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We show that lim sup | E (G) | / | V (G) | = 2.5 over all 4-critical planar graphs G, answering a question of Grünbaum from 1988. [ABSTRACT FROM AUTHOR]

Understanding how landscape composition and configuration drive the dynamics of pests and their various natural enemies is crucial to enhance biological control services (biocontrol). Geographic variability in landscape effects prompts questions about whether this is due to genuine differences or methodological differences among studies, given that most studies are conducted in a single region. This study investigated how the ecological function of parasitoids and predators responds to landscape traits in three regions encompassing an agriculture intensification gradient. The effects of landscape structure and configuration differed among regions and natural enemies. Non-crop habitats increased the abundance of parasitoids only in two less intensified regions presumably due to insufficient amount of non-crop habitats in the intensified region (typically < 10%). Nevertheless, their biological control efficiency (BCE) was consistently increased by non-crop habitats across regions. Higher maize proportion increased predator abundance and their BCE in the two nonmountainous regions. The value of maize as a source habitat for predators may have been limited in the mountainous region due to the lower aphid abundances there. Edge density positively affected abundances of predators and parasitoids, but only positively increased the BCE of all natural enemies combined. Inconsistent regional responses to the same landscape variables suggest that a uniform integrated pest management strategy for alfalfa is impractical. However, increasing edge density should be a useful first step for supporting diverse natural enemy communities and their biocontrol potential. [ABSTRACT FROM AUTHOR]

Aim: Habitat conversion is the number one threat to biodiversity. The loss of biodiversity due to habitat loss might be exacerbated if species are harmed by fragmentation per se—the breaking apart of natural habitat that remains (hereafter fragmentation). However, the evidence that species are harmed by habitat fragmentation is mixed. Studies at the patch scale tend to show that fragmentation reduces diversity due to negative demographic effects on species' dispersal, survival and fecundity. In contrast, studies at the landscape scale tend to show that fragmentation increases diversity. This discrepancy may be partly due to geometric effects, defined as greater species turnover between patches in more fragmented landscapes. Although these effects have been demonstrated theoretically and are expected to be stronger across larger spatial extents, it is unclear whether they are likely to occur in real‐world settings with both realistic landscape patterns and communities. Here, we investigated the possibility of geometric effects using simulations combined with real‐world landscape and community data. Location: New Jersey, northeastern USA. Time period: Current. Taxa studied: Bees. Methods: We focused on landscape sizes within the typical range for protected areas (36–576 ha), simulated forest loss using real landscape patterns, and simulated forest‐bee communities based on field data we collected. Results: We found weak but positive effects of fragmentation: immediately following forest destruction, the most fragmented forests harboured up to 7.3% more species than the least fragmented forests of the same area, in agreement with observational studies of biodiversity along fragmentation gradients. In contrast to expectations, however, the overall effects of fragmentation did not change with spatial extent. Conclusions: Our results suggest that fragmentation can mitigate biodiversity loss immediately following habitat destruction, but that the benefits do not vary strongly with spatial extent in real‐world landscapes and at extents relevant to land management. [ABSTRACT FROM AUTHOR]

Agricultural intensification not only increases food production but also drives widespread biodiversity decline. Increasing landscape heterogeneity has been suggested to increase biodiversity across habitats, while increasing crop heterogeneity may support biodiversity within agroecosystems. These spatial heterogeneity effects can be partitioned into compositional (land‐cover type diversity) and configurational heterogeneity (land‐cover type arrangement), measured either for the crop mosaic or across the landscape for both crops and semi‐natural habitats. However, studies have reported mixed responses of biodiversity to increases in these heterogeneity components across taxa and contexts. Our meta‐analysis covering 6397 fields across 122 studies conducted in Asia, Europe, North and South America reveals consistently positive effects of crop and landscape heterogeneity, as well as compositional and configurational heterogeneity for plant, invertebrate, vertebrate, pollinator and predator biodiversity. Vertebrates and plants benefit more from landscape heterogeneity, while invertebrates derive similar benefits from both crop and landscape heterogeneity. Pollinators benefit more from configurational heterogeneity, but predators favour compositional heterogeneity. These positive effects are consistent for invertebrates and vertebrates in both tropical/subtropical and temperate agroecosystems, and in annual and perennial cropping systems, and at small to large spatial scales. Our results suggest that promoting increased landscape heterogeneity by diversifying crops and semi‐natural habitats, as suggested in the current UN Decade on Ecosystem Restoration, is key for restoring biodiversity in agricultural landscapes. [ABSTRACT FROM AUTHOR]

