Landscape Pattern Changes Research Articles

Unveiling the Secrets: How Landscape Patterns Shape Habitat Quality in Northeast China Tiger and Leopard National Park

The Northeast China Tiger and Leopard National Park (NCTLNP) is a critical habitat for the endangered Amur tiger and Amur leopard, making it a global biodiversity hotspot. This study explores how changes in landscape patterns have influenced habitat quality in the park, aiming to develop strategies for enhancing biodiversity conservation and ensuring the park’s long-term sustainability. From 2012 to 2017, habitat quality in the NCTLNP experienced a significant decline; however, the launch of the national park pilot program in 2017 resulted in improvements, particularly in core protected areas, where habitat quality increased and landscape fragmentation decreased. These findings indicate that the national park initiative reduced the degradation of habitat quality. Key landscape metrics, especially the Shannon Diversity Index (SHDI), were found to significantly affect habitat quality. Additionally, the interaction between SHDI and landscape contagion (CONTAG) played a pivotal role in shaping habitat quality over time. Areas with high SHDI and low CONTAG showed declines in habitat quality, pointing to the need for focused conservation efforts. This study offers valuable insights for policymakers seeking to improve habitat quality through targeted landscape management practices.

Differences in Anthropogenic Impacts of Typical Mid- to High-Latitude Wetlands in the Heilongjiang Basin

Wetlands represent one of the three principal ecosystems and serve a vital function in the protection of water resources and the regulation of climate. However, wetlands are currently experiencing significant challenges, particularly in the agriculturally productive wetlands of the Heilongjiang River Basin, which have been considerably impacted by human activities. This study focuses on three representative wetlands situated within the Heilongjiang River Basin. This study analyses changes in wetland area and landscape patterns from 2002 to 2022, as well as the impact of agriculture and impervious surface expansion on the wetlands. The findings indicate that agricultural expansion is the primary driver of wetland area loss. The wetland area affected by agriculture demonstrates the most significant change, with the largest observed shift reaching 47.2%. The expansion of impervious surfaces was found to have a significant impact on wetland fragmentation, resulting in a notable decrease in wetland connectivity. This was evidenced by a reduction in the average patch size, which decreased by 14.68 ha over the decade from 2007 to 2017, a period during which impervious surfaces expanded. This paper identifies the distinctions in the influence of diverse human activities on wetland landscape patterns in the Heilongjiang Basin and employs natural samples for control, thereby attenuating the impact of the natural environment. This study offers a novel perspective on the processes of wetland change and the maintenance of wetland health, which is crucial for the realisation of clean water and sanitation (Sustainable Development Goal 6.6).

Impacts of land use and land cover change on the landscape pattern and ecosystem services in the Poyang Lake Basin, China

ContextDecades of intensifying human activities have led to drastic changes in land use and land cover (LULC) in the Poyang Lake Basin (PLB), resulting in significant changes in landscape pattern and ecosystem service value (ESV), thereby affecting regional sustainability.ObjectivesWe focused on understanding the impact of LULC changes on the landscape pattern and ESV of the PLB and used the Patch-generating Land Use Simulation model (PLUS) to predict LULC changes in 2050.MethodsWe evaluated landscape patterns using landscape metrics and calculated ESV using the ecosystem service equivalent factor method. The Pearson correlation coefficient was used to analyze the correlation between landscape patterns and ESV from 1990 to 2020. Then, we combined the PLUS model and the ecosystem service equivalent factor method to calculate the ESV under multiple scenarios from 2020 to 2050.ResultsFrom 1990 to 2020, the LULC of the PLB changed to varying degrees. The PLB has undergone a rapid process of landscape fragmentation, and the total ESV of the PLB has decreased. The total ESV was positively correlated with the CONTAG index and negatively correlated with the SHDI index. Between 2020 and 2050, the ESV of the PLB is projected to decrease under the NDS (nature development scenario) and EDS (economic development scenario) and increase under the EPS (ecological protection scenario).ConclusionsESV responded to changes in landscape pattern. We recommend that the PLB should increase patch connectivity. Additionally, future development in the PLB should prioritize ecological protection to prevent further declines in ESV.

