Landscape Ecology Research Articles

Eyes on nature: Embedded vision cameras for terrestrial biodiversity monitoring

Abstract We need comprehensive information to manage and protect biodiversity in the face of global environmental challenges, and artificial intelligence is required to generate that information from vast amounts of biodiversity data. Currently, vision‐based monitoring methods are heterogenous; they poorly cover spatial and temporal dimensions, overly depend on humans, and are not reactive enough for adaptive management. To mitigate these issues, we present a portable, modular, affordable and low‐power device with embedded vision for biodiversity monitoring of a wide range of terrestrial taxa. Our camera uses interchangeable lenses to resolve barely visible and remote targets, as well as customisable algorithms for blob detection, region‐of‐interest classification and object detection to automatically identify them. We showcase our system in six use cases from ethology, landscape ecology, agronomy, pollination ecology, conservation biology and phenology disciplines. Using the same devices with different setups, we discovered bats feeding on durian tree flowers, monitored flying bats and their insect prey, identified nocturnal insect pests in paddy fields, detected bees visiting rapeseed crop flowers, triggered real‐time alerts for waterfowl and tracked flower phenology over months. We measured classification accuracies (i.e. F1‐scores) between 55% and 95% in our field surveys and used them to standardise observations over highly resolved time scales. Our cameras are amenable to situations where automated vision‐based monitoring is required off the grid, in natural and agricultural ecosystems, and in particular for quantifying species interactions. Embedded vision devices such as this will help addressing global biodiversity challenges and facilitate a technology‐aided agricultural systems transformation.

Multilayer networks in landscape ecology: a case study to assess changes in aquatic habitat connectivity for flying and non-flying benthic macroinvertebrates in a Danube floodplain

ContextIn efforts to mitigate anthropogenic impacts on floodplain biodiversity, restoration measures that enhance habitat connectivity have been applied. However, these approaches have either neglected the spatial position of water bodies or the dynamic nature of the floodplain ecosystem.ObjectivesThis study focuses on the novel application of the multilayer network framework to assess changes in the aquatic habitat connectivity in floodplains, showcasing its application in the context of aquatic passive dispersal (drift) of two indicator groups of benthic macroinvertebrates (Oligochaetes and Chironomids)MethodsOur case study is located in the Donau-Auen National Park in Austria and follows floodplain restoration measures (side-channel reconnection) applied in the mid-1990s. Multilayer networks were constructed to represent the conditions before, short-term, and long-term after restoration to quantify habitat connectivity across inundation frequencies. Our network analyses involved multilayer correlation, static and dynamic monolayer centralities (centrality profiles), and multilayer centrality assessments. We used a Partial Least Squares Regression analysis as a variable selection tool to identify which centrality measures better explained the variance in α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} diversity and Local Contributions to Beta Diversity (LCBD) of benthic macroinvertebrates.ResultsIn the short-term, our connectivity analysis indicated an increase in habitat connectivity. However, centrality profiles, multilayer correlation, and multilayer centrality techniques identified a long-term decrease in connectivity. Multilayer centralities had higher Variable Importance in the Projection scores (VIP) than their monolayer counterpart in explaining variations in α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} diversity and LCBD for strict aquatic dispersers. Meanwhile, for flying dispersers, monolayer centralities had the highest VIP scores for explaining α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} diversity.ConclusionsThis study underscores the relevance of integrating dynamic aspects of water-mediated transport beyond traditional pairwise distances. Although in this study we apply this tool by showcasing the aquatic passive dispersal mode, the application of this method can be extended to other dispersal modes and representative abilities for diverse groups of aquatic organisms. The expanding cross-disciplinary applications and open-source tool development for multilayer networks offer practical implications for planning and evaluating management measures.

Regional variation in the landscape ecology of West Nile virus sentinel chicken seroconversion in Florida.

