Edge Density Research Articles

The cooling capacity of urban vegetation and its driving force under extreme hot weather: A comparative study between dry-hot and humid-hot cities

Extreme heat events in cities necessitate closer examination of urban vegetation’ capacity to mitigate extreme hot weather. However, the cooling capacity of vegetation (CCV) and its driving forces of 2D and 3D landscape metrics under extreme hot weather conditions in dry-hot and humid-hot cities, particularly within different functional zones is still not well understood. The results indicate that the CCV is more pronounced in humid-hot cities than in dry-hot cities, particularly during periods of extreme hot weather. This CCV varied significantly across different functional zones, being the lowest in commercial zones and the highest in green space zones. Moreover, residential zones in humid-hot cities have higher CCV when the weather is more extreme. In dry-hot and humid-hot cities, urban vegetation landscape configuration metrics (such as patch and edge densities) contribute significantly to the CCV, and landscape composition (vegetation coverage) also contributes, with a significant increase during periods of extreme hot weather, particularly in humid-hot cities. Additionally, the 3D building morphology plays a crucial role in moderating the CCV; however, its impact diminishes during extreme heat. We also found that the CCV does not increase further after vegetation coverage is greater than 30–40 % in dry-hot cities, compared to approximately 60–80 % in humid-hot cities. The CCV increased nonlinearly with increasing urban vegetation largest patch index and decreasing urban vegetation patch density in dry-hot and humid-hot cities, with different thresholds of vegetation coverage and largest patch index under normal and extreme hot weather. A higher building height increased the CCV in humid-hot cities and reduced the CCV in dry-hot cities, particularly under extreme hot weather, and sparse high-rise buildings were better suited to humid-hot cities for increasing urban CCV. These findings provide valuable insights for urban planners to enhance the urban CCV, contributing to long-term urban resilience and public health protection during extreme heat events.

Exploring the physics of a high-performance H-mode scenario with small ELMs at low collisionality in JET with Be/W wall

A new H-mode regime at low density and low edge safety factor (q 95 = 3.2, with Ip = 3 MA) that combines high energy confinement, stationary conditions for density and radiation and small Edge Localized Modes (ELMs) have been found in JET with Be/W wall. Such a regime is achieved by operating without external gas puffing, leading to a decrease in the edge density and a substantial increase in rotation and ion temperature in both the pedestal and the core region. Transport modelling shows a reduction of the turbulence, which starts in the pedestal region and extends into the plasma core, and outward impurity convection, consistent with the improved energy confinement and the lack of W accumulation observed in those conditions. In addition, large type I ELMs, typically found in gas-fuelled plasmas, are replaced by smaller and more frequent ELMs, whose appearance is correlated with a substantial reduction of the pedestal density and its gradient. Pedestals in this operating regime are stable to peeling–ballooning modes, consistent with the lack of large ELMs. This is in contrast to results in unfuelled JET-C plasmas that typically operated at higher pedestal densities and developed low frequency, large type I ELMs, thus pointing to the low density as one of the critical parameters for accessing this small ELMs regime in JET. This small ELMs regime exhibits the same low pedestal collisionality ( νe,ped∗∼0.1 ) expected in ITER and operates at low q 95, thus making it different from other small ELMs regimes that are typically obtained at higher q 95 and higher pedestal collisionality. These features make this newly developed H-mode regime in JET with Be/W wall a valuable tool for exploring the underlying transport, the different mechanisms of turbulence stabilization, as well as the physics associated with the appearance of small ELMs in high-temperature plasmas at ITER relevant pedestal collisionality.

Insights of ecological resilience in Caatinga assemblages – landscape configuration drives Chrysomeloidea (Coleoptera) diversity in a seasonally dry tropical forest

Seasonally Dry Tropical Forests (SDTFs) have long suffered from chronic, intensive and extensive landscape transformations due to human activities, challenging biodiversity conservation in this biome. The Caatinga is the largest Neotropical SDTF, serving as an excellent model to understand how land use changes modulate ecological communities. In this study, we assessed the effects of landscape configuration and composition on the abundance and diversity of Chrysomeloidea in a region of Caatinga. We sampled beetles in 10 landscape units, in which we measured landscape configuration (patch size, edge density) and composition (landscape diversity, patch richness). Hill numbers (q0, q1, q2) were used to analyze the diversities of Chrysomeloidea. A total of 484 individuals belonging to 82 species were collected. Landscape configuration affected Chrysomeloidea assemblages with a positive correlation between edge density and Chrysomeloidea diversity. We provide a new perspective regarding the spatial distribution of Chrysomeloidea in Caatinga and conclude that landscape configuration, but not composition, directly affects Chrysomeloidea assemblages.

