Shannon Entropy Index Research Articles

Comparying two methods of disparity analysis of the anterior portion of m1 in the gray voles (Rodentia, Arvicolini) in a model sample: frequency analysis of morphotypes and geometric morphometrics

An analysis of disparity of the anterior portion of m1 shape in the gray voles in an artificial sample consisting of 5 groups with different frequency distributions of 5 morphotypes was carried out. Two main approaches were applied: (a) traditional analysis of frequency distribution of discrete morphotypes and (b) geometric morphometrics (GM) based on a strictly quantitative description of the shape of anterior portion of m1. The groups were compared quantitatively: Cavalli-Sforz–Edwards’ coefficient was applied in the first case, while the thin plate spline and Procrustes analyses in the second; their results were analyzed using a number of standard statistical methods (dispersion analysis, discriminant analysis, multidimensional scaling). Disparity within the groups was assessed using Shannon entropy index and averaged Procrustes distance. Traditional and GM approaches were shown to provide very similar results, with GM having a number of important advantages by being strictly quantitative. The second approach is recommended as the basic to replace the traditional one for explorations in disparity of tooth crown shape in the voles.

Diverse pathways to permanent childlessness in Singapore: A latent class analysis.

The proportions of adults reaching midlife without having children have been rising rapidly across the globe, particularly in Asia. However, little is known about the pathways to permanent childlessness within the region's childless population. This study utilized latent class analysis (LCA) to typologize pathways to childlessness based on dynamic characteristics of multiple life domains (i.e., partnership, education, and occupation) among 489 childless Singaporeans aged 50 and above from a 2022 nationwide survey. Additionally, we utilized multinomial logistic regressions to examine the sociodemographic correlates of pathway profiles and Shannon's entropy index to assess the heterogeneity in pathways to childlessness among successive cohorts. Results revealed five distinct profiles of pathways to childlessness: the Never-Married Semi-Professionals, the Low-Flex Blue-Collars, the Highly Educated Professionals, the Ever-Married Semi-Professionals, and the Flexible Blue-Collars. These pathway profiles were significantly associated with sociodemographic characteristics such as gender and family background. Women's pathways to childlessness were more standardized and heavily influenced by partnership characteristics, compared to those of men. The childless from privileged family background were less likely to follow pathways characterized by disadvantageous education and occupational status. There were also rising trends of voluntary childlessness among married childless individuals and increasing heterogeneity in pathways to childlessness across successive birth cohorts. In sum, our findings are consistent with some of the predictions of the Second Demographic Transition theory, suggesting that Singapore may be experiencing a demographic transition characterized by rising childlessness, decoupling of marriage and childbearing, and de-standardization of the life course.

An analysis of urban sprawl growth and prediction using remote sensing and machine learning techniques

This study examines urban growth to support sustainability by investigating urban sprawl in the Vila Velha Urban Agglomeration (UA). If the spatial area of Vila Velha UA increases by 24.36%, from 22.98 km2 in 1994 to 51.64 km2 in 2024, urban sprawl may affect surrounding areas. Landsat satellite images from 1994, 2004, 2014, and 2024 were analyzed to study the spatiotemporal pattern of urban growth. Shannon's entropy index identified urban sprawl in Vila Velha UA. The QGIS software's MOLUSCE (Modules for Land Use Change Simulations) plug-in, utilizing Cellular Automata (CA) and Artificial Neural Network-Multi Layer Perceptron (ANN-MLP) models, forecasted urban expansion for 2034. The built-up area is projected to increase from 51.64 km2 in 2024 to 62.31 km2 in 2034. Shannon's entropy index indicated a high rate of urban sprawl. Remote sensing and machine learning techniques are crucial for understanding spatial trends, forecasting future expansion, and informing sustainable urban planning. These methods facilitate an accurate assessment of urbanization dynamics, aiding in developing strategies to manage and mitigate sprawl's adverse impacts. This study offers a unique approach to defining urban growth, emphasizing the need for zoning regulations, green space conservation, and infrastructure development to curb urban sprawl and promote sustainable growth in Vila Velha.

