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White sharks (Carcharodon carcharias) are among the most widespread, charismatic, and studied predators in the ocean. However, their conservation status is concerning in many ocean sectors, most notably the Mediterranean Sea, which hosts one of the least known and most endangered populations globally. Though they were historically abundant and widely distributed in the region, Mediterranean white sharks have declined to dangerously low abundance levels, impacted by centuries of coastal and, more recently, industrial fishing. The IUCN lists this species as Critically Endangered in the region, but information about its current abundance and ecology is scarce, hindering effective management and conservation. Here, we describe our initial effort to find and track the remaining Mediterranean white sharks and report what we have learned from these activities. In 2021-2023, we conducted three pilot expeditions in the Sicilian Channel, covering four major sites, collecting 159 eDNA samples, and carrying out 359 hrs of pelagic mid-water baited video surveys, 43 hours of deep-water benthic baited video surveys, and 111 hrs of fishing. Baited video surveys detected 42 species of bony fishes, elasmobranchs, marine mammals, and turtles. We detected white sharks at four sites from eDNA samples. Though we did not observe white sharks directly, these activities supported the identification of one of the last strongholds of this population in the region and started a multi-institutional white shark conservation program in the Mediterranean Sea, aiming to track the last white sharks in the region, estimate their abundance and extinction risk, characterize the species' ecology and inform management and conservation. [ABSTRACT FROM AUTHOR]

Identifying areas susceptible to invasion by an alien species is a strategy of prevention. We used national herbaria and global databases to assess the invasion trends of the two aquatic invasive species Ludwigia hexapetala and Ludwigia peploides subsp. montevidensis in Italy. We defined the invasion status with invasion curves and predicted potentially suitable areas with Species Distribution Models based on WorldClim variables and the human footprint index. Low seasonal variation in temperature and precipitation, temperature ≥ 20 °C in the driest period of the year and low precipitation in the coldest period are the bioclimatic factors that most account for the potential distribution of the two species. The human footprint has a lower relative importance than bioclimatic variables. All Italian peninsula appears as a suitable bioclimatic environment for the invasion of the two Ludwigia species, with over 90% of areas with high suitability lying below 600 m altitude. Only mountain regions and the islands appear less suitable. The agricultural land at the foothill of the Appennine in the Mediterranean region is the most vulnerable to the invasion. Considering the trend of the invasion curves, which have been sharply rising for the latest decades, there are reasons to expect that the alien Ludwigia species will continue their expansion, if no timely and effective actions are taken. Informative campaigns, accurate monitoring and prompt management are fundamental preventive tools in areas predicted as vulnerable to invasion by this study. [ABSTRACT FROM AUTHOR]

White sharks (Carcharodon carcharias) are among the most widespread, charismatic, and studied predators in the ocean. However, their conservation status is concerning in many ocean sectors, most notably the Mediterranean Sea, which hosts one of the least known and most endangered populations globally. Though they were historically abundant and widely distributed in the region, Mediterranean white sharks have declined to dangerously low abundance levels, impacted by centuries of coastal and, more recently, industrial fishing. The IUCN lists this species as Critically Endangered in the region, but information about its current abundance and ecology is scarce, hindering effective management and conservation. Here, we describe our initial effort to find and track the remaining Mediterranean white sharks and report what we have learned from these activities. In 2021-2023, we conducted three pilot expeditions in the Sicilian Channel, covering four major sites, collecting 159 eDNA samples, and carrying out 359 hrs of pelagic mid-water baited video surveys, 43 hours of deep-water benthic baited video surveys, and 111 hrs of fishing. Baited video surveys detected 42 species of bony fishes, elasmobranchs, marine mammals, and turtles. We detected white sharks at four sites from eDNA samples. Though we did not observe white sharks directly, these activities supported the identification of one of the last strongholds of this population in the region and started a multi-institutional white shark conservation program in the Mediterranean Sea, aiming to track the last white sharks in the region, estimate their abundance and extinction risk, characterize the species’ ecology and inform management and conservation.

Abstract The distribution of public health commodities is a challenging activity directly responsible for the success of a public health program or intervention. Getting the distribution strategy right is a major concern of many health program implementers and stakeholders in Nigeria. This study intends to look at available models previously or currently used for the distribution of public health commodities in Nigeria. Literature search was carried out in PubMed and Google Scholar on articles related to the public health commodities distribution models in Nigeria. Websites of health organizations operating in Nigeria and publicly funded health institutions were also visited for gray literatures on public health commodities distribution strategies. The study shows the absent of scientific publication as source of information on the distribution model; instead, most of the research publications were review publications in addition to program reports from international nongovernmental organizations and health authorities in Nigeria. Direct delivery and information capture, pull and push, hub and spoke, 5 tier, vertical distribution, integrated distribution models were some of the models identified from the study. Analysis from the review suggests hub/spoke model and integrated model as a desirable model for the distribution of public health commodities.