How landscape composition and configuration impact the distribution of multi-vector and multi-host mosquito vector-borne disease systems, such as West Nile virus (WNV), remains challenging because of complex habitat and resource requirements by hosts and vectors that affect transmission opportunities. We examined correlations between landscape composition and configuration and 2018 WNV sentinel chicken seroconversion in Florida, USA across the state and within five National Oceanic Atmospheric Administration (NOAA) bioclimatic regions to understand strength and variation of landscape effects during an elevated transmission year. Although few landscape studies have examined WNV in Florida, we expected higher percentages of residential or medium-developed landscapes and more fragmented landscapes would be positively correlated with WNV seroconversion owing to the main mosquito vector habitats and avian host distributions. However, we expected to find variation in the importance of forest, wetland, and agriculture landscapes across bioclimatic regions in the state. WNV seroconversion rates were calculated using Florida 2018 Department of Health WNV sentinel chicken seroconversion data from 187 flocks maintained by mosquito control programs. Percent land cover and edge density metrics were calculated for multiple land cover classes and within multiple buffer distances from chicken coops using 2019 National Land Cover Data. We used binomial generalized linear mixed effects models to calculate the importance of landscape metrics to WNV seroconversion. We found no statewide predictors of seroconversion, but as expected, the importance of landscape varied across regions. In the north-central part of the state, we found higher seroconversion in less populated suburban areas while higher seroconversion in south-central Florida was correlated with fragmented forested areas within 0.5 km of coops and intact woody wetland areas within 2 km of coops. This work corroborates previous findings that consistent landscape predictors of WNV are difficult to identify across broader geographic areas and sets the stage for additional work that incorporates climate and landscapes interactions for a greater understanding of WNV ecology in this geographic region.

Joint guarantee rate index assessment of the contribution of agricultural water-saving measures to river ecological flow in water shortage areas

Reconciling higher ecological water demands and economic purposes with finite freshwater resources remains one of the great management dilemmas. Low water efficiency and large water consumption in agricultural irrigation hinder the protection of river ecological flow in the water shortage areas of Northwest China. By analyzing the surplus and shortage of river ecological protection targets, the intensity guarantee rate index is innovatively proposed to quantitatively evaluate the important contribution of improved water-saving measures for river flow restoration. It compensates for the shortcomings of the duration guarantee rate index in evaluation that may mask ecological problems. Considering ecological baseflow, fish species, and landscape water demand, the ecological flow interval (6.00–12.42 m3/s) was determined. Three scenarios are highlighted for different typical years and irrigation regimes in combination with planting structure adjustment and irrigation water utilization coefficient. In 75 %, 90 %, and 95 % typical years, the maximum total annual water-savings (Scenario 3) are 57.3, 57.1, and 87.2 million m3 (sufficient irrigation); 32.2, 33.9, and 35.5 million m3 (deficit irrigation) respectively. The guarantee degree of river ecological flow under both irrigation regimes increased from the previous 65.6 % to a maximum of 91.7 % and 81.2 %. The increase in the daily guarantee rate and decrease in the intensity guarantee rate under the aforementioned three scenarios indicate a reduction of damage depth and duration of ecological flow. By using a quantitative study, it is pointed out that improving agricultural water-saving is a reasonable and necessary way to protect the river flow.

Ecological Suitability Evaluation of City Construction Based on Landscape Ecological Analysis

