paper, the Beibu Gulf Mangrove National Natural Reserve of China was selected as a study area. A sustainable development perspective was integrated into a static capability approach theory framework, focusing on changes in capability approach with a dynamic, long-term gaze, and the impact of coastal zone ecological protection policies on farmers' multidimensional well-being was measured at spatial and temporal scales. The results indicate that ecological conservation policies reduce the level of capability approach of farm households in the short term. However, from a dynamic and long-term perspective, once the “pain period” is over, the capability approach can be continuously improved, achieving a win-win situation for both farmer well-being and ecological sustainability. This result also innovatively verified the core of the capability approach, which states that “freedom” under the capability approach framework is not unrestricted freedom, but restricted freedom. This will further expand and improve the relevant research of Sen's capability approach theory, and is also a beneficial exploration of combining Sen's capability approach theory with the Sustainable Development Goals. In order to solve the contradiction between peasant household welfare development and environmental protection, we need to explore a new scheme. The results of the study provide the government and policy makers with ideas for improving ecological protection policies, along with a more accurate and scientific basis for optimizing the multidimensional welfare compensation system to improve the feasibility and effectiveness of policy implementation.

Impact of Ecological Conservation Policy of Landscape Resources on the Behavior Intention of Stakeholders in Shennongjia National Park

Scenic resources are the essence of natural and human resources in national parks, and the effectiveness of conservation policy implementation is the key to achieving the ecological integrity, authenticity and typicality of national parks. Based on the research hypothesis of the relationship between "conservation behavior intention" and "conservation policy" of national park landscape resources proposed by Shennongjia National Park, this study establishes a second-order SEM, reveals the internal relationship between the conservation behavior intention and conservation policy of national park landscape resources, and puts forward the optimization path of the management and control path of national park landscape resources conservation through difference analysis. The research results show that national park landscape resource conservation policy has a significant positive impact on social norms, and directly affects conservation behavior intentions through social norms; Community residents are more concerned about the impact of conservation policies on their production and lifestyle, while tourists pay more attention to the ecological environment quality of landscape resources and the implementation of relevant policies such as recreational facilities. The management of legislation policy directly affects the existing way of scenic resources in Shennongjia National Park, and affects the establishment of community management and control mechanism and the behavior of community residents through social norms. This study puts forward the strategy of optimizing the national park landscape resource conservation policy in four aspects, namely, ecological environment sustainability, ecological conservation policy system, coordinated and orderly management and control mechanism, and joint construction of harmonious social relations.

Multiple pressures and vegetation conditions shape the spatiotemporal variations of ecosystem services in the Qinghai-Tibet Plateau.

Human activities and environmental change can impact the supply of ecosystem services (ESs) as pressures. Understanding the mechanisms of these impacts is crucial to support ecological conservation and restoration policy and applications. In this study, we highlighted the contribution of vegetation to mitigating these impacts on ESs in the Qinghai-Tibet Plateau (QTP) of China. First, we identified hot and cold spots of pressures from human activities and environmental factors and mapped the cumulative provision of five ESs (i.e., water yield, soil retention, carbon sequestration, habitat quality, and landscape aesthetics). Then, we clustered these ESs into five bundles based on their supply level. Furthermore, structural equation modeling was used to quantify the pathways of multiple pressures on ESs. The results indicated that 1) for 2000, 2010 and 2019, the percentages of hot spots with high pressure were 28.88%, 27.59% and 45.66% respectively, with significant spatial heterogeneity from northwest to southeast; 2) both regions with high and low cumulative ES values experienced increased volatility; and 3) the joint effects of multiple pressures shaped ESs through pressure-ES (direct) and pressure-vegetation-ES (indirect) pathways. Specifically, precipitation had the largest positive effect on regulating services (rα ≥ 0.76), and landscape fragmentation had the largest negative effect on cultural services (-0.10 ≤ rα ≤ -0.07). Vegetation played an important role in modulating multiple pressures on ESs. This study contributes to ecosystem management by effectively coping with anthropogenic and environmental pressures and sustaining the supply of ESs, particularly in alpine and plateau regions.

Molecular diet analysis enables detection of diatom and cyanobacteria DNA in the gut of Macoma balthica.

Detritivores are essential to nutrient cycling, but are often neglected in trophic networks, due to difficulties with determining their diet. DNA analysis of gut contents shows promise of trophic link discrimination, but many unknown factors limit its usefulness. For example, DNA can be rapidly broken down, especially by digestion processes, and DNA provides only a snapshot of the gut contents at a specific time. Few studies have been performed on the length of time that prey DNA can be detected in consumer guts, and none so far using benthic detritivores. Eutrophication, along with climate change, is altering the phytoplankton communities in aquatic ecosystems, on which benthic detritivores in aphotic soft sediments depend. Nutrient-poor cyanobacteria blooms are increasing in frequency, duration, and magnitude in many water bodies, while nutrient-rich diatom spring blooms are shrinking in duration and magnitude, creating potential changes in diet of benthic detritivores. We performed an experiment to identify the taxonomy and quantify the abundance of phytoplankton DNA fragments on bivalve gut contents, and how long these fragments can be detected after consumption in the Baltic Sea clam Macoma balthica. Two common species of phytoplankton (the cyanobacteria Nodularia spumigena or the diatom Skeletonema marinoi) were fed to M. balthica from two regions (from the northern and southern Stockholm archipelago). After removing the food source, M. balthica gut contents were sampled every 24 hours for seven days to determine the number of 23S rRNA phytoplankton DNA copies and when the phytoplankton DNA could no longer be detected by quantitative PCR. We found no differences in diatom 18S rRNA gene fragments of the clams by region, but the southern clams showed significantly more cyanobacteria 16S rRNA gene fragments in their guts than the northern clams. Interestingly, the cyanobacteria and diatom DNA fragments were still detectable by qPCR in the guts of M. balthica one week after removal from its food source. However, DNA metabarcoding of the 23S rRNA phytoplankton gene found in the clam guts showed that added food (i.e. N. spumigena and S. marinoi) did not make up a majority of the detected diet. Our results suggest that these detritivorous clams therefore do not react as quickly as previously thought to fresh organic matter inputs, with other phytoplankton than large diatoms and cyanobacteria constituting the majority of their diet. This experiment demonstrates the viability of using molecular methods to determine feeding of detritivores, but further studies investigating how prey DNA signals can change over time in benthic detritivores will be needed before this method can be widely applicable to both models of ecological functions and conservation policy.