The distribution of public health commodities is a challenging activity directly responsible for the success of a public health program or intervention. Getting the distribution strategy right is a major concern of many health program implementers and stakeholders in Nigeria. This study intends to look at available models previously or currently used for the distribution of public health commodities in Nigeria. Literature search was carried out in PubMed and Google Scholar on articles related to the public health commodities distribution models in Nigeria. Websites of health organizations operating in Nigeria and publicly funded health institutions were also visited for gray literatures on public health commodities distribution strategies. The study shows the absent of scientific publication as source of information on the distribution model; instead, most of the research publications were review publications in addition to program reports from international nongovernmental organizations and health authorities in Nigeria. Direct delivery and information capture, pull and push, hub and spoke, 5 tier, vertical distribution, integrated distribution models were some of the models identified from the study. Analysis from the review suggests hub/spoke model and integrated model as a desirable model for the distribution of public health commodities. [ABSTRACT FROM AUTHOR]

With over 40% of species threatened with extinction, the distributional range of most amphibians is still unknown, generating uncertainty whether species are naturally rare, under‐sampled, or difficult to detect. We implemented a modelling approach that uses bromeliads as surrogates to predict the distribution of habitat specialist frogs that lack distributional data. We aimed to predict and survey potential new sites for the occurrence of a rare and microendemic bromeliad‐dwelling frog from the Atlantic Rainforest of Brazil. We used Maxent to predict suitable areas based on climate and topographic profiles, combined with 21 occurrence records of bromeliads within which our target frog species (Crossodactylodes itambe) is strictly restricted. The bromeliad‐based models identified four areas potentially suitable, and subsequent surveys revealed an entirely new species of a rare bromeliad‐dwelling frog in one of the areas. We demonstrate that using easy‐to‐survey surrogate species that have a strong relationship with species that are hard to detect has enormous potential to reveal crucial information on the potential ranges and distribution of cryptic taxa. Such a surrogate modelling approach could be extended to other habitat specialist species that lack distribution data, such as amphibians restricted to specific refugia and/or reproduction sites. This could improve the targeting of surveys and increase understanding of the patterns of rarity and the drivers of species distribution, especially for areas with high endemicity and range‐restricted frogs. [ABSTRACT FROM AUTHOR]

Introduction: In order to dispatch frequency regulation resources in regional power grids efficiently and promote the development of spot markets, China Southern Power Grid (CSG) established the unified frequency regulation control area. However, the existing regional control performance standards (CPS) for evaluating the performance of frequency control in bulk power systems is no longer suitable for the unified frequency control mode. Method: This paper proposed an innovative frequency control performance standard, named tertiary control performance standards (TCPS) and used Gaussian mixture model (GMM) and folded normal distribution (FND) to describe the distributions of frequency deviations and power deviations of tie line. Result and Discussion: Based on these probability models, the parameters of the proposed TCPS can be determined optimized. Finally, case studies were carried out with the practical data from CSG and indicated that the parameters of proposed TCPS index could be calculated and improved the control performance for the real time power balance of the regional power grid with spot markets. [ABSTRACT FROM AUTHOR]

A handful of known bumble bee species (Bombus) have been transported worldwide and introduced in non-native regions for crop pollination, leading to long-lasting biological invasions. The introductions and invasions of European Bombus terrestris and, previously, of Bombus ruderatus in southern South America have been associated with sharp population declines of the giant Patagonian bumblebee, Bombus dahlbomii. We gathered a comprehensive database of occurrence records for B. dahlbomii, B. ruderatus, and B. terrestris from museums and citizen science sources. Multivariate bioclimatic niche analyses and species distribution models were used to determine the extent of climatic niche overlap between invasive and native species and the potential effects of current and future climatic scenarios on the distribution of these bumblebees. We found extensive pairwise niche overlap between the three bumble bee species, B. terrestris versus B. ruderatus (67%), B. terrestris versus B. dahlbomii (61%), and B. ruderatus versus B. dahlbomii (46%). Compared to its historical records, the current distribution of B. dahlbomii is narrowing and is expected to shrink even more under the most climatically pessimistic future scenario, while that of B. terrestris shows an extensive, still expanding distribution. However, the models show that in the case of a climatic pessimistic future scenario, B. terrestris will also slow down its expansion on the continent. Finally, we discuss the consequences of the large niche overlap between the introduced bumble bee species and endangered B. dahlbomii and the effect of climate change on these three species of bumble bees in South America. [ABSTRACT FROM AUTHOR]

Estimating low flow quantiles is essential for regulating minimum flow requirements and ensuring water availability, ecological health, and overall system sustainability. This study aims to quantify regional low flows by analyzing low-flow time series in data-limited environments. We utilized annual minimum 7-day instantaneous streamflow data collected from gaging stations. Discordancy measure assessments revealed that all sites were homogeneous, forming a single region. We employed Easy-Fit Statistical Software to select the best-fit probability distribution model and determine estimation parameter values. Through goodness-of-fit tests (GOFs), the Generalized Pareto model emerged as the most suitable, predicting low flow quantiles for 100-year returns. Rigorous application of GOFs ensures the statistical soundness of the model, capturing underlying data patterns. A correlation coefficient determination (R2) of 0.989 demonstrates the high satisfaction of the selected distribution model. The developed regression line for the region exhibited strong agreement between predicted low flows and catchment area. Thus, accurate estimation proves valuable in environmental and human-influenced decision-making processes, providing insights into low-flow behavior and mitigating drought effects on aquatic ecosystems.

