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Bacterial communities play a crucial role in maintaining the stability of river ecosystems and driving biogeochemical cycling, exhibiting high sensitivity to environmental change. However, understanding the spatial scale effects and assembly mechanisms of riverine bacterial communities under distinct anthropogenic disturbances remains a challenge. Here, we investigated bacterial communities across three distinct watersheds [i.e., intensive urban (UW), intensive agricultural (AW), and natural (NW)] in both dry and wet seasons. We explored biogeographic patterns of bacterial communities and the influence of landscape patterns at multi-spatial scales and water chemistry on bacterial communities. Results showed that α diversity was significantly lower in UW and AW compared to NW, particularly in the dry season. A gradient of β diversity with NW > UW > AW was observed across both seasons (p < 0.05). Pseudomonadota, Bacteroidota, and Actinobacteriota were the most abundant phyla across all watersheds, with specific taxa enriched in each watershed (i.e., the class Actinobacteria was significant enrichment in UW and AW, and Clostridia in NW). The influence of landscape patterns on bacterial communities was significantly lower in human-disturbed watersheds, particularly in UW, where this influence also varied slightly from near riparian buffers to sub-watershed. Homogeneous selection and drift jointly dominated the bacterial community assembly across all watersheds, with homogeneous selection exhibiting a greater influence in UW and AW. Landscape patterns explained less variance in bacterial communities in UW and AW than in NW, and more variance was explained by water chemistry (particularly in UW). These suggest that the stronger influence of species sorting in UW and AW was driven by more allochthonous inputs of water chemistry (greater environmental stress). These findings provide a theoretical foundation for a deeper understanding of riverine bacterial community structure, spatial scale effects, and ecological management under different anthropogenic activities. [ABSTRACT FROM AUTHOR]

Since the Anthropocene, ecosystems have been continuously deteriorating due to global climate change and human intervention. Exploring the changing characteristics of land use/land cover (LULC), landscape pattern and ecosystem service (ES) and their drivers is crucial for regional ecosystem management and sustainable development. Taking the Bohai Rim region of China as an example, we used the land use transfer matrix, landscape pattern index and InVEST model to analyze the changing characteristics of LULC, landscape pattern and six key ESs [crop production (CP), water yield (WY), carbon storage (CS), soil conservation (SC), habitat quality (HQ), landscape aesthetics (LA)] during 2000–2020. Detailed analysis of the natural and anthropogenic factors affecting the landscape pattern and ES changes has been considered in this study. The results show that the areas of forest, water and impervious land increased, while those of cropland, shrubs, grassland and barren land decreased during 2000–2020. The landscape was fragmented, complex and decentralized during 2000–2015, while the three trends eased during 2015–2020. From 2000 to 2020, CP, WY, and SC capacity show an increasing trend, while CS, HQ, and LA capacity tend to a decline. Natural factors (e.g., precipitation, temperature, altitude) and human factors (e.g., technological progress, policy changes, and LULC forms) are the main factors affecting landscape pattern and ESs. The present study can provide theoretical basis for ecological restoration, ecological product value realization, and land planning in the typical developed urban area. [ABSTRACT FROM AUTHOR]

The development of mining cities has led to changes in land use and the evolution of landscape patterns. Constructing an ecological security evaluation system can reflect the ecological security status of mining city areas and provide planning references for these cities. This study, based on Heihe City's land use data from 1980 to 2020, systematically analyzes the spatial and temporal evolution characteristics of land use, landscape patterns, and landscape ecological security levels by constructing a land use transfer matrix and calculating landscape pattern indices and landscape ecological security indices. The results show that: 1) Forest land is the main type of land use in Heihe City, accounting for over 50% of the total area. Land use changes primarily occurred between 2000–2010 and 2010–2020, with the spatial pattern characterized by overall stability and localized dramatic shifts, mainly involving the conversion of forest land to farmland and unused land. 2) From 1980 to 2020, the landscape ecological security pattern in Heihe City improved. Landscape diversity and landscape contagion increased, while landscape fragmentation, the largest patch area, and the average patch area decreased. Land use was optimized overall, but the trend of forest fragmentation became noticeable. 3) Between 1980 and 2020, the landscape ecological security level in Heihe City improved significantly. Driven by ecological restoration policies, the ecological security level in the southern region greatly improved, while the spatial pattern continued to show a trend of lower security in the south and higher security in the north. Specifically, the area proportions of low-security and relatively low-security areas increased by 6.23% and 9.55%, respectively. The spatial clustering of landscape ecological security levels is evident, with high-high value clustering mainly in the north and low-low value clustering mainly in the south. It is necessary to further promote ecological protection in the north to ensure the ecological barrier function, while strengthening ecological restoration in the south to improve ecological security levels. Additionally, continuous macro-policy regulation is needed to maintain long-term ecological security in Heihe City. The ecological security level of mining city landscapes is influenced by economic dependence, policy constraints, and environmental issues. This study can provide guidance for planning improvements in the study area and other mining cities. [ABSTRACT FROM AUTHOR]

Urban green spaces (UGSs) are integral to urban ecosystems, providing multiple benefits to human well-being. However, previous studies mainly focus on the quantity or quality of UGSs, with less emphasis on a comprehensive analysis. This study systematically examined the spatiotemporal UGS dynamics in the Pearl River Delta urban agglomeration (PRDUA) in China from the perspectives of the area, spatial configuration, and quality, using the high spatial resolution (30 m) Landsat-derived land-cover data and Normalized Difference Vegetation Index (NDVI) data during 1985–2021. Results showed the UGS area in both the old urban districts and expanded urban areas across all nine cities in the PRDUA has experienced a dramatic reduction from 1985 to 2021, primarily due to the conversion of cropland and forest into impervious surfaces. Spatially, the fragmentation trend of UGSs initially increased and then weakened around 2010 in nine cities, but with an inconsistent fragmentation process across different urban areas. In the old urban districts, the fragmentation was mainly due to the loss of large patches; in contrast, it was caused by the division of large patches in the expanded urban areas of most cities. The area-averaged NDVI showed a general upward trend in urban areas in nearly all cities, and the greening trend in the old urban districts was more prevalent than that in the expanded urban areas, suggesting the negative impacts of urbanization on NDVI have been balanced by the positive effects of climate change, urbanization, and greening initiatives in the PRDUA. These findings indicate that urban greening does not necessarily correspond to the improvement in UGS states. We therefore recommend incorporating the three-dimensional analytical framework into urban ecological monitoring and construction efforts to obtain a more comprehensive understanding of UGS states and support effective urban green infrastructure stewardship. [ABSTRACT FROM AUTHOR]

Runoff research serves as the foundation for watershed management, and the relationship between runoff and landscape pattern represents a crucial basis for decision-making in the context of watershed ecological protection and restoration. However, there is a paucity of research investigating the multi-scale spatial relationship between runoff and landscape patterns. This study employs the Poyang Lake Basin (PLB) as a case study for illustrative purposes. The construction of the soil and water assessment tool (SWAT) model is the initial step in the process of carrying out runoff simulation, which in turn allows for the analysis of the spatial–temporal characteristics of runoff. Subsequently, Pearson's correlation analysis, global linear regression and geographically weighted regression (GWR) models are employed to examine the impact of landscape composition on runoff. Finally, the spatial relationship between runoff and landscape pattern is investigated at the landscape and class scales. The results of the study demonstrate the following: (1) runoff in the PLB exhibited considerable spatial–temporal heterogeneity from 2011 to 2020. (2) Forest was the most prevalent landscape type within the PLB. Landscape composition's impact on runoff exhibited non-linear characteristics, with forest, cropland, barren, and grassland influencing runoff in decreasing order. (3) A spatial relationship between runoff and landscape pattern was observed. At the landscape scale, patch diversity significantly influenced runoff, and reducing patch diversity primarily increased runoff. At the class scale, forest and cropland patch areas had the greatest impact on runoff, potentially enhanced by improving patch edge density. (4) Nine sub-basins needing ecological restoration were identified, with restoration pathways developed based on spatial relationships between runoff and landscape patterns. This study elucidates the impact of landscape composition and pattern on runoff, thereby providing a basis for informed decision-making and technical support for the ecological restoration and management of the watershed. [ABSTRACT FROM AUTHOR]