Ecological suitability evaluation is a critical component of regional sustainable development and construction, serving as a foundation for optimizing spatial patterns of regional growth. This is particularly pertinent in karst mountainous regions characterized by limited land resources and heightened ecosystem vulnerability, where a quantitative assessment of ecological suitability for land development is both crucial and urgent. Based on the fundamental principles of structural and functional dynamics in landscape ecology, this study focuses on Gui’an New Area, a designated urban development zone situated in the karst landscape of Guizhou Province. An index system was established encompassing three dimensions: ecological elements, ecological significance, and ecological resilience, utilizing the integrated ecological resistance (IER) model to evaluate the suitability of regional development and construction. The results reveal that the eastern region exhibits higher suitability compared to the central and western regions, with the northwest region demonstrating the lowest suitability overall. Relatively speaking, the evaluation of geological environment suitability and the comprehensive ecological constraints associated with development and construction indicates that the areas currently planned and ongoing reflect flat terrain and low ecological risk. Furthermore, within the scope of ecosystem dynamic adaptation, developmental activities in these regions exert minimal impact on the natural ecosystem, thereby demonstrating a high suitability for development and construction. In terms of future key development zones, areas with gentle slopes ranging from 8 to 15 degrees are recommended, aligning with the actual requirements for cultivated land protection. The total area designated as prohibited development zones constitutes the smallest proportion, representing only 9.45%, which is significantly lower than that of priority development zones (38.75%) and moderate development zones (22.45%). From the perspective of landscape ecology, this paper provides a comprehensive investigation into the ecological suitability evaluation system for development and construction in the karst regions of Southwest China, offering valuable insights for assessing ecological suitability in similar areas.

Oncometabolites at the crossroads of genetic, epigenetic and ecological alterations in cancer.

By the time a tumor reaches clinical detectability, it contains around 108-109 cells. However, during tumor formation, significant cell loss occurs due to cell death. In some estimates, it could take up to a thousand cell generations, over a ~ 20-year life-span of a tumor, to reach clinical detectability, which would correspond to a "theoretical" generation of ~1030 cells. These rough calculations indicate that cancers are under negative selection. The fact that they thrive implies that they "evolve", and that their evolutionary trajectories are shaped by the pressure of the environment. Evolvability of a cancer is a function of its heterogeneity, which could be at the genetic, epigenetic, and ecological/microenvironmental levels [1]. These principles were summarized in a proposed classification in which Evo (evolutionary) and Eco (ecological) indexes are used to label cancers[1]. The Evo index addresses cancer cell-autonomous heterogeneity (genetic/epigenetic). The Eco index describes the ecological landscape (non-cell-autonomous) in terms of hazards to cancer survival and resources available. The reciprocal influence of Evo and Eco components is critical, as it can trigger self-sustaining loops that shape cancer evolvability [2]. Among the various hallmarks of cancer [3], metabolic alterations appear unique in that they intersect with both Evo and Eco components. This is partly because altered metabolism leads to the accumulation of oncometabolites. These oncometabolites have traditionally been viewed as mediators of non-cell-autonomous alterations in the cancer microenvironment. However, they are now increasingly recognized as inducers of genetic and epigenetic modifications. Thus, oncometabolites are uniquely positioned at the crossroads of genetic, epigenetic and ecological alterations in cancer. In this review, the mechanisms of action of oncometabolites will be summarized, together with their roles in the Evo and Eco phenotypic components of cancer evolvability. An evolutionary perspective of the impact of oncometabolites on the natural history of cancer will be presented.

Hierarchical Analysis of Miombo Woodland Spatial Dynamics in Lualaba Province (Democratic Republic of the Congo), 1990–2024: Integrating Remote Sensing and Landscape Ecology Techniques

Lualaba Province, located in the southeastern Democratic Republic of the Congo (DRC), consists of five territories with varied dominant land uses: agriculture (Dilolo, Kapanga, and Musumba in the west) and mining (Mutshatsha and Lubudi in the east). The province also includes protected areas with significant governance challenges. The tropical dry forests that cover the unique Miombo woodland of Lualaba are threatened by deforestation, which poses risks to biodiversity and local livelihoods that depend on these forests for agriculture and forestry. To quantify the spatio-temporal dynamics of Lualaba’s landscape, we utilized Landsat images from 1990 to 2024, supported by a Random Forest Classifier. Landscape metrics were calculated at multiple hierarchical levels: province, territory, and protected areas. A key contribution of this work is its identification of pronounced deforestation trends in the unique Miombo woodlands, where the overall woodland cover has declined dramatically from 62.9% to less than 25%. This is coupled with a marked increase in landscape fragmentation, isolation of remaining woodland patches, and a shift toward more heterogeneous land use patterns, as evidenced by the Shannon diversity index. Unlike previous research, our study distinguishes between the dynamics in agricultural territories—which are particularly vulnerable to deforestation—and those in mining areas, where Miombo forest cover remains more intact but is still under threat. This nuanced distinction between land use types offers critical insights into the differential impacts of economic activities on the landscape. Our study also uncovers significant deforestation within protected areas, underscoring the failure of current governance structures to safeguard these critical ecosystems. This comprehensive analysis offers a novel contribution to the literature by linking the spatial patterns of deforestation to both agricultural and mining pressures while simultaneously highlighting the governance challenges that exacerbate landscape transformation. Lualaba’s Miombo woodlands are at a critical juncture, and without urgent, coordinated intervention from local and international stakeholders, the ecological and socio-economic foundations of the region will be irreversibly compromised. Urgent action is needed to implement land conservation policies, promote sustainable agricultural practices, strengthen Miombo woodland regulation enforcement, and actively support protected areas.