Response of water quality in major tributaries to the difference of multi-scale landscape indicators in Dongting Lake basin, China.

River water quality has been increasingly deteriorated because of the influence of natural process and anthropogenic activities. Quantifying the influence of landscape metrics, namely topography and land use pattern, which encompass land use composition and landscape configuration, across different spatial and seasonal scales that reflect natural process and anthropogenic activities, is highly beneficial for water quality protection. In this study, we focused on investigating the effects of topography, landscape configuration and land use composition on water quality at different spatial scales, including 1-km buffer and sub-watershed, and seasonal scales, including wet and dry season, based on the monthly water quality data in 2016 of Dongting Lake in China. Multivariate statistical analysis of redundancy analysis and partial redundancy analysis was used to quantify the contributions of these factors under different scales. Our results showed that among the three environmental groups, topography made the greatest pure contribution to water quality, accounting for 11.4 to 30.9% of the variation. This was followed by landscape configuration, which accounted for 9.4 to 23.0%, and land use composition, which accounted for 5.9 to 15.7%. More specifically, water body made the greatest contribution to the water quality variation during dry season at both spatial scales, contributing 16.6 to 17.2% of the variation. In contrast, edge density was the primary interpreter of the variability in water quality during wet season at both spatial scales, accounting for 9.9 to 11.1% of the variation. The spatial variability in the influence of landscape metrics on water quality was not markedly distinct. However, these metrics have a minimal impact difference on water quality at the buffer scale and the sub-watershed scale. Moreover, the contribution of landscape configuration varied the most from the buffer to sub-watershed scales, indicating its importance for the spatial scale difference in water quality. The findings of this study offer useful insights into enhancing water quality through improved handling of landscape metrics.

Exploring fracture of H-BN and graphene by neural network force fields

Extreme mechanical processes such as strong lattice distortion and bond breakage during fracture often lead to catastrophic failure of materials and structures. Understanding the nucleation and growth of cracks is challenged by their multiscale characteristics spanning from atomic-level structures at the crack tip to the structural features where the load is applied. Atomistic simulations offer ‘first-principles’ tools to resolve the progressive microstructural changes at crack fronts and are widely used to explore the underlying processes of mechanical energy dissipation, crack path selection, and dynamic instabilities (e.g. kinking, branching). Empirical force fields developed based on atomic-level structural descriptors based on atomic positions and the bond orders do not yield satisfying predictions of fracture, especially for the nonlinear, anisotropic stress–strain relations and the energy densities of edges. High-fidelity force fields thus should include the tensorial nature of strain and the energetics of bond-breaking and (re)formation events during fracture, which, unfortunately, have not been taken into account in either the state-of-the-art empirical or machine-learning force fields. Based on data generated by density functional theory calculations, we report a neural network-based force field for fracture (NN-F3) constructed by using the end-to-end symmetry preserving framework of deep potential—smooth edition (DeepPot-SE). The workflow combines pre-sampling of the space of strain states and active-learning techniques to explore the transition states at critical bonding distances. The capability of NN-F3 is demonstrated by studying the rupture of hexagonal boron nitride (h-BN) and twisted bilayer graphene as model problems. The simulation results elucidate the roughening physics of fracture defined by the lattice asymmetry in h-BN, explaining recent experimental findings, and predict the interaction between cross-layer cracks in twisted graphene bilayers, which leads to a toughening effect.

Assessing the effects of urban green spaces metrics and spatial structure on LST and carbon sinks in Harbin, a cold region city in China