The gullies and valleys of the Loess Plateau, as key ecological zones for soil erosion control, play a critical role in the region's sustainable development under increasing urbanization. This study employed the Soil and Water Assessment Tool (SWAT) to analyze the impacts of land use/cover changes (LUCC) on runoff at multiple spatial scales and locations within the Sanchuan River Basin (SRB) in the loess hilly and gully region. The methodology integrates SWAT modeling with LUCC scenario analysis, focusing on spatial and scale effects of land use changes on hydrological processes. The results revealed distinct spatial differences, with diminishing LUCC impacts on streamflow from the upper to lower reaches of the basin, regardless of land use type. Scale effects were also evident: grassland effectively controlled runoff within 300 m of riparian zones, while forest land was most effective beyond 750 m. A relatively insensitive range for runoff changes was observed between 300 and 750 m. These findings highlight the critical role of LUCC in influencing runoff patterns and underscore the importance of region-specific and scale-sensitive land use management strategies. This research provides valuable guidance for sustainable land planning, particularly in riparian zones, to enhance runoff control and optimize ecological benefits. [ABSTRACT FROM AUTHOR]

Urbanization and industrialization have led to obvious changes in the ecological environment and landscape pattern in the Beijing–Tianjin–Hebei region. Therefore, it is crucial to clarify the spatial–temporal changes in vegetation cover and its landscape pattern and conduct its analysis with the driving factors for ecological preservation in the Beijing–Tianjin–Hebei region. This study combined AVHRR GIMMS NDVI and MODIS NDVI data based on the ESTARFM model to obtain a high spatial–temporal resolution for vegetation cover; it then analyzed the vegetation cover changes at the type and landscape scales using a landscape index and explored the driving factors of the landscape pattern through principal component analysis. The results show that (1) the vegetation is mainly of medium and higher coverage and is distributed in the northeast, the western part of the Taihang Mountains and the central plains in the study area. From 1985 to 2022, there was no statistically significant difference in the overall change in its coverage. (2) From 1985 to 2022, at the landscape level, the vegetation cover landscape exhibited the following characteristics: increased fragmentation, an increase in the complexity of the landscape shape, a decrease in connectivity, a discrete landscape and a decrease in species diversity. At the type level, the medium vegetation demonstrated the most significant degree of fragmentation. The high-vegetation-cover areas exhibited a more concentrated distribution. Additionally, the low, lower and higher vegetation types displayed an increase in complexity, shape, discreteness and heterogeneity within the landscape. (3) Meanwhile, the principal component analysis showed that the changes in the landscape pattern of vegetation cover were mainly the result of the combined effects of climatic and anthropogenic factors in the Beijing–Tianjin–Hebei region. The human factor played the dominant role; this was followed by larger contributions from climatic factors. In addition to offering pertinent scientific insights for the maximization of the ecological environment and the fostering of regional ecological and sustainable development in the Beijing–Tianjin–Hebei region, the aforementioned analysis and research could serve as the foundation for the sustainable management and planning of vegetation cover. [ABSTRACT FROM AUTHOR]

Landscape simulation and prediction are crucial for understanding the dynamic evolution and future trends of wetlands. However, only a few existing studies have focused on the applicability and limitations of commonly used land-use/cover change (LUCC) simulation models in lake wetland landscapes. Taking Shengjin Lake Reserve in China as the study area, we firstly analyzed landscape variations during 2010–2020 using multisource remote sensing images. Then, the patch-generating land-use simulation (PLUS) model was employed to simulate wetland landscapes in 2020, the accuracy and limitation of which in simulating lacustrine wetlands were also explored. Lastly, the changing trends of wetland landscapes in 2030 under different development scenarios were predicted. The results show that the landscape of Shengjin Lake Reserve has changed significantly during 2010–2020, with increases in mudflats, reservoirs/ponds, woodlands, and built-up land, and there has been decreases in lakes, grass beaches, and croplands. The PLUS model demonstrated an ideal simulation accuracy for Shengjin Lake Reserve, with the overall accuracy exceeding 80%, kappa coefficient greater than 0.75, and figure of merit (FOM) coefficient of 0.35, indicating that the model can capture the dynamic changes in wetland landscapes accurately. The simulation accuracy can be effectively improved with the adjacent initial year, shorter time interval, and the primary driver factors. Under the natural development scenario, the number of patches in the Shengjin Lake Reserve increased sharply, and landscape fragmentation intensified. Under the urban development scenario, the expansion of built-up land increased, and the average patch area increased. In the ecological protection scenario, the Shannon diversity index and Shannon evenness index of the landscape improved significantly, and the natural wetlands such as grass beaches and lakes can be protected effectively. Our study confirms the applicability of the PLUS model in simulating and predicting lacustrine wetlands landscapes, and the conclusions provide a scientific basis for formulating reasonable development strategies to realize wetland resource conservation and management. [ABSTRACT FROM AUTHOR]

Wetlands serve as crucial ecological buffers, significantly influencing temperature reduction, carbon storage, regional climate regulation, and urban wastewater treatment. To elucidate the relationship between wetland landscape patterns and ecological environment, and to accurately assess lake ecosystems, this study proposes a semi-supervised classification method based on RSEI and K-Means. By integrating landscape pattern indices, the Remote Sensing Ecological Index (RSEI), and disturbance proximity, a comprehensive evaluation of the ecological quality of the Dianchi wetlands was conducted. The results indicate that the RSEI-K-Means method, with K set to 50, achieved overall accuracies (OAs) and Kappa values of 0.91 and 0.88, surpassing the SVM's 0.85 and 0.80. This method effectively combines ecological and landscape indices without relying on extensive training samples, enhancing accuracy and speed in wetland information extraction and addressing the challenges of spatial heterogeneity. This study reveals that from 2007 to 2009, and 2013 to 2015, landscape patterns were significantly influenced by the rapid expansion of Kunming city, exacerbating wetland fragmentation. Notably, significant ecological quality changes were observed in 2009 and 2013, with gradual recovery post-2013 due to strengthened environmental protection policies. The RSEI disturbance proximity analysis indicated that the affected areas were primarily concentrated in regions of high human activity, confirming the method's high sensitivity and effectiveness. This study can help in wetland ecosystem research and management. [ABSTRACT FROM AUTHOR]

With the development of urbanization, the spatial and temporal distribution characteristics of the urban landscape pattern play a decisive role in the intensity of the urban heat island (UHI) effect. A panel data model was constructed to study the relationship between the UHI effect and landscape pattern in Kunming from 1995 to 2020 at four different scales. The results indicate: (1) The landscape pattern of Kunming changed obviously with time, the artificial patch increased, the natural patch decreased, and the UHI effect became more and more obvious; (2) With an increase in scale, the number of influencing variables continues to grow, and the impact of artificial patches gradually intensifies; (3) The normalized difference water index (NDWI) has the greatest influence on the UHI, and the cooling effect is more obvious with the increase in scale. Unlike previous studies, the spatial configuration of the landscape in Kunming City had a stronger effect on the UHI effect than the landscape grouping and vegetation index; (4) This paper introduces the panel data model into the discussion of the UHI for the first time, providing a new method for better understanding the changing patterns of the urban thermal environment. [ABSTRACT FROM AUTHOR]

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Spatial scale is a key factor, which affects the accuracy of spatial expression and further influences the spatial planning of a research area. In order to help improve the efficiency and accuracy of optimal scale selection for all sizes of research areas, a universal two-layer theoretical framework for optimal scale selection was proposed in this paper. Port area was taken as an example to systematically clarify the application of the proposed framework, and the scale selection model for port spatial expression was established. Least-squares-based mean change point analysis was introduced into the model, and the concept of a comprehensive change point was proposed to form the criterion for optimal port scale selection. First, an appropriate scale domain was preliminarily determined by the upper scale selection model. Then, the lower scale selection model determined the final appropriate scale domain and took the corresponding scale of a minimum comprehensive change point as the final optimal scale for port spatial expression. Finally, a port area in Qingdao in eastern China was taken to verify the feasibility of the proposed model, and the optimal scale was suggested to be 14 m. The proposed framework in this paper helps ensure the accuracy of spatial expression and reduce spatial data redundancy, and it can provide the methodological references for planners to better spatialize a research area, which will guarantee the subsequent spatial planning work. [ABSTRACT FROM AUTHOR]

