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How do species' distributions respond to their environments? This question was at the heart of the Clements-Gleason controversy, ecology's most famous debate. Do species respond to the environment in concerted ways, leading to distinct and cohesive assemblages (the Clementsian paradigm), or do species respond to the environment independently (the Gleasonian paradigm)? Using plant occurrences along the elevation gradient of Pikes Peak (Colorado) as a lens through which to gain insight into Clements's perspectives on the debate, we formally test for community patterns along this gradient using a modern framework unavailable at the time of Clements and Gleason. The Pikes Peak region was Clements's study area for more than 40 years, where he established a research lab and distributed sites along the elevational gradient. His investigations of plant distributions on this mountain likely influenced his views on communities. We found mixed support for the paradigms, with neither the Gleasonian paradigm nor the Clementsian paradigm fully supported. While distributions along the gradient showed evidence of clustering of species range edges, considered to be consistent with the Clementsian paradigm, the pattern was weak, and neither range edges nor species turnover peaked at ecotone elevations, as expected under the Clementsian paradigm. Our results illuminate the Clements-Gleason debate by allowing us to probe issues that complicate conclusively testing the paradigms, such as deciding on how we quantify environmental gradients and determining the appropriate scales for community patterns and processes that might generate them. Revisiting the debate also revealed that Clements's and Gleason's views had more in common than we realize. The debate may be less neatly resolved than we assume from mythos, and it continues to have relevance to basic and applied ecology today, as its legacy has shaped our (still tenuous) notion of ecological communities and the trajectory of our field. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical analysis of semantic convergence in transformer-based language models, drawing inspiration from the concept of fractal self-similarity. We introduce and prove a novel theorem characterizing the gradient of embedding similarity across layers. Specifically, we establish that there exists a monotonically increasing function that provides a lower bound on the rate at which the average cosine similarity between token embeddings at consecutive layers and the final layer increases. This establishes a fundamental property: semantic alignment of token representations consistently increases through the network, exhibiting a pattern of progressive refinement, analogous to fractal self-similarity. The key challenge addressed is the quantification and generalization of semantic convergence across diverse model architectures and input contexts. To validate our findings, we conduct experiments on BERT and DistilBERT models, analyzing embedding similarities for diverse input types. While our experiments are limited to these models, we empirically demonstrate consistent semantic convergence within these architectures. Quantitatively, we find that the average rates of semantic convergence are approximately 0.0826 for BERT and 0.1855 for DistilBERT. We observe that the rate of convergence varies based on token frequency and model depth, with rare words showing slightly higher similarities (differences of approximately 0.0167 for BERT and 0.0120 for DistilBERT). This work advances our understanding of transformer models' internal mechanisms and provides a mathematical framework for comparing and optimizing model architectures. [ABSTRACT FROM AUTHOR]

This study investigates dosimetric influence and gradient-analysis of leaf-width of various Multi-leaf-collimators (MLC) from Truebeam and Halcyon linear accelerators. The leaf-width effects of Millennium120 and HD120MLC from Truebeam and SX1 and SX2 from Halcyon were studied using virtual phantom in Eclipse16.1.2 TPS. Target structures consist of bore and wave cylinders of equally spaced projected Planning target volume (PTV) of diameters ranging from 1-to-5 cm and 20 cm length. Treatment plans for all PTVs, and four different MLCs configurations from both machines were created utilizing 6MVFFF beam to deliver dose of 50Gy/25# using IMRT and VMAT. Plans were evaluated using plan quality indices including dose conformity, homogeneity, gradient radius, and Monitor-unit (MU). Also, dose gradients were analyzed by estimating distinct integral volume V D% and paired-t-tests were performed to evaluate statistical differences. All the plan satisfied the minimum criteria of D 95 % ≥prescription dose and V 107 % ≤2cc. Mean conformity and homogeneity indices for SX1MLC(CI = 0.680,HI = 0.022) were found significantly higher and lower than SX2(CI = 0.746,HI = 0.016), Millennium120 (CI = 0.739,HI = 0.012), and HD120MLC(CI = 0.745,HI = 0.017), respectively. However, CI and HI for SX2, Millennium120, and HD120MLC found comparable. Gradient radius enclosing 50 % of isodose observed maximum and minimum for SX1 and HD120MLC, respectively. Plan MUs for Truebeam MLCs were found approximately 25 % higher than Halcyon MLCs. Dose distribution generated using SX2 and Millennium120 found comparable, however p ≤ 0.05 ascertained substantial differences among SX1, Millennium120, and HD120MLC. MLC leaf-width influences intensity-modulation and significantly alters dosimetric outcome depending on the magnitude of the leaf-width. HD120MLC does not show much significant advantages over SX2 and Millennium120 except gradient control. Halcyon SX1MLC produces least effective plan compared to all other MLC types. However, SX2 and Millennium120 can produce plans of comparable quality except plan MUs difference. [ABSTRACT FROM AUTHOR]

Context: The spatial distribution of plant diversity in urban areas is fundamental to understanding the relationship between urbanization and biodiversity. Previous research has primarily focused on taxonomic levels to assess species richness. In contrast, investigations into the spatial patterns of phylogenetic diversity in urban plants remain limited. Objectives: This study aims to investigate the spatial patterns of plant phylogenetic diversity along an urban–rural gradient and quantify how phylogenetic diversity and the degree of urbanization are related. Methods: A survey of vascular plants was conducted at 134 randomly selected sample plots along four urban–rural transects in Shanghai, China. Three phylogenetic diversity metrics were calculated: Faith’s phylogenetic diversity (PD), net relatedness index (NRI), and net nearest taxon index (NTI), along with the urbanization degree index (UDI). Regression analysis was employed to quantify the spatial patterns of plant phylogenetic diversity across different taxa along the urban–rural gradients and their relationships with UDI. Results: The study observed seven distinct patterns of plant phylogenetic diversity along the urban–rural gradients in different taxa, which support the previous hypotheses that biological distribution patterns at the species level also hold true at the phylogenetic level. Faith’s phylogenetic diversity (PD) showed a linear increase with increasing UDI for total, woody, perennial, and cultivated plant assemblages. The UDI explained 3–36% of the variation in PD for these taxa. In contrast, PD for annual and spontaneous plants exhibited a linear decrease with increasing UDI, which explained 25% and 3% variation in PD for annual and spontaneous plants, respectively. The net relatedness index (NRI) for woody, perennial, and cultivated plants, as well as the net nearest taxon index (NTI) for perennial and cultivated plants, linearly increases with UDI, whereas the NRI for total, annual, and spontaneous plants, as well as NTI for total, woody, annual, and spontaneous plants linearly decrease with UDI. However, some of these trends were only marginally significant. Conclusions: The spatial patterns of plant phylogenetic diversity varied along the urban-to-rural gradients, indicating that urban environmental filtering has an impact on plant phylogenetic diversity. Urbanization increased the phylogenetic richness of different plant taxa in Shanghai but resulted in more clustering and relatedness of species within plant assemblages. Phylogenetic richness exhibited a linear increase with UDI, while the phylogenetic divergence decreased with UDI. The UDI is a useful predictor for examining variations in plant phylogeny due to urbanization. Our findings provide insights into how urbanization impacts plant phylogenetic diversity, helping urban plant diversity conservation. [ABSTRACT FROM AUTHOR]

Understanding the spatial patterns of urban building morphology is crucial for revealing the interplay between the built and social environments. Previous research has predominantly concentrated on the computation of building-level metrics which makes it challenging to quantify and compare spatial patterns and variations across different cities. Using the newly available world settlement footprint 3D (WSF3D) data, this study examines the spatial patterns of urban building morphology across various cities within the Guangdong-Hong Kong-Macao Greater Bay Area, a rapidly urbanizing region in China. Specifically, we applied a concentric ring approach to delineate the spatial gradients of the building fraction, area, height, and volume from the urban center to the suburban fringes. Subsequently, we utilized dynamic time warping and a multi-dimensional scaling technique facilitating a comparative analysis of these gradients across cities. Developed cities demonstrated more homogenous distributions of building morphologies; however, notable differences were observed among the spatial patterns of distinct building metrics. Furthermore, a correlation between the spatial patterns of urban building morphology and degree of urban development was revealed, suggesting that developed cities exhibit significantly smaller declines in building morphology from the urban core to the rural periphery.