In the face of accelerated urbanization, urban green spaces (UGSs) are crucial in alleviating urban heat island effects. This study investigates the link between UGS landscape patterns, plant community characteristics, Land surface temperature (LST), and Annual carbon sequestration of plant community (ACSPC) across different seasons and scales in Harbin by remote sensing and field measurements. The results show that (1) The LST in urban built-up areas shows an increasing trend, and its correlation with UGS exhibits seasonal fluctuations. (2) Landscape pattern metrics significantly relate to LST, particularly at 1500 and 1260 m window scales. (3) In summer and winter, Aggregation index (AI) , Mean patch area (AREA_MN), Edge density (ED), Percentage of landscape (PLAND), Mean patch shape index (SHAPE_MN), Mean diameter at breast height (MDBH), Mean canopy diameter (MCD), Average carbon sequestration capacity(ACSC), and Leaf area index (LAI) are positively correlated, whereas Sky view factor (SVF) is negatively correlated with ACSPC. (4) LAI, SVF and MCD (winter) significantly affect LST. MDBH, MCD, and SVF in summer significantly influence ACSPC. This research elucidates the effect of UGS landscape patterns and plant community characteristics on urban heat islands and carbon sinks, providing vital insights for urban ecological improvement.

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

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

Study on the influence of landscape pattern on the spread of pine wilt disease from a multi-scale perspective

Since the introduction of pine wilt disease (PWD) into Chongqing, China, it has been continuously spreading, posing a significant threat to the local forest ecosystem dominated by pine forests. Utilizing data spanning the last two decades on the PWD epidemic subcompartment and host coniferous forest in Chongqing, this study employs a geographic detector model to scrutinize the impact of forest landscape patterns on PWD dissemination at the county, township, and 1 km grid scales. The findings reveal three distinct stages of the PWD epidemic in Chongqing from 2001 to 2020: diffusion, stabilization, and outbreak. The western and central regions of Chongqing experienced severe impacts, while the southern part exhibited relatively milder effects. Across the three spatial scales, various landscape pattern indices exhibit robust and consistent impacts on PWD occurrence. Notably, patch area emerges as the most influential factor, with an explanatory power reaching 0.228. Additionally, landscape shape index, number of patches, patch density, river and road exert substantial influence on PWD incidence. Conversely, the impact of edge density, landscape dominance, landscape separation, and landscape fragmentation on PWD occurrence is comparatively weak. Moreover, the interaction of different landscape pattern factors nonlinearly enhances the explanatory power of PWD occurrence. Among these interactions, the synergy between patch area and landscape dominance proves to have the highest explanatory power for the spatial differentiation of PWD at 0.718. This study explores the relationship between the invasion and spread of PWD and landscape patterns, offering useful insights for the prevention and early warning of PWD. Additionally, this research provides valuable reference points for promoting the healthy and sustainable development of forest resources in China.

Are recyclable plastics eco-friendly? Recycled PVC microplastics show higher toxicity than pristine PVC on Vallisneria natans, regardless of Cadmium

As environmental awareness increases, the use of recyclable plastics has risen. However, it is currently unclear whether recycled microplastics (MPs) pose a lesser or greater environmental risk than pristine MPs. Cadmium (Cd), known for its toxicity to most organisms, can bind with MPs and accumulate in sediments. Few studies have explored the environmental risks posed by the coexistence of recycled MPs and pristine MPs with Cd to rooted macrophytes. We investigated the effects of recycled PVC MPs (R-PVC-MPs) and pristine PVC MPs (PVC-MPs) on Vallisneria natans in the presence and absence of Cd. Results showed that at moderate and high Cd levels, R-PVC-MPs reduced plant Cd enrichment. Despite this, the fresh weight of V. natans exposed to R-PVC-MPs was significantly lower than those exposed to PVC-MPs. Furthermore, R-PVC-MPs had more negative impacts on the physiological traits of V. natans than PVC-MPs, as chlorophyll was significantly reduced across all Cd levels. At high Cd levels, both R-PVC-MPs and PVC-MPs caused significantly high oxidative stress, with no significant differences observed. The PCoA plot showed that different MPs cause noticeable variations within the same Cd concentration. The trait network diagrams illustrated strong interactions among traits, with R-PVC-MPs showing the highest complexity. Lower average degree and decreased edge density indicate that traits of plants with R-PVC-MPs addition are more independent of each other. Our findings suggest that recycled PVC MPs pose a greater environmental risk than pristine PVC MPs, offering reference for assessing the risks of recycled plastics in freshwater ecosystems.