Water environment quality is profoundly driven by a series of landscape characteristics. However, current knowledge is limited to the independent response of water quality to single landscape elements; this has led to poor knowledge of the potential role of structural coupling within landscapes in driving water quality changes, especially in those agroforestry-mixed mountainous watersheds with highly embedded forest-clustered landscapes and abundant headstreams. Given this fact, this study aims to evaluate whether and how the source–sink coupling structure of forest-clustered landscapes systematically drives headstream quality dynamics. We first systematically assessed the association pattern of source and sink structures within forest-clustered landscapes, and then innovatively proposed and constructed a functional framework of source–sink coupling structure of landscapes across 112 agroforestry-mixed mountainous sub-watersheds in Chongqing, China. On this basis, we further evaluated the driving pattern and predictive performance of the source–sink coupling structure of landscapes behind headstream quality dynamics. We report three findings: (1) headstream quality varied across agroforestry-mixed sub-watersheds, mapping out the source–sink structures and functions of landscapes; (2) there was significant functional coordination between source–sink structures of the forest-clustered landscapes, which significantly drove headstream quality dynamics; (3) the structural positioning and differences of the forest-clustered landscapes along the multivariate functional axes directly corresponded to and predicted headstream quality status. These findings together highlight a key logic that the response of water quality dynamics to landscapes is essentially that to the functional coupling between the source–sink structures of landscapes, rather than the simple combination of a single landscape contribution. This is the first study on the landscape–runoff association from the perspective of source–sink structural coupling, which helps to deepen understanding of the correlation mechanism between water dynamics and landscape systems, and provides a new functional dimension to the development of future landscape ecological management strategies from a local to a global scale. [ABSTRACT FROM AUTHOR]

In the rapid process of urbanization, revealing the patterns and driving forces behind the evolution of blue–green spaces holds significant value for optimizing urban blue–green environments. This study systematically investigates the spatial–temporal evolution characteristics and driving forces of blue–green space in the Chengdu–Chongqing Economic Circle from 1990 to 2020, utilizing GIS technology, landscape pattern analysis, and geographic detectors. The research findings indicate the following: (1) The area of blue–green space in the study area exhibits a general trend of initial growth followed by decline, with significant changes occurring between 2010 and 2020. (2) The fragmentation degree of blue–green space is gradually increasing, while connectivity among landscapes is decreasing; however, there has been an increase in landscape distribution uniformity. More than 90% of blue–green spaces expanded mainly through adjacency patterns. (3) In examining driving forces, it was found that temperature, topographic relief, elevation, population density, and construction intensity are the primary driving factors. Notably, the influence of natural factors has diminished over time while human social factors have significantly intensified. This study offers solutions for optimizing the configuration of blue–green spaces within the Chengdu–Chongqing Economic Circle. It also serves as a reference case for promoting high-quality urbanization in developing countries undergoing rapid urbanization. [ABSTRACT FROM AUTHOR]

Introduction: Transportation corridors, as special economic corridors, have a greater impact on land cover and landscape pattern changes. Methods: Therefore, 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. Result: The 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 landuse 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. [ABSTRACT FROM AUTHOR]

[Display omitted] Urban landscape is directly perceived by residents and is a significant symbol of urbanization development. A comprehensive assessment of urban landscapes is crucial for guiding the development of inclusive, resilient, and sustainable cities and human settlements. Previous studies have primarily analyzed two-dimensional landscape indicators derived from satellite remote sensing, potentially overlooking the valuable insights provided by the three-dimensional configuration of landscapes. This limitation arises from the high cost of acquiring large-area three-dimensional data and the lack of effective assessment indicators. Here, we propose four urban landscapes indicators in three dimensions (UL3D): greenness, grayness, openness, and crowding. We construct the UL3D using 4.03 million street view images from 303 major cities in China, employing a deep learning approach. We combine urban background and two-dimensional urban landscape indicators with UL3D to predict the socioeconomic profiles of cities. The results show that UL3D indicators differs from two-dimensional landscape indicators, with a low average correlation coefficient of 0.31 between them. Urban landscapes had a changing point in 2018–2019 due to new urbanization initiatives, with grayness and crowding rates slowing, while openness increased. The incorporation of UL3D indicators significantly enhances the explanatory power of the regression model for predicting socioeconomic profiles. Specifically, GDP per capita, urban population rate, built-up area per capita, and hospital count correspond to improvements of 25.0%, 19.8%, 35.5%, and 19.2%, respectively. These findings indicate that UL3D indicators have the potential to reflect the socioeconomic profiles of cities. [ABSTRACT FROM AUTHOR]

Human activities, such as reservoir construction and riverbed sand extraction, significantly influence the hydrological and sedimentary dynamics of natural rivers, thereby directly or indirectly affecting river landscape pattern distribution. This study primarily focused on the lower Beijiang River (LBR) in China, an area characterized by intensive human activity. River landscape patterns were studied using historical topographical data and time-series Landsat remote sensing images. Natural and anthropogenic factors were considered to explore the driving forces behind the evolution of landscape patterns. The results indicated that the topography of the LBR underwent significant downcutting from 1998 to 2020. The average elevation of the study area decreased by 3.6 m, and the minimum thalweg elevation decreased by 6.7 m. Over the past 30 years, the local vegetation showed a relatively stable spatial distribution, whereas the area of sand remained relatively stable before 2012, followed by a sudden decline, and tended to stabilize in the last decade. The water area exhibited a gradually increasing trend. The transition maps indicated that the spatial changes in sand were the most significant, with only 39.6% of the sand remaining unchanged from 1998 to 2009 and 32.3% from 2009 to 2020. The corresponding landscape patterns showed that the fragmentation degree of sand increased, with the mean patch size decreasing by 69.2%. The aggregation of water intensified, as its aggregation index increased from 93.31% to 95.41%, while the aggregation of vegetation remained relatively minor, ranging from 89.52% to 90.12%. The annual average temperature, annual average maximum temperature, and annual rainfall days had the strongest correlations with the vegetation landscape pattern indices. Additionally, human activities may have been the primary driver of the landscape pattern evolution of water and sand. The findings of this study have positive implications for the maintenance of the diversity and stability of river ecosystems. [ABSTRACT FROM AUTHOR]