The Maritaing region in East Nusa Tenggara Province, Indonesia, offers significant geothermal potential for direct power generation and use. This study aims to re-evaluate the geothermal system model in the Maritaing geothermal field using high-resolution gravity inversion. High-resolution gravimetric data were collected using satellite observations and data processing techniques, allowing a better understanding of the subsurface geological structure and density distribution of rocks associated with the geothermal reservoir. This study applied data corrections to acquire complete Bouguer anomalies, gravity gradient analysis to detect geological structures, and inversion modeling of residual gravity anomalies to predict subsurface rock density distribution. The complete Bouguer anomalies exhibit positive values ranging from 70 to 140 mGal and have a northwest–southeast orientation, indicating the existence of andesitic lava and pyroclastic volcanic rocks. Gravity gradient analysis determines the geological structures, such as faults or fractures, used as conduits to create Kura Hot Springs. The model provides useful insights into geological occurrences, such as faults, rock layers, and reservoir accumulations that support geothermal fluids. Based on the present study’s findings, we provide recommendations for developing and managing geothermal resources in the Maritaing area. [ABSTRACT FROM AUTHOR]

Due to the economic importance and ecological vulnerability of coastal areas, the optimization of spatial patterns is important for the sustainable development of coastal zones. In this study, a new landscape pattern index gradient analysis method coupled with wavelet algorithm (GA-WA) was explored to balance the development and protection activities in the coastal zone. First, based on the classification results of remote sensing images, the gradient detection of the coastal zone was carried out using the cumulative moving window method, and the calculation of the landscape pattern index was carried out using Fragstats software to obtain the gradient change curve of the landscape pattern index. Secondly, the wavelet algorithm was applied to micro-analyze the above gradient change curves, and the results of multiscale analysis of the landscape pattern index in the study area were obtained. Finally, it is demonstrated how this method can help in practical decision making. It was found that:(1) The landscape pattern index gradient analysis method coupled with wavelet algorithms offers a new approach to balance the development and protection of coastal zones. This approach presents an innovative method for optimizing the ecological pattern of coastal zone landscapes from the perspective of macro–micro combination, which is not only applicable to coastal zones but also can be extended to other strip corridor landscapes.(2) The gradient analysis of the coastal zone landscape pattern index provides results at multiple spatial scales, which is superior to the analysis at a single spatial scale. The results of the gradient analysis method are finer and more stable, which solves the uncertainty problem of traditional landscape pattern index analysis. There is a significant difference between the landscape indices of the overall landscape and the gradient landscape, in which the AREA_MN index of the ecological land has the largest difference, reaching 110.18%.(3) Wavelet coefficient variance diagrams, real component contour diagrams, and modulus squared diagrams reveal the characteristics, cycles, and patterns of landscape dynamics changes, as well as the distribution at different gradient window scales. These tools help to identify the driving factors and development trends of landscape dynamics changes and solve problems of functional positioning in undeveloped areas, as well as the transformation of microscopic small parcels within developed areas. By analyzing regular cycles of landscape index changes, it is possible to determine the functional positioning of land and to position human intervention through peaks to guard against risky gradient windows.

In this paper, we propose the gradient-oriented prioritization meta-learning (GOPML) algorithm, a new approach for few-shot fault diagnosis in industrial systems. The GOPML algorithm utilizes gradient information to prioritize tasks, aiming to improve learning efficiency and diagnostic accuracy. This method contrasts with conventional techniques by considering both the magnitude and direction of gradients for task prioritization, which potentially enhances fault classification performance in scenarios with limited data. Our evaluation of GOPML's performance across varied fault conditions and operational contexts includes extensive testing on the Tennessee Eastman Process (TEP) and Skoltech Anomaly Benchmark (SKAB) datasets. The results indicate a consistent level of performance across different dataset divisions, suggesting its utility in practical industrial settings. The adaptability of GOPML to specific task characteristics, particularly in environments with sparse data, represents a notable contribution to the field of meta-learning for industrial fault diagnosis. GOPML shows promise in addressing the challenges of few-shot fault diagnosis in industrial systems, contributing to the growing body of research in this area by offering an approach that balances accuracy and generalization with limited data. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical analysis of semantic convergence in transformer-based language models, drawing inspiration from the concept of fractal self-similarity. We introduce and prove a novel theorem characterizing the gradient of embedding similarity across layers. Specifically, we establish that there exists a monotonically increasing function that provides a lower bound on the rate at which the average cosine similarity between token embeddings at consecutive layers and the final layer increases. This establishes a fundamental property: semantic alignment of token representations consistently increases through the network, exhibiting a pattern of progressive refinement, analogous to fractal self-similarity. The key challenge addressed is the quantification and generalization of semantic convergence across diverse model architectures and input contexts. To validate our findings, we conduct experiments on BERT and DistilBERT models, analyzing embedding similarities for diverse input types. While our experiments are limited to these models, we empirically demonstrate consistent semantic convergence within these architectures. Quantitatively, we find that the average rates of semantic convergence are approximately 0.0826 for BERT and 0.1855 for DistilBERT. We observe that the rate of convergence varies based on token frequency and model depth, with rare words showing slightly higher similarities (differences of approximately 0.0167 for BERT and 0.0120 for DistilBERT). This work advances our understanding of transformer models’ internal mechanisms and provides a mathematical framework for comparing and optimizing model architectures.

Urban green infrastructure (UGI) that provides diverse ecosystem services are crucial components of a city. Achieving appropriate density and equitable distribution of UGI is highly significant for urban planning to ensure sustainable and high-quality development. However, there is still a lack of an applied method for effectively measuring spatial equity of UGI in cities with multiple scales, which impairs the ability to regularly monitor it. Furthermore, the extent to which UGI should be implemented in urban planning in China is still uncertain. In this study, a “Structure-Function-Zoning“ analysis framework for the spatial pattern of UGI is proposed. A monitoring index system in terms of the structure and functions of UGI is first established. Then, an approach for measurement of spatial distribution equity of UGI is developed based on a spatial zoning strategy along the urban expansion axis. And a weighted index is proposed for comprehensive evaluation of UGI pattern. Using three Chinese cities (i.e., Beijing, Tianjin, Shijiazhuang) as examples, our research shows that the UGI pattern of Tianjin is distributed more balanced from urban center to suburb among the cities and Shijiazhuang shows relatively poor spatial equity of UGI. In terms of comprehensive evaluation of UGI pattern, Beijing and Tianjin are both rated as “moderate” while Beijing was slightly better than Tianjin, and Shijiazhuang was rated as “relatively poor”. The proposed analysis framework is designed to access the structure and function of UGI in a way that can be spatially differentiated, easily described, and clearly compared for cities of different sizes. More broadly, the comprehensive index adopted in the study can be regarded as a simple and practical tool to perform regular monitoring and provide early warning for UGI planning in urban renewal process.