Quantifying Forest Cover Loss during the COVID-19 Pandemic in the Lubumbashi Charcoal Production Basin (DR Congo) through Remote Sensing and Landscape Analysis

In the context of the Lubumbashi Charcoal Production Basin (LCPB), the socio-economic repercussions of the COVID-19 pandemic have exacerbated pressures on populations dependent on forest resources for their subsistence. This study employs a comprehensive methodological approach, integrating advanced remote sensing techniques, including image classification, mapping, and detailed landscape analysis, to quantify alterations in forest cover within the LCPB during the pandemic period. Our findings reveal a consistent trend of declining forested area, characterized by processes of attrition and dissection observed throughout various study phases, spanning from May 2019 to November 2023. This reduction in forest cover, notably more pronounced in the vicinity of Lubumbashi city and the northern zone of the LCPB, proved to be less pronounced between November 2019 and September 2020, underscoring the influence of COVID-19 pandemic-induced confinement measures on forest management practices in the region. However, subsequent to this period of restriction, deforestation activity intensified, leading to significant landscape transformations within the LCPB, primarily attributable to expanded human activities, consequently resulting in a notable decrease in the proportion of land occupied by these natural ecosystems. Consequently, the size of the largest forest patch declined substantially, decreasing from 14.62% to 8.20% between May 2019 and November 2023, thereby fostering a heightened density of forest edges over time. Our findings provide a significant contribution to understanding the complex interactions between the COVID-19 pandemic and deforestation phenomena, emphasizing the urgent need to adopt adaptive management strategies and appropriate conservation measures in response to current economic challenges.

Podejście oparte na GIS analizie do relacji między jednostkami gruntów a użytkowaniem gruntów w centralnym regionie Portugalii

Land units refer to coherent spatial areas characterized by a degree of homogeneity concerning certain properties like geology, soils, and climate. The Land use mosaic corresponds to a circumstantial layer representing the landscape’s present state, depicting the present resource allocation factors. Nevertheless, the stable potential layer is related to the stable characteristics of each site and allows the identification of use constraints or potentials. In this study, we use a methodology based on the land unit concept to define a stable potential layer at a regional level. Therefore, land units were delimited for the Central region of Portugal, resulting from the combination of geomorphology, soil parent material, and bioclimatic influence. For each land unit representative sample areas were characterized in terms of their land use mosaic characteristics. For that purpose, selected landscape metrics were used to quantify the land use mosaic geometrical attributes: Shannon’s Diversity Index, Edge Density, Mean Patch Size, and Number of Patches. The existing land use types were also quantified. Finally, a cluster analysis was performed to define groups of samples representing the land units with similar land-use mosaic types. The landscape metrics that best explain the influence of the permanent structure of the territory on the circumstantial structure of use are Shannon's Diversity Index, Edge Density, and Number of Patches. The highest diversity land cover patterns are located in formations with a lithology rich to very rich in silica under Mesomediterranean dry to subhumid climate. The validation of the previously defined land units confirmed the reliability of the proposed methodology, with most of the land units strongly influencing the land use mosaic. The delimitation and characterization of homogeneous land units are useful for the definition of soil suitability and for the choice of the most appropriate uses and activities by the stakeholders.

Związek między wzorem krajobrazu a zakłóceniami powodowanymi przez człowieka w latach 1990-2018 w Portugalii kontynentalnej

The land use/land cover pattern of landscapes as the main element of the landscape structure has an important role in landscape management, nature conservation, and preservation, considering its ability to provide valuable information about the spatial distribution and changes in land cover that occur on the Earth's surface. On the other hand, human activities have caused significant impacts on ecosystems, resulting in a loss of biodiversity, increased risks of erosion and soil degradation, and wildfires. In the last few decades, the growing trend of occurrence of negative effects on land use/land cover has not contributed to the achievement of sustainable development goals (SDGs), considering that the relationship between humankind and the environment is an extremely fragile equilibrium. In recent decades, large-scale land use and land cover (LULC) patterns have shown stability, but there have been significant dynamics observed specifically in forest areas and agricultural land. Among these changes, the conversion of maritime pine to eucalyptus stands out as the most relevant transition in terms of forest and agroforestry use classes. This conversion is a result of economic incentives available, which have contributed to the gain in forested areas. This study intends to verify how the alteration of the landscape configuration, represented by different metrics of configuration and diversity, is related to the intensity of human disturbance. The objectives of the study are: (1) to quantify the change in land use/land cover (LULC) patterns and the degree of human disturbance in Mainland Portugal between 1990 and 2018, and (2) to study the relationship between LULC configuration and the impact resulting from human disturbance under different levels of intensity, to understand how changing trends in landscape pattern can serve as indicators to estimate landscape changes resulting from human actions. The Hemeroby index (HI) was calculated to quantify the impacts on ecosystems resulting from disturbance caused by human actions. Based on the Hemeroby index value analysis for the period between 1990 and 2018, the level of naturalness increased in 58% of the country, mainly in the south and east of Portugal. The landscape pattern was quantified using a set of metrics, namely Mean Patch Size (MPS), Mean Shape Index (MSI), Total Edge (TE), Mean Patch Fractal Dimension (MPFD), and Mean Perimeter-Area Ratio (MPAR). To identify the existing statistical correlations between the geometric parameters of the landscape and the HIs values, the Spearman method was used. At the landscape level, the metrics TE and MSI have a strong negative correlation with HI. This suggests that landscapes with greater structural complexity are good indicators of low levels of hemeroby. At the class level, edge density (ED) and mean patch size (MPS) showed a significant correlation with the Hemeroby index for seminatural areas (all metrics), artificial surfaces and forests (TE, MSI, and MPS), agricultural areas (TE, MPS, and MPFD), and Bare Ground (TE, MSI, and MPFD).