The main causes of habitat conversion, degradation, and fragmentation—all of which add to the loss in biodiversity—are human activities, such as urbanization and farmland reclamation. In order to inform scientific land management and biodiversity conservation strategies and, therefore, advance sustainable development, it is imperative to evaluate the effects of land-use changes on biodiversity, especially in areas with high biodiversity. Using data from five future land-use scenarios under various Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs), this study systematically assesses the characteristics of land-use and landscape pattern changes in southwest China by 2050. This study builds a comprehensive biodiversity index and forecasts trends in species richness and habitat quality using models like Fragstats and InVEST to evaluate the overall effects of future land-use changes on biodiversity. The research yielded the subsequent conclusions: (1) Grasslands and woods will continue to be the primary land uses in southwest China in the future. But the amount of grassland is expected to decrease by 11,521 to 102,832 km2, and the amounts of wasteland and urban area are expected to increase by 8130 to 16,293 km2 and 4028 to 19,677 km2, respectively. Furthermore, it is anticipated that metropolitan areas will see an increase in landscape fragmentation and shape complexity, whereas forests and wastelands will see a decrease in these aspects. (2) In southwest China, there is a synergistic relationship between species richness and habitat quality, and both are still at relatively high levels. In terms of species richness and habitat quality, the percentage of regions categorized as outstanding and good range from 71.63% to 74.33% and 70.13% to 75.83%, respectively. The environmental circumstances for species survival and habitat quality are expected to worsen in comparison to 2020, notwithstanding these high levels. Western Sichuan, southern Guizhou, and western Yunnan are home to most of the high-habitat-quality and species-richness areas, while the western plateau is home to the majority of the lower scoring areas. (3) The majority of areas (89.84% to 94.29%) are forecast to undergo little change in the spatial distribution of biodiversity in southwest China, and the general quality of the ecological environment is predicted to stay favorable. Except in the SSP1-RCP2.6 scenario, however, it is expected that the region with declining biodiversity will exceed those with increasing biodiversity. In comparison to 2020, there is a projected decline of 1.0562% to 5.2491% in the comprehensive biodiversity index. These results underscore the major obstacles to the conservation of biodiversity in the area, highlighting the need to fortify macro-level land-use management, put into practice efficient regional conservation plans, and incorporate traditional knowledge in order to save biodiversity. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Urban green space (UGS) is a crucial physical area that supports the functioning of urban ecosystems, and its changes affect urban ecological balance. In order to accurately analyze the dynamic processes and transfer targets of UGS during urbanization, this study proposes a new method of UGS assessment based on multi-temporal Landsat remote sensing data. This method is integrated with intensity analysis and landscape pattern indices so as to explore the spatio-temporal dynamics of the evolution process, landscape pattern, and driving forces of UGS from 2000 to 2022 in the resource-based city of Taiyuan in central China. The results of the case study show that rapid urbanization brought about a continuous reduction in UGS in the study area, but the trend of decreasing gradually slowed down; UGS patches have become more dispersed and isolated, bare land has been targeted for both gains and losses of UGS, and ecological restoration of bare land mitigated the rapid reduction of UGS. The results of this study not only confirm the applicability of this methodology for monitoring and assessing the evolution of UGS, but also reveal the identification of the targeting or avoidance of other categories during the conversion of UGS. Thus, the potential factors influencing changes in UGS can be analyzed to guide and safeguard sustainable development. [ABSTRACT FROM AUTHOR]

Reservoir projects often have significant impacts on ecosystems. The resulting environmental problems hinder the ecologically sustainable development of project areas. Research focusing on landscape pattern vulnerability could shed light on ecological restoration in disturbed sites. However, few studies have specifically examined reservoir areas in this context. This study investigates the spatial distribution characteristics, change rules, spatial autocorrelation, and driving forces of landscape pattern vulnerability in the Qianping Reservoir area (3859.16 hm2) from 2000 to 2020 using land use data. The findings reveal several key points: (1) Over the study period, cultivated land, grassland, and forest land are the key landscape types, covering more than 90% of the area. Cultivated land decreased by 481.57 hm2 as other land use types expanded. (2) Vulnerability remained stable in the first decade but sharply increased from 2010 to 2020, showing a trend of spatial aggregation. Reservoir construction and simultaneous ecological restoration efforts led to shifts in vulnerability zones across the landscape. (3) Spatial distribution of landscape pattern vulnerability shows a positive correlation, which strengthened by 2020 compared to earlier years. (4) Man-made factors, particularly land use changes, significantly influence landscape pattern vulnerability, with their impact growing over time. These findings not only provide a scientific basis for ecological restoration and landscape reconstruction in the Qianping Reservoir area but also offer insights applicable to similar environments. Overall, this study enhances theoretical understanding of reservoir landscape pattern vulnerability and contributes valuable perspectives on ecological restoration strategies for reservoir areas. [ABSTRACT FROM AUTHOR]

Vegetation cover can regulate regional climate and associated dry–wet variations. However, the effects of the quantitative structure and landscape pattern of vegetation cover on climatic drought remain unclear. Yunnan Province in China, with its abundant vegetation resources, provides a good setting for addressing this research gap. Our objective is to provide guiding recommendations for climate-warming mitigation through the study of the topic. This study adopted four periods of vegetation cover data, from 1992 to 2020, and explored their dynamics. Monthly average precipitation and temperature data from 125 meteorological stations in Yunnan were used to calculate standardized precipitation–evapotranspiration index (SPEI) for 1992–2020 to understand the responses of climatic drought to vegetation cover dynamics. The correlations between quantitative structure, landscape pattern, and climatic drought were investigated by Pearson's correlation coefficient in 10 km, 20 km, 30 km, and 40 km grid cells, respectively. The results indicate that changes in the quantitative structure of vegetation could influence regional climates, with the contributions to climatic drought mitigation ranked in the following order: broad-leaved forest > shrubland > needle-leaved forest > cropland > grassland. Landscape patterns significantly affected local climates, where broad-leaved and needle-leaved forests had the strongest and most stable correlations with climatic drought, whereas shrubland and grassland showed weaker correlations. The correlations between landscape patterns and climatic drought were stronger during the dry season than the rainy season. Factors such as the landscape dominance index, fragmentation index, and aggregation index had a significant impact on climatic drought. The dominant and aggregated-distribution broad-leaved forests were conducive to climatic drought mitigation, while needle-leaved forests, croplands, and grasslands might exacerbate climatic drought. [ABSTRACT FROM AUTHOR]

This empirical research utilized geographic information system (GIS) data and involved kernel density estimation (WKDE), ecological footprint modeling, landscape index analysis, and spatial analysis methods. A plateau landscape ecological risk model is constructed, and the temporal and spatial changes in the road network pattern and the landscape ecological risk in the region in 2012 and 2020 are investigated. The study results identify that the expansion of the road network led to a rapid increase in construction land area and a decrease in cultivated land area. However, there is little impact on other landscape types. The study reveals that road network expansion leads to landscape ecological risk changes, primarily in low-altitude urban centers. The risk levels decrease with increasing ecological risk levels, with the proportion of road level lengths increasing and decreasing. Landscape ecological risk and road level is correlated. This study will interest practitioners engaged in ecosystem management, infrastructure planning, and transportation systems development, as well as researchers in these and related areas. [ABSTRACT FROM AUTHOR]

Shantytowns, characterized by poor living conditions and simple houses, necessitate efficient extraction and analysis for urban planning. This paper proposes a multi-scale and global-local information interactive attention transformer (MGLI-Former) for shantytown extraction from high-resolution remote sensing images. First, the multi-level feature fusion block (MLFFB) integrates neighborhood encoding features to prevent the loss of small-target shantytowns. Second, joint global and local information transformer blocks (JGLB) effectively combine global and local features. Finally, boundary and feature joint optimization loss (BF-Loss) refines the output by edges and high-level semantics. Experiments in Beijing and Shanghai demonstrate the MGLI-Former achieved optimal visual and quantitative extraction evaluations. The F1-score, IoU, Precision, and Recall are 86.92%, 76.87%, 86.84%, 87.01% and 72.33%, 56.66%, 69.29%, 75.65%, respectively. Furthermore, the use of UIS-Shenzhen datasets and fine-tuning experiments with mixed datasets further validate the robustness and generalization capabilities of MGLI-Former. Moreover, spatial and landscape patterns of shantytowns in Beijing and Shanghai reveal: (1) Beijing’s shantytowns radiate uniformly from the old city center, whereas Shanghai exhibits a multi-core diffusion pattern. (2) Shanghai's shantytown distribution is clustered, while Beijing's shantytown distribution is more uniform. MGLI-Former demonstrates the potential for extracting shantytowns and has significant urban planning and management implications.

Coastal zones have intense human activity and are ecologically fragile. Assessing ecological risks in coastal zones is crucial to promoting ecological safety and sustainable development for coastal cities. However, the relationship between ecological risk assessment and distance from the coastline is indeterminate in current research. To solve this problem, this study constructs the sea–land gradient and reconstructs the landscape pattern index and landscape ecological risk index (ERI) considering the sea–land gradient paradigm. This study aims to analyze the spatial–temporal variation characteristics and effects of the sea–land gradient on landscape pattern and ecological risk in Dalian City from 2000 to 2015. The results show the following: (1) between 2000 and 2015, a significant effect of coastline on the coastal landscape pattern in Dalian is reducing landscape fragmentation. The extent of this influence gradually diminished along the sea–land gradient. The landscape aggregation of urban building sites near the sea was relatively high and gradually increased over the years; (2) in Dalian, the landscape ERI has decreased near the sea and increased near the inland year by year; (3) the dominant pattern of landscape ecological risk was characterized by a transition from high to low levels within the [0, 2.5] km zone, while a transition from low to high levels predominated within the [2.5, Max] km zone; and (4) the northern region in Dalian primarily goes from high to low risk in the buffer zone near the landside, whereas the southern area has this changing pattern in the buffer zone near the seaside.