Modeling species distribution and predicting the effects of climate change on plant species decline are necessary in restoration programs. This study aimed to predict the occurrence and decline of Astragalus verus under climate change in Central Iran with an area of about 123,167 km2. We recorded 12 and 71 sites for the dead and alive species using the stratified sampling method, respectively. The general circulation model of CCSM4 was applied at two timeframes of present and 2050 under two climate change scenarios of RCP2.6 and RCP8.5. Four environmental variables of annual mean temperature, the maximum temperature of the warmest month, the precipitation of the coldest quarter, and elevation were selected as the inputs of the nine statistical models. Results indicated that Random Forest model had the best performance in predicting climatic niche and decline of A. verus (AUC and TSS of 0.99) compared to the other models. The suitable habitat and decline for this species are 12.4% and 19.87% of the study area, respectively. With the estimated temperature rise of 3 °C under the CCSM4-RCP2.6 scenario, A. verus habitat will shrink by about 3.4% of the study area and will move toward higher elevations with colder temperatures in the future. Most changes in the suitability of the species will occur in the altitude range of 1800 to 2200 meters because the most temperature and precipitation variations will happen in this elevation stratum. The results can be used to prevent its rapid dieback or even restore vegetation cover in regions with similar conditions. [ABSTRACT FROM AUTHOR]

With the help of gradient analysis and Ellenberg eco-scales, factors of differentiation of vegetation cover (moisture, illumination, soil acidity, and soil richness in mineral nitrogen) were revealed. Using nonmetric scaling, an ordination diagram of the distribution of geobotanical descriptions was created for 50 years of research (from 1971 to 2021). Correlation of ordination axes and ecological factors was carried out. On the ordination diagram and according to the results of cluster analysis, geobotanical descriptions form three distinct groups corresponding to certain time periods. Changes in the species composition in plant communities are caused by changes in illumination, moisture, and trophicity. Under the influence of drainage and successions of the vegetation cover for 50 years, on the site of a mesotrophic hummock-flark herb sphagnum mire, represented by mesotrophic hydrohygrophilous mire species, an oligotrophic hummock lawn dwarf-sphagnum pine forest was formed, formed by oligotrophic, mesohygrophilic forest-mie species. [ABSTRACT FROM AUTHOR]

The average numbers of birds recorded over the first half of summer (May 16–July 15) from 1880 to 2019 (with intervals predominantly since 1960) have been analyzed to identify the spatial typological structures and organization of bird assemblages in northern Eurasia. Overall, 352 researchers have been involved in collecting this material for 110 years. Data processing is carried out with multivariate statistics methods, including cluster analyses, qualitative linear approximation to the connectivity matrices, and the gradient and expert approaches. Therefore, the main spatial trends in corvid communities and the natural and anthropogenic regimes correlating with them have been identified. The relationship between the spatial variability of the assemblages of these birds and the heterogeneity of habitats has been assessed. The quasi-fractal patterns of spatial differentiation of communities are shown. The analysis of corvid groups based on factor classification give unsatisfactory results on approximation for spatial and typological variability in their assemblage abundance at the confined-landscape scale level, while it shows rather high informativity of classification of species abundance across all 8144 habitats. A satisfactory explanation of heterogeneity in communities of Corvidae was achieved only after averaging the values for abundances of bird species associated with landcover types. It is impossible to get an idea about them based on cluster analysis, while the gradient and expert (speculative) approaches followed by estimating the informativity of concepts may be considered acceptable for such generalizations. The techniques indicated above contribute to a higher informativity score incorporating representiveness by the average abundance values, which had sevenfold and threefold increases in terms of the explained dispersion and the multiple coefficients of correlation, respectively. In addition, structural classifications of species and, especially, territorial communities acquire a two-dimensional reticular (grid-based) structure. The formalized classification of corvid species is seven times and two times more informative about distribution similarity and assemblages, respectively, than the expert and speculative ideas. [ABSTRACT FROM AUTHOR]

In this paper, we propose the gradient-oriented prioritization meta-learning (GOPML) algorithm, a new approach for few-shot fault diagnosis in industrial systems. The GOPML algorithm utilizes gradient information to prioritize tasks, aiming to improve learning efficiency and diagnostic accuracy. This method contrasts with conventional techniques by considering both the magnitude and direction of gradients for task prioritization, which potentially enhances fault classification performance in scenarios with limited data. Our evaluation of GOPML’s performance across varied fault conditions and operational contexts includes extensive testing on the Tennessee Eastman Process (TEP) and Skoltech Anomaly Benchmark (SKAB) datasets. The results indicate a consistent level of performance across different dataset divisions, suggesting its utility in practical industrial settings. The adaptability of GOPML to specific task characteristics, particularly in environments with sparse data, represents a notable contribution to the field of meta-learning for industrial fault diagnosis. GOPML shows promise in addressing the challenges of few-shot fault diagnosis in industrial systems, contributing to the growing body of research in this area by offering an approach that balances accuracy and generalization with limited data.

It is important to effectively detect, mitigate, and defend against Android malware attacks, because Android malware has long represented a major threat to Android app security. Characterizing and classifying similar malicious apps into groups plays a particularly crucial role in building a secure Android app ecosystem. The classification of malware families can efficiently enhance the malware detection process and systematically elucidate malware patterns. In this paper, we propose a novel efficient deep learning network with multi-streams for Android malware family classification. We first obtain the input data for a convolutional neural network (CNN) in string format from some main files or sections contained in each Android malicious app. We then classify malware families by applying a 1-dimensional convolution filter-based network for the files or sections. Further, by using gradient analysis to visualize the important files and sections in malicious apps, we attempt to intuitively grasp which files or sections are the most significant for malware family classification. To validate the effectiveness of our approach, we conduct extensive experiments with the well-known DREBIN and AMD malware datasets, and we compare our approach with existing methods. Our experimental results show that the 1D CNN model is more accurate than the 2D CNN model, and that the code_item part in the classes.dex is the most relevant feature for malware classification, as it is more relevant than other parts such as AndroidManifest.xml and certificate. The proposed method achieves the best accuracy of 93.2% by using 1D convolution filters with multi-streams for the main files and sections of the malware samples.

Shallow lakes are prone to water quality deterioration and are difficult to manage. Turbidity is a physical parameter commonly used to estimate water quality. Revealing the spatiotemporal variations in turbidity can help determine the risk areas of water turbidity to achieve efficient protection and management of water resources. Here, we conducted continuous field observations and monitoring of turbidity in Baoan Lake (114°39′–114°46′E, 30°12′–30°18′N), a shallow lake (average depth: 2.27 m) in southeastern Hubei Province, China, from July 2019 to May 2022, to perform gradient analysis and determine risk levels of water turbidity. Results showed that the average turbidity of the Baoan Lake varied within the range of 9.0–48.8 NTU. Water turbidity fluctuated, reaching peaks in summer or autumn, and troughs in winter. The overall variation of water turbidity in spring and summer ranged within 15 NTU, while in autumn and winter it was over 29 NTU. The turbidity of Zhuti and Qiaodun Lakes (ZL and QL, respectively) was often higher than that of Xiaosihai and Biandantang Lakes (XL and BL, respectively), showing a turbidity decrease from southeast to northwest, especially in winter. A gradient function describing the spatial variation in turbidity was summarized. The parameters of the function had implicit meanings for spatial variations in turbidity. Parameter a influenced the form of the fitting curve. Parameters b and c reflected the range of turbidity values. The two points of the second derivative of the function were considered to indicate the radius of the risk area in a concentric manner. The methodology proposed to identify the risk levels of water turbidity entails the calculation of the risk values for different seasons. Thus, this study provides a new tool for quantifying spatial gradient variation of water turbidity and a new method for determining high-risk areas and risk levels of water turbidity.

The deep boundary and contact relationship between the Yangtze and Cathaysia Blocks (the major tectonic units of the Southern China Block), as well as the tectonic attributes of the Jiangnan Orogenic Belt, have remained unknown or controversial. Using data recorded by 128 portable broadband stations and 96 permanent stations, we obtained high-resolution images of crustal thickness and Poisson’s ratio in the study area. The influences of crustal anisotropy and inclined interface were eliminated by using the newly proposed receiver function H–κ–c stacking method. We then used a gradient analysis method to obtain crustal thickness gradients at the boundary of the Yangtze and Cathaysia Blocks for the first time. Our results reveal that the crustal thickness varies from >38 km in the Qinling–Dabie Orogenic Belt to 0.27) are concentrated on the flanks of the deep fault zone and the continental margin of the study area; those with low Poisson’s ratios (5 km/°). Combined with the velocity structure and discontinuity characteristics at different depths, these findings suggest that the Jiujiang–Shitai fault may constitute a deep tectonic boundary dividing the Yangtze and Cathaysia Blocks on the lithospheric scale. Moreover, our results support that the Cathaysia Block subducted northwest-ward toward the southeastern margin of the Yangtze Block in the Neoproterozoic, and that the Jiujiang–Shitai buried fault and Jiangshan–Shaoxing fault are the deep and shallow crustal contact boundaries of the two Blocks, respectively; that is, the Yangtze Block overlaps the Cathaysia Block.