How do landscape patterns in urban parks affect multiple cultural ecosystem services perceived by residents?

Cultural ecosystem services (CES) provided by urban parks are crucial for encouraging residents to engage with nature and enhance their physical and mental well-being. Measuring these services from the residents' perception perspective is essential. Previous studies often focus on a specific type of CES, lacking explicit links between the landscape composition and configuration of urban parks and residents' perceptions of various CES. The main objective of this study, therefore, was to explore the effects of urban park landscape patterns on residents' CES perceptions. We took 12 urban parks in Chengdu, China, and assessed residents' CES perceptions through content analysis of social media texts. Spatial patterns of the parks were analyzed using remote sensing interpretation and field surveys. Correlation analysis examined the relationship between landscape patterns and residents' perceptions, with further verification through questionnaires and face-to-face interviews. Findings revealed that at the landscape level, landscape aggregation of parks was negatively correlated with aesthetic perceptions but positively correlated with recreational perceptions. Landscape diversity negatively impacted perceptions of sports and health (S&H). At the class level, natural elements significantly influenced residents' perceptions of aesthetic and S&H. Specifically, aesthetic perceptions were minimized when the landscape shape index of water bodies reached 6.36 or when the proportion of green space was 56.5 %. Road edge density negatively affected perceptions of S&H and influenced the distribution of water bodies and green spaces. These findings are crucial for optimizing park structures to deliver efficient CES and provide strategies for integrating ecosystem services into environmental management from a public perception perspective.

Quantifying spatial complexity in submerged aquatic vegetation landscapes using remote sensing: Lessons from simulated and real landscapes

AbstractThe spatial organization of vegetation has been shown to be a strong indicator of ecological state in multiple ecosystems. In this study, we analyze the relationships between spatial complexity metrics in submerged aquatic vegetation (SAV) landscapes, and we explore the potential of satellite remote sensing to quantify these metrics in submerged environments. To do so, we estimated an array of complexity metrics over both simulated and real SAV landscapes of contrasted spatial organization. All these landscapes were artificially manipulated to (i) simulate remote sensing noise associated with the low signal‐to‐noise ratio (SNR) of aquatic environments and environmental noise generated by wind and waves, and (ii) reduce their spatial resolution from very high (2 m) to medium (30 m). Among these treatments, spatial resolution and low SNR (represented by sensor noise) had the strongest impacts on the perceived spatial complexity of the landscapes, while the impact of environmental noise was highly dependent on resolution. Although single metrics were deemed insufficient to characterize the spatial complexity of a landscape, a combination of informational complexity metrics such as the clumpy index, mean information gain, landscape shape index, and edge density provided a robust explanation of variation in the real and simulated datasets. These findings suggest that remote sensing has a strong potential for the ecological monitoring of SAV by contributing to establishing the link between SAV spatial structure and ecological status.