Milk microbiome in the first month of lactation and at weaning from ewes supplemented with zinc pre- and postpartum.

Mastitis is an important disease with economic and welfare implications in both clinical and subclinical states. The aim of this research was to sequence the hypervariable V4 region of the 16S rRNA gene to describe the microbial diversity and taxonomy of milk from clinically healthy ewes (Rambouillet, WF = 9; Hampshire, BF = 5). Experimental ewes represented a subset of a larger study assessing the impacts of divergent dietary zinc (Zn) concentrations [1 × National Academics of Sciences, Engineering, and Medicine (NASEM) recommendations = CON or 3 × NASEM recommendations = ZnTRT] throughout late gestation and lactation. Milk was collected at four periods during early lactation (18 to 24h, 7 d, 14 d, and 21 d postpartum) and at weaning (84 ± 14 d postpartum). Somatic cell counts (SCC) were quantified, averaged, and classed (low: < 500 × 103; medium: 500 × 103 - 100 × 104; high: > 100 × 104 cells/mL). Milk samples (n = 67) were sequenced to identify bacteria and archaea; the most abundant phyla were Actinobacteria, Bacteroidetes, Cyanobacteria, Euryarchaeota, Firmicutes, Fusobacteria, Lentisphaerae, Proteobacteria, Spirochaetes, Tenericutes, Saccharibacteria TM7, and Verrucomicrobia. Mastitis pathogens were among the most relatively abundant genera, including Staphylococcus, Mannheimia, Corynebacterium, and Pseudomonas. Effects of breed, dietary Zn concentration, SCC class, and their two-way interactions on milk microbiome diversity and taxonomy were assessed within early lactation (using a repeated measures model) and weaning samples. Alpha-diversity metrics included Pielou's evenness, Faith's phylogenetic diversity, and Shannon's entropy indices. The main and interactive effects between Zn treatment, breed, SCC class, and period were variable in early lactation and not evident in weaning samples. Milk from BF ewes had increased Faith's phylogenetic diversity and Shannon's entropy, and differed in unweighted UniFrac composition (P ≤ 0.10). Milk from CON ewes had a reduced rate of composition change through early lactation (P = 0.02) indicating greater microbiome stability than ZnTRT ewe milk. These results support that milk is not sterile, and breed, dietary Zn concentration, and SCC class variably affect the milk microbiome. Findings from the current study provide important foundational insights into the effects of increased dietary Zn supplementation on longitudinal changes in the milk microbiome and associations with mammary gland health and mastitis.

Research on the Source Convergence Diagnose Method of Monte Carlo Critical Calculation for Loosely Coupled System

In order to improve the reliability and accuracy of Monte Carlo program in the critical safety calculation of loosely coupled systems, an improved Shannon entropy diagnose method considering the distribution of fission sources and the statistical bias is proposed in this paper. The relative deviation of the distribution of fission sources between adjacent generations and the standard deviation of fission source is proposed. The standard deviation of fission source distribution during source iteration are used as the weight of fission source distribution. Finally, an improved Shannon entropy diagnose method considering the distribution of fission sources and the statistical bias is proposed. This improved Shannon entropy convergence index makes up for the shortcomings of traditional Shannon entropy for lacking the details of local fission source. The improved Shannon entropy convergence index is applied to the benchmark problem: loosely coupled solution Slabs. The results show that compared with the traditional Shannon entropy index, this improved Shannon entropy is more sensitive to the iterative convergence process and can more intuitively and accurately determine the convergence of fission source distribution accompanied by source iteration.