Species' responses to broad‐scale environmental or spatial gradients are typically unimodal. Current models of species' responses along gradients tend to be overly simplistic (e.g., linear, quadratic or Gaussian GLMs), or are suitably flexible (e.g., splines, GAMs) but lack direct ecologically interpretable parameters. We describe a parametric framework for species‐environment non‐linear modelling ('senlm'). The framework has two components: (i) a non‐linear parametric mathematical function to model the mean species response along a gradient that allows asymmetry, flattening/peakedness or bimodality; and (ii) a statistical error distribution tailored for ecological data types, allowing intrinsic mean–variance relationships and zero‐inflation. We demonstrate the utility of this model framework, highlighting the flexibility of a range of possible mean functions and a broad range of potential error distributions, in analyses of fish species' abundances along a depth gradient, and how they change over time and at different latitudes. [ABSTRACT FROM AUTHOR]

On the Kamchatka Peninsula, Far East Russia, Pinus pumila-dominated communities occur from sea level up to 1200 m and geographically from the southern extremity of the peninsula up to the Kamchatka Isthmus and the Koryak Upland. Variation in species composition and abundance in P. pumila stands are determined mainly by the habitat’s moisture, soil fertility (expressed as the litter-humus coefficient) and altitude. The fertility level of the habitats has a significant positive impact especially on the abundance of the herb layer species, and to a lesser extent on the cover of the shrub layer. The growth of dwarf-shrubs and lichens is inhibited in habitats with better fertility. In relation to the fertility gradient, the vertical structure of the communities is also changing explicitly; the thickness of snow cover and exposition has a modest effect on the vegetation of P. pumila stands on Kamchatka. The analysed set of 272 relevés were clustered into six community type groups: (i) pure dwarf-pine communities, (ii) shrub-rich communities, (iii) dwarf-shrub-rich communities, (iv) herb-grass-rich communities, (v) moss-rich communities and (vi) lichen-rich communities; further 18 community types were established. They have a fairly good correspondence with most of the syntaxa described by previous scholars, but this is not always the case.

Long-term monitoring of middle taiga wetland vegetation has been undertaken at the Kindasovo Forest and Mire Research Station, which is located within the Koivu-Lambasuo Nature Reserve in southern Karelia (north-west Russia). This article revisits the results of 50 years’ monitoring of post-drainage succession in a meso-oligotrophic dwarf shrub - Sphagnum pine mire. The purpose of drainage was to improve the quality of the site for forestry. Gradient analysis and Ellenberg’s indicator values were used to associate differentiation of the plant cover with the main environmental factors (availability of moisture and light, soil acidity, soil mineral nitrogen content), and thus to distinguish three chronological drainage periods on the basis of changes in the plant communities, which are then described. The initially understocked dwarf shrub - Sphagnum pine stand (low quality forest) evolved over 50 years into a well-stocked pine stand, but this was not a sufficient period for the ground cover vegetation to reach a new stable state. Nonetheless, analysis of species composition dynamics during the three drainage periods showed that species diversity increased from 17 to 31 species, wetland species were preserved but their prevalence and percentage cover declined, and forest-associated species appeared.

• GA-WA provides a novel approach for balancing coastal zone development and protection. • Gradient analysis provides landscape pattern analysis at multiple spatial scales. • A notable difference in landscape index between whole and gradient coastal landscape. • GA-WA can be used as ecological corridor planning to locate function of micro patches. Due to the economic importance and ecological vulnerability of coastal areas, the optimization of spatial patterns is important for the sustainable development of coastal zones. In this study, a new landscape pattern index gradient analysis method coupled with wavelet algorithm (GA-WA) was explored to balance the development and protection activities in the coastal zone. First, based on the classification results of remote sensing images, the gradient detection of the coastal zone was carried out using the cumulative moving window method, and the calculation of the landscape pattern index was carried out using Fragstats software to obtain the gradient change curve of the landscape pattern index. Secondly, the wavelet algorithm was applied to micro-analyze the above gradient change curves, and the results of multiscale analysis of the landscape pattern index in the study area were obtained. Finally, it is demonstrated how this method can help in practical decision making. It was found that: (1) The landscape pattern index gradient analysis method coupled with wavelet algorithms offers a new approach to balance the development and protection of coastal zones. This approach presents an innovative method for optimizing the ecological pattern of coastal zone landscapes from the perspective of macro–micro combination, which is not only applicable to coastal zones but also can be extended to other strip corridor landscapes. (2) The gradient analysis of the coastal zone landscape pattern index provides results at multiple spatial scales, which is superior to the analysis at a single spatial scale. The results of the gradient analysis method are finer and more stable, which solves the uncertainty problem of traditional landscape pattern index analysis. There is a significant difference between the landscape indices of the overall landscape and the gradient landscape, in which the AREA_MN index of the ecological land has the largest difference, reaching 110.18%. (3) Wavelet coefficient variance diagrams, real component contour diagrams, and modulus squared diagrams reveal the characteristics, cycles, and patterns of landscape dynamics changes, as well as the distribution at different gradient window scales. These tools help to identify the driving factors and development trends of landscape dynamics changes and solve problems of functional positioning in undeveloped areas, as well as the transformation of microscopic small parcels within developed areas. By analyzing regular cycles of landscape index changes, it is possible to determine the functional positioning of land and to position human intervention through peaks to guard against risky gradient windows. [ABSTRACT FROM AUTHOR]

Anthropogenic pollution plays an important part in deteriorating the water quality of rivers all over the world, especially in urban areas of Africa where water quality monitoring is still seriously constrained by the limited test facility and capability. In this study, for evaluating the impact of urbanization on the river water quality, we investigated four typical urban rivers of Tanzania through the upper-urban-down gradient assessment approach and analyzed by water quality index (WQI) and statistical methods. The physicochemical indices monitored in these rivers revealed that the contents of those indicators of TN, TP, PO43−, NH4+, CODMn, and NO3− were accumulated significantly in the lower reaches of the cities, which indicated the life-type pollution characteristics in such urban rivers of Africa. The following main conclusions are achieved from this study. The water quality of 30% of the investigated river sections is in the medium to good status based on the subjective WQI with sensory factors included. Moreover, the sections with obvious water quality decline are mainly limited to the river segments within the urban central area, and severe pollution of water bodies is closely related to large cities, indicating an increasing pollution tendency with the quickly growing population. Therefore, to help formulate water pollution control policies in response to the rapid urban expansion in African countries, it is necessary to adopt an economical and feasible method to carry out early monitoring of surface water quality timely. [ABSTRACT FROM AUTHOR]

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The ecological niche sensu Hutchinson is defined as the set of environmental conditions allowing a species to grow, maintain, and reproduce. This conception of the niche, which is assimilated to a p‐dimensional hypervolume, with p representing all environmental variables, has been widely applied in ecology. However, displaying the niche hypervolume has proved challenging when more than three environmental dimensions are considered simultaneously. We propose a simple method (implemented in the specieschrom R package) that displays the full multidimensionality of the ecological niche of a species into a two‐dimensional space by means of a graphic we call species chromatogram. This method gives a graphical summary of the niche by representing together abundance gradients with respect to all environmental variables. A chromatogram enables niche optimums and breaths to be rapidly quantified, and when several chromatograms are examined (one per species), rapid comparisons can be made. From our chromatograms, we proposed a procedure that quantifies niche optimum and breadth as well as niche overlapping (index D) and the identification of the most discriminant combination of environmental variables. We apply these analyses on eight planktonic species collected by the Continuous Plankton Recorder (CPR) survey in the North Atlantic Ocean using 10 environmental variables. We display their full multidimensional niches and quantify their niche optimums and breadths along each dimension. We also compare our index D with other indices by means of hypervolume and dynRB R packages. By catching the full complexity of the niche, species chromatograms allow many different niche properties to be rapidly assessed and compared among species from niche optimums and breadths to the identification of the most relevant environmental parameters and the degree of niche overlapping among species. Species chromatograms may be seen as species' fingerprint and may also allow a better identification of the mechanisms involved in species assembly. [ABSTRACT FROM AUTHOR]