Author Correction: Remote sensing analysis of spatiotemporal impacts of anthropogenic influence on mountain landscape ecology in Pir Chinasi national park

Author Correction: Remote sensing analysis of spatiotemporal impacts of anthropogenic influence on mountain landscape ecology in Pir Chinasi national park

The Effects of Spatial Structure and Development Intensity of the Urban Landscape on Bird Biodiversity in Anhui Province

Exploring the factors that drive changes in biodiversity is a hot and critically important topic in landscape ecology and biogeography. In this study, semi-structured citizen science data and bird distribution maps were employed to gather data from 2015 to 2020 for the calculation of bird species richness, the Shannon index, and the Pielou index in Anhui Province. These metrics were utilized to assess avian biodiversity and to elucidate the spatial patterns of biodiversity distribution across the region. In this research, a structural equation model (SEM) was utilized to investigate the relationships between the three dimensions of landscape spatial structure, urban development intensity, and environmental factors on bird biodiversity, and a conceptual framework was established to identify the key driving factors. The validity, reliability, and fit of the hypothesized model were substantiated through rigorous testing, demonstrating its reasonableness. The results indicate the following: (1) In landscape spatial structure, landscape composition and configuration play crucial roles in influencing bird diversity. An increased proportion of cultivated land negatively impacts bird diversity, whereas the expansion of forested areas promotes it. At the configuration level, the Largest Patch Index (LPI) significantly enhances bird diversity, serving as the primary driving force. Landscape spatial structure affects bird diversity both directly, through its composition, and indirectly, through its configuration. (2) The dimension of urban development intensity generally shows significant negative impacts; among these, GDP has the greatest comprehensive impact and shows a significant negative impact. (3) Topography has the greatest overall impact on bird diversity among the environmental factors, with a predominantly direct positive effect. (4) Overall, urban landscape spatial structure and urban development intensity are the main driving forces of bird diversity in Anhui Province, the greatest of which is the direct effect of the urban development intensity. These results provide an important scientific basis for landscape planning and ecological protection and provide inspiration for assessing the driving factors of animal and plant diversity in other regions.

Blinded by the view? An ecological landscape is more than just pretty scenery

Report from the Research Council of Norway’s conference on “The changing landscape”, Oslo, 27-28 March 2001.

Phytoclimatological study in the high plains of Sétif: application of the bioclimatic classification system (Algeria)