This study proposes a novel image segmentation algorithm for estimating the average size of densely packed grains, particles, cells, powders, bubbles, and aggregates. The algorithm comprises two sub-algorithms: valley edge detection and grain size estimation. The valley edge detection sub-algorithm identifies weak edges among grains using four directions. In contrast, the grain size estimation sub-algorithm calculates the average size of the grains based on the detected edge density. The algorithm can recognize grains with circular, elliptical, or other regular shapes without explicitly delineating each grain, making it ideal for complex and densely packed grain images. The algorithm was tested using various samples, including aggregate particles, tomatoes, chicken/duck eggs, turtle eggs, soybeans, lawn seeds, rapeseeds, and other seeds, and the testing results were satisfactory. The proposed algorithm is 200-500 times faster than ordinary grain image segmentation algorithms. It is suitable for online applications that require real-time image processing of densely packed and detailed grain images. [ABSTRACT FROM AUTHOR]

Graph drawing beyond planarity is a research area that has received an increasing attention in the last twenty years, driven by the necessity to mitigate the visual complexity inherent in geometric representations of non-planar graphs. This research area stems from the study of graph layouts with forbidden crossing configurations, a well-established subject in geometric and topological graph theory. In this context, the contribution of this paper is as follows: 1) We introduce a new hierarchy of graph families, called $k^{+}$ -real face graphs; for any integer $k \geq 1$ , a graph G is a $k^{+}$ -real face graph if it admits a drawing $\Gamma $ in the plane such that the boundary of each face (formed by vertices, crossings, and edges) contains at least k vertices of G (“ $k^{+}$ ” stands for k or more); 2) We give tight upper bounds on the edge density of $k^{+}$ -real face graphs, namely we prove that n-vertex $1^{+}$ -real face and $2^{+}$ -real face graphs have at most $5n-10$ and $4n-8$ edges, respectively. Furthermore, in a constrained scenario in which all vertices must lie on the boundary of the external face, $1^{+}$ -real face and $2^{+}$ -real face graphs have at most $3n-6$ and $2.5n-4$ edges, respectively; 3) We characterize the complete graphs that admit a $k^{+}$ -real face drawing or an outer $k^{+}$ -real face drawing for any $k \geq 1$ . We also provide a clear picture for the majority of complete bipartite graphs; and 4) We establish relationships between $k^{+}$ -real face graphs and other prominent beyond-planar graph families; notably, we show that for any $k \geq 1$ , the class of $k^{+}$ -real face graphs is not included in any family of beyond-planar graphs with hereditary property.

Education informatization is an important means to improve the quality of education and teaching as well as a basic condition for the innovative reform and application of education and teaching, which also means that education informatization cannot be separated from the construction of digital learning resources. This paper utilizes the advantage of Flash technology’s integration of multiple media elements to design physics animation courseware. Then, it combines the color histogram and edge density analysis algorithm to segment the animated visual scene of physics courseware, optimize the production process of Flash physics animated courseware, and establish a scientific evaluation standard for courseware quality. The average scores of the four dimensions of manipulability, stability, aesthetics, and compatibility in the evaluation results of physics animated courseware in this paper are all higher than 4 points. The students who apply physics animated courseware to teach improve their learning attitudes, learning behaviors, and learning effects by 11.61, 7.33, and 6.54, respectively, compared with the traditional physics teaching, and all of them are significantly different (P

Rich club is a special phenomenon in complex networks. It refers to the nodes with high degrees (i.e., rich nodes) that tend to connect with each other to form a "rich club". This phenomenon exists in many real networks, especially in social networks. However, there are also some networks not having this phenomenon, for example, in many biological networks. Thus, a natural question comes up: do these rich nodes contact with each other through an "agent"? Two rich nodes do not connect directly, but they can establish a connection by an "agent", i.e., they can connect with each other within two steps. If the rich nodes tend to connect with each other within two steps, we say that they form a "2-step rich club". The traditional rich club is then called "1-step rich club". In this paper, we aim to design one method to detect the "2-step rich club" phenomenon in real networks and check whether this new "2-step rich club" phenomenon commonly exists in real networks. We find that most networks with "1-step rich club" will also have "2-step rich club". However, there also exist few networks having "2-step rich club" structure while not having "1-step rich club" structure. In particular, either 1-step rich-club phenomenon or 2-step rich-club phenomenon exists in most social networks. [ABSTRACT FROM AUTHOR]