Abstract The ecological niche sensu Hutchinson is defined as the set of environmental conditions allowing a species to grow, maintain, and reproduce. This conception of the niche, which is assimilated to a p‐dimensional hypervolume, with p representing all environmental variables, has been widely applied in ecology. However, displaying the niche hypervolume has proved challenging when more than three environmental dimensions are considered simultaneously. We propose a simple method (implemented in the specieschrom R package) that displays the full multidimensionality of the ecological niche of a species into a two‐dimensional space by means of a graphic we call species chromatogram. This method gives a graphical summary of the niche by representing together abundance gradients with respect to all environmental variables. A chromatogram enables niche optimums and breaths to be rapidly quantified, and when several chromatograms are examined (one per species), rapid comparisons can be made. From our chromatograms, we proposed a procedure that quantifies niche optimum and breadth as well as niche overlapping (index D) and the identification of the most discriminant combination of environmental variables. We apply these analyses on eight planktonic species collected by the Continuous Plankton Recorder (CPR) survey in the North Atlantic Ocean using 10 environmental variables. We display their full multidimensional niches and quantify their niche optimums and breadths along each dimension. We also compare our index D with other indices by means of hypervolume and dynRB R packages. By catching the full complexity of the niche, species chromatograms allow many different niche properties to be rapidly assessed and compared among species from niche optimums and breadths to the identification of the most relevant environmental parameters and the degree of niche overlapping among species. Species chromatograms may be seen as species’ fingerprint and may also allow a better identification of the mechanisms involved in species assembly.

The Landsat images of the 2000, 2005, 2010, 2015, 2018 are selected as the data source to retrieve land cover and surface temperature data. The contribution of Sink-Source landscape pattern to the heat island and its ecological effects on urban and rural gradient were analyzed by using Heat Index (HI), Sink and Source Landscape Contribution (CIsink, CIsource) and Landscape Effect Index (LI) in Haikou. The results show that the heat island is concentrated on the West Coast, and in the central urban and Jiangdong New Area; the HI shows a pattern of decreasing value with the following land types: "Bare land>Artificial surface>Source landscape>Shrub grassland>Farmland>Sink landscape>Woodland>Water body". In the central city section, the CIsink and CIsource are relatively large in these five periods. The LI decreases rapidly along the urban-rural gradient, promoting the Urban Heat Island (UHI) to a large degree. In contrast, the suburban area contributes to a lesser degree. Overall, the LI fluctuates, the proportion of mitigating UHI is large, and there is a second peak outside the city center. The existing Source-Sink Landscape contributes the most to UHI in the central urban area, and this contribution decreases along the urban-rural gradient. With the continuous expansion of city-town areas, the proportion of Sink areas has increased along the gradient, and the proportion of Source areas has subsequently declined, resulting in the spatial transfer and diffusion of UHI. Therefore, a UHI mitigation strategy based on the theory of regional landscape systems is proposed here. [ABSTRACT FROM AUTHOR]

Introduction: Mexico concentrates around 11 % of the world’s bird species, of which 20 % are endemic to the country, with the highest number concentrated in the Western region. Objective: To analyze composition, diversity and avifaunal distribution along an elevation gradient in Western Mexico. Methods: The research was done in the Sierra de Manantlán Biosphere Reserve. We recorded seen or heard bird species in 28 fixed count points along a 1 000 m elevation gradient. Comparative richness and sampling completeness were determined with interpolation and extrapolation curves. Belts were compared with NonParametric Multi-Response Permutation. Correlations and indirect ordinations were used to analyze changes in richness and abundance. Results: We recorded 129 species (estimate: 96 % completeness): 19 endemics to Mexico, 13 in some risk category, and 21 considered indicators. Elevation determined the distribution and abundance of species, and the lower elevational bands, had the highest richness and abundance values. Conclusion: The highest species richness and abundance were recorded at lower elevations, with a significant change in composition and type of indicator species by belt. The numbers of endemic and at-risk species remained constant with elevation. [ABSTRACT FROM AUTHOR]

Abstract Semi‐natural mountain grasslands are increasingly exposed to environmental stress under climate change. However, which are the environmental factors that limit plants in these grasslands? Also, is the present management effective against these changes? Fitness‐related functional traits may offer a way to detect changes in performance and provide new insights into their vulnerability to climate change. We investigated changes in performance and variability of functional traits of the mountain grassland target species Arnica montana along a climate gradient in Central German low mountain ranges. This gradient represents at its lower end climate conditions that are expected at its upper end under future climate change. We measured vegetative, generative, and physiological traits to account for multiple ways of plant responses to the environment. Using mixed effects and multivariate models, we evaluated changes in trait values among individuals as well as the variability of their populations in order to assess performance under changing summer aridity and different management regimes. Fitness‐related performance of most traits showed strongly positive associations with reduced summer aridity at higher elevations, while only specific leaf area and leaf dry matter content showed no association. This suggests a higher performance level at less arid montane sites and that the physiological traits are less sensitive to this climate change factor. The coefficient of variation of almost all traits declined steadily with decreasing site aridity. We suggest that this reduced variability indicates a lower environmental stress level for A. montana toward its environmental optimum at montane elevations, especially because the trait performance increased simultaneously. Surprisingly, management factors and habitat characteristics had only low influence on both trait performance and variability. In summary, summer aridity had a stronger effect to shape the trait performance and variability of A. montana under increased environmental stress than management and other habitat characteristics.

This study examined early stages (3-5 years) of spontaneous primary vegetation succession on a model locality drastically altered by long term fluvial deposition of copper tailings in Eastern Serbia. In a large-scale survey, 115 samples of herbaceous vegetation (with a total of 75 species) were harvested from standardized 1m x 1m quadrates, and concomitant soil samples collected and their relevant physicochemical properties analysed. Primary succession depended on the establishment of five pioneer species (Rumex acetosella, Agrostis capillaris, Calamagrostis epigeios, Persicaria lapathifolia and Chenopodium botrys). Unconstrained ordination showed very clear vegetation gradients, significantly correlated with the key soil constraints (from Cu excess to low pH and nutrient deficiency), while the distribution of the five edificatory pioneers showed high degree of dependence on the micro-level habitat conditions. This work demonstrates that in such a complex setup with severe abiotic filtering, sufficient sampling effort can reveal strong patterns in a process commonly considered very stochastic.

Variation in community composition and species turnover are different types of beta diversity, expressing non-directional and directional changes, respectively. While directional changes (e.g. turnover) along geographic gradients can be studied in any direction depending on the hypothesis of interest to researchers, temporal changes can only be meaningfully studied from past to present. Although a wide variety of methods exist for partitioning variation and related community-level phenomena such as similarity, richness difference and nestedness, approaches evaluating species turnover along geographic or temporal gradients, based on an analogous conceptual framework, are rare. We therefore look into the possibilities for examining different aspects of directional changes along a gradient when presence-absence community data are available. Measures of community overlap, as well as species loss and gain from one sampling unit to another along a gradient are combined to define a variety of turnover and nestedness concepts and to derive functions for their quantification. Each concept represents an ecological phenomenon to be indicated (indicandum), whereas measures (indicators) quantify relevant properties of these concepts. The measures use the raw number of species as well as relativized forms in accordance with the well-known Jaccard and Sørensen indices. The main innovation is the development of new measures of directional community change. We demonstrate differences between traditional non-directional and the new directional measures and use several examples to show that actual communities display directional responses to a particular ecological gradient. The new measures therefore reveal an uncovered aspect of community ecology.