Energy, Trophic Dynamics and Ecological Discounting

Ecosystems provide humanity with a wide variety and high economic value-added services, from biomass structuring to genetic information, pollutants’ decomposition, water purification and climate regulation. The foundation of ecosystem services is the Eltonian Pyramid, where via prey–predator relationships, energy metabolism and biomass building take place. In the context of existing ecosystem services classification and valuation methods (e.g., CICES, MEA, TEEB), financial investments in ecosystem services essentially address the conservation of trophic pyramids. Our work’s main target is to investigate how trophic pyramids’ dynamics (stability or instability) impact the long-run discounting of financial investments on ecosystem services’ value. Specifically, a trophic pyramid with highly fluctuating populations generates higher risks for the production of ecosystem services, hence for ecological finance instruments coupled to them, due to higher temporal uncertainty or information entropy that should be incorporated into their discount rates. As this uncertainty affects negatively the net present value (NPV) of financial capital on ecosystem services, we argue that the minimization of biomass fluctuations in trophic pyramids via population control should be among the priorities of ecosystem management practices. To substantiate our hypothesis, we construct a logistic predation model, which is consistent with the Eltonian Pyramid’s ecological energetics. As the logistic predator model’s parameters determine the tropic pyramid’s dynamics and uncertainty, we develop an adjusted Shannon entropy index (H(N)ADJ) to measure this effect as part of the discount rate. Indicatively, we perform a Monte Carlo simulation of a pyramid with intrinsic growth parameter values that yield oscillating population sizes. Finally, we discuss, from an ecological energetics standpoint, issues of competition and diversity in trophic pyramids, as special dimensions and extensions of our analytical framework.

Mixture Design of Experiments as Strategy for Portfolio Optimization

Portfolio analysis is widely used by financial investors to find portfolios producing efficient results under various economic conditions. Markowitz started the portfolio optimization approach through mean-variance, whose objective is to minimize risk and maximize the return. This study is called Markowitz Mean-Variance Theory (MVP). An optimal portfolio has a good return and low risk, in addition to being well diversified. In this paper, we proposed a methodology for obtaining an optimal portfolio with the highest expected return and the lowest risk. This methodology uses Mixture Design of Experiments (MDE) as a strategy for building non-linear models of risk and return in portfolio optimization; computational replicas in MDE to capture dynamical evolution of series; Shannon entropy index to handle better portfolio diversification; and desirability function to optimize multiple variables, leading to the maximum expected return and lowest risk. To illustrate this proposal, some time series were simulated by ARMA-GARCH models. The result is compared to the efficient frontier generated by the traditional theory of Markowitz Mean-Variance (MVP). The results show that this methodology facilitates decision making, since the portfolio is obtained in the non-dominated region, in a unique combination. The advantage of using the proposed method is that the replicas improve the model precision.

Determining Attribute—Response Relationships of Soils under Different Land Uses: A Case Study

Soil researchers are interested in a gaining better understanding of the soil system state by analyzing its properties and their dynamics in time as well as in relation to land use change. Tilled, abandoned, and forest soils were assessed regarding attribute–response relationships for the bulk density (BD), total porosity (TP), volumetric moisture (θv), and penetration resistance (PR) with the use of the interquartile ratio (IRI) integrated into a resilience formula and Shannon entropy indices. The IRI results differentiated soil properties according to agrotechnics (wheel track vs. between wheels) and the state of the system (tilled vs. abandoned vineyard). Entropy (En) indicated a high level of uncertainty for PR. The linear regression applied to the pairs of BD-TP, TP-θv, and PR-θv showed better results for the IRI weight (IRIweight) compared to the entropy weight (Enweight) for the soil between the wheels. The soil of the abandoned vineyard showed a faster tendency toward resilience that was more pronounced in the tilled wheel tracks than in the area between the wheels. The IRI can thus be an alternative to entropy in the evaluation of the response of some soil properties according to their use. When integrated into a resilience formula, the IRI can estimate the dynamics of soil properties for abandoned land compared to reference soil.

Shannon Entropy and Herfindahl-Hirschman Index as Team's Performance and Competitive Balance Indicators in Cyclist Multi-Stage Races.