BACKGROUND: Pine wilt disease (PWD) outbreaks have affected extensive areas of South China's forests, but the factors explaining landscape patterns of pine mortality are poorly understood. The objective of this study was to determine the relative importance of stand structure, topography, landscape context, and beetle pressure in explaining PWD severity. During 2020–2021, we identified 66 plots based on mapped PWD infestation severity. We built PWD infestation maps for 2019–2021 through field surveys. Stand structure and topography were obtained from Forest Resources Management 'One Map' and elevation raster data. We then used 'One Map' and PWD infestation maps to determine landscape context and beetle pressure variables at different spatial scales. The relative importance of 12 explanatory variables was analyzed using multi‐model inference. RESULTS: In this study, we show that: (i) 1 km was the best spatial scale related to pine mortality, and (ii) models including landscape context and beetle pressure were much better at predicting pine mortality than models using only stand‐level variables. CONCLUSION: Landscape‐level variables, particularly beetle pressure, were the most consistent predictors of subsequent pine mortality within susceptible stands. These results may help forest managers identify locations vulnerable to PWD and improve existing strategies for outbreak control. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The massive declines in terrestrial arthropods reported across Europe call for effective methods to monitor and promote biodiversity in human-dominated landscapes. Previous studies vary in their support for the suitability of plants as indicators of arthropod diversity, while the potential of subsets of conservation-relevant plant species to estimate arthropod richness remains to be tested. Moreover, the relative importance of plant species richness compared to other factors driving arthropod richness, such as land-use intensity, habitat amount and landscape configuration, is poorly understood. We conducted a multi-scale field study in Southern Germany, sampling vascular plants and terrestrial arthropods in four local land-use types (forest, grassland, arable field, settlement) across large-scale gradients of climate and land-use intensity. We obtained an extensive arthropod dataset using Malaise traps as sampling method and DNA metabarcoding for species identification. We compared the correlation of three sets of plant species richness (total, red-listed and biotope-indicator plants) with arthropod richness, including different trophic and taxonomic groups. Using mixed-effect models, we assessed the partial effects of plant species richness, habitat amount and landscape configuration on local arthropod richness while controlling for climate and land-use effects, and explored the environmental drivers of plant species richness. Arthropod species numbers of all trophic groups strongly responded to species numbers of plants that indicate protected habitats, while red-listed plant species richness was a key determinant for the richness of red-listed arthropods and butterflies. In most cases, plant species richness and temperature were stronger drivers of arthropod richness than the amount of surrounding semi-natural habitat and landscape configuration. While total plant species richness was highest in settlements, the richness of biotope-indicator plants was highest in forests and positively influenced by the amount of semi-natural habitat and edge density. The number of red-listed plant species increased with edge density at the landscape scale but was independent of habitat amount. We conclude that the richness of conservation-relevant plant species provides a powerful indicator of arthropod diversity, and underpins the potential of such plant lists for monitoring habitat quality. Our study highlights the importance of openings in forests for conservation of plants and arthropods as well as of preserving and restoring fragments of high-quality biotopes in agricultural and urban areas where the amount of semi-natural habitat is limited.

Context: There is a long-standing quest in landscape ecology for holistic biodiversity metrics accounting for multi-taxa diversity in heterogeneous habitat mosaics. Passive acoustic monitoring of biodiversity may provide integrative indices allowing to investigate how soundscapes are shaped by compositional and configurational heterogeneity of mosaic landscapes. Objectives: We tested the effects of dominant habitat and landscape heterogeneity on acoustic diversity indices across a large range of mosaic landscapes from two long-term socio-ecological research areas in Occitanie, France and Arizona, USA. Methods: We assessed acoustic diversity by automated recording for 44 landscapes distributed along gradients of compositional and configurational heterogeneity. We analyzed the responses of six acoustic indices and a composite multiacoustic index to habitat type and multi-scale landscape metrics for three time periods: 24 h-diel cycles, dawns and nights. Results: Landscape mosaics dominated by permanent grasslands in Occitanie and woodlands in Arizona produced the highest values of acoustic diversity. Moreover, several indices including H, ADI, NDSI, NP and the multiacoustic index consistently responded to edge density in both study regions, but with contrasting patterns, increasing in Occitanie and decreasing in Arizona. Landscape configuration was a key driver of acoustic diversity for diel and nocturnal soundscapes, while dawn soundscapes depended more on landscape composition. Conclusions: Acoustic diversity was correlated more with configurational than compositional heterogeneity in both regions, with contrasting effects explained by the interplay between biogeography and land use history. We suggest that multiple acoustic indices are needed to properly account for complex responses of soundscapes to large-scale habitat heterogeneity in mosaic landscapes. [ABSTRACT FROM AUTHOR]