Multi-Scenario Prediction of Landscape Ecological Risk in the Sichuan-Yunnan Ecological Barrier Based on Terrain Gradients

Land use changes induced by human activities change landscape patterns and ecological processes, threatening regional and global ecosystems. Terrain gradient and anthropogenic multi-policy regulation can have a pronounced effect on landscape components. Forecasting the changing trend of landscape ecological risk (LER) is important for national ecological security and regional sustainability. The present study assessed changes in LER in the Sichuan-Yunnan Ecological Barrier over a 20-year period using land use data from 2000, 2010, and 2020. The enhanced Markov-PLUS (patch-generating land use simulation) model was used to predict and analyze the spatial distribution pattern of LER under the following three scenarios. These were business-as-usual (BAU), urban development and construction (UDC), and ecological development priority (EDP) in 2030. The influence of terrain conditions on LER was also explored. The results showed that over the past 20 years, the LER index increased and then decreased and was dominated by medium and low risk, accounting for more than 70% of the total risk-rated area. The highest and higher risk areas for the three future scenarios have increased in spatial extent. The UDC scenario showed the largest increase of 3341.13 km2 and 2684.85 km2, respectively. The highest-risk level has a strong selectivity for low gradients, with high-level risks more likely to occur at low gradients. The response of ecological risk to gradient changes shows a positive correlation distribution for high-gradient areas and a negative correlation distribution for low-gradient areas. The influence of future topographic gradient changes on LER remains significant. The value of multiscale geographically weighted regression (MGWR) for identifying the spatial heterogeneity of terrain gradient and LER is highlighted. It can play an important role in the formulation of scientific solutions for LER prevention and of an ecological conservation policy for mountainous areas with complex terrain.

Exploring zonation strategy in land management of urban agglomeration

Land use/cover change (LUCC), especially of urban expansion, drives terrestrial carbon stock change in urban agglomeration. Due to the spatial heterogeneity of urban agglomeration, zonation supplies a possible way for land management in metropolises to achieve land use sustainability. In this study, we took Beijing-Tianjin-Hebei (BTH) region, known as the Capital Economic Zone, as an example and proposed a zonation strategy, as well as land management of each zone, to better adjust LUCC planning. BTH region was divided as Ecological Barrier (EB) zone, Potential Carbon Sequestration (PCS) zone and Potential Carbon Loss (PCL) zone, by evaluating topography, carbon storage and historic carbon stock change from 1990 to 2020. The EB zone was characterized as area of high carbon density, storing around 50% of carbon stock of BTH region. It experienced 52 Mt carbon stock loss from 1990 to 2020. PCL zone was characterized as area of high carbon stock loss of 122 Mt from 1990 to 2020. PCS zone was characterized as area of carbon stock increase by 7.23 MtC from 1990 to 2020. We analysed LUCC for each zone and found distinct drivers of carbon stock change. Based on zonation analysis, ecological engineering projects should continue in the PCS zone, leading to a carbon increase of 0.18 Mt C per year. Revegetation and strict ecological conservation policies were suggested to the EB zone, giving a potential of 58.9–186 Mt C carbon gain. Internal conversion between urban and rural construction land was proposed to the PCL zone, which can possibly achieve zero carbon loss of urban sprawl.

Ecological quality assessment and monitoring using a time-series remote sensing-based ecological index (ts-RSEI)

ABSTRACT Ecological quality assessment is fundamental to revealing changes in ecological environments before the development of effective ecological conservation policies. The complex ecological environment can be assessed more reliably when multiple remote sensing indices are integrated, such as in the use of the prevalent Remote Sensing-based Ecological Index (RSEI). However, for effective ecological quality assessment, the requirement of acquisition time consistency for images has become an outstanding issue for broadening the application of the RSEI. In this study, we adjusted the RSEI to the Continuous Change Detection and Classification (CCDC) algorithm that predicts synthetic images instead of real images. Based on this algorithm, we mapped time-series RSEI (ts-RSEI), which provide comparable results for tracing the dynamics of ecological quality at any time. Our major findings are as follows: (1) The RSEI is very sensitive to the timespan of the image acquisition dates, with the Mean Absolute Difference (MAD) of 0.111 (19.2%) when the interval between dates exceeds one month. (2) The ts-RSEI from synthetic images is comparable to the RSEI from real images, with the MAD of 0.075 (10.5%), which is superior to that of two real images with the timespan of half-a-month. (3) For Hangzhou, the ecological quality was maintained for almost the past 35 years (the ts-RSEI changed from 0.679 to 0.705). However, special attention should be paid to the spatial polarization between natural (“better”) and human-dominated (“worse”) environments. The high temporal consistency and the capability of any- time mapping of the ts-RSEI are expected to be of value to policy makers and authorities in implementing effective ecological conservation measures.