Satellite Reveals a Coupling between Forest Displacement and Landscape Fragmentation across the Economic Corridor of the Eurasia Continent

Jointly building the Economic Corridor of the Eurasia Continent (ECEC), which is one of the most important parts of the Silk Road Economic Belt, is a pivotal initiative for fostering regional development. Forests, which serve as a green foundation of economic resilience, underpin this effort. However, there is an imbalance in ecological status due to differences in natural resources and the social economy along the economic corridor. This imbalance has led to alterations in landscapes, yet the specific changes and their underlying relationships are still much less understood. Here, we quantitatively detected changes in the forest landscape and its ecological efforts over the ECEC via widespread, satellite-based and long-term land cover maps released by the European Space Agency (ESA) Climate Change Initiative (CCI). Specifically, the coupling between changes in forest coverage and landscape patterns, e.g., diversity, was further examined. The results revealed that forest coverage fluctuated and declined over the ECEC from 1992 to 2018, with an overall reduction of approximately 9784.8 km2 (i.e., 0.25%). Conversions between forests and other land cover types were widely observed. The main displacements occurred between forests and grasslands/croplands (approximately 48%/21%). Moreover, the landscape diversity in the study area increased, as measured by the effective diversity index (EDI), during the study period, despite obvious spatial heterogeneity. Notably, this pattern of landscape diversity was strongly associated with forest displacement and local urban development through coupling analysis, consequently indicating increasing fragmentation rather than biological diversity. This study highlights the coupled relationship between quantitative and qualitative changes in landscapes, facilitating our understanding of environmental protection and policy management.

Assessment of the spatial-temporal impact of the Longhai Railway transportation corridor on land cover changes and landscape patterns

IntroductionTransportation corridors, as special economic corridors, have a greater impact on land cover and landscape pattern changes.MethodsTherefore, 10 buffer zones were established at 1 km intervals on both sides of the Longhai Railway as the centerline to trace the impact of the railroad corridor on the land use change and regional landscape pattern change of the cities along the line from 1985 to 2020.ResultThe results show that: (1) The land cover changes along the railroad corridor during the 35 years are mainly characterized by the conversion between cropland, grassland, and construction land. Compared with 1985, in 2020, the construction land increased by 161.96%, the grassland area decreased by 11.83%, and the cropland area decreased by 15.83%. (2) The fragmentation of land patches and vegetation coverage is negatively and positively correlated with the buffer zone distance, respectively. In the same year, the comprehensive land-use dynamic degree is smaller as it is further away from the railway. The nighttime light index in the buffer zone is significantly correlated with the land aggregation index and average patch area, and the closer to the railroad, the higher the land aggregation index of construction land. (3) In terms of zoning, the intensity of land cover and landscape pattern changes in the eastern section is higher than that in the western section, with a higher degree of land fragmentation and more agglomeration of construction land, and the transportation corridor has a greater impact on the change of integrated land use motives in this region. The results of the study can provide a scientific basis for optimising the spatial pattern of land and improving the ecological environment in the construction of cross-regional transport corridors.

Impact of landscape pattern changes on ecosystem service values in the Fenhe River Basin in China

The evolution of landscape patterns affects the supply of ecosystem services. It is important to explore the relationship between them to improve regional ecological stability and maintain ecological health. The Fenhe River is the second largest tributary of the Yellow River and it represents a fragile ecological environment. Our study aimed to analyze the impact of changes in landscape patterns on the value of ecosystem services (ESV) in the Fenhe River Basin (FRB). Land use data from 2000, 2010, and 2020 were used to extract landscape pattern indices. Methods such as ecosystem service value accounting, sensitivity analysis, correlation analysis, and geodetector modeling were employed to investigate changes in landscape patterns and ESV, and to identify the driving forces and impacts of these changes on ESV. The results showed that (1) from 2000 to 2020, the dominant landscape in the FRB was cultivated land, followed by forestland and grassland, which together covered 92% of the total area. (2) Over the past 20 years, the extent of landscape fragmentation had continued to increase and ecological function had deteriorated. (3) ESV had continued to decrease. The ESV provided by the regulating service function was the largest, accounting for over 49% of the total ESV. Support service function was second, accounting for over 34%. (4) The total ESV had a strong negative correlation with Shannon's diversity index (SHDI) and Shannon's evenness index(SHEI), a significant positive correlation with Contagion index (CONTAG). (5)The Human Activity Index (HAI) had a significant impact on changes in ESV, with an influence value of 0.6192, and its synergistic effect with NDVI further enhances this impact, achieving a synergy score of 0.71. Additionally, natural factors such as topography and climate also had significant effects on ESV changes.This study provides an evidence-based theoretical reference to guide the enhancement of the natural environment of the FRB and maintain highquality development of regional landscapes.