While it is common practice in applied network analysis to report various standard network summary statistics, these numbers are rarely accompanied by uncertainty quantification. Yet any error inherent in the measurements underlying the construction of the network, or in the network construction procedure itself, necessarily must propagate to any summary statistics reported. Here we study the problem of estimating the density of an arbitrary subgraph, given a noisy version of some underlying network as data. Under a simple model of network error, we show that consistent estimation of such densities is impossible when the rates of error are unknown and only a single network is observed. Accordingly, we develop method-of-moment estimators of network subgraph densities and error rates for the case where a minimal number of network replicates are available. These estimators are shown to be asymptotically normal as the number of vertices increases to infinity. We also provide confidence intervals for quantifying the uncertainty in these estimates based on the asymptotic normality. To construct the confidence intervals, a new and nonstandard bootstrap method is proposed to compute asymptotic variances, which is infeasible otherwise. We illustrate the proposed methods in the context of gene coexpression networks. for this article are available online. [ABSTRACT FROM AUTHOR]

Northeastern México is one of the most diverse regions in the country with high mammal richness. This region also sits on the northern periphery of the geographic distribution of ocelots (Leopardus pardalis), which are listed as endangered in México. Ocelot ecology in northeastern México is poorly known at local and landscape levels, especially in the ecologically rich temperate sierras, a perceived stronghold for ocelots. We used an occupancy approach to estimate ocelot-habitat use in Tamaulipan thornshrub and tropical deciduous forests and a spatially explicit capture–recapture (SECR) framework to estimate density of ocelots in the northern edge of the Sierra Tamaulipas, México. From May to December 2009, we conducted two camera trap surveys (summer: 20 camera stations; fall: 58 camera stations) on Rancho Caracol and Rancho Camotal, north of the Rio Soto de La Marina. We found ocelot detections were higher in areas with increasing patch density of tropical deciduous forest and habitat use was greater in Tamaulipan thornshrub and tropical deciduous forests with lower edge densities. Ocelot densities varied by sex, with females achieving greater densities (7.88 ocelots/100 km2 [95% CI: 4.85–12.81]) than males (3.81 ocelots/100 km2 [95% CI: 1.96–7.43]). Ocelots were averse to areas with high densities of edge cover in each woody community, supporting the notion of a forest patch interior species. Despite the study occurring 11 years ago, population densities were also among the highest reported in México using spatially explicit capture–recapture methods, The high ecological integrity of the habitat within the Sierra de Tamaulipas, recent protection as a Biosphere Reserve, and remote rugged terrain suggest long-term security of the ocelot population in this region. [ABSTRACT FROM AUTHOR]

Seed dispersal by frugivorous animals is important for plant mobility, regeneration and persistence. Human‐caused landscape change is thought to disrupt seed dispersal, but evidence is scarce. We performed a comprehensive meta‐analysis on the effects of habitat spatial pattern on frugivory and seed dispersal. We found 233 effects from 71 studies. At a patch or local scale, altered habitat spatial pattern was measured as declining patch size, increasing patch isolation or habitat edge (versus interior). At a landscape scale it was measured as declining amount of habitat, increasing mean patch isolation, increasing number of patches or increasing habitat edge in the landscape. We found overall negative effects of altered habitat spatial pattern on: 1) the quantity of frugivory or seed dispersal, 2) the number of species involved in a plant–frugivore interaction and 3) seed dispersal distance. Moderator variable analysis was only possible for the first of these. It revealed negative responses of the quantity of frugivory or seed dispersal to habitat loss at both the local scale (declining patch size), and the landscape scale (declining habitat amount), but little evidence for a response to habitat edge at either scale. In addition, altered habitat spatial pattern reduced the quantity of frugivory or seed dispersal more strongly in temperate than tropical areas. Finally, the few‐recorded effects of landscape‐scale fragmentation per se (increasing patch density or edge density) on the quantity of frugivory or seed dispersal were mixed and weak. Our meta‐analysis reinforces the notion that habitat loss is a major threat to frugivory and seed dispersal by animals, and reveals an insufficiency of studies of the effects of habitat fragmentation per se. Thus, based on the current literature, we conclude that maintaining and increasing habitat amount is vital for maintaining seed dispersal by frugivorous animals. [ABSTRACT FROM AUTHOR]