The desert locust Schistocerca gregagia (Forskål, 1775) is one of the most harmful migratory pests in the world, posing a major threat to agricultural production, livelihoods, and food security. Climate, land use, and topography influence the distribution of desert locusts, but few studies have integrated all the factors on a global scale to explore the suitable areas for desert locusts and the paths through which this species could potentially spread. In this study, we established ensemble distribution models to investigate the distribution patterns and driving factors of desert locusts under baseline and future scenarios; we used ensembled niche dynamic models to evaluate their niche conservation during outbreaks. The results showed that the most important factor influencing desert locust distribution is climate, especially the minimum temperature of the coldest month, the annual precipitation, and the mean temperature of the driest quarter. Some areas with little or no desert locust distribution at present will be suitable for desert locusts in the future, and highly suitable contiguous areas may become the dispersal paths. The results also showed that the climatic niche of the desert locust is still conservative, which might explain why desert locusts tend to retreat after intermittent outbreaks rather than settle at the site of invasion. Therefore, more attention should be paid to the areas that are highly suitable for desert locusts, the key factors driving their outbreaks, and the shifting of their climatic niche in order to prevent desert locusts from settling in invasion areas and affecting local ecosystems and food security. [ABSTRACT FROM AUTHOR]

Abstract European grasslands face strong declines in extent and quality. Many grassland types are priority habitats for national and European conservation strategies. Countrywide, high spatial resolution maps of their distribution are often lacking. Here, we modelled the spatial distribution of 20 permanent grassland habitats at the level of phytosociological alliances across Switzerland at 10x10 m resolution. First, we applied ensemble models to provide distribution maps of the individual habitat types, using training data from various sources. Copernicus Sentinel satellite imagery and variables describing climate, soil and topography were used as predictors. The performance of these models was assessed based on the true skill statistics with a split‐sampling of the data. Second, the individual maps were combined into countrywide maps of the most and second most likely habitat type, respectively, using an expert‐based weighting approach. The performance of the combined map for the most likely habitat type was assessed via an independent testing dataset and a comparison of the predicted habitat‐type proportions with extrapolations from field surveys. Most individual maps had useful to excellent predictive performance (TSS ≥ 0.6). For most grid cells in the combined maps, the most and second most likely habitat types were either ecologically closely related or representing two grassland types along a nutrient gradient. The same was true for omission errors. We found good agreement between the predicted and estimated proportions from field surveys. The area of raised bogs appears to be underestimated, while dry grasslands showed highest agreement. This work highlights the potential of earth observation data at fine spatial and temporal resolution to map habitats at broad scales, thereby providing the foundation for diverse conservation applications. A particular challenge remains in capturing the transition from nutrient‐poor to nutrient‐rich grasslands, which is highly important for biodiversity conservation.

Species distribution models (SDMs) have been widely employed to evaluate species–environment relationships. However, when extrapolated over broad spatial scales or through time, these models decline in their predictive ability due to variation in how species respond to their environment. Many models assume species–environment relationships remain constant over space and time, hindering their ability to accurately forecast distributions. Therefore, there is growing recognition that models could be improved by accounting for spatio-temporal nonstationarity – a phenomenon wherein the factors governing ecological processes change over space or time. Here, we investigated nonstationarity in American pika (Ochotona princeps) relationships with climatic variables in the Rocky Mountains (USA). We first compared broad-scale differences in pika–climate patterns for occupancy and population density across the Southern, Central, and Northern Rockies. Next, we investigated within-ecoregion variation across four mountain ranges nested within the Northern Rockies. Lastly, we tested whether species–climate relationships changed over time within the Central Rockies ecoregion. Across all analyses, we found varying levels of nonstationarity among the climate metrics for both occupancy and density. Although we found general congruence in temperature metrics, which consistently had negative coefficients, and moisture metrics (e.g., relative humidity), which had positive coefficients, nonstationarity was greatest for summer and winter precipitation over both space and time. These results suggest that interpretations from one ecoregion should not be applied to other regions universally – especially when using precipitation metrics. The within-ecoregion analysis found much greater variation in the strength-of-relationship coefficients among the four mountain ranges, relative to the inter-regional analysis, possibly attributable to smaller sample sizes per mountain range. Lastly, the importance of several variables shifted through time from significant to insignificant in the temporal analysis. Our results collectively reveal the overall complexity underlying species–environment relationships. With rapidly shifting conditions globally, this work adds to the growing body of literature highlighting how issues of spatio-temporal nonstationarity can limit the accuracy, transferability, and reliability of models and that interpretations will likely be most robust at local to regional scales. Diagnosing, describing, and incorporating nonstationarity of species–climate relationships into models over space and time could serve as a pivotal step in creating more informative models.