Evaluation of Ecological Sensitivity and Spatial Correlation Analysis of Landscape Patterns in Sanjiangyuan National Park

The Sanjiangyuan region, situated on the Qinghai–Tibetan Plateau, constitutes an exceptionally delicate ecological environment. Alterations in the region’s ecological landscape stem not only from natural factors but also from significant anthropogenic influences, exerting a notable impact on the sustainable economic and social development of the region’s middle and lower reaches. Consequently, investigating changes in the landscape pattern of Sanjiangyuan National Park holds paramount importance for comprehending the formation mechanism of spatial landscape distribution in the area. This study analyzes the ecological sensitivity and landscape pattern of Sanjiangyuan National Park in Qinghai Province, China, utilizing ArcGIS 10.8 and Fragstats 4.2. Employing the bivariate spatial autocorrelation analysis method, the research uncovers the spatial distribution characteristics between ecological sensitivity and landscape pattern, along with their aggregated change traits. The findings reveal that ecological sensitivity areas within the park encompass varying degrees, ranging from extremely sensitive to insensitive. The area of moderately sensitive zones in the Yellow River source region is 7279.67 km2 (39.17%), whereas the corresponding area in the Yangtze River source region is 32,572.34 km2 (36.30%). The eastern and northern parts of the Sanjiangyuan National Park exhibit significant landscape fragmentation. Ecological sensitivity varies markedly across different regions, with the southern and some northern areas showing higher sensitivity. In the Lancang River source park and the southern part of the Yellow River source park, the Largest Patch Index (LPI) and Ecological Sensitivity Index exhibit a high–high (HH) clustering pattern, indicating strong ecological connectivity in these areas. These regions also feature high Total Edge (TE), Number of Patches (NP), Patch Density (PD), and Edge Density (ED), indicating a complex landscape structure and abundant habitat edge areas. The study recommends restoring ecological connectivity in highly fragmented areas and implementing strict protection measures in sensitive regions to maintain ecosystem health and biodiversity. These findings provide a foundation for developing targeted ecological protection measures to enhance ecosystem health and biodiversity conservation in the area. This research aligns with several Sustainable Development Goals (SDGs), including Climate Action, Life on Land, and Clean Water and Sanitation, by promoting sustainable ecosystem management and biodiversity conservation.

Consensus Subspace Graph Regularization based on prior information for multiplex network clustering

Multiplex network clustering can identify the common cluster structure shared by all layers, which is of great significance for downstream research such as personalized recommendations of social relationships and the mining of social media communication behaviors. Traditional multiplex network clustering methods rely only on the topological structure and are suitable for networks with clear structures. However, real-world networks often suffer from sparse connectivity and noisy edges. In addition, the current methods based on prior information only use the obtained consensus prior information as a preprocessing method for multiplex networks, and do not fully utilize and integrate the prior information in the clustering process, resulting in a low accuracy. To solve the problem of insufficient utilization of prior information, we propose a Consensus Subspace Graph Regularization (CSGR) approach for multiplex network clustering, which integrates topological information with the consensus prior information of a network. We first construct the consensus prior matrix of a network by a non-overlapping greedy search method, which represents a subset of the network that consists of nodes with high edge density. Then we construct a graph regularization term, which encodes the consensus prior information, to optimize the generation of a joint low-dimensional representation within the consensus subspace for the entire multiplex network. Finally, we employ the consensus prior matrix to denoise each network layer, thereby yielding a precise low-dimensional representation of each layer for consensus subspace fusion. In addition, comprehensive experiments have demonstrated that CSGR improves the clustering accuracy of real-world networks by an average of 1.56%.

The effect of impurity seeding on edge toroidal rotation in the ADITYA-U tokamak

Intrinsic toroidal rotation velocity (Vφ ) has been measured from the Doppler shift of C5+ carbon spectral lines (at 529.05 nm) in the edge region of the ADITYA-U tokamak without any auxiliary torque input in an ohmically heated pure hydrogen (H2) plasma as well as in H2 plasmas seeded with medium-Z (neon and argon) impurities . The toroidal rotation in the edge region is observed to reverse its direction from the counter-current to the co-current direction with an increase in plasma current beyond I p ∼ 145–150 kA. Furthermore, a systematic decrease in the co-current Vφ has been observed with the edge density, which tends to decrease to almost zero velocity with an increase in the edge density. The injection of medium-Z (neon and argon) impurities is observed to influence the edge toroidal rotation significantly. In low I p discharges, argon injection leads to a reversal of edge intrinsic rotation from the counter-current to the co-current direction. In high I p discharges, both neon and argon seeding enhance the co-current rotation by about ∼5–10 km s−1, at a constant I p compared to pure H2 discharges. Simultaneous measurements of the edge radial electric field, E r, shows that the E r × Bθ flow seems to be driving the edge toroidal rotation in ADITYA-U. With impurity injection, the E r also gets modified, leading to an observed increase in the edge toroidal rotation.