It seems that one cannot find many papers relating entropy to sport competitions. Thus, in this paper, I use (i) the Shannon intrinsic entropy (S) as an indicator of "teams sporting value" (or "competition performance") and (ii) the Herfindahl-Hirschman index (HHi) as a "teams competitive balance" indicator, in the case of (professional) cyclist multi-stage races. The 2022 Tour de France and 2023 Tour of Oman are used for numerical illustrations and discussion. The numerical values are obtained from classical and and new ranking indices which measure the teams "final time", on one hand, and "final place", on the other hand, based on the "best three" riders in each stage, but also the corresponding times and places throughout the race, for these finishing riders. The analysis data demonstrate that the constraint, "only the finishing riders count", makes much sense for obtaining a more objective measure of "team value" and team performance", at the end of a multi-stage race. A graphical analysis allows us to distinguish various team levels, each exhibiting a Feller-Pareto distribution, thereby indicating self-organized processes. In so doing, one hopefully better relates objective scientific measures to sport team competitions. Moreover, this analysis proposes some paths to elaborate on forecasting through standard probability concepts.

Identifying factors affecting irrigation metrics in the Haor basin using integrated Shannon's entropy, fuzzy logic and automatic linear model

The sustainability of agricultural practices is seriously threatened by the quality of water used for irrigation. This paper aims to evaluate the suitability of irrigation water and identify the region suitable for agricultural use in the Haor basin of Bangladesh using conventional irrigation indices such as sodium adsorption ratio (SAR), percent sodium (Na%), magnesium hazard ratio (MHR), permeability index (PI), and Kelly's ratio (KR), as well as novel irrigation indices such as, Shannon's entropy index for irrigation water quality (EWQ) and fuzzy logic index for irrigation water quality (FIWQI). The main influences of groundwater and surface water parameters on irrigation indices were predicted using automatic linear modeling (ALM). Forty water samples were collected from shallow tube wells, rivers, canals, ponds, and drainage systems within agricultural land sampled and analyzed for cations and anions. SAR and KR show that 52.5% and 60% of the samples exceeded the allowable level, respectively, indicating that they were unsuitable for irrigation. According to EWQI, about 55% of the analyzed samples were of good quality, while 45% were of medium quality. ALM predicted that KR (0.98), Na% (0.87), and MHR (0.14) were the main significant factors affecting SAR and KR. ALM shows that elevated sodium, magnesium, and calcium are the most important factors affecting irrigation water suitability. The EWQI and FIWQI integrated models showed that water from nearly 30% of the sampling sites would need treatment before use. A new suitability map created by overlaying all parameters showed that surface water and some groundwater in the western and southwestern portions are suitable for agriculture. The north-central part is unsuitable for irrigation due to excessive sodium and magnesium levels. This paper will highlight the irrigation pattern for regional water resource use, identify new suitable regions, and improve sustainable agricultural practices in the Haor basin.

Multigroup Multimodality Index: A Method to Solve the Issue of Transport Mode Classification in Measuring Multimodality

Recent methods to measure multimodality only consider the diversity and evenness of mode use, while ignoring that the classification of transport modes also matters. This study proposes a multigroup multimodality index to measure the extent of being multimodal at both single mode and mode group levels in a nested manner. The index is compared with the two most commonly used indices, the Herfindahl-Hirschman index and the Shannon Entropy index, to assess its reliability and improvement over existing approaches. Results show that the multigroup multimodality index can simultaneously distinguish the degree of being multimodal at both mode level and group level, which addresses the classification issue in measuring multimodality.