Abstract Melanoides tuberculata is a freshwater snail native to Old World tropical areas but has invaded tropical and subtropical regions around the world. In Argentina, populations established in natural environments were reported from northeastern tropical provinces. Here we report for the first time the presence of M. tuberculata in a geothermally warmed channel in temperate Southern Pampas. We mapped its distribution in the channel, searched for its presence in five nearby basins, estimated the risk of establishment and expansion in Argentina with distribution models and analyzed shape variation through geometric morphometrics. Melanoides tuberculata was recorded exclusively in the channel in sites with temperatures between 20 and 40°C, with almost no overlap with other snails. No evidence of M. tuberculata was found in nearby basins. The distribution model predicted that only northernmost areas from Argentina are suitable for this species, where it could impact snail communities and food webs if introduction through the aquarium trade is not prevented. The absence of males indicates parthenogenetic reproduction and probably a recent invasion. Shell shape variation in this population, 15 % of which is attributable to allometry, encompasses the shapes of specimens from other South American populations, suggesting that all belong to the same lineage.

European grasslands face strong declines in extent and quality. Many grassland types are priority habitats for national and European conservation strategies. Countrywide, high spatial resolution maps of their distribution are often lacking. Here, we modelled the spatial distribution of 20 permanent grassland habitats at the level of phytosociological alliances across Switzerland at 10x10 m resolution. First, we applied ensemble models to provide distribution maps of the individual habitat types, using training data from various sources. Copernicus Sentinel satellite imagery and variables describing climate, soil and topography were used as predictors. The performance of these models was assessed based on the true skill statistics with a split‐sampling of the data. Second, the individual maps were combined into countrywide maps of the most and second most likely habitat type, respectively, using an expert‐based weighting approach. The performance of the combined map for the most likely habitat type was assessed via an independent testing dataset and a comparison of the predicted habitat‐type proportions with extrapolations from field surveys. Most individual maps had useful to excellent predictive performance (TSS ≥ 0.6). For most grid cells in the combined maps, the most and second most likely habitat types were either ecologically closely related or representing two grassland types along a nutrient gradient. The same was true for omission errors. We found good agreement between the predicted and estimated proportions from field surveys. The area of raised bogs appears to be underestimated, while dry grasslands showed highest agreement. This work highlights the potential of earth observation data at fine spatial and temporal resolution to map habitats at broad scales, thereby providing the foundation for diverse conservation applications. A particular challenge remains in capturing the transition from nutrient‐poor to nutrient‐rich grasslands, which is highly important for biodiversity conservation. [ABSTRACT FROM AUTHOR]

The desert locust Schistocerca gregagia (Forskål, 1775) is one of the most harmful migratory pests in the world, posing a major threat to agricultural production, livelihoods, and food security. Climate, land use, and topography influence the distribution of desert locusts, but few studies have integrated all the factors on a global scale to explore the suitable areas for desert locusts and the paths through which this species could potentially spread. In this study, we established ensemble distribution models to investigate the distribution patterns and driving factors of desert locusts under baseline and future scenarios; we used ensembled niche dynamic models to evaluate their niche conservation during outbreaks. The results showed that the most important factor influencing desert locust distribution is climate, especially the minimum temperature of the coldest month, the annual precipitation, and the mean temperature of the driest quarter. Some areas with little or no desert locust distribution at present will be suitable for desert locusts in the future, and highly suitable contiguous areas may become the dispersal paths. The results also showed that the climatic niche of the desert locust is still conservative, which might explain why desert locusts tend to retreat after intermittent outbreaks rather than settle at the site of invasion. Therefore, more attention should be paid to the areas that are highly suitable for desert locusts, the key factors driving their outbreaks, and the shifting of their climatic niche in order to prevent desert locusts from settling in invasion areas and affecting local ecosystems and food security.