Spatiotemporal evolution of ecological environmental quality and its dynamic relationships with landscape pattern in the Zhengzhou Metropolitan Area: A perspective based on nonlinear effects and spatiotemporal heterogeneity

Understanding the spatiotemporal dynamics between landscape pattern changes and ecological environmental quality is essential for optimizing regional landscapes and improving the ecological environment. However, previous studies have certain shortcomings in understanding both aspects: On one hand, ecological environment assessments that overlook air quality may be misleading; On the other hand, the spatiotemporal driving mechanisms between landscape patterns and ecological environmental quality are still unclear. This study considers air quality information, refines ecological remote sensing indices, and employs the Random Forest-Multiscale Geographically and Temporally Weighted Regression (RF-MGTWR) analytical framework to reveal the nonlinear effects and spatiotemporal heterogeneity between landscape patterns and ecological environmental quality across the dimensions of aggregation, connectivity, and diversity. The results indicate:(1) ARSEI (Advanced Remote Sensing Ecological Index) is more suitable for assessing ecological environment quality in areas with air pollution compared to RSEI (Remote Sensing Ecological Index). (2) Ecological environmental quality is most strongly influenced by landscape connectivity, followed by diversity and aggregation. The driving effects of landscape aggregation, diversity, and connectivity will change around the values of 91, 0.64, and 80, respectively, all exhibiting complex nonlinear relationships.(3) Landscape patterns exhibit opposing trends in ecological benefits between urban centers and rural areas: In urban centers, landscape aggregation is negatively correlated with ecological environmental quality, while increased connectivity and diversity have positive effects; this is reversed in areas with good ecological conditions. As urbanization progresses, the positive impacts of landscape connectivity and diversity are enhanced, although the positive effects of diversity gradually diminish. (4) The combination of random forests and MGTWR offers a comprehensive and innovative perspective for analyzing driving mechanisms. Based on the findings, landscape planners should pay attention to the impact thresholds, scales of action, and spatiotemporal heterogeneity between landscape indicators and ecological environment quality.

Spatio-temporal variations and multi-scenario simulation of landscape ecological risk in the drylands of the Yellow River Basin.

Over the past decades, the drylands of the Yellow River Basin (YRBD) have undergone profound changes in landscape patterns and ecological dynamics, significantly impacting regional sustainable development. To assess the spatio-temporal variations of ecological risk in the YRBD and provide guidance for sustainable regional development, we constructed a coupled Land Use-Landscape Ecological Risk Model-Geographical Detector-PLUS framework for the assessment, analysis, and simulation of dryland landscape ecological risk (LER). The main findings are as follows: (1) Between 2000 and 2020, the area of built-up land, forest, grassland, and water in the YRBD increased, while the area of unused land and cropland decreased. (2) LER exhibited significant spatial heterogeneity, dominated by Sub-low and Low risks. High risk areas were primarily located in the western Inner Mongolia Plateau, whereas Low risk areas were prevalent in the Loess Plateau, with an overall decline in risk levels over the 20years. (3) Water resources, ecological status, and human activities are the main driving factors affecting LER, with the impact of human activities becoming increasingly significant over the past 20years. (4) Under three development scenarios in 2030, the LER is projected to further decrease, although the impact of these scenarios varies across different research sub-regions. Notably, the Ecological Priority Scenario emerges as more effective in mitigating regional LER. (5) Developing precise land use policies tailored to regional characteristics, continuously implementing ecological restoration projects, strengthening water resource management, and enhancing monitoring capabilities are effective ways to reduce LER in the YRBD. This study systematically quantified the impact of different development scenarios on LER in the YRBD, revealing its spatio-temporal characteristics, and emphasized the importance of planning guidance, ecological restoration, and risk monitoring to align regional development with ecological protection. The findings provide scientific evidence for ecological protection and sustainable development in the YRBD and other drylands, offering valuable insights for global dryland ecological risk management.