Application of bivariate approaches for flood susceptibility mapping: a district level study in Eastern India

The main objective of this present study is to prepare flood susceptibility mapping using bivariate approaches considering parameters such as rainfall, geomorphology, geology, soil, elevation, ground slope, curvature of the land, flow directions, stream density, distance from road, distance from river, land use land cover, topographic wetness index, normalized differentiate vegetation index and water index. Bivariate methods like Shannon's Entropy Index (SEI) and Weight of Evidence (WofE-IV) models have been used in conjunction with remote sensing and geographical information system and it was found that 17.77% (SEI) and 11.20% (WofE-IV) area of the district categorized as highly susceptible to flood especially found in the adjoining area of Tangon, Punarbhaba, and Atreyee rivers. Around 26–35% of the total area is safe from flood especially located in the Tapan and Banshihari block. The area under curve values (SEI = 0.954, WofE-IV = 0.913) shows that both models are performing well for flood susceptibility mapping.

Immune repertoire and responses to neoadjuvant TCHP therapy in HER2-positive breast cancer.

Despite the introduction of trastuzumab, pathologic complete response (pCR) is not attained in approximately 30-40% of Human epithelial growth factor receptor-2-positive breast cancer. Tumor-infiltrating lymphocytes (TIL) have been suggested as a predictive marker of treatment response, albeit not always effective. We investigated the relationship between trastuzumab, docetaxel, carboplatin, and pertuzumab (TCHP) treatment and immune repertoire as a treatment response predictor. In all, 35 cases were divided into two experimental groups: 10 and 25 cases in the preliminary and main experiments, respectively. In the preliminary experiment, the biopsy tissues before TCHP treatment and the surgical tissues after TCHP treatment were compared. In the main experiment, the biopsy tissues before TCHP treatment were compared according to the TCHP treatment response. The T-cell repertoire for TRA, TRB, TRG, and TRD, and B-cell repertoire for immunoglobulin heavy, immunoglobulin kappa, and immunoglobulin lambda were evaluated. Whole transcriptome sequencing was also performed. In the preliminary experiment, the density and richness of the T-cell receptor (TCR) and B-cell receptor (BCR) repertoires decreased after treatment, regardless of TCHP response. In the main experiment, the Shannon's entropy index, density, and length of CDR3 of the TCR and BCR repertoires did not differ significantly in patients who did and did not achieve pCR. The pCR and non-pCR subgroups according to the level of TILs revealed that the non-pCR/lowTIL group had a higher proportion of low-frequency clones than the pCR/lowTIL group in TRA (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 63% versus 45.3%; <0.01%, 32.9% versus 51.8%, p < 0.001) and TRB (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 26.5% versus 14.7%; <0.01%, 72.0% versus 84.1%, p < 0.001). The role of the diversity, richness, and density of the TCR and BCR repertoires as predictive markers for TCHP response was not identified. Compositions of low-frequency clones could be candidates for predictive factors of TCHP response; however, validation studies and further research are necessary.

ТРУДНО ЛИ БЫТЬ ПРИЕЗЖИМ СТУДЕНТОМ: ПРОБЛЕМЫ ТРУДОУСТРОЙСТВА ВЫПУСКНИКОВ

The paper studies the problems of employment of university graduates in combination with the facts of students moving to study. Graduates are considered as a whole, without division into bachelors and masters. To determine the relationships, the method of correlation and regression analysis, the Shannon entropy index, and statistical grouping tools are used. Trends are determined by four groups of regions, each of which is formed taking into account the number of enterprises in the region. Comparability of regions by groups helps to identify a sufficient number of significant relationships.

Shannon Entropy-based urban spatial fragmentation to ensure sustainable development of the urban coastal city: A case study of Semarang, Indonesia