Abstract With the development of urbanization, the spatial and temporal distribution characteristics of the urban landscape pattern play a decisive role in the intensity of the urban heat island (UHI) effect. A panel data model was constructed to study the relationship between the UHI effect and landscape pattern in Kunming from 1995 to 2020 at four different scales. The results indicate: (1) The landscape pattern of Kunming changed obviously with time, the artificial patch increased, the natural patch decreased, and the UHI effect became more and more obvious; (2) With an increase in scale, the number of influencing variables continues to grow, and the impact of artificial patches gradually intensifies; (3) The normalized difference water index (NDWI) has the greatest influence on the UHI, and the cooling effect is more obvious with the increase in scale. Unlike previous studies, the spatial configuration of the landscape in Kunming City had a stronger effect on the UHI effect than the landscape grouping and vegetation index; (4) This paper introduces the panel data model into the discussion of the UHI for the first time, providing a new method for better understanding the changing patterns of the urban thermal environment.

Abstract Exploring the relationship between land use cover/change (LUCC) and ecosystem service value (ESV) under different future scenarios can provide guidance for selecting future development patterns and for the scientific utilization of land resources in the region. In this study, LUCC under different scenarios in the North Slope of Tianshan Mountain (NSTM) was simulated using the PLUS model. The ESV coefficients were adjusted for regional differences and social development factors to better reflect the actual situation in the study area. The interactions between LUCC, landscape pattern (LSP), and ESV were systematically analyzed, while at the same time, ESV and the level of economic development were fitted to the Ecological Kuznets Curve, which was then used to determine its trend and inflection point. The following conclusions were drawn: (1) Cropland and unused land are the main types of land use change in the NSTM, both historically and in the future. Cropland shows an increase in the natural development scenario and a decrease in the ecological protection scenario. Unused land shows an increase in the different development scenarios, indicating that unused land has higher development potential in the NSTM. NSTM shows a continuous decrease in ESV in the natural development scenario and a continuous increase in ESV in the ecological protection scenario. (2) LSP in both historical and future NSTM have evolved to show fragmentation, heterogeneity, and complexity in patch forms. However, this trend is slower in the ecological protection scenario than in the natural development scenario. LUCC, LSP, and ESV form an integrated framework of interactions, where LUCC influences ESV through LSP, and changes in ESV feedback to LUCC through LSP, which acts as a bridging mediator. (3) The Ecological Kuznets Curve of NSTM exhibits an N-shape, showing a clear overall rightward trend across different development scenarios at the annual level. At the interannual level, the curves for the natural development scenario are situated in the middle of the declining phase of the N-shape, with no ecological inflection point occurring during the study period. In contrast, the curves for the ecological protection scenario display a declining-ascending trend, with the ecological inflection point occurring when per capita GDP reaches 2.5 × 10^6 CNY.

Abstract City parks can cool the surrounding environment and mitigate the urban heat island (UHI) effect, considerable improving the city’s adaptability to climate. In this study, 20 city parks in Nanjing, China, were considered, and four indexes for quantifying the cooling benefits from a cumulative impact perspective were proposed. These indexes are park cooling area (PCA), park cooling efficiency (PCE), park cooling intensity (PCI), and park cooling gradient (PCG). The results reveal the following: first, city parks have a positive impact on the surrounding thermal environment. The factors park area (PA), park perimeter (PP), landscape shape index (LSI), and normalized difference vegetation index (NDVI) determine cooling benefits. Second, PA and PP are significantly positively correlated with PCA but are significantly negatively correlated with PCE. LSI is negatively correlated with PCE, while NDVI is positively correlated with PCI and PCG. No significant correlation exists between the four cooling indexes and modified normalized difference water index(MNDWI). Finally, different parks exhibit variations in their ability to provide cooling benefits. Special or community parks are more appropriately situated in areas with constrained urban land resources. In designing comprehensive parks, the intricate boundary features and vegetation conditions need to be considered to optimize their cooling effects. Moreover, a larger number of residents are allowed to enjoy cooling services. The findings of this project will aid in the construction and optimization of city parks in future to combat the UHI effect.

The study of landscape patterns in the context of carbon neutrality can significantly influence regional carbon emissions. Also at stake is the effectiveness of global ecological protection. The researchers used Cite Space visualization software to analyze 7758 documents related to the Web of Science Core Collection database. The period was 2001 to 2024. The results of the study show that: (1) research in this field can be divided into three periods: germination(2001–2007), fluctuation(2008–2019), and rapid development(2019–2024). The core authors are Li Wei, Wang Kai, and Liu Yang. (2) Through in-depth analyses of research in this field, we have found that the study of landscape patterns in the context of carbon neutrality is interdisciplinary. For example, it is closely related to the disciplines of environmental science, energy and fuels, green and sustainable science and technology, and environmental studies. (3) Changes in keywords of landscape pattern research in the context of carbon neutrality in the same period. The main research directions include Carbon dioxide, Optimization, Management, etc. The frontier areas include carbon neutrality, CO2 emissions, carbon emission, etc. The future research directions include environmental quality, environmental regulations, urban agglomeration, etc.

Wind power has been developing rapidly as a key measure to mitigate human-driven global warming. The understanding of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still limited. In this study, we combined remote sensing and on-site investigations to identify wind farm locations in Inner Mongolia and performed landscape pattern analyses using Fragstats. We explored the impacts of wind farms on land surface temperature (LST) and vegetation net primary productivity (NPP) between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm areas. The results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in 2020. Spatially, wind farms are mainly clustered in three aggregation areas in the center. Further, wind farms increased nighttime LST, with a mean value of 0.23 °C, but had minor impacts on the daytime LST. Moreover, wind farms caused a decline in NPP, especially over forest areas, with an average reduction of 12.37 GC/m². Given the impact of wind farms on LST and NPP, we suggest that the development of wind farms should fully consider their direct and potential impacts. This study provides scientific guidance on the spatial pattern of future wind farms.

The aim is to analyse the landscape diversity (LD) of the northern sub‐area of the Volga River delta landscape using a series of mathematical operations.The work is based on full‐stack landscape works including field experiments. Descriptive method, GIS‐analysis and remote sensing data were used in the work.A set of landscape diversity indices was calculated for the northern sub‐area of the Volga Delta landscape on the basis of mathematical apparatus and the entropic complexity of landscape pattern (or Shannon diversity index) of the studied region was estimated. The results of the analysis made it possible to identify two habitats with rather high landscape diversity indices in this region.LD is one of the most important geographical characteristics of the region and allows assessment of the stability of geosystems to anthropogenic loads, reflection on the nature of economic development and use of geosystems and their conservation potential. By comparing HR indicators and retrospective analysis of economic development of the Volga River Delta, it was found that areas with low landscape diversity index were more often used for agriculture, as single large tracts are easier to adapt to economic needs. Areas with a complex morphological structure and, accordingly, a high level of landscape diversity are generally not subject to most types of economic impact.