Landscape pattern prediction method based on ANN-CA-Markov coupling model

The simulation and prediction of landscape patterns can provide a reference for the formulation of ecological space security policies and management and control measures. Therefore, it is necessary to use objective and accurate scientific methods to make accurate simulation predictions. In this study, the quantitative prediction of the Markov model is combined with the advantages of the space-time simulation of the CA model, and the artificial neural network (ANN) module is used for calculation and coupling correction. The Kappa coefficient and the FoM (figure of merit) index are used to test the simulation accuracy. Based on this process, the changes of the landscape pattern in Mudanjiang City at three time points in 2000, 2010 and 2020 were analyzed, and the simulation prediction was made based on this. The experimental results show that the CA-Markov model using the ANN module for coupling correction can be tested for accuracy in the study area, and its Kappa coefficient is 0.834 and the FoM index is 0.001. The model meets the requirements of the landscape pattern for the accuracy of simulation and prediction, and the prediction and analysis of the study area is carried out, and the accurate prediction results are obtained.The results of the study were: Looking at the change in landscape pattern over the 20 years from 2000 to 2020, significant changes occurred in the areas of arable land and artificial surface. The total area of arable land decreased by nearly 130 km2, while the area of artificial surface (i.e., built-up land) increased by about 167 km2. The forest area initially decreased and then increased, with an overall increase of approximately 56 km2, while the water and grassland areas first increased and then decreased. In terms of spatial distribution, the changes in agricultural and forest land are mainly concentrated in the central area where urban development is intensive and in the northern forest area. The results of this study are quite important for policy formulation, according to which it was found that human activities, especially urbanization, have led to a decrease in the area of forested land, and therefore the implementation of the natural forest protection policy can lead to a sustained increase in the area of forested land.

Impacts of Land Use Changes on Landscape Patterns and Ecosystem Service Values in Counties (Villages) in Ethnic Regions of China: A Case Study of Jianghua Yao Autonomous County, Hunan Province

This study, using Jianghua Yao Autonomous County in Hunan Province as a case, systematically analyzes the response of ecosystem service value (ESV) to land use and landscape pattern changes by employing landscape-level indices and landscape-type-level indices. The findings provide a reliable basis for scientifically formulating land use planning and ecological protection policies in ethnic regions, thereby promoting regional ecological security and sustainable development. This study reveals that (1) the land use structure in the county underwent significant changes between 2000 and 2020, with grassland and shrubland areas decreasing substantially by 71.66% and 78.41%, respectively, while urban and arable land areas increased significantly by 228.30% and 15.84%, respectively. Particularly under the scenario of prioritizing economic development, these changes led to increased landscape fragmentation and a decline in ecosystem service value (from CNY 296.571 billion in 2020 to CNY 287.959 billion in 2030). (2) In contrast, the scenarios of ecological protection and sustainable development significantly enhanced the region’s ecosystem service value by increasing forest and water area, effectively maintaining the stability of the landscape pattern. These findings provide important evidence for the formulation of scientifically sound land use planning and ecological protection policies, contributing to the dual goals of economic development, tourism growth and ecological protection in Jianghua Yao Autonomous County and similar regions.