Landscape configuration and storm characteristics drive spatial patterns of wind disturbance in boreal forest landscapes

ContextWind is an important disturbance in circumboreal forests, and its frequency and severity may change with climate change, highlighting the need to understand the drivers of wind disturbance. Currently, how landscape configuration drives wind disturbance is poorly understood.ObjectivesWe investigated whether and how landscape configuration is related to the extent and spatial pattern of wind disturbance, and how these relationships vary between windstorms and thunderstorms.MethodsWe used salvage logging data after 16 storms that occurred in Finland between 2011 and 2021. We placed a total of 301 landscapes, each encompassing an area of 8024 ha, within the storm tracks and used regression models to test how wind disturbance extent, disturbance patch size, number of disturbance patches, and disturbance patch clustering were related to landscape configuration and storm characteristics.ResultsIncreasing mean gap size and edge density, including permanent openings (e.g., lakes) and recent harvest gaps, increased disturbance extent, disturbance patch size, and number of disturbance patches. Conversely, increasing mean harvest gap size decreased disturbance patch clustering. Increasing wind speed had the largest contribution to increasing disturbance extent and number of disturbance patches, and decreasing disturbance patch clustering, with the magnitude of the effect varying between windstorms and thunderstorms.ConclusionsThe extent and spatial pattern of wind disturbances varied with landscape configuration and storm characteristics. Disturbance patches were larger in landscapes with large canopy gaps, resulting in a greater disturbance extent, exacerbated by increasing wind speed and thunderstorm development.

The importance of private gardens and their spatial composition and configuration to urban heat island mitigation

Small Urban Green Infrastructure (UGI; green areas < 2 ha) represents the best opportunity to mitigate Urban Heat Island (UHI) and directly promote microclimate regulation. However, few studies investigate the cooling capacity (CC) of small UGI and how their spatial organization influences its provision. Here, we used an urban cooling model and landscape metrics to understand how UGI in public and private domains influences microclimate regulation in a dense urban region of Rio de Janeiro. Our findings highlight the significant correlation between private UGI and CC, explaining over 80 % of its variation. We found an interaction between UGI composition (i.e. the amount of UGI) and configuration (i.e. spatial distribution of UGI). Nevertheless, UGI configuration exerted the greatest influence with edge density being the most significant landscape metric, suggesting that, with an equivalent green area, patchwork or numerous smaller green areas enhance CC compared to fewer larger ones. This study underscores the pivotal role of private UGI organization in tropical and dense urban context, where public UGI is neglected. We conclude that UGI awareness initiatives must systematically pay attention to spatial configuration of the small UGI, aligning interventions with urban dwellers' needs in order to guarantee microclimate regulation provision.

Invertebrate Responses to Large- and Small-Scale Drivers in Coastal Phragmites australis Beds in the Northern Baltic Sea

Phragmites australis is a common helophyte, covering much of the sheltered and shallow soft bottoms along the coasts of the Baltic Sea. Despite the expansion of P. australis over the past decades, there is little information on aquatic macroinvertebrates within P. australis beds. In this study, we examined the effect of large-scale (wave exposure, nutrients) and small-scale (distance from the seaward edge, live and dead stalk density, epiphyte and rhizome biomass) drivers on the density, taxa richness, diversity, and community structure of epifauna and infauna in monospecific P. australis beds around the Åland Islands and the Archipelago Sea. We found that higher wave exposure and nutrient levels generally supported higher epi- and infauna abundance and taxa richness. The effects on Shannon–Wiener diversity were less evident apart from an increase of the infauna diversity in the Archipelago Sea with increasing nutrient levels. On a local scale, the distance from the seaward edge, live and dead stalk density, and epiphyte biomass had varying effects on both epi- and infauna communities in the different regions. Rhizome biomass had no effect on either the epi- or infauna abundance, taxa richness, or diversity. Furthermore, according to existing studies, other habitats, e.g., Zostera marina meadows, Fucus vesiculosus belts, and vegetated soft-bottomed shallow bays, are generally characterized by more abundant fauna, except for the infauna, which had a higher density in P. australis beds than in vegetated soft-bottomed shallow bays. P. australis are a widespread, expanding, and understudied habitat with an important role in supporting coastal biodiversity.