The Global Bioclimatic Classification System (WBCS) by Rivas-Martínez is an effective approach to reflect and study the role of climate in determining the potential distribution of natural vegetation at various temporal and spatial scales. In particular, the diversity of physical characteristics in the Setifian high plains leads to the complexity of large-scale phytogeographic belts. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), have been created for the study area based on Rivas-Martínez's global bioclimatic classification system for current and future climate scenarios, using the parallel climate model from CMIP5 (Coupled Model Intercomparison Project) under the intermediate greenhouse gas emission scenario (RCP4.5). Precipitation and temperature data from the "WorldClim" dataset were used as the data source. These climatic variables were reduced to a spatial resolution of 1 km. The objective is to understand how the climate is evolving in this region, what the consequences are, and what the future holds for these natural ecosystems. A phytosociological study complemented by satellite image analysis reveals a high diversity of pre-forestry formations. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and the magnitude of change, 2) identify and locate the new projected isobioclimates, and 3) explore the compositional changes in vegetation types among analogous isobioclimatic zones. The ordination of the relationships between vegetation and bioclimates shows a strong correlation between Rivas-Martinez indices and the distribution and composition of vegetation. Changes in ombrotype, thermotype, bioclimate, ombrotype, and isobioclimate differed between the current and future series. The resulting map presents 9 isobioclimatic units, which are advantageous for confirming the diagnosis of bioclimatic characteristics and describing the relationships between climatic variables and the corresponding distributions of natural vegetation. We identified eight different isobioclimates for the current period (1979-2013) and seven for the future period (2050), three thermotype horizons for both the current and future periods, and finally, four ombrotype horizons for the period (1979-2013), while two ombrohorizons represent the period (2050). This approach is useful for explaining territorial diversity in environmental applications related to ecological adaptation assessment, nature conservation, landscape regionalization, and planning.

Landscape Ecological Risk Assessment and Evaluation of Influencing Factors of Jinsha River Basin in Yunnan Province Based on Land Use/Cover Change

Landscape Ecological Risk Assessment and Evaluation of Influencing Factors of Jinsha River Basin in Yunnan Province Based on Land Use/Cover Change

Spatial Pattern and Influence Mechanisms of Forest Land Quality under the Background of Carbon Peaking and Carbon Neutrality: A Case Study in Kaizhou District, Chongqing, China

Since the goals of carbon peaking and carbon neutrality have been established, forest carbon sinks have garnered significant attention. As a fundamental component of forest carbon sinks, the quality of forest land significantly influences the carbon sink capacity of forests. This study utilized Kaizhou District, Chongqing City, a typical forest area as a case study, and used the correction method, factor method, CASA model, landscape ecology indexes, and canonical correlation analysis to evaluate the level of forest land quality and reveal the spatial distribution pattern and influencing mechanisms of forest land quality. The results showed that: (i) The quality index of public welfare forest land was distributed in [37.89, 148.15], and each quality level was diversified in space. The quality index of commodity forest land was distributed in [40.00, 92.67], and some high-quality forest land appeared in the transition zone of each region; (ii) The forest land quality index and the amount of net primary productivity passed the correlation test. Primary net productivity was higher on forest land with a high-quality index and lower on forest area with a low-quality index; (iii) public welfare forest land was mainly positively affected by community structure, average annual precipitation, average annual temperature, and soil moisture. Commodity forest land was mainly positively affected by average annual temperature, soil moisture, and slope aspect. However, landform had a significant negative impact on the two types of forest land. Given these findings, we also proposed a series of measures aimed at promoting the sustainable development of research on regional forest land.

The Landscape Ecological Quality of Two Different Farm Management Models: Polyculture Agroforestry vs. Conventional

Low-intensity, diversified agricultural land use is needed to counteract the current decline in agrobiodiversity. Landscape ecology tools can support agrobiodiversity assessment efforts by investigating biodiversity-related ecological functions (pattern–process paradigm). In this study, we test a toolkit of landscape ecology analyses to compare different farm management models: polyculture agroforestry (POLY) vs. conventional monoculture crop management (CV). Farm-scale analyses are applied on temperate alluvial sites (Po Plain, Northern Italy), as part of a broader multi-scale analytical approach. We analyze the landscape ecological quality through landscape matrix composition, patch shape complexity, diversity, metastability, and connectivity indices. We assess farm differences through multivariate analyses and t-tests and test a farm classification tool, namely, a scoring system based on the relative contributions of POLY farms, considering their deviation from a local CV baseline. The results showed a separate ecological behavior of the two models. The POLY model showed better performance, with significant positive contributions to the forest and semi-natural component equipment and diversity; agricultural component diversity, metastability; total farm diversity, metastability, connectivity, and circuitry. A reference matrix for the ecological interpretation of the results is provided. Farm classification provides a quick synthesis of such contributions, facilitating farm comparisons. The methodology has a low cost and quickly provides information on ongoing ecological processes resulting from specific farm management practices; it is intended to complement field-scale assessments and could help to meet the need for a partially outcome-based assessment of good farm practice.