Small watersheds are the best control and management unit for improving soil conservation services in karst areas

Climate factors and changes in landscape patterns are often recognized as the primary drivers of soil conservation services. The influence mechanism of climate factors and landscape patterns on soil conservation service is scale-dependent and spatial heterogeneous. However, it is not clear whether small watershed scale is more conducive to soil erosion control than large scale such as county scale and township scale. For the purpose of creating land use development plans that take local conditions into account, it is crucial to clarify the effects of climate and landscape pattern factors on soil conservation change. Wujiang River basin (WRB), a typical karst basin located in the catchment of the largest first-level tributary on the upper Yangtze River in China, was used as the study area in this research. Soil conservation services provided by water erosion control (SPC) in WRB from 2005 to 2020 were evaluated using the RUSLE model based on the modified rock exposure rate. By using stepwise regression model and multi-scale geographically weighted regression model (MGWR), the spatial heterogeneity of the influence of different driving factors on soil conservation service was comprehensively studied at the scale of district, township and small watershed. The results show that the SPC fluctuates obviously, but the trend is not significant. Climate factor is the dominant factor affecting SPC. With the change of scale from large to small, the adjusted R2 of the regression model gradually increases, especially the factors related to landscape pattern, and more driving factors can be revealed more comprehensively and effectively. Therefore, the small watershed scale is the best control unit to improve the SPC when formulating the regional management landscape plan. The findings of this research also have benchmark significance for other ecological fragile areas, and can provide more comprehensive suggestions for local ecosystem management and landscape planning.

Utilizing deep transfer learning to discover changes in landscape patterns in urban wetland parks based on multispectral remote sensing

Urban wetland parks are essential for protecting ecosystems and alleviating urban heat island effects. Owing to the impact of urban sprawl and human activities, habitats in wetland parks have become increasingly fragmented, evoking an urgent need to accurately monitor and analyze such changes. In this study, a transfer learning-based ResNet-18 method was proposed to classify the landscape patterns of urban wetland parks by integrating the advantages of remote sensing technologies, i.e., long-time series of Gaofen-2 and high-accuracy data of unmanned aerial vehicle remote sensing. The proposed method solves the dual problems of low precision and sparse sample data in landscape pattern classification. By employing the proposed method, we realized long-time-series, high-accuracy analysis of landscape pattern changes in a national wetland park. Our results showed that the overall accuracy was 90.69–97.96 % and Kappa coefficient was stable between 0.865 and 0.968, fully verifying the effectiveness and reliability of our method. We revealed a shrinking trend in the area of water bodies along with an expanding trend in the area of other land types. Thus, our findings reflect the significant impact of urban sprawl on the landscape patterns of wetland parks.

Spatiotemporal landscape pattern changes and their effects on land surface temperature in greenbelt with semi-arid climate: A case study of the Erbil City, Iraq

Urban expansion of cities has caused changes in land use and land cover (LULC) in addition to transformations in the spatial characteristics of landscape structure. These alterations have generated heat islands and rise of land surface temperature (LST), which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas. Greenbelts are employed as an urban planning containment policy to regulate urban expansion, safeguard natural open spaces, and serve adaptation and mitigation functions. And they are regarded as a powerful measure for enhancing urban environmental sustainability. Despite the fact that, the relation between landscape structure change and variation of LST has been examined thoroughly in many studies, but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well, with the lacking of comprehensive research combing both aspects. Accordingly, this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq. The study utilized remote sensing data to retrieve LST, classified LULC, and calculated landscape metrics for analyzing spatial changes during the study period. The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area. The Pearson’s correlation showed the significant effect of Vegetation 1 type (VH), cultivated land (CU), and bare soil (BS) on LST, as increase of LST was related to the decrease of VH and the increases of CU and BS, while, neither Vegetation 2 type (VL) nor built-up (BU) had any effects. Additionally, the spatial distribution of LULC also exhibited significant effects on LST, as LST was strongly correlated with landscape indices for VH, CU, and BS. However, for BU, only aggregation index metric affected LST, while none of VL metrics had a relation. The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment, and further promote sustainable development and enhance well-being in the cities with semi-arid climate.