Aim: Recent changes in land use have led to substantial loss and fragmentation of semi‐natural grasslands. We assessed the relative effect of current and historical landscape composition, and landscape change on the genetic diversity and gene flow of a characteristic grassland plant. Location: Calcareous grasslands on Muhu and Saaremaa islands in Western Estonia, Europe. Methods: We used landscape genetic methods to study the genetic patterns of the grassland plant Primula veris. We applied a high‐throughput sequencing method (double‐digest restriction site‐associated DNA sequencing, ddRADseq) to obtain 2,619 putatively neutral single‐nucleotide polymorphism (SNP) markers. We examined the impact of the historical (80 years ago) and current amount and edge density of 19 grasslands, the amount of woody elements in the surroundings of the study grasslands and the change in the area of these habitats on the current genetic diversity within populations and genetic differentiation between populations of P. veris. Results: Genetic diversity within populations of P. veris was lower in landscapes with more pronounced grassland loss over the past 80 years. Higher historical grassland edge density in the surrounding landscape led to higher genetic diversity of P. veris. Higher historical proportion of grasslands between the study populations led to lower genetic differentiation, indicating higher (historical) gene flow between those populations. Main conclusions: Although the study grasslands experienced a drastic loss in the area and connectivity over the past century, patterns of genetic diversity and gene flow of P. veris still largely mirror the effect of historical landscape, especially grassland edge density and at larger scales the historical proportion of grasslands between study populations. Thus, measures of genetic diversity and gene flow in P. veris may have a lagged response to landscape change, offering a window for preserving the still existing genetic diversity through immediate restoration activities. [ABSTRACT FROM AUTHOR]

Abstract Humans modify landscapes for a variety of reasons including agriculture, urbanization, and to facilitate recreation. Landscape modifications can lead to complete loss of existing cover types and/or fragmentation of remaining cover types. Grasslands are one of the ecosystems most heavily impacted by human modifications; however, for many species, an understanding of how fragmentation affects population parameters is lacking. We investigated the influence of landscape fragmentation on survival, reproduction, and density using the northern bobwhite (Colinus virginianus), a facultative grassland species, as our case study. We experimentally manipulated the level of edge density (none, low, and high) of bobwhite management units and estimated seasonal survival, productivity, and autumn densities. Winter survival was lower in edge density treatments, relative to the control. An increase in migratory raptor density during the winter, along with a decrease in thermal refugia, may be contributing to lower winter survival in edge density treatments. Fecundity was higher in the edge density treatments, relative to the control, and was negatively related to winter survival. Similarly, breeding season survival was higher in more fragmented sites. This indicated a density‐dependent relationship, where lower bird densities at the beginning of the breeding season possibly led to greater resource availability, and thus survival and productivity, of the birds that remained. However, a density‐dependent response in breeding season survival and productivity was not enough to offset the negative impact of edges in the low edge density sites. Consequently, autumn density was lower relative to both control and high edge density treatments. Our study demonstrates the importance of capturing the entire life cycle when exploring the relationship between landscape pattern and population parameters.

Hubs are highly connected brain regions important for coordinating processing in brain networks. It is unclear, however, which measures of network "hubness" are most useful in identifying brain regions critical to human cognition. We tested how closely two measures of hubness--edge density and participation coefficient, derived from white and gray matter, respectively--were associated with general cognitive impairment after brain damage in two large cohorts of patients with focal brain lesions (N = 402 and 102, respectively) using cognitive tests spanning multiple cognitive domains. Lesions disrupting white matter regions with high edge density were associated with cognitive impairment, whereas lesions damaging gray matter regions with high participation coefficient had a weaker, less consistent association with cognitive outcomes. Similar results were observed with six other gray matter hubness measures. This suggests that damage to densely connected white matter regions is more cognitively impairing than similar damage to gray matter hubs, helping to explain interindividual differences in cognitive outcomes after brain damage. [ABSTRACT FROM AUTHOR]