Savanna occurs in specific locations throughout the Indonesian archipelago, including some high rainfall regions. Little is known about its defining characteristics, such as structure, composition or diversity, and what these characteristics reveal about the origin and age of these savannas. At four locations in eastern Java (Baluran National Park & Alas Purwo National Park), Bali (Bali Barat National Park) and Lombok (Rinjani National Park), we used plots to record the abundance and cover of plant species and to measure local environmental parameters. MODIS burned-area product and field observations were used to obtain information on recent fires. We compared each savanna in terms of dominant species, species diversity and species richness. We also used ANOSIM to analyse the variation in community composition and canonical correspondence analysis to explore relationships between floristic and measured environmental factors. Our results showed there were distinct gradients in elevation (along with related climatic factors such as temperature and precipitation) and fire regime linked to floristic composition across the savannas of Java, Bali and Lombok Islands. Each savanna was characterized by a different set of woody and grass species, with invasive alien species, such as Acacia nilotica (syn. Vachellia nilotica), Lantana camara and Chromolaena odorata, being particularly important in differentiating between savannas. Characteristics of the Baluran savanna suggest that this ecosystem may be of considerable age, whereas the other savannas are likely to be maintained by regular fire. This study is the first study to describe more thoroughly the savanna plant community in the wetter parts of Indonesian archipelago and should serve as a valuable foundation for further studies on the Indonesian savannas and those of other parts of Southeast Asia. [ABSTRACT FROM AUTHOR]

Aims: This paper presents the results of phytosociological research on scree vegetation in the northern Apennines with the aim of comparing vegetation types classified in different syntaxa. The specific objectives were: 1) to identify, classify and describe the vegetation units of scree communities; 2) to pinpoint the main ecological gradients underlying different vegetation units; and 3) to identify a possible hierarchy of predictor variables explaining floristic differences between vegetation types. Study area: The study area lies on the northern border of the Italian Peninsula, between 44° and 44°45' N and 9°20' and 10°45' E, characterized by a large variety of scree habitats and representing both a centre of endemism and a phytogeographic transition zone between the Alps and Apennines. Methods: The study was based on a dataset including 364 relevés taken according to the Braun-Blanquet method, which were then classified following an unsupervised numerical procedure. Species fidelity was used to define the diagnostic species of the associations. PCA and RDA ordinations were employed to perform ecological analyses using both Ellenberg Indicator Values as indirect variables and directly measured or calculated variables. Results: A total of 15 plant associations were identified, belonging to 6 alliances and 4 different orders (Thlaspietalia rotundifolii, Arabido alpinae-Petasitetalia paradoxi, Achnatheretalia calamagrostis and Androsacetalia alpinae) within the class Thlaspietea rotundifolii. All associations were described according to their floristic composition, structure, syntaxonomy, habitat and distribution. Conclusions: Nine scree associations and two alliances - endemic to the study area - are described here for the first time. The syntaxonomic scheme followed is in accordance with that proposed in the EuroVegChecklist, with a few important exceptions. The largest variation in vegetation types was found along complex environmental gradients and the most important factors driving the difference between the four orders were gravel size, elevation and the geological substrate. [ABSTRACT FROM AUTHOR]

On the Kamchatka Peninsula, Far East Russia, Pinus pumila-dominated communities occur from sea level up to 1200 m and geographically from the southern extremity of the peninsula up to the Kamchatka Isthmus and the Koryak Upland. Variation in species composition and abundance in P. pumila stands are determined mainly by the habitat's moisture, soil fertility (expressed as the litter-humus coefficient) and altitude. The fertility level of the habitats has a significant positive impact especially on the abundance of the herb layer species, and to a lesser extent on the cover of the shrub layer. The growth of dwarf-shrubs and lichens is inhibited in habitats with better fertility. In relation to the fertility gradient, the vertical structure of the communities is also changing explicitly; the thickness of snow cover and exposition has a modest effect on the vegetation of P. pumila stands on Kamchatka. The analysed set of 272 relevés were clustered into six community type groups: (i) pure dwarf-pine communities, (ii) shrub-rich communities, (iii) dwarf-shrub-rich communities, (iv) herb-grass-rich communities, (v) moss-rich communities and (vi) lichen-rich communities; further 18 community types were established. They have a fairly good correspondence with most of the syntaxa described by previous scholars, but this is not always the case. [ABSTRACT FROM AUTHOR]

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

In the process of forming and transmitting images through communication channels, they are exposed to various types of noise, which in some cases leads to deterioration of visual quality and loss of areas of images. Reducing such defects is an urgent task in many applications in filtering and recovering data. Methods and technologies of data recovery in digital image filtering problems have been studied, which made it possible to formulate the main directions of improving data recovery processes without deteriorating their quality. Known classical filtering methods, such as the median filter, Gaussian filter, Wiener filter and others, used in known modern image processing software packages, often do not have satisfactory efficiency in processing specific types of noise and often lead to partial loss of useful signal. The aim of the work is to increase the efficiency of image filtering in the development of a new method of the smallest finite differences and the creation of an interactive web service for its implementation. The proposed method of filtering allows you to effectively eliminate pulsed noise from video data, taking into account a priori information about the noise without significant distortion of useful information. The found quantitative characteristics of the evaluation of the efficiency of the method show better results of pulse noise filtering in the image in comparison with the known ones. During the development of the method, a physic-mathematical interpretation of the recovery of digital images when interacting with additive pulse noise was used, and a gradient analysis model was used using the final differences of the pixel values of the images. The proposed algorithm is used to restore test images, the analysis of digital processing in comparison with other known methods using quantitative and qualitative characteristics. The advantage of the created Internet service is the implementation of flexible and efficient functions of digital image filtering, which is absent in the well-known graphics packages Adobe Photoshop, Paint, GIMP and others. In addition, the proposed solutions in the form of an Internet service are a good compromise between ease of implementation and quality of filtering, compared to powerful but difficult to implement and resource-intensive image processing systems. [ABSTRACT FROM AUTHOR]

Urban areas contain a complex mixture of surface materials resulting in mixed pixels that are challenging to handle with conventional mapping approaches. In particular, for spaceborne hyperspectral images (HSIs) with sufficient spectral resolution to differentiate urban surface materials, the spatial resolution of 30 m (e.g. EnMAP HSIs) makes it difficult to find the spectrally pure pixels required for detailed mapping of urban surface materials. Gradient analysis, which is commonly used in ecology to map natural vegetation consisting of a complex mixture of species, is therefore a promising and practical tool for pattern recognition of urban surface material mixtures. However, the gradients are determined in a data-driven manner, so analysis of their spatial transferability is urgently required. We selected two areas—the Ostbahnhof (Ost) area and the Nymphenburg (Nym) area in Munich, Germany—with simulated EnMAP HSIs and material maps, treating the Ost area as the target area and the Nym area as the well-known area. Three gradient analysis approaches were subsequently proposed for pattern recognition in the Ost area for the cases of (i) sufficient samples collected in the Ost area; (ii) some samples in the Ost area; and (iii) no samples in the Ost area. The Ost samples were used to generate an ordination space in case (i), while the Nym samples were used to create the ordination space to support the pattern recognition of the Ost area in cases (ii) and (iii). The Mantel statistical results show that the sample distributions in the two ordination spaces are similar, with high confidence (the Mantel statistics are 0.995 and 0.990, with a significance of 0.001 in 999 free permutations of the Ost and Nym samples). The results of the partial least square regression models and 10-fold cross-validation show a strong relationship (the calculation-validation R2 values on the first gradient among the three approaches are 0.898, 0.892; 0.760, 0.743; and 0.860, 0.836, and those on the second gradient are 0.433, 0.351; 0.698, 0.648; and 0.736, 0.646) between the ordination scores of the samples and their reflectance values. The mapping results of the Ost area from three approaches also show similar patterns (e.g. the distribution of vegetation, artificial materials, water, and ceremony area) and characteristics of urban structures (the intensity of buildings). Therefore, our findings can help assess the transferability of urban material gradients between similar urban areas.