Introduction: The selection of an optimal scale or granularity in landscape analysis is pivotal for uncovering inherent patterns and changes driven by processes. Variations in spatial resolution can significantly alter the proportions and distributions of various landscape types, thereby impacting the assessment of landscape patterns. Despite its importance, the scale factor is frequently neglected in studies focusing on long-term landscape dynamics. Methods: Bridging this gap, we utilized remote sensing imagery data from 1986 to 2020 for Lushui City, integrating remote sensing (RS) and geographic information system (GIS) technologies to generate land cover maps. Our focus centered on investigating the sensitivity of landscape pattern indices within the 30-1000m scale. Combining the first scale domain with an information loss assessment model, we identified the optimal granularity for the analysis, conducting a detailed spatiotemporal examination of landscape pattern from 1986 to 2020 using the index analysis method. Results and discussion: The results show that: (1) The dominance of forests in Lushui City, yet reveal a significant increase in construction land area over the study period, primarily driven by the conversion of forest and grassland. (2) Among the 10 examined indices, four (PD, ED, TE, and LSI) demonstrated predictable responses to changes in granularity, while three (PAFEAC, COHESION, AI) exhibited unpredictable stepwise reactions. Three indices (LPI, SHDI, PLAND) displayed minimal regularity to granularity changes. (3) The optimal long-term landscape analysis granularity for Lushui was identified as 100 m. (4) Before 1996, the city's landscape exhibited characteristics of aggregation, good connectivity, and minimal anthropogenic disturbance. However, post-1996, the landscape experienced disruptions, leading to an overall increase in fragmentation. The expansion of cultivated land and construction land due to urbanization has intensified landscape fragmentation. However, policies such as converting cropland to forest and planned ecological civilization initiatives have restored forest coverage and improved landscape cohesion and connectivity in Lushui City. This research offers vital insights for ecological planning and resource management in alpine valley watershed cities, deepening our grasp of landscape pattern evolution. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Using ArcGIS and RS technology, this study took TM images and Landsat images in 2002-2020 as data sources and combined with field research data. The temporal and spatial change characteristics of land use and the dynamic change characteristics of landscape pattern in Liangucheng National reserve were analyzed by using the transfer matrix method and the landscape pattern index method, and the result showed that the main land types of the reserve were grassland, sandy land and woodland, with a total area of 93.08%-93.26%. In 2020, the area of cultivated land, woodland and saline-alkali land increased compared with 2002, while the area of construction land and sandy land decreased, while the area of bare land remained constant. After 2013, woodland and grassland increased steadily, while the area of arable land, sandy land and construction land decreased. The changes of landscape pattern indexes of different types in the reserve were small, and the differences of fractional dimensional index and aggregation index of different land use types were small. The maximum patch index of woodland and sandy land decreased year by year, while the landscape shape index increased slowly year by year, and the degree of fragmentation increased but the increase degree was very small. The main driving forces of land use structure and landscape pattern change were human factors, sand and vegetation factors. On the whole, the landscape fragmentation degree of the reserve remained stable, and the whole ecosystem was not rich in land use, and ecological stability was low. This study is of great significance to land rational planning and ecological restoration in Minqin Liangucheng National Nature Reserve. [ABSTRACT FROM AUTHOR]

Using the land use data set from 2000 to 2020 as the data source, GIS technology was used to explore the characteristics of land use change in Zhaotong city from three aspects: land use transfer matrix, standard deviation ellipse and center of gravity transfer model, and landscape pattern index was used to analyze the landscape pattern evolution from the landscape level and landscape type level. The results show that: (1) The main land types in Zhaotong are forest land, cultivated land and grassland, the growth rate of construction land is the largest, the standard deviation ellipse of grassland is the least obvious, and the distribution of center of gravity of cultivated land, forest land and grassland is relatively stable. (2) From the landscape level, the number of patches increased, the degree of connectivity decreased, the largest patch distribution dominance weakened, the degree of fragmentation increased, the connectivity decreased, the cohesion decreased and the complexity increased. (3) From the landscape type level, the landscape type with the largest patch number, patch density and edge density is cultivated land, the landscape type with the largest patch index and aggregation index is woodland, the landscape type with the largest mean patch fractal dimension is construction land, and the landscape type with the largest interspersion & juxtaposition index is water. [ABSTRACT FROM AUTHOR]

Identifying the evolution of sloping cultivated land (SCL) abandonment and its influencing factors in China's karst mountainous areas (KMA) is highly significant to ensuring the sustainable utilization of cultivated land and ecological environment restoration in mountainous regions. Based on the highresolution remote sensing images and digital elevation model (DEM) of the Huajiang Canyon (HC) from 2004 to 2020, this paper analyzes the distribution pattern, evolutionary rule, driving mechanism, and effect of SCL abandonment in the KMA of southwestern China in the micro spatial unit through the landscape pattern index, buffer analysis, and spatial autocorrelation analysis. The results show that: (1) the abandonment of SCL in the HC mainly occurs in the karst peak cluster and trough valley areas of southwestern, southern, and the northeastern areas, with severe rocky desertification having scarce SCL and relatively little abandoned cultivated land (ACL); (2) The trend of the ACL in KMA from 2004 to 2020 shows continuous growth, and the ACL patches are fragmented; (3) Abandonment of SCL is more pronounced at higher elevations, and the possibility of abandonment of SCL is greater at steeper slopes, with the ACL mainly evolving into low-covered grassland, shrub forests, and Zanthoxylum bungeanum forests; (4) The abandonment of SCL around rural settlements in the HC is a process from far to near, with farmers being the first to abandon SCL far from their settlements, but the abandonment of SCL around the roads is distributed in a fluctuating trend; (5) The abandonment of SCL in KMA is the result of the interaction of numerous factors, with socio-economic factors being the dominant ones. The abandonment of SCL has brought ecological and economic benefits to the KMA, and provided evidence of global greening in the micro-space. The results of this study can provide scientific references for rational land management and ecological environment restoration in mountainous areas around the world. [ABSTRACT FROM AUTHOR]

The landscape pattern controls the energy flow and water sediment process of the watershed, which is an important factor affecting nitrogen and phosphorus loss in small watershed. In order to understand the responses of rainfall-runoff processes and nitrogen and phosphorus exports to landscape pattern, two typical small watersheds, Shuangxi (agroforestry catchment) and Shiqiao (forest catchment) in the upper watershed of Liangzi Lake area of Hubei Province, were selected as the research objects. The water quality and quantity at the outlet of the watersheds were continuously monitored from January to December and a secondary rainfall event in 2016. The results showed that the landscape patterns had a significant impact on responses of rainfall-runoff processes. Compared with Shuangxi, the runoff process in Shiqiao small watershed showed a trend of shorter convergence time, faster runoff response speed and larger runoff modulus. The monthly concentrations of total nitrogen (TN) and total phosphorus (TP) in Shuangxi small watershed were in the range of 1.29~4.28 mg/L and 0.04~0.22 mg/L, which were higher than those of Shiqiao (TN:0.62~1.90 mg/L; TP:0.02~0.11 mg/L), respectively. Nitrate nitrogen (NO-³-N) was the major form of TN in the two small catchments, accounted for 51.8%~88.2%, but the proportion of NO-³-N to TN in Shuangxi small watershed was higher than those of Shiqiao. The concentrations of ammonium (NH+4-N) and nitrite nitrogen (NO-²-N) remained at a low level and exhibited no obvious trend. The emission fluxes of TN and TP in Shuangxi small watershed were in the range of 1.83~20.03 g/s and 0.04~1.45 g/s,which were higher than those of Shiqiao (TN:0.62~10.01 g/s; TP:0.01~0.54g/s), respectively. It was also found that there was a significant positive correlation between the TN and TP emission flux and runoff in the same period. The annual loss intensity of TN and TP in Shuangxi small watershed were 3.68 t/(km² · a) and 0.20 t/(km² · a), which were 1.32 and 1.30 times greater than those of Shiqiao, respectively. The losses of TN and TP in both small watersheds mainly occurred between April and July with frequent rainfall events, accounting for more than 70% of the annual total losses. In conclusion, different landscape patterns had a significant impact on the losses of TN and TP. Accordinglly, rational fertilization to reduce anthropogenic nitrogen and phosphorus loss and optimization of land use to store water and preserve soil are scientific measures to improve the water environment in the watershed. The study could provide more insights for reducing agricultural non-point source pollution in Liangzi Lake region and similar other regions. [ABSTRACT FROM AUTHOR]