Humans modify landscapes for a variety of reasons including agriculture, urbanization, and to facilitate recreation. Landscape modifications can lead to complete loss of existing cover types and/or fragmentation of remaining cover types. Grasslands are one of the ecosystems most heavily impacted by human modifications; however, for many species, an understanding of how fragmentation affects population parameters is lacking. We investigated the influence of landscape fragmentation on survival, reproduction, and density using the northern bobwhite (Colinus virginianus), a facultative grassland species, as our case study. We experimentally manipulated the level of edge density (none, low, and high) of bobwhite management units and estimated seasonal survival, productivity, and autumn densities. Winter survival was lower in edge density treatments, relative to the control. An increase in migratory raptor density during the winter, along with a decrease in thermal refugia, may be contributing to lower winter survival in edge density treatments. Fecundity was higher in the edge density treatments, relative to the control, and was negatively related to winter survival. Similarly, breeding season survival was higher in more fragmented sites. This indicated a density‐dependent relationship, where lower bird densities at the beginning of the breeding season possibly led to greater resource availability, and thus survival and productivity, of the birds that remained. However, a density‐dependent response in breeding season survival and productivity was not enough to offset the negative impact of edges in the low edge density sites. Consequently, autumn density was lower relative to both control and high edge density treatments. Our study demonstrates the importance of capturing the entire life cycle when exploring the relationship between landscape pattern and population parameters. [ABSTRACT FROM AUTHOR]

Wildlife corridors are critical for maintaining the viability of isolated wildlife populations and conserving ecosystem functionality. Anthropogenic pressure has negatively impacted wildlife habitats, particularly in corridors between protected areas, but few studies have yet quantitatively assessed habitat changes and corresponding wildlife presence. We quantified land use/land cover and human–elephant conflict trends over the past two decades in the Wami Mbiki–Saadani (WMS) wildlife corridor, Tanzania, using RS and GIS combined with human–wildlife conflict reports. We designed landscape metrics and habitat suitability models for the African savanna elephant (Loxodonta africana) as a large mammal key species in the WMS ecosystem. Our results showed that forest cover, a highly suitable habitat for elephants, decreased by 3.0% between 1998 and 2008 and 20.3% between 2008 and 2018. Overall, the highly suitable habitat for elephants decreased by 22.4% from 1998 to 2018, when it was scarcely available and when small fragmented patches dominated the unprotected parts of the corridor. Our findings revealed that large mammalian habitat conservation requires approaches beyond habitat-loss detection and must consider other facets of landscape patterns. We suggest strengthening elephant habitat conservation through community conservation awareness, wildlife corridor mapping, and restoration practices to ensure a sustainable pathway to human–wildlife coexistence.

Conservation corridors are an interesting strategy considering the increasing forest conversion by agricultural areas. We used Bayesian multispecies occupancy model in order to assess the occupancy of mammal species along the Manu-Tambopata conservation corridor (4 164.06 km²), located in the southern Peruvian Amazon. We installed 102 camera traps between May and October of 2017 (8 104 camera days), in four management regimes: Río Los Amigos conservation concession, forestry concessions (ACOMAT), Tambopata National Reserve and agricultural lands. Twenty-seven species of terrestrial mammals were recorded; however, models did not reveal significant differences in species richness among management regimes, although an effect of edge density on community-level occupancy was evident. Non-significant relationships were found between commonly hunted species and management regimes, apart from the white-lipped peccary; however, short-eared dog (Atelocynus microtis) and jaguar (Panthera onca) occupancy were significantly lower on agricultural lands. Our results suggested that, in general, the management regimes and covariables (edge density and distance toroads) did not have an effect at the community level but did have species-specific effects for some species (e.g., A. microtis). MAT corridor is still a space where it is feasible to maintain healthy populations of mammals, although its long-term viability requires ensuring connectivity at both a functional and structural levels. [ABSTRACT FROM AUTHOR]

Patterned fabrics are generally constructed from the periodic repetition of a primitive pattern unit. Repeat pattern segmentation of printed fabrics has a very significant impact on the pattern retrieval and pattern defect detection. In this paper, we propose a new approach for repeat pattern segmentation by employing the adaptive template matching method. In contrast to the traditional method for template matching, the proposed algorithm first selects an adaptive size template image in the repeat pattern image based on the size of the original image and its local maximum edge density. Then it uses the sum of absolute differences as the matching features to identify the matched regions in the original image, and the minimum envelope border of the primitive pattern, typically as a parallelogram, can be determined from the results of the four adjacent matched templates. Finally, image traversal base on the obtained parallelogram is implemented over the original image using minimum information loss theory to produce a well-segmented primitive pattern with a complete edge structure. The results from the experiments conducted using an extensive database of real fabric images show that the proposed algorithm has the advantage of rotation invariance and scaling invariance and will not be affected when the background or foreground color is changed. [ABSTRACT FROM AUTHOR]