AIM: Assess climatic risk to vegetation types associated with tropical and temperate ecosystems based on exposure analysis, which models future risk as a function of deviation from current climate variable distributions. LOCATION: Oaxaca State, Mexico. TAXON: Broadly defined vegetation types used in state‐ and national‐level vegetation classification systems. These types can be grouped into series representing dry‐to‐wet conditions for tropical and temperate vegetation. METHODS: We used climate exposure analysis to compare current and future climate parameters for the major vegetation types of Oaxaca. This technique integrates a recent vegetation map with historical climate data (1981–2010) to produce a baseline climate layer that is compared to climate projections made with five different global circulation models for near‐future (2015–2039) and end‐century (2075–2099) periods using two emissions scenarios (RCP 4.5 and 8.5). We classified the frequency distribution of the baseline climate into five exposure classes where the closer values are to mean climate conditions, the lower the exposure. Future exposure was estimated by classifying the vegetation pixels into the same exposure classes, now based on future climate values. Increased exposure risk was assessed based on the fraction of pixels that moved into higher exposure classes from one period to another. RESULTS AND MAIN CONCLUSIONS: Our analysis showed four general trends: (a) the higher, current track emissions scenario produced much larger end‐century climate exposure; (b) for the tropical vegetation series, tropical evergreen forests are projected as most exposed by end‐century; (c) for the temperate vegetation series the matorral‐shrubland and conifer forests are the most impacted; and (d) the five GCMs considered showed some convergence in their end‐century climate exposure predictions, with coastal and low‐elevation areas of the State projected to experience the greatest exposure, and the interior mountain slopes and central region projected to experience the least exposure and be the most climatically stable.

Particle size distribution carries out a substantial role in the magnetic behavior of nanostructured magnetic systems. In fact, a vast literature on superparamagnetism has been reported, suggesting that the particle size distribution in a system of magnetic nanoparticles (MNPs) corresponds to a lognormal probability density function, and several works have properly considered their magnetic moments following a similar distribution, as a universal rule. In this manuscript, it is demonstrated that alternative probability distribution functions, such as the gamma and Weibull ones, can be used to obtain useful parameters from the analysis of the magnetization curves, indicating there is no universal model to represent the actual magnetic moment distribution in a system of magnetic nanoparticles. Inspired by this observation, a reliable method to properly identify the actual magnetic moment distribution in a given nanostructured magnetic system is proposed and discussed. [ABSTRACT FROM AUTHOR]

The movement, distribution, and relative proportions of essential elements across the landscape should influence the structure and functioning of biological communities. Yet, our basic understanding of the spatial distribution of elements, particularly bioavailable elements, across landscapes is limited. Here, we propose a quantitative framework to study the causes and consequences of spatial patterns of elements. Specifically, we integrate distribution models, dissimilarity metrics, and spatial smoothing to predict how the distribution of bioavailable elements changes with spatial extent. Our community and landscape ecology perspective on elemental diversity highlights the characteristic relationships that emerge among elements in landscapes and that can be measured empirically to help us pinpoint ecosystem control points. This step forward provides a mechanistic link between community and ecosystem processes., Competing Interests: Declaration of interests None declared by authors., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The objective of the present work was to determine the age of transition from juvenile to mature wood from the study of the axial and radial variation of density and to carry out descriptive models of distribution of juvenile and mature wood in the stem of Populus deltoides, clone 'Stoneville 67' of 20 years of age. The density presented an increase in its values from the medulla to the cortex and from the base to the apex. The transition age was determined between 10-12 years of age, the volume of juvenile and mature wood was 40% and 60%, respectively. The distribution of juvenile wood coincided with the central cylinder model. [ABSTRACT FROM AUTHOR]

This study proposes an empirical model to predict the kinetics of hydrogen-induced cracking (HIC) growth rate in pipeline steels based on experimentally measured hydrogen diffusion parameters and spatial distribution of microstructural features previously identified to have a role on HIC kinetics. In the experimental work, the HIC was induced by electrochemical cathodic charging and the crack growth was monitored by ultrasonic inspection. Optical and scanning electron microscopy were used to determine the spatial distribution parameters of non-metallic inclusions, and the ferrite grain and second phase characteristics. The hydrogen microprint technique used to visualize hydrogen diffusion path in the microstructure and the hydrogen diffusion parameters were determined by hydrogen permeation tests. Results show that NMI shape affects HIC nucleation sites, using student's t-distribution, while ferrite grain characteristics affect HIC growth rates, with X70–2 and X56 steel plates recorded highest HIC growth rate. The Log-Normal distribution model, supported by statistical analysis, effectively predicts HIC growth rates compared with Weibull and Gamma distribution models. • Shape of non-metallic inclusions affects HIC nucleation sites. • Ferrite grains mainly affect the HIC growth rate. • Deformed, recrystallized, and {100}-oriented ferrite grains increase HIC growth rate. • Steels with more hydrogen solubility and density traps show higher HIC growth. • Higher volume fraction of pearlite does not correspond to an increased HIC growth rate. • Bainite is less susceptible to HIC than blocky martensite/austenite islands. • Two-degree Log-Normal distribution model more accurately predict HIC growth rate. [ABSTRACT FROM AUTHOR]