Remote Sensing Evaluation and Monitoring of Spatial and Temporal Changes in Ecological Environmental Quality in Coal Mining-Intensive Cities

In coal-dependent urban economies, the dichotomy between resource exploitation and ecological conservation presents a pronounced challenge. Traditional remote sensing ecological assessments often overlook the interplay between mining activities and urban environmental dynamics. To address this gap, researchers developed an innovative Resource-Based City Ecological Index (RCEI), anchored in a Pressure–State–Response (PSR) framework and synthesized from six discrete ecological indicators. Utilizing geodetic remote sensing data, the RCEI facilitated a comprehensive spatiotemporal analysis of Jincheng City’s ecological quality from 1990 to 2022. The findings corroborated the RCEI’s efficacy in providing a nuanced portrayal of the ecological state within mining regions. (1) Jincheng City’s ecological quality predominantly sustained a mudhopper-tier status, exhibiting an overarching trend of amelioration throughout the study period. (2) Disparities in ecological landscape quality were pronounced at the county level, with Moran’s Index exceeding 0.9, signifying a clustered ecological quality pattern. High–high (H–H) zones were prevalent in areas of elevated altitude and dense vegetation, whereas low–low (L–L) zones were prevalent in urban and mining sectors. (3) Further, a buffer zone analysis of two coal mines, differing in their mining chronology, geographical positioning, and operational status, elucidated the ecological impact exerted over a 32-year trajectory. These insights furnish a robust scientific and technical foundation for resource-centric cities to fortify ecological safeguarding and to advance sustainable development stratagems.

Environmental Factors Drive the Biogeographic Pattern of Hippophae rhamnoides Root Endophytic Fungal Diversity in the Arid Regions of Northwest China.

Hippophae rhamnoides subsp. sinensis Rousi (Abbrev. H. rhamnoides) stands as a vital botanical asset in ameliorating the ecological landscape of the arid regions in Northwest China, where its rhizospheric microorganisms serve as linchpins in its growth and developmental dynamics. This study aimed to explore the community structure characteristics and origin differences of root endophytic fungi in H. rhamnoides. Samples were collected from 25 areas where H. rhamnoides is naturally distributed along an altitude gradient in the northwest region. Then, endophytic fungi from different regions were analyzed by using high-throughput sequencing technology to compare the structural characteristics of endophytic fungi and examine their association with environmental factors. FUNGuild was employed to analyze the community structure and functions of endophytic fungi, and the results showed that each region had its own dominant endophytic fungal flora, demonstrating the differences in origin of endophytic fungi, and the specific endophytic flora acquired from the original soil in the growing season of H. rhamnoides will help us construct the microecological community structure. Furthermore, the study identified and assessed the diversity of fungi, elucidating the species structure and highlighting dominant species. The RDA analysis revealed that available phosphorus (AP), available potassium (AK), and total nitrogen (TN) exhibit significant correlations with the composition and diversity of root-associated fungi. In conclusion, the fungal community structure is similar within the same region, while significant differences exist in the taxonomic structure and biodiversity among different regions. These findings shed light on the intricate interplay and mechanisms governing the ecological restoration of H. rhamnoides, offering a valuable framework for advancing green ecology initiatives and harnessing the potential of root-associated microorganisms in this species.

Analysis of changes and driving forces of landscape pattern vulnerability at Qianping Reservoir in Central China.

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.

How many parameters are needed to represent polar sea ice surface patterns and heterogeneity?