Amphibians play a key role in structuring biological assemblages of agricultural landscapes, but they are threatened by global agricultural intensification. Landscape structure is an important variable influencing biodiversity in agricultural landscapes. However, in the Yangtze River Delta, where a "farmland-orchard-fishpond" agricultural pattern is common, the effects of landscape construction on anuran populations are unclear. In this study, we examined the effects of agricultural landscape parameters on the abundance and body condition of the rice frog (Fejervarya multistriata), which is a dominant anuran species in farmland in China. Employing a visual encounter method, we surveyed rice frog abundance for 3 years across 20 agricultural landscapes. We also calculated the body condition index (BCI) of 188 male frog individuals from these agricultural landscapes. Landscape variables, comprising landscape compositional heterogeneity (using the Shannon diversity index of all land cover types except buildings and roads), landscape configurational heterogeneity (using landscape edge density), breeding habitat diversity (using the number of 5 waterbody types available as breeding habitats), and areas of forest were also measured for each 1-km radius landscape. We found that the amount of forest in each agricultural landscape had a significant positive relationship with rice frog abundance, and breeding habitat diversity was positively related to the BCI of male rice frogs. However, body condition was negatively impacted by landscape configurational heterogeneity. Our results suggested the importance of nonagricultural habitats in agricultural landscapes, such as waterbodies and forest, to benefit rice frog population persistence. [ABSTRACT FROM AUTHOR]

Patterned fabrics are generally constructed from the periodic repetition of a primitive pattern unit. Repeat pattern segmentation of printed fabrics has a very significant impact on the pattern retrieval and pattern defect detection. In this paper, we propose a new approach for repeat pattern segmentation by employing the adaptive template matching method. In contrast to the traditional method for template matching, the proposed algorithm first selects an adaptive size template image in the repeat pattern image based on the size of the original image and its local maximum edge density. Then it uses the sum of absolute differences as the matching features to identify the matched regions in the original image, and the minimum envelope border of the primitive pattern, typically as a parallelogram, can be determined from the results of the four adjacent matched templates. Finally, image traversal base on the obtained parallelogram is implemented over the original image using minimum information loss theory to produce a well-segmented primitive pattern with a complete edge structure. The results from the experiments conducted using an extensive database of real fabric images show that the proposed algorithm has the advantage of rotation invariance and scaling invariance and will not be affected when the background or foreground color is changed. [ABSTRACT FROM AUTHOR]

Paraphrases are well-known as synonyms that express the same context in different articulations. Extracting paraphrases from a large text corpus is a challenging task in Natural Language Processing applications. The present work proposes a graph based clustering technique for discovering labels of crime reports based on extracted paraphrases from large untagged crime corpora. Initially, the entity pairs are represented as shallow parse trees where the headword in each tree reflects the actual meaning of the phrase between the entities. Though the phrases having similar headwords have been collected together, there exist many phrases between the entities that express similar context without sharing the same headword. Therefore, clustering is done to create a group of similar meaning phrases termed as paraphrases. A complete weighted graph is constructed with the phrases as nodes and cosine similarity between pair of phrases as the weight of an edge with the phrases as terminal nodes. The graph is made sparse by removing edges with weights less than a threshold value and clustering coefficient has been calculated for each node. The subgraph(s) comprising node(s) with the highest clustering coefficient has been extracted with their adjacent edges. The remaining nodes with their adjacent edges in the graph are added one at a time to an extracted subgraph, if and only if the average clustering coefficient of the resultant subgraph increases and an agglomerative merging technique is applied to merge the extracted subgraphs until no merging takes place. Finally, each subgraph represents a cluster of phrases, yields one aspect of crime. Based on the extracted paraphrases, the reports can be easily labelled. The proposed work deals with crime reports for United States of America (USA), United Arab Emirates (UAE) and India and the evaluation is performed in terms of various supervised and unsupervised techniques. • Novel approach for labelling crime reports. • Three important crime aspects are considered. • Graph based hierarchical clustering of paraphrases is done. • Proposed sparsity scheme is compared with edge density and Gini index based sparsity. • The experimental results show the effectiveness of the work. [ABSTRACT FROM AUTHOR]