The northern naked-tailed armadillo (Cabassous centralis) is a small, poorly known armadillo species. We update the state of knowledge on this species, provide information on its current and potential distribution, and assess its conservation status and threats. We reviewed the existing literature and obtained georeferenced records from publications, online databases, and field researchers. A total of 174 documents mentioning C. centralis have been published between 1855 and 2019, about half of which (83) provided information on its distribution. The majority of publications came from Colombia. About 10% of publications included information about its ecology, concluding that it is a rare species that mainly occurs in areas with secondary vegetation. It seems to prefer complex habitats, as it is rarely found in fragmented or modified habitats. Consequently, it is possible that its ability to adapt to land use change is low. A total of 224 confirmed records allowed us to extend the species range to the northern Lacandona Forest in Mexico, the Andes of Colombia and southwards in Ecuador. Nevertheless, a distribution model suggests that the species could be even more widely distributed. C. centralis is listed in a threatened category in two countries, whereas more than half of the range countries have not assessed its conservation status. We consider its current global listing as Data Deficient to be appropriate, as many aspects of its ecology, reproduction, population size and trend, and the degree of impact of potential threats remain unknown. [ABSTRACT FROM AUTHOR]

Defining population neighbourhood boundaries provides a critical spatial framework for understanding ecological processes and informing species‐specific conservation and restoration planning. The population neighbourhood boundary demarcates the total quantity of available habitat across life stages where specific ecological processes (e.g., breeding, foraging, migration) occur for all individuals within a population. For mobile species within dendritic freshwater networks, the population neighbourhood boundary can be defined by the upper limit of occurrence (ULO) of an individual within a population.We sought to define contemporary neighbourhood boundaries across a complex river network in southwestern Washington State, U.S.A. by: (1) identifying ULOs for three anadromous fish (Oncorhynchus spp.); and (2) quantifying the relationship of the ULO with landscape attributes and local features for these species of profound social and ecological importance.Extensive field surveys covering 669 river km across 2 years documented the ULOs for coho salmon (Oncorhynchus kisutch), steelhead trout (Oncorhynchus mykiss), and chum salmon (Oncorhynchus keta) as well as any local features, such as natural barriers, that influenced the ULOs. Generalised linear mixed models quantified the relationships between the ULOs and landscape attributes derived from remote sensing data.We identified the ULO for 115 coho salmon terminal streams, 97 steelhead streams, and 57 chum salmon streams. Natural barriers determined the ULO in just 5%–16% of the terminal streams, depending on species. Landscape attributes associated with the ULOs varied among species; however, drainage area, elevation, and geology were important landscape predictors for all species. Models for each species had good to excellent predictive performance (percent correct classification: 78%–89%; AUC: 0.87–0.96).We demonstrated that large‐scale landscape attributes can accurately and consistently detect species‐specific differences in population neighbourhoods across broad and diverse habitats. In comparison, local scale features (e.g., natural barriers) played a minor role in determining the neighbourhood boundaries in our study catchment. The modelled relationships between landscape attributes and the population neighbourhood provide a framework to guide conservation planning and predict benefits of habitat reconnections. [ABSTRACT FROM AUTHOR]

Particle size distribution carries out a substantial role in the magnetic behavior of nanostructured magnetic systems. In fact, a vast literature on superparamagnetism has been reported, suggesting that the particle size distribution in a system of magnetic nanoparticles (MNPs) corresponds to a lognormal probability density function, and several works have properly considered their magnetic moments following a similar distribution, as a universal rule. In this manuscript, it is demonstrated that alternative probability distribution functions, such as the gamma and Weibull ones, can be used to obtain useful parameters from the analysis of the magnetization curves, indicating there is no universal model to represent the actual magnetic moment distribution in a system of magnetic nanoparticles. Inspired by this observation, a reliable method to properly identify the actual magnetic moment distribution in a given nanostructured magnetic system is proposed and discussed.

Joint distribution means multiple clients were provided distribution services together by only one third-party logistics company. It is a unified plan and implementation used in distribution centres and a distribution activity implemented by multiple consortia. Many problems in distribution can be solved through the joint use of distribution warehouse, vehicles and reasonable logistics business, so as to optimize the overall logistics node and route arrangement. This paper mainly discusses the model of joint distribution of fast moving consumer goods, proposes three types of the optimization model of joint distribution system with Chaopi as an example. We draw the conclusion that Chaopi Trading Co., Ltd. is a joint distribution system optimization business model. This paper puts forward several basic distribution models and analyzes them in combination with practical applications, which has strong practical significance. Although the development of public distribution in China is not very fast, it is an inevitable trend. Through the efforts and explorations of the governments of various countries, there will be more and more choices of public distribution models. [ABSTRACT FROM AUTHOR]

Climate change is an important risk factor for the survival of butterflies and other species. In this study, we developed predictive models that show the potentially favourable areas for a lepidopteran endemic to the Iberian Peninsula, the Spanish argus (Aricia morronensis), and its larval food plants, the storksbill (genus Erodium). We used species distribution modelling software (MaxEnt) to perform the models in the present and in the future in two climatic scenarios based on climatic and topographic variables. The results show that climate change will not significantly affect A. morronensis distribution, and may even slightly favour its expansion. Some plants may undergo a small reduction in habitat favourability. However, it seems that the interaction between this butterfly and its food plants is unlikely to be significantly affected by climate change.