The Giant Panda National Park (GPNP) and its surrounding areas constitute a comprehensive ecosystem aimed at protecting the natural habitat of giant pandas, maintaining biodiversity, and ensuring ecological balance. Investigating the spatial correlation between landscape pattern indices and ecological sensitivity (ES) in this area is a crucial step in the construction of ecological civilization and contributes significantly to ecological conservation, restoration, and environmental management. This study utilized Geographic Information Systems (GIS) and Fragstats software to select nine ecological evaluation factors and four landscape pattern indices to comprehensively evaluate the ES and landscape patterns of the GPNP and its surrounding areas. This study discovered that the ecological sensitivity of the GPNP is substantially higher than that of the neighboring areas, with the northern Qionglai Mountain area and the western Minshan area showing the highest concentrations of exceptionally high sensitivity. Highly sensitive areas account for 35.22% of the study region, concentrated in areas within the national park, except the Qinling area, as well as the western and southern surrounding areas. The distribution of moderately sensitive areas is more uniform, while low and insensitive areas are found primarily in the northern and eastern areas, along with the national park's environs. Patch density (PD) within the GPNP is lower than in surrounding areas, with higher PD in the northern and central parts. The landscape division index (DIVISION) decreases from west to east, and the landscape disturbance index (LDI) is significantly lower within the national park than in surrounding areas, with small areas of high LDI in the entire study region. Moran's index analysis of the GPNP and its surrounding areas shows that ecological sensitivity is positively correlated with landscape pattern indices (PD, SPLIT, DIVISION, and LDI), with the strongest correlation between DIVISION and ecological sensitivity. Spatially, the internal areas of the national park have lower landscape pattern indices but higher ecological sensitivity, while the eastern region exhibits severe landscape fragmentation. Major clusters of high and low values are found around the Qionglai-Daxiangling area, indicating that these areas of high ecological sensitivity have complex landscape structures, numerous habitat edges, and significant impacts on biodiversity and ecological processes. Overall, the areas surrounding the GPNP exhibit lower ecological sensitivity levels and higher landscape fragmentation, emphasizing the need for focused ecological protection in the northern part of the QLS region and the western part of the MS region. Additionally, attention should be given to the impact of landscape fragmentation in the surrounding areas in the interior of the GPNP. These results provide scientific evidence for the sustainable development of the GPNP and its surrounding areas. [ABSTRACT FROM AUTHOR]

City parks and green space are vital in coordinating urban space and improving the urban ecological environment. Park and green space accessibility is an essential indication of urban livability. Recently, Hefei has become the city with the fastest GDP growth rate in China, little is known about the accessibility and landscape patterns of parks and green spaces in Hefei. We used GIS network analysis and landscape pattern indices to explore the parks and green spaces in the main urban area of Hefei. The results showed that the accessibility to parks and green spaces in the main urban area of Hefei is poor in walking mode, with less than 50% of people able to reach parks and green spaces within 15 minutes. Contrastingly, the accessibility to parks and green spaces in the main urban area of Hefei is good in cycling mode, with 98.06% of people able to reach parks and green spaces within 15 minutes. Furthermore, the parks and green spaces in Hefei have low dimensional indices, indicating high human intervention and regular landscape shapes, which are not conducive to maintaining urban biodiversity and creating natural green landscapes. The spread indices and fragmentation indices of each administrative district are high, indicating a uniform distribution of parks and green spaces. Our study analyzes the accessibility and landscape patterns of parks and green spaces in Hefei, and it will provide a scientific reference for park and green space planning in Hefei. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) changes driven by ecological restoration and protection projects play a pivotal role in reshaping landscape patterns. However, the specific impacts of these projects on landscape structure remain understudied. In this research, we applied geographically weighted regression (GWR) to analyze the spatial relationships between typical land use expansion and landscape pattern characteristics in the Lesser Khingan Mountains–Sanjiang Plain region between 2017 and 2022. Our results indicate three key findings: (1) Significant spatial heterogeneity exists in the relationship between landscape patterns and land use expansion, which varies across geographic locations; (2) Ecological restoration projects generally reduce fragmentation, dominance, and heterogeneity while enhancing connectivity, particularly in forest and farmland regions. However, excessive land use expansion in certain areas may reverse these positive effects; (3) Landscape complexity increases in high-altitude mountainous regions due to land use expansion but decreases in plains, particularly in forest-to-farmland conversions. These findings provide new insights into how landscape patterns respond to ecological restoration efforts and offer actionable guidance for improving future land use planning and policy decisions. Our study highlights the need to consider local geomorphological factors when designing ecological projects, ensuring that restoration efforts align with regional landscape dynamics to maintain landscape integrity. [ABSTRACT FROM AUTHOR]

This study aims to investigate the changes in landscape metrics with varying spatial resolution from Sentinel-2 (10 m), SPOT 7 (1.5 m), Pleaides (0.5 m), and Worldview-4 (0.3 m) images. We implemented Geographic Object-Based Image Analysis (GEOBIA) techniques to all images to identify 21 land use and land cover (LULC) classes, which were then used to calculate several landscape metrics. We performed the Welch hypothesis testing on the class-level landscape metrics and applied Standardized Principal Component Analysis (PCA) with the correlation matrix to reveal the multivariate pattern of landscape metrics. Our results showed that 10 m and even the 1.5 m spatial resolutions cannot guarantee the identification of all LULC classes, and class areas change with varying spatial resolution (sometimes with 200% differences). Sentinel-2 images have some limitations, specifically from the landscape ecological planning perspective; on the other hand, Pleaides and Worldview-4 seem good alternatives to understand habitats' viability and landscape isolation/connectivity. [ABSTRACT FROM AUTHOR]

Land cover analysis is a key method used to understand past land use patterns and explore the driving forces and processes behind them. This study focuses on land cover in 18 counties and cities of Hainan Island, delving into the driving factors of land cover in specific areas of Hainan Island, including the southern, northern, eastern, western, inland, and coastal regions. The effects of socio-economic factors, landscape pattern, and urban functional units on land cover are considered, and three hypotheses are proposed to explain the observed trends. The results indicate that house prices are positively correlated with construction area, woodlands land, and urban green space, thereby supporting the luxury effect hypothesis on land cover. In addition, construction age was negatively correlated with the woodlands area, confirming the role of the inverse legacy effect hypothesis in land cover. Other relationships between urban functional units and land cover emphasized the importance of the land use hypothesis in land cover planning. These results will help decision-makers and managers to better understand the current drivers of land cover, allowing for a more scientific basis when planning and managing urban land cover. [ABSTRACT FROM AUTHOR]

The Kuye River is the second largest tributary of the middle Yellow River. (1) Background: The Kuye River Basin, a typical erosion area of the Loess Plateau region, faces significant environmental challenges and intense human activities. Balancing environmental sustainability and economic development in this region is urgent. (2) Methods: This study analyses the phenomena, evolutionary processes, driving mechanisms, and future development trends. We assess ecological risks and drivers of land use change using data from 2000, 2005, 2010, 2015, and 2022. (3) Results: Farmland, grassland, and construction land are the main land use types, accounting for 85.63% of the total area. Construction land increased by 7.95 times over 22 years, mainly due to the conversion of woodland, grassland, and farmland. The landscape pattern increased in patches from 4713 in 2000 to 6522 in 2022. Patch density decreased from 0.0945 to 0.0771 between 2000 and 2015, then rose to 0.0788 in 2022. Post-2015, increased human intervention and urban development led to significant landscape fragmentation and higher ecological risk, expected to persist until 2030. Geographical detector analysis identified distance from roads, distance from cities, night light, and precipitation as key factors influencing landscape ecological risk. The interaction of anthropogenic disturbance with other factors showed a non-linear increase in risk, with combined factors having a greater impact than individual ones. (4) Conclusions: The Kuye River Basin's landscape ecological risk is influenced by both natural conditions and human activities. To achieve sustainability, it is essential to protect critical areas, regulate development, and improve the adaptive management of ecological risks through innovative policies, integrated regulations, and technological solutions for ecosystem restoration. These findings provide empirical evidence to support decision-making and underscore the need for comprehensive strategies to mitigate ecological risks and promote sustainable development in the Kuye River Basin. [ABSTRACT FROM AUTHOR]