Forest fragmentation and deforestation are major causes of biodiversity loss around the globe. Owing to high human and cattle population in India, the immense pressure on natural resources has led to greater degradation of natural ecosystems. The landscape-level changes have in turn resulted in changes in species diversity and composition. Adilabad district has the largest proportion of forest area in Telangana, India. We studied the impact of land right awards granted under the Recognition of Forest Rights Act (RoFR), 2006 in the Adilabad Division. We hypothesize that the forest area awarded to the tribal under RoFR and illegal encroachment in forests have adversely impacted the forest biodiversity. To verify our hypothesis, we calculated edge density (ED), patch density (PD) and core area index (CAI) of all the Reserve Forest areas using FRAGSTATS and compared the results with the pre-RoFR situation. Our results indicate that ED and PD increased predominantly across the Reserve Forest blocks where a large number of rights was granted under RoFR, whereas CAI decreased. Statistically for all the three parameters, pre- and post-RoFR values were found to be significantly different indicating that the changes due to implementation of RoFR have a significant adverse impact on the forests. Our findings are consistent with our hypothesis, and indicate that the continued use of forest areas for agriculture in RoFR and encroachment areas may further adversely impact the ecosystem. There is an urgent need to identify and implement conservation actions that would allow restoration of biodiversity of the Reserve Forest areas adversely affected by land rights awarded under RoFR. Measures such as aggregation of the scattered RoFR areas towards the Reserve Forest boundary and improved agricultural practices such as agroforestry may alleviate such adverse impacts. [ABSTRACT FROM AUTHOR]

Managing agricultural landscapes to support biodiversity and ecosystem services is a key aim of a sustainable agriculture. However, how the spatial arrangement of crop fields and other habitats in landscapes impacts arthropods and their functions is poorly known. Synthesising data from 49 studies (1515 landscapes) across Europe, we examined effects of landscape composition (% habitats) and configuration (edge density) on arthropods in fields and their margins, pest control, pollination and yields. Configuration effects interacted with the proportions of crop and non‐crop habitats, and species' dietary, dispersal and overwintering traits led to contrasting responses to landscape variables. Overall, however, in landscapes with high edge density, 70% of pollinator and 44% of natural enemy species reached highest abundances and pollination and pest control improved 1.7‐ and 1.4‐fold respectively. Arable‐dominated landscapes with high edge densities achieved high yields. This suggests that enhancing edge density in European agroecosystems can promote functional biodiversity and yield‐enhancing ecosystem services. [ABSTRACT FROM AUTHOR]

• Municipalities with the potential to spread the yellow fever virus exhibited a higher amount of forest edge. • Statistical models showed a strong association between forest edge density and the risk of occurrence of epizootics. • Fragmented landscapes with a higher degree of connectivity favor the spread of YFV. • Landscapes with fewer connections tend to act as dead zones for the circulation of the virus. The intense process of deforestation in tropical forests poses serious challenges for the survival of biodiversity, as well as for the human species itself. This scenario is supported by the increase in the incidence of epidemics of zoonotic origin observed over the last few decades. In the specific case of sylvatic yellow fever (YF), it has already been shown that an increase in the transmission risk of the causative agent (yellow fever virus - YFV) is associated with areas with a high degree of forest fragmentation, which can facilitate the spread of the virus. In this study we tested the hypothesis that areas with more fragmented landscapes and a higher edge density (ED) but a high degree of connectivity between forest patches favor YFV spread. To this end, we used YF epizootics in non-human primates (NHPs) in the state of São Paulo to build direct networks, and used a multi-selection approach to analyze which landscape features could facilitate YFV spread. Our results showed that municipalities with the potential to spread the virus exhibited a higher amount of forest edge. Additionally, the models with greater empirical support showed a strong association between forest edge density and the risk of occurrence of epizootic diseases, as well as the need for a minimum threshold of native vegetation cover to restrict their transmission. These findings corroborate our hypothesis that more fragmented landscapes with a higher degree of connectivity favor the spread of YFV, while landscapes with fewer connections tend to act as dead zones for the circulation of the virus. Additive effect between probability of occurrence of YF epizootics in NHPs and edge density (ED) (A) and largest patch index (LPI) (B). ED exhibited a strong association with the occurrence of epizootics, while LPI also had a positive association but with a weaker individual contribution. The blue line corresponds to the best fit, and the gray area represents the 95% confidence intervals. [Display omitted] [ABSTRACT FROM AUTHOR]