Implications of landscape changes for ecosystem services and biodiversity: A national assessment in Ecuador

Ecuadorian ecosystems experience high pressure due to anthropogenic activities and climate change. Despite the need of regular monitoring of biodiversity and ecosystem services (BES), attempts to assess the current and future interdependencies of BES and landscape changes are still lacking. This study suggests a spatial assessment of the capacity of ecosystems/land use types to provide BES as status quo and its future development under scenarios of deforestation and climate change. To address data scarcity and improve legitimacy, spatial modeling was combined with participatory approaches. Specifically, changes in landscape pattern were simulated using a modeling platform that combines Geographic Information System (GIS) and Cellular Automaton (CA) modules. Experts in ecosystem conservation and management participated through surveys and workshops. Food, drinking water, service water, soil erosion control, water flow regulation, pollination/seed dispersal, regulation of macro climate, and landscape aesthetic/amenity were identified as the most relevant ES. Among the forest ecosystems, Páramo-related ecosystems were regarded to provide multiple ES with high capacities. Compared to the current status, the deforestation scenario showed to decrease most BES by 20–25 %, while increasing food provision by 5 %, as a trade-off. Regarding the climate change scenarios, the “Representative Concentration Pathways” (RCP) by 2070 were simulated with an increase in temperature of 2 °C (RCP 2.6) and of 4 °C (RCP 6.0). RCP 6.0 showed more noticeable impact than RCP 2.6, which caused a decrease in most BES whereas an increase in food provision due to the possible expansion of arable land into higher altitudes. The results of the spatial assessment also indicated high and low potential areas for BES provision. Such information can support decision-making for BES management e.g., priority areas for actions. Furthermore, the applied spatially explicit assessment could be a starting point for a regular assessment of BES, which has not yet been implemented in Ecuador.

Assessing the Effectiveness of Large-Scale Ecological Restoration Measures in the Liaohe Estuary Using a Landscape Pattern Perspective

In recent years, the Chinese government implemented many policies and actions to restore coastal wetlands. This study focused on assessing how these projects have influenced the landscape patterns of the Liaohe Estuary, an area of critical importance. By analyzing remote sensing images from 2009 to 2022, we determined the spatiotemporal changes in landscape pattern, fragmentation, and conversion. Results showed that (1) Reed (Phragmites australis) fields were the dominant landscape feature and covered 46.3–48.2% of the area; however, road was the serious factor in fragmenting these wetlands. Seepweed (Suaeda salsa) marshes, an iconic and characteristic wetland of the region, gradually expanded towards the estuary and coast over the study years. (2) Landscape fragmentation increased and seasonally changed during the study period and restoration measures actually resulted in more fragmentation of the landscape. (3) Ponds replaced 14.28 km2 natural landscape in the development stage and 40.93 km2 were restored to natural landscape during restoration and maintenance. (4) Active restoration projects caused landscape fragmentation to sharply increase initially, but then fragmentation declined as passive restoration continued in the maintenance stage. This study suggests that road construction should be carefully deliberated in ecologically sensitive areas and that ecological restoration (a combination of active and passive restoration) in the Liaohe Estuary region showed evidence of temporal lag and hysteresis that may be important for research in the future.

Progress in Ecosystem Services Research Under the Evolution of Land Use Landscape Patterns

Land use change (LUUC) is the most intuitive reflection of human activities and a key driver causing changes in ecosystem types and landscape pattern evolution [162]. Changes in land use patterns, structure, composition, intensity, and spatial patterns due to natural and anthropogenic factors affect ecosystem processes such as species movement, soil erosion, and patterns of biodiversity distribution, which in turn affect a wide range of ecosystem services, such as food provisioning, flood storage, soil retention, and soil and water conservation, and ultimately affect human well-being. Most studies have shown that changes in land use landscape patterns affect ecosystem services through multiple pathways, including changes in biodiversity, ecosystem processes and habitats. Land use change and ecosystem services have a reciprocal relationship, and the evolution of land use landscape pattern will directly affect or change the structure and function of ecosystems, which ultimately affects ecosystem services, while the results of the ecosystem services assessment can also provide a scientific basis for the formulation of relevant policies. Therefore, understanding the relationship between the evolution of land-use landscape patterns and the response of ecosystem services can not only clearly reveal the process of land-use landscape evolution, but also more accurately assess the function of ecosystem services, which can promote the scientific formulation and effective implementation of relevant planning and protection policies.