Abstract. Sea ice surface patterns encode more information than can be represented solely by the ice fraction. The aim of this paper is thus to establish the importance of using a broader set of surface characterization metrics and to identify a minimal set of such metrics that may be useful for representing sea ice in Earth system models. Large-eddy simulations of the atmospheric boundary layer over various idealized sea ice patterns, with equivalent ice fractions and average floe areas, demonstrate that the spatial organization of ice and water can play a crucial role in determining boundary layer structures. Thus, various methods used to quantify heterogeneity in categorical lattice-based spatial data, such as those used in landscape ecology and Geographic Information System (GIS) studies, are employed here on a set of recently declassified high-resolution sea ice surface images. It is found that, in conjunction with ice fraction, patch density (representing the fragmentation of the surface), the splitting index (representing variability in patch size), and the perimeter–area fractal dimension (representing the tortuosity of the interface) are all required to describe the two-dimensional pattern exhibited by a sea ice surface. For surfaces with anisotropic patterns, the orientation of the surface relative to the mean wind is also needed. Finally, scaling laws are derived for these relevant landscape metrics, allowing for their estimation using aggregated spatial sea ice surface data at any resolution. The methods used in and the results gained from this study represent a first step toward developing further methods for quantifying variability in polar sea ice surfaces and for parameterizing mixed ice–water surfaces in coarse geophysical models.

Landscape transition-induced ecological risk modeling using GIS and remote sensing techniques: a case of Saint Martin Island, Bangladesh.

Uncontrolled human activity and nature are causing the deterioration of Saint Martin Island, Bangladesh's only tropical island, necessitating sustainable land use strategies and ecological practices. Therefore, the present study measures the land use/cover transition from 1974 to 2021, predicts 2032 and 2042, and constructs the spatiotemporal features of the Landscape Ecological Risk Index based on land use changes. The study utilized Maximum Likelihood Classification (MLC) on Landsat images from 1974, 1988, 2001, 2013, and Sentinel 2B in 2021, achieving ≥ 80% accuracy. The MLP-MC approach was also used to predict 2032 and 2042 LULC change patterns. The eco-risk index was developed using landscape disturbance and vulnerability indices, Bayesian Kriging interpolation, and spatial autocorrelations to indicate spatial clustering. The research found that settlements increased from 2.06 to 28.62ha between 1974 and 2021 and would cover 41.22ha in 2042, causing considerable losses in agricultural areas, waterbodies, sand, coral reefs, and vegetation. The area under study showed a more uniform and homogenous environment as Shannon's diversity and evenness scores decreased. The ecological risk of Saint Martin Island increased from 4.31 to 31.05ha between 1974 and 2042 due to natural and human factors like erosion, tidal bores, population growth, coral mining, habitat destruction, and intensive agricultural practices and tourism, primarily in Nazrul Para, Galachipa, and Western Dakhin Para. The findings will benefit St. Martin Island stakeholders and policymakers by providing insights into current and potential landscape changes and land eco-management.

Application and prospect of landscape ecology in territorial spatial planning.

Territorial spatial planning could achieve the integration of various plans, resulting in a unified "multi-plan integration" map. Such planning emphasizes the efficient use of territorial spatial patterns and structures to ensure functional perfection, and serves as the spatial framework for building a modern socialist country, particularly in the areas of ecological security and ecological civilization. The past few decades have seen rapid advances in the development of landscape ecology in China. The core concept of "pattern-process-function" has gained significant progress and been widely applied in the initial phase of territorial spatial planning at various levels. We outlined the advancements in the territorial spatial planning system and the core research theories and technologies in landscape ecology. We discussed the progress and shortcomings of key theories and methods of landscape ecology in practical applications of territorial spatial planning, such as ecological security patterns, pattern and process, and scale effects. We proposed the future application of landscape ecology theories and technologies in territorial spatial planning, including overall ecological effects, scale effects, and regional ecological network optimization. Future developments in landscape ecology, especially research on the "human-place-ecology" coupling based on the latest Big Data and AI technology for sustainable development, will provide robust theoretical and methodological supports for the scientific formulation of territorial spatial planning in China.