As a major method for relation extraction, distantly supervised relation extraction (DSRE) suffered from the noisy label problem and class imbalance problem (these two problems are also common for many other NLP tasks, e.g., text classification). However, there seems no existing research in DSRE or other NLP tasks that can simultaneously solve both problems, which is a significant insufficiency in related researches. In this paper, we propose a loss function which is robust to noisy label and efficient for the imbalanced class dataset. More specific, first we quantify the negative impacts of the noisy label and class imbalance problems. And then we construct a loss function that can minimize these negative impacts through a linear programming method. As far as we know, this seems to be the first attempt to address the noisy label problem and class imbalance problem simultaneously. We evaluated the constructed loss function on the distantly labeled dataset, our artificially noised dataset, human-annotated dataset of Docred, as well as the artificially noised dataset of CoNLL 2003. Experimental results indicate that a DNN model adopting the constructed loss function can outperform other models that adopt the state-of-the-art noisy label robust or negative sample robust loss functions. [ABSTRACT FROM AUTHOR]

Aim: While we understand broad climate drivers of insect distributions throughout the Arctic, less is known about the role of spatial processes in determining these relationships. As such, there is a need to understand how spatial controls may influence our interpretations of chironomid environment relationships. Here, we evaluated whether the distribution of chironomids followed spatial gradients, or were primarily controlled by environmental factors. Location: Eastern Canadian Arctic, Greenland, Iceland. Taxon: Non‐biting midges (Chironomidae). Methods: We examined chironomid assemblages from 239 lakes in the western North Atlantic Arctic region (specifically from the Arctic Archipelago of Canada, two parts of west Greenland (the southwest and central west) and northwest Iceland). We used a combination of unconstrained ordination (Self Organizing Maps); a simple method with only one data matrix (community data), and constrained ordination (Redundancy Analysis); a canonical ordination with two datasets where we extracted structure of community related to environmental data. These methods allowed us to model chironomid assemblages across a large bioregional dimension and identify specific differences between regions that were defined by common taxa represented across all regions in high frequencies, as well as rare taxa distinctive to each region found in low frequencies. We then evaluated the relative importance of spatial processes versus local environmental factors. Results: We find that environmental controls explained the largest amount of variation in chironomid assemblages within each region, and that spatial controls are only significant when crossing between regions. Broad‐scale biogeographic effects on chironomid distributions are reflected by the distinct differences among chironomid assemblages of Iceland, central‐west Greenland, and eastern Canada, defined by the presence of certain common and low‐frequency, rare taxa for each region. Environmental gradients, especially temperature, defined species distributions within each region, whereas spatial processes combine with environmental gradients in determining what mix of species characterizes each broad and geographically distinct island region in our study. Main conclusions: While biogeographic context is important for defining interpretations of environmental controls on species distributions, the primary control on distributions within regions is environmental. These influences are fundamentally important for reconstructing past environmental change and better understanding historical distributions of these insect indicators. [ABSTRACT FROM AUTHOR]

The goals of the present study were to analyze changes in land cover and to estimate a future scenario for 2028 using an artificial neural network in the Karaj Metropolis. To this end, the effects of land use changes in response to urban expansion on landscape patterns were investigated in three baseline, current, and future scenarios using landscape metrics and gradient analysis. The results showed that during a 22-year period, the agricultural and Garden lands have been severely damaged due to urban expansion. The results of the evaluation of changes in landscape also indicate that urban expansion in in development in the north-south transect to the margins (especially northward) and the east-west transect with a gentle slope to the west of the region. It is also anticipated that in the future scenario, if the current trend continues, the northern margin of Karaj metropolis will be changed from natural environment to a completely human-made one. Therefore, considering the results of the Pd and Ed metrics in both transects over the three examined years, it can be said that the area has expanded to the margin and there has not been much changes in the landscape of downtown. In addition, the decrease in the Pd and NP in all three scenarios indicates the consistency of urban landscape. In general, population growth and urban development have made the landscape pattern in Karaj metropolis to be a more regular and less varied one. The results indicate that spatial heterogeneity has altered the landscape patterns. Therefore, the growth of construction land in some areas should be restricted, and balanced development should be adopted to prevent the fragmentation of the landscape. [ABSTRACT FROM AUTHOR]

Long-term monitoring of middle taiga wetland vegetation has been undertaken at the Kindasovo Forest and Mire Research Station, which is located within the Koivu-Lambasuo Nature Reserve in southern Karelia (north-west Russia). This article revisits the results of 50 years' monitoring of post-drainage succession in a meso-oligotrophic dwarf shrub - Sphagnum pine mire. The purpose of drainage was to improve the quality of the site for forestry. Gradient analysis and Ellenberg's indicator values were used to associate differentiation of the plant cover with the main environmental factors (availability of moisture and light, soil acidity, soil mineral nitrogen content), and thus to distinguish three chronological drainage periods on the basis of changes in the plant communities, which are then described. The initially understocked dwarf shrub - Sphagnum pine stand (low quality forest) evolved over 50 years into a well-stocked pine stand, but this was not a sufficient period for the ground cover vegetation to reach a new stable state. Nonetheless, analysis of species composition dynamics during the three drainage periods showed that species diversity increased from 17 to 31 species, wetland species were preserved but their prevalence and percentage cover declined, and forest-associated species appeared. [ABSTRACT FROM AUTHOR]

Climate change and the expected increase in frequency of dry summers are likely to affect the growth of important tree species. We investigated relationships between morphological and chemical leaf traits of European beech (Fagus sylvatica L.) and environmental factors along a water availability gradient consisting of 12 sites located throughout Switzerland. We found that leaf dry mass and leaf area tended to decrease with increasing long-term mean annual precipitation (MAP) and actual to potential transpiration (AT/PT), two correlated variables that form the water availability gradient. These results contrast with those of several other studies, and might be explained by favorable temperature and humidity conditions during leaf formation in spring at the dry sites. Although the relationship was not linear over the whole gradient, the drier sites were characterized by beech with a lower specific leaf area, along with higher foliar potassium (K) and lower foliar nitrogen (N) concentrations. These patterns likely reflect strategies developed as an adaptation to reduced water availability, but they also result from variation in the availability of nutrients in soil across our sites. In the case of N, there are indications that atmospheric deposition plays a role in foliar concentrations.

Abstract Complex processes related to biotic and abiotic forces can impose limitations to assembly and composition of plant communities. Quantifying the effects of these constraints on plant functional traits across environmental gradients, and among communities, remains challenging. We define ecological constraint (Ci) as the combined, limiting effect of biotic interactions and environmental filtering on trait expression (i.e., the mean value and range of functional traits). Here, we propose a set of novel parameters to quantify this constraint by extending the trait‐gradient analysis (TGA) methodology. The key parameter is ecological constraint, which is dimensionless and can be measured at various scales, for example, on population and community levels. It facilitates comparing the effects of ecological constraints on trait expressions across environmental gradients, as well as within and among communities. We illustrate the implementation of the proposed parameters using the bark thickness of 14 woody species along an aridity gradient on granite outcrops in southwestern Australia. We found a positive correlation between increasing environmental stress and strength of ecological constraint on bark thickness expression. Also, plants from more stressful habitats (shrublands on shallow soils and in sun‐exposed locations) displayed higher ecological constraint for bark thickness than plants in more benign habitats (woodlands on deep soils and in sheltered locations). The relative ease of calculation and dimensionless nature of Ci allow it to be readily implemented at various scales and make it widely applicable. It therefore has the potential to advance the mechanistic understanding of the ecological processes shaping trait expression. Some future applications of the new parameters could be investigating the patterns of ecological constraints (1) among communities from different regions, (2) on different traits across similar environmental gradients, and (3) for the same trait across different gradient types.