This study examines the extent to which the Shannon Entropy Index (H) can be used to ensure urban growth sustainability by measuring the spatial dispersion pattern of a built-up area. The Shannon Entropy Index was calculated based on the proximities to the city center (HCC) and the main road (HMR), which divide the study area into 17 zones. Data from Landsat 5- TM Imagery 2011 and Landsat 8- OLI Imagery 2016 and 2021 were used to extract urban built-up areas through image classification using the Support Vector Machine (SVM) Algorithm and measure their growth over time. The results show the normalized Shannon Entropy Index for the proximities to the city center (HCC′) and the main road (HMR′). HCC′ was found to be 0.93 in 2021 and increased by 0.44 during 2011–2021, while HMR′ was recorded to be 0.68 in 2021 and increased by 0.27 during 2011–2021, indicating that urban development in Semarang City has become increasingly fragmented. Among the 17 existing zones, the peri-urban areas of southeast part zones in Semarang (III-BP and IV-AP) were found to have the largest relative Shannon Entropy Index (H') of 0.98 and 0.96, respectively, indicating that this area is developing irregularly and spreading out compared to the city center, which is unsustainable built-up area growth. We call for an integrated space utilization control strategy between the city center and the peri-urban area. Our study demonstrates the capacity of using the Shannon Entropy Index to detect potential areas of unsustainable development in a coastal city with diverse development dynamics, which can also be applied in other coastal cities to prevent unsustainable development.

Using airborne and DESIS imaging spectroscopy to map plant diversity across the largest contiguous tract of tallgrass prairie on earth

Grassland ecosystems are under threat globally, primarily due to land-use and land-cover changes that have adversely affected their biodiversity. Given the negative ecological impacts of biodiversity loss in grasslands, there is an urgent need for developing an operational biodiversity monitoring system that functions in these ecosystems. In this paper, we assessed the capability of airborne and spaceborne imaging spectroscopy (also known as hyperspectral imaging) to capture plant α-diversity in a large naturally-assembled grassland while considering the impact of common management practices, specifically prescribed fire. We collected a robust in-situ plant diversity data set, including species composition and percent cover from 2500 sampling points with different burn ages, from recently-burned to transitional and pre-prescribed fire at the Joseph H. Williams Tallgrass Prairie Preserve in Oklahoma, USA. We expressed in-situ plant α-diversity using the first three Hill numbers, including species richness (number of observed species in a plant community), exponential Shannon entropy index (hereafter Shannon diversity; effective number of common species, where species are weighed proportional to their percent cover), and inverse Simpson concentration index (hereafter Simpson diversity; effective number of dominant species, where more weight is given to dominant species) at four different plot sizes, including 60 m × 60 m, 120 m × 120 m, 180 m × 180 m, and 240 m × 240 m. We collected full-range airborne hyperspectral data with fine spatial resolution (1 m) and visible and near-infrared spaceborne hyperspectral data from DESIS sensor with coarse spatial resolution (30 m), and used the spectral diversity hypothesis—i.e., that the variability in spectral data is largely driven by plant diversity—to estimate α-diversity remotely. In recently-burned plots and those at the transitional stage, both airborne and spaceborne data were capable of capturing Simpson diversity—a metric that calculates the effective number of dominant species by emphasizing abundant species and discounting rare species—but not species richness or Shannon diversity. Further, neither airborne nor spaceborne hyperspectral data sets were capable of capturing plant α-diversity of 60 m × 60 m or 120 m × 120 m plots. Based on these results, three main findings emerged: (1) management practices influence grassland biodiversity patterns that can be remotely detected, (2) both fine- and coarse-resolution remotely-sensed data can detect the effective number of dominant species (e.g., Simpson diversity), and (3) attention should be given to site-specific plant diversity field data collection to appropriately interpret remote sensing results. Findings of this study indicate the feasibility of estimating Simpson diversity in naturally-assembled grasslands using forthcoming spaceborne imagers such as National Aeronautics and Space Administration's Surface Biology and Geology mission.

Spatial heterogeneity in drinking water sources in the Greater Accra Metropolitan Area (GAMA), Ghana