Integrating Future Multi-Scenarios to Evaluate the Effectiveness of Ecological Restoration: A Case Study of the Yellow River Basin

Ecological restoration is an important strategy for mitigating environmental degradation, and the effectiveness evaluation of ecological restoration is of profound significance for the scientific implementation of restoration projects. This study improved the Patch-generating Land Use Simulation (PLUS) model. It was used to simulate the land use patterns under multi-scenarios such as natural development (ND), economic priority (EP), and ecological restoration (ER) in 2030. An evaluation framework covering ecological “Restoration–Monitoring–Effectiveness” (RME) was proposed. Based on 30 m high-resolution remote-sensing data from 2000 to 2020, the land use distribution, landscape pattern changes, and ecosystem services under different scenarios were evaluated and predicted in the Yellow River Basin of Sichuan to verify the effectiveness of the evaluation framework. The results showed the following: (1) Under the ER scenario, the transfer of land use types in 2020–2030 was mainly characterized by an increase in the area of wetlands and a decrease in the area of built-up land. (2) There were obvious differences in land use and landscape patterns under different scenarios. Compared with the ND and EP scenarios, the growth of the construction rate was suppressed in the ER scenario, and the coverage of grassland and wetlands increased significantly. (3) The mean values of ecosystem services in the ER scenario were higher than those in the ND and EP scenarios. These findings clearly indicate that the RME evaluation system can accurately evaluate the ecological restoration effects under multi-scenarios in the future, providing a new perspective for ecological restoration evaluation in other regions.

Impacts of urban-rural integration on landscape patterns and their implications for landscape sustainability: The case of Changsha, China

ContextLandscape patterns result from complex social-ecological interactions, such as urban-rural integration which is especially notable in China. However, the impacts of urban-rural integration on landscape sustainability remain understudied.ObjectivesOur objectives were to examine the impacts of urban-rural integration on landscape patterns and to explore its implications for landscape sustainability.MethodsThe study area is the Changsha metropolitan area in central China, which has undergone urban-rural integration since 2005. A three-step approach was used to (1) assess the spatiotemporal patterns of urban-rural integration dynamics with a multidimensional indicator system, (2) quantify landscape pattern dynamics using landscape metrics, and (3) explore the main drivers and processes involved in urban-rural integration responsible for the observed changes in landscape patterns through a time-fixed effects model.ResultsOur findings reveal a significant increase in the level of urban-rural integration in the Changsha metropolitan area from 2005 to 2020. Concurrently, the regional landscape has experienced increasing trends characterized by the loss and fragmentation of natural and agricultural patches, as well as heightened connectivity among constructed patches. Urban-rural integration exerts notable impacts on landscape patterns through processes such as societal convergence, economic interaction, technology sharing, and spatial interlinkage, subsequently influencing landscape (un)sustainability.ConclusionsThe different drivers and processes of urban-rural integration have varying effects on landscape patterns, with complex and intertwined impacts on landscape sustainability. Therefore, integrated landscape governance is imperative for addressing the disadvantages of urban-rural integration while strategically leveraging its advantages in various social-ecological contexts.

Analysis of Landscape Pattern Evolution and Impact Factors in the Mainstream Basin of the Tarim River from 1980 to 2020

The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River.

Indirect non-linear effects of landscape patterns on vegetation growth in Kunming City

Urban greening is becoming an important strategy in improving urban ecosystem services and sustainability. Identifying the response of vegetation to urbanization and urban landscape patterns can help in planning for urban greening. Urbanization may lead to both direct and indirect effects on vegetation, and the indirect effects of urbanization on vegetation growth (UIE-VG) have been paid much attention recently in large scale. In this study, we investigated the spatiotemporal evolution of UIE-VG and the effects of landscape patterns on UIE-VG using the boosted regression tree model and remotely sensed data. An increase in average UIE-VG from 4 to 56% was found during urbanization of Kunming, the case study area in southwest China. However, UIE-VG exhibited high variations due to landscape pattern changes at the local scale. Overall, area-related and aggregation-related landscape metrics had greater effects on UIE-VG than the other metrics. The increase and aggregation of built-up land enhanced UIE-VG by 3.1–81.3% while the increase and aggregation of unused land and waterbodies reduced UIE-VG by 0.7–20.6%. Moreover, we found that the large and aggregated vegetation areas may mitigate the negative UIE-VG in low urbanization areas. Our findings have important implications for integrating urban landscape planning into sustainable urban greening strategies.