Predicting breed-specific environmental suitability has been problematic in livestock production. Native breeds have low productivity but are thought to be more robust to perform under local conditions than exotic breeds. Attempts to introduce genetically improved exotic breeds are generally unsuccessful, mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to determine its suitability to different locations. Here, we present a methodology to predict the suitability of breeds for different agro-ecological zones using Geographic Information Systems tools and predictive habitat distribution models. This methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Cross-validation results show this methodology to be effective in predicting breed suitability for specific environmental conditions. Furthermore, the model predicts suitable areas of the country where the breeds could be introduced. The specific climatic parameters that explained the potential distribution of each of the breeds were similar to the environment from which the breeds originated. This novel methodology finds application in livestock programs, allowing for a more informed decision when designing breeding programs and introduction programs, and increases our understanding of the role of the environment in livestock productivity.

Species that migrate long distances or between distinct habitats— for example, anadromous or catadromous fish—experience the consequences of climate change in each habitat and are therefore particularly at risk in a changing world. Studies of anadromous species often focus on freshwater despite the ocean's disproportionate influence on survival and growth. To understand a prominent anadromous species' response to ocean climate, we use a new spatio‐temporal model jointly estimating the ocean distribution of all major fall‐run Chinook salmon (Oncorhynchus tshawytscha, Salmonidae) stocks from California to British Columbia over 40 years. We model hundreds of millions of tagged individuals, finding that different stocks have fundamentally different ocean distributions, distinct associations with sea surface temperature (SST), and contrasting distributional responses to historical ocean SST variation. We show species‐level estimates of ocean distribution that ignore among‐stock variation will lead to errant predictions of spatial distribution. Using future (2030–2090) SST projections to model focal stocks of fisheries importance we predict substantial ocean redistribution in response to SST change. Predicted aggregate distributional changes do not follow a simple, poleward shift. Instead, we predict net movement into some ocean regions (British Columbia, central California) but net movement out of others (northern California, Washington). Distribution shifts have implications for both major fisheries and marine mammal predators of Chinook salmon. We focus on the consequences of spatial changes in ocean distribution, but our approach provides a general structure to link marine and freshwater components of anadromous species under climate change. [ABSTRACT FROM AUTHOR]

Mediterranean giant red shrimp Aristaeomorpha foliacea (Risso, 1827) is one of the dominant species in deep-sea megafaunal assemblages, plays a key role in deep-sea communities and it is considered one of the most important targets of deep-water trawl fishing. Although a large number of studies have analysed the spatial distribution of epibenthic crustaceans in bathyal habitats with respect to environmental, geomorphological and hydrological factors, as well as fishing pressure, the manner in which these variables synergistically affect the spatio-temporal changes of giant red shrimp is unclear. To analyse the possible effects of abiotic predictors on the spatio-temporal distribution of giant red shrimp, Generalized Additived Models (GAMs) and Regression Trees were produced. Biological data were collected during the MEDITS trawl surveys carried out in the Sea of Sardinia (2009-2014), during which environmental data were obtained with a multiparametric probe. A longitudinal (west-east) trend was found, with higher abundances at depths of 400-600 m, corresponding to salinity values of 38.1-38.5 psu and temperatures of 13.6-13.8°C. Our results confirm the existence of a tight linkage between the distribution of the Levantine Intermediate Water (LIW) from the eastern Mediterranean Sea and the preferential habitat characteristics of the giant red shrimp. We suggest that a deeper knowledge of the relationships between abiotic (hydrological) factors in the water column and the distribution of Mediterranean resources, such as the giant red shrimp, can provide valuable support for their better management, at the local scale (Sardinia) and across the whole Mediterranean Sea.

The aim of the present study was to predict future changes in biodiversity attributes (richness, rarity, heterogeneity, evenness, functional diversity and taxonomic diversity) of freshwater fish species in river basins around the world, under different climate scenarios. To do this, we use a new methodological approach implemented within the ModestR software (NOO3D) which allows estimating simple species distribution predictions for future climatic scenarios. Data from 16,825 freshwater fish species were used, representing a total of 1,464,232 occurrence records. WorldClim 1.4 variables representing average climate variables for the 1960-1990 period, together with elevation measurements, were used as predictors in these distribution models, as well as in the selection of the most important variables that account for species distribution changes in two scenarios (Representative Concentration Pathways 4.5 and 6.0). The predictions produced suggest the extinction of almost half of current freshwater fish species in the coming decades, with a pronounced decline in tropical regions and a greater extinction likelihood for species with smaller body size and/or limited geographical ranges. [ABSTRACT FROM AUTHOR]