Universal access to safe drinking water is essential to population health and well-being, as recognized in the Sustainable Development Goals (SDG). To develop targeted policies which improve urban access to improved water and ensure equity, there is the need to understand the spatial heterogeneity in drinking water sources and the factors underlying these patterns. Using the Shannon Entropy Index and the Index of Concentration at the Extremes at the enumeration area level, we analyzed census data to examine the spatial heterogeneity in drinking water sources and neighborhood income in the Greater Accra Metropolitan Area (GAMA), the largest urban agglomeration in Ghana. GAMA has been a laboratory for studying urban growth, economic security, and other concomitant socio-environmental and demographic issues in the recent past. The current study adds to this literature by telling a different story about the spatial heterogeneity of GAMA’s water landscape at the enumeration area level. The findings of the study reveal considerable geographical heterogeneity and inequality in drinking water sources not evidenced in previous studies. We conclude that heterogeneity is neither good nor bad in GAMA judging by the dominance of both piped water sources and sachet water (machine-sealed 500-ml plastic bag of drinking water). The lessons from this study can be used to inform the planning of appropriate localized solutions targeted at providing piped water sources in neighborhoods lacking these services and to monitor progress in achieving universal access to improved drinking water as recognized in the SDG 6 and improving population health and well-being.

Heritage Trees as an Important Sanctuary for Saproxylic Beetles in the Central European Landscape: A Case Study from Litovelské Pomoraví, Czech Republic

Intensive forest and agroforestry management has greatly reduced the biodiversity of saproxylic organisms. Large trees are one of the most important refuges of saproxylic beetles. These large trees that grow outside and inside the forest are declining in the wider landscape. Heritage trees are one of the essential groups of beneficial trees in the landscape. We investigated saproxylic beetles associated with 35 selected oak heritage trees in Litovelské Pomoraví in the eastern Czech Republic. The study aimed to investigate the distribution of saproxylic beetles on trees growing inside or at the edge of forest stands, or on free-growing heritage trees. The other studied variables were the height, DBH, and light condition (sunny or shady) of heritage trees. The results showed that sunny habitats were the only significant factor found for all saproxylic species. However, the significance of increasing tree trunk dimension was found for the endangered species. Diversity indices q = 0 (species richness) and q = 1 (exponential of Shannon entropy index) were also higher for sunny trees, while solitary trees showed a high Shannon index value despite the low number of samples. Redundancy analysis of saproxylic species showed that the preferred habitats of most species were sunny massive solitary oaks. The results indicated that strictly protected heritage trees scattered in the landscape are crucial sanctuaries for many species—especially in landscapes where there are not enough suitable habitats for saproxylic beetles. Finding, conserving, and protecting these rare types of massive trees in the landscape has a significant impact on the conservation of saproxylic beetle biodiversity.

Clinical code usage in UK general practice: a cohort study exploring 18 conditions over 14 years

ObjectiveTo assess the diagnostic Read code usage for 18 conditions by examining their frequency and diversity in UK primary care between 2000 and 2013.DesignPopulation-based cohort studySetting684 UK general practices contributing...

Impact of Grazing on Diversity of Semi-Arid Rangelands in Crete Island in the Context of Climatic Change.

The rangelands of Crete island (Greece) are typical Mediterranean habitats under high risk of degradation due to long-term grazing and harsh climatic conditions. We explored the effect of abiotic (climatic conditions, altitude) and biotic factors (long-term grazing by small ruminants) on the floristic composition and diversity of selected lowland (Pyrathi, Faistos) and highland (Vroulidia, Nida) rangelands. In each rangeland, the ground cover was measured, and the floristic composition was calculated in terms of five functional groups: grasses, legumes, forbs, phrygana, and shrubs. The aridity index, species turnover, species richness, Shannon entropy, and Gini–Simpson index (with the latter two converted to the effective number of species) were calculated. Our results reveal that highlands are characterized by the highest aridity index (wetter conditions). Lowland rangelands, compared to highland, exhibited a higher percentage contribution of grasses, legumes, and forbs, while species turnover decreased along the altitudinal gradient. The Shannon entropy index was correlated (a) positively with Gini–Simpson and mean annual temperature and (b) negatively with mean annual precipitation, aridity index, and altitude. Moreover, the Gini–Simpson index correlated positively with mean annual temperature and negatively with altitude. Our results could help to understand the effects of grazing on rangeland dynamics and sustainability in semi-arid regions in the context of climatic change.