Human disturbance in the landscape lead to dramatic changes in the spatial structure of landscape patterns. This paper takes the Chongqing Three Gorges Reservoir area of China as case study to carry out gradient change analysis of the landscape pattern. Firstly, the coupled inflection point analysis, information loss method, and principal component analysis are used to determine the optimal grain size in a landscape gradient analysis. Secondly, the multidirectional gradient transect method is selected to analyze the law of landscape gradient change and the change of the landscape index. Finally, we analyzed various landscapes at the type level and obtained the distributions of the landscape types. The research highlights the gradient characteristics and landscape structure responses of typical transects of landscape subdivision types. The main results are as follows: (1) The optimal grain size of gradient analysis is 50 m. The patch density, patch shape complexity, and land use abundance of transects from the head to the tail of the reservoir increase. (2) At the landscape level, low mountain areas are more strongly blocked, and landscape connectivity reaches a minimum. At the type level, the landscape shape in the urban-rural interface zone is more complex. (3) Various landscape types are regularly ordered and form the gradient of "urban-agricultural-natural." [ABSTRACT FROM AUTHOR]

Semi‐natural mountain grasslands are increasingly exposed to environmental stress under climate change. However, which are the environmental factors that limit plants in these grasslands? Also, is the present management effective against these changes? Fitness‐related functional traits may offer a way to detect changes in performance and provide new insights into their vulnerability to climate change. We investigated changes in performance and variability of functional traits of the mountain grassland target species Arnica montana along a climate gradient in Central German low mountain ranges. This gradient represents at its lower end climate conditions that are expected at its upper end under future climate change. We measured vegetative, generative, and physiological traits to account for multiple ways of plant responses to the environment. Using mixed effects and multivariate models, we evaluated changes in trait values among individuals as well as the variability of their populations in order to assess performance under changing summer aridity and different management regimes. Fitness‐related performance of most traits showed strongly positive associations with reduced summer aridity at higher elevations, while only specific leaf area and leaf dry matter content showed no association. This suggests a higher performance level at less arid montane sites and that the physiological traits are less sensitive to this climate change factor. The coefficient of variation of almost all traits declined steadily with decreasing site aridity. We suggest that this reduced variability indicates a lower environmental stress level for A. montana toward its environmental optimum at montane elevations, especially because the trait performance increased simultaneously. Surprisingly, management factors and habitat characteristics had only low influence on both trait performance and variability. In summary, summer aridity had a stronger effect to shape the trait performance and variability of A. montana under increased environmental stress than management and other habitat characteristics. [ABSTRACT FROM AUTHOR]

A seminal paper in biogeography is reviewed. Whittaker's 1956 paper in Ecological Monographs introduced gradient analysis as a conceptual framework. This approach replaced community classification as the preferred methodology among US ecologists and biogeographers. It later developed into the foundation for species distribution modeling. Although the paper underlies a continuing rift between US and European scientists, both groups recognize its importance for relating ecological processes to geographical patterns. [ABSTRACT FROM AUTHOR]

Aims: The native woody vegetation from the Espinal phytogeographic province in central Argentina, found in subtropical-warm temperate climates, represents part of the southernmost seasonally dry forest in South America. Although this vegetation has been studied for over a century, a complete phytosociological survey is still needed. This lack of knowledge makes its spatial delimitation and the establishment of efficient conservation strategies particularly difficult. The main goals of this study were to classify these forests and assess their current forest cover and to better define the extent of the Espinal phytogeographic province in Córdoba region, central Argentina. Study area: Espinal Phytogeographic Province in Córdoba region, central Argentina (ca. 101,500 km2). Methods: We sampled 122 stands following the principles of the Zürich-Montpellier School of phytosociology; relevés were classified through the ISOPAM hierarchical analysis. The extent of the Espinal phytogeographic province was established by overlaying previous vegetation maps, and a map showing the current distribution of forest patches was constructed based on a supervised classification of Landsat images. Results: Four woody vegetation types of seasonally dry subtropical forest were identified based on the fidelity and the abundance of diagnostic species: (1) Aspidosperma quebracho-blanco forest; (2) Zanthoxylum coco forest; (3) Geoffroea decorticans forest; and (4) Prosopis caldenia forest. These vegetation types were segregated along gradients of temperature and precipitation seasonality and soil-texture and sodium content. The remaining forest patches represent 3.43% of the extent of the Espinal province in Córdoba region of which only 1.05% is represented in protected areas. Conclusions: We present a classification of the Espinal forest based on a complete floristic survey. Despite the dramatic forest loss reported, our results show that some forest patches representative of the Espinal are still likely to be found in the area. However, urgent measures should be taken to establish new protected natural areas in order to preserve the last remaining forest patches. [ABSTRACT FROM AUTHOR]

• A "Structure-Function-Zoning" framework is presented for UGI analysis. • Gradient analysis is adopted along urban expansion axis. • Index that measures spatial equity of UGI is developed. • An approach is proposed for comprehensive evaluation of UGI pattern. • The simple and practical indices can carry out supervision and early warning for UGI planning. Urban green infrastructure (UGI) that provides diverse ecosystem services are crucial components of a city. Achieving appropriate density and equitable distribution of UGI is highly significant for urban planning to ensure sustainable and high-quality development. However, there is still a lack of an applied method for effectively measuring spatial equity of UGI in cities with multiple scales, which impairs the ability to regularly monitor it. Furthermore, the extent to which UGI should be implemented in urban planning in China is still uncertain. In this study, a "Structure-Function-Zoning" analysis framework for the spatial pattern of UGI is proposed. A monitoring index system in terms of the structure and functions of UGI is first established. Then, an approach for measurement of spatial distribution equity of UGI is developed based on a spatial zoning strategy along the urban expansion axis. And a weighted index is proposed for comprehensive evaluation of UGI pattern. Using three Chinese cities (i.e., Beijing, Tianjin, Shijiazhuang) as examples, our research shows that the UGI pattern of Tianjin is distributed more balanced from urban center to suburb among the cities and Shijiazhuang shows relatively poor spatial equity of UGI. In terms of comprehensive evaluation of UGI pattern, Beijing and Tianjin are both rated as "moderate" while Beijing was slightly better than Tianjin, and Shijiazhuang was rated as "relatively poor". The proposed analysis framework is designed to access the structure and function of UGI in a way that can be spatially differentiated, easily described, and clearly compared for cities of different sizes. More broadly, the comprehensive index adopted in the study can be regarded as a simple and practical tool to perform regular monitoring and provide early warning for UGI planning in urban renewal process. [ABSTRACT FROM AUTHOR]

Late Cretaceous coastal plain deposits of the Prince Creek Formation (PCF) offer a rare glimpse into an ancient, high-latitude, arctic greenhouse ecosystem for which there is no modern analog. Here, we employ quantitative biofacies analysis to explore the spatio-temporal variability in PCF palynomorph and microbiota assemblages from nine paleosol horizons exposed along the Colville River, North Slope, Alaska. Biofacies results provide insight into paleoenvironmental controls on the coastal plain ecosystem. Cluster and ordination analyses recognize five biofacies and the following two assemblage types: (1) fern and moss dominated assemblages and (2) algae dominated assemblages. Ordination arrays biofacies along environmental gradients related to soil moisture and marine influence. Fern and moss dominated biofacies from regularly water-logged paleosols along lake and swamp margins on the lower delta plain clearly segregated from algae dominated assemblages of periodically drier levee-overbank paleosols. These results support previous interpretations from the sedimentology, paleopedology, and geochemistry of PCF paleosols that suggest that fluctuations in the water table, related to seasonal river discharge and variations in topography and drainage, controlled soil development and vegetation growth across the coastal plain. This quantitative biofacies-based approach provides an independent predictive tool and cross-check for interpreting environmental conditions along any ancient coastal ecosystem.