Landscape pattern is one of the most intuitive manifestations of land use change. In order to evaluate the evolution of land use and landscape pattern in Luoyang city, and then provide reference for land resource management and ecosystem protection in Luoyang City, based on the remote sensing monitoring data of land use in China from 2000 to 2020 and the PLUS model, the changes of land use type and landscape pattern under the inertia development scenario and ecological protection scenario in Luoyang City in 2030 were simulated and predicted. The results show that from 2000 to 2020, the land use types of Luoyang are mainly cultivated land, forest land and grassland, and the overall regional land use fluctuation is small, and land use is in the development stage. In 2030, under the inertia development scenario, the land evolution rate of Luoyang City is increased, and the ecological land use shows a shrinking trend. Under the ecological protection scenario, the expansion of construction land is limited, the ecological land area increased, and the regional ecological benefit increased significantly. [ABSTRACT FROM AUTHOR]

Determining an appropriate grain size is crucial in landscape pattern analysis and ecological research. In order gain deeper insights into the spatial diversity and dynamic characteristics of landscape pattern, based on the survey data of the 12 hm² large plot in Jiangxi Guanshan National Nature Reserve in 2015 and 2020, the grain size effect of landscape indices in eight different landscape types within the range of 5-50 meters were analyzed; the variation coefficients were used to reveal the changing characteristics of different landscape pattern indices as the grain size increased, and the optimal grain size was selected based on the inflection points of changes in various landscape indices. The results were as follows: (1) Based on the importance value analysis, eight different landscape types were identified in the arbor layer of the plot, including forest gap, bamboo forest, Cunninghamia lanceolata forest, Pinus massoniana forest, broad-leaved forest, bamboo and Cunninghamia lanceolata mixed forest, bamboo and Pinus massoniana mixed forest, Cunninghamia lanceolata and Pinus massoniana mixed forest. (2) The overall distribution of patches in the landscape was relatively balanced, and the distribution pattern remained relatively stable. At larger spatial grain size, the aggregation of each landscape type increased, leading to a higher probability of landscape merging. In contrast, at smaller granularity, there was a noticeable trend of fragmentation in landscape types, providing a more comprehensive display of the quantity, density, and shape of each landscape type. Patch density (PD), number of patches (NP), edge density (ED), landscape shape index (LSI), mean fractal dimension index (FRAC_MN), contagion index (CONTAG) exhibited significant negative correlations with increasing grain size, while mean patch area (AREA_MN), Shannon's diversity index (SHDI), Shannon's evenness index (SHEI) exhibited significant positive correlations with increasing grain size. (3) The coefficients of variation for landscape indices PD, NP, ED, LSI, and AREA_MN were the highest, combining landscape structural stability and diversity, the changes in different landscape indices were primarily concentrated around the inflection point at 5 meters. These results illustrate the diversity of landscape types, with the coefficient of variation reflecting the most sensitive characteristics of landscape pattern changes. This study suggests that a grain size of 5 meters is optimal for studying the landscape pattern of subtropical evergreen broad-leaved forests in Guanshan, Jiangxi. This study provides favorable evidence for the restoration of forest resources and stand stucture. [ABSTRACT FROM AUTHOR]

The study of the spatio-temporal distribution and evolution trends of water resources in large regions plays an important role in the study of regional water resource planning, regional economic and social development, and water disasters. In this study, a Landsat multi-index relationship and water probability thresholding method is developed based on the Google Earth Engine (GEE) platform, which can support the integration of multiple Landsat satellites. The algorithm jointly combines multiple remote sensing metrics along with the calculation of water probability to produce an interannual water body product for the Jianghan Plain on a 20-year time series. The results indicate that the Landsat multi-index relationship algorithm used in this study has high accuracy in extracting long-term water bodies in extensive, flat terrain areas such as the Jianghan Plain, with an overall accuracy (OA) of 97.23%. By analyzing the water body products and landscape patterns, we have identified the following features: (1) From 2002 to 2021, the changes in river water bodies in the Jianghan Plain were relatively small, and some lakes experienced a shrinkage in area. Overall, there is a strong correlation between water distribution and precipitation. (2) The complexity index of water bodies shows a strong negative correlation with effective irrigation area and population, indicating a strong mutual influence between water bodies and socio-economic activities. (3) Through the study of the distribution characteristics of built-up areas and the water system, it was found that for large rivers, the larger the size of the river, the more built-up areas are nearby. Most extensive built-up areas are located near large rivers. This study contributes to providing methods and data support for urban planning, water resource management, and disaster research in the Jianghan Plain. [ABSTRACT FROM AUTHOR]

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Context: Birds, as indicators of biodiversity, are experiencing habitat reduction and loss due to landscape changes. Evidence is mounting that the response of bird richness to landscape patterns remains controversial on a global scale. In this study, we conducted a quantitative global synthesis to gain a comprehensive understanding of this relationship. Our findings contribute to the development of bird conservation strategies that align with the objectives of SDG15. Objective: Through a quantitative review, this study investigated the effects of landscape patterns on bird richness and analyzed the sources of heterogeneity in the results. Methods: A random-effects model was utilized to merge the impacts of landscape metrics on bird richness, and a meta-regression analysis was performed to investigate the origins of heterogeneity. Results: The review encompassed 101 articles from 51 countries worldwide. Field sampling emerged as the primary method for acquiring bird data, with multiple linear regression and generalized linear models as the main analytical approaches. The meta-analysis results highlighted landscape area as a crucial factor influencing bird richness. Regarding landscape composition, the proportions of forests, shrublands, and water bodies positively impacted bird richness, while agricultural land and urban land had negative effects. The relationship between landscape complexity and bird richness is influenced by factors, including net primary productivity (NPP) and precipitation. Landscape heterogeneity was identified as a contributing factor to increased species richness. Conclusion: Compared to landscape complexity, indicators of landscape composition and heterogeneity are more suitable as reference tools for bird conservation. The results of landscape complexity exhibit variation. Moreover, our findings underscore the crucial role of preserving forested areas in supporting bird diversity, emphasizing the necessity to account for regional variations when establishing forest cover thresholds. [ABSTRACT FROM AUTHOR]

Small-scale agroforestry patches possess irreplaceable value compared to large-scale patches. In southwestern mountainous cities of China, the complex terrain and urbanization have led to the presence of numerous small, fragmented agroforestry patches around urban areas. These patches serve as crucial habitats for endemic species and provide essential space for wild food sources, thereby contributing to a range of ecosystem services. Consequently, their proper conservation and utilization planning are of paramount importance. This study investigates the transformation characteristics of landscape patterns of mountainous small-scale agroforestry patches and their constituent elements across urban–rural gradients, identifying the driving factors behind these transformations to support conservation and utilization planning. From an urban–rural gradient perspective, four directional transects were selected and divided into uniform sample grids. Using Fragstats 4.3, landscape indices of small-scale agroforestry patches were calculated, analyzing the transformation characteristics of these patches and their elements across different gradients. Spearman correlation coefficients in SPSS were employed to assess the influence of terrain and relevant anthropogenic factors on the transformation of agroforestry patches. The findings reveal the following: (1) Small-scale agroforestry patches and their elements exhibit similar patterns in terms of size, fragmentation, dispersion, and connectivity, showing an "increasing trend in size and connectivity, decreasing fragmentation, and fluctuating dispersion" from urban centers to natural areas, with slight variations in orchard patches. However, patch cohesion and shape complexity display nonlinear differentiated transformation characteristics. (2) Overall, small-scale agroforestry patches are significantly influenced by anthropogenic construction factors, with the landscape pattern of forest patches notably affected by terrain factors. (3) Across urban–rural gradient zones, the landscape patterns of small-scale agroforestry patches in urban centers, suburbs, and rural natural areas are more affected by terrain factors, whereas those in urban construction zones are significantly influenced by anthropogenic construction factors. The findings of this study provide a scientific basis for the conservation and planning of mountainous small-scale agroforestry patches. [ABSTRACT FROM AUTHOR]