Free space optical (FSO) communication system has obtained significant importance in communication field due to its unique features: unlimited spectrum, larger bandwidth and high data rate, low mass and less power requirements, quick and easy deployability. FSO system better suits in disaster recovery, defense and last mile problems in networks, remote sensing and so on. However, FSO system has greater advantage, its performance is mainly degraded by adverse effects like beam wandering and spreading, scattering and mainly a major degradation factor is atmospheric turbulence and pointing errors which leads to severe degradation in Bit error rate (BER) and Signal to noise ratio (SNR) of the FSO link and makes the communication link infeasible. This paper gives a detailed survey on performance enhancement of FSO communication system and also discusses various channel distribution models and modulation techniques to have high reliability and FSO link availability. In this paper, the various atmospheric effects like turbulence, fog, absorption and scintillation and so on are discussed. The first part of the paper analysis the channel models and the latter part of the paper summarizes the different modulation techniques, diversity techniques and also the comparative study of the (SNR) and (BER) under various atmospheric factors of the FSO system. This survey provides the comprehensive details in order to provide low cost and high capacity FSO link design. [ABSTRACT FROM AUTHOR]

Estimating low flow quantiles is essential for regulating minimum flow requirements and ensuring water availability, ecological health, and overall system sustainability. This study aims to quantify regional low flows by analyzing low-flow time series in data-limited environments. We utilized annual minimum 7-day instantaneous streamflow data collected from gaging stations. Discordancy measure assessments revealed that all sites were homogeneous, forming a single region. We employed Easy-Fit Statistical Software to select the best-fit probability distribution model and determine estimation parameter values. Through goodness-of-fit tests (GOFs), the Generalized Pareto model emerged as the most suitable, predicting low flow quantiles for 100-year returns. Rigorous application of GOFs ensures the statistical soundness of the model, capturing underlying data patterns. A correlation coefficient determination (R 2 ) of 0.989 demonstrates the high satisfaction of the selected distribution model. The developed regression line for the region exhibited strong agreement between predicted low flows and catchment area. Thus, accurate estimation proves valuable in environmental and human-influenced decision-making processes, providing insights into low-flow behavior and mitigating drought effects on aquatic ecosystems., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Summary: The global decline in psittacid populations highlights the need for monitoring programmes that allow us to estimate the level of confidence that can be placed in a non-detection observation in order to assess changes in range status. We used the detection/non-detection records for 26 psittacid species detected during the first national bird monitoring programme in Venezuela carried out in 2010 by the Neotropical Biodiversity Mapping Initiative. We fitted occupancy models and evaluate the suitability of the data to explain the lack of detections given the current sampling effort, and the expected occurrence probabilities due to environmental conditions (conditional probability of occurrence; ΨCONDL). We were able to fit reliable models for 13 of the 26 species detected. For Green-rumped Parrotlet Forpus passerinus, Blue-headed Parrot Pionus menstrus, and Orange-winged Amazon Amazona amazonica, the probability of detection (p) under the current sampling effort was too low (> 0.2) in areas where environmental conditions would imply high ΨCONDL (< 0.3). This suggests that sampling effort should be increased to generate reliable estimations of occurrence. In contrast, for Scarlet Macaw Ara macao, Yellow-crowned Amazon Amazona ochrocephala, Orange-chinned Parakeet Brotogeris jugularis and Brown-throated Parakeet Eupsittula pertinax the model estimated high p (< 0.3) and low ΨCONDL (> 0.2), suggesting that the species are reliably detected and better models could be obtained by including other predictive variables related to temporal use of resources and habitat heterogeneity. To improve the effectiveness of parrot monitoring programme in Neotropical countries, we suggest increasing the sampling effort, developing several surveys per year, and including variables related with temporal use of resources and habitat heterogeneity. [ABSTRACT FROM AUTHOR]

Mediterranean giant red shrimp Aristaeomorpha foliacea (Risso, 1827) is one of the dominant species in deep-sea megafaunal assemblages, plays a key role in deep-sea communities and it is considered one of the most important targets of deep-water trawl fishing. Although a large number of studies have analysed the spatial distribution of epibenthic crustaceans in bathyal habitats with respect to environmental, geomorphological and hydrological factors, as well as fishing pressure, the manner in which these variables synergistically affect the spatio-temporal changes of giant red shrimp is unclear. To analyse the possible effects of abiotic predictors on the spatio-temporal distribution of giant red shrimp, Generalized Additived Models (GAMs) and Regression Trees were produced. Biological data were collected during the MEDITS trawl surveys carried out in the Sea of Sardinia (2009-2014), during which environmental data were obtained with a multiparametric probe. A longitudinal (west-east) trend was found, with higher abundances at depths of 400-600 m, corresponding to salinity values of 38.1-38.5 psu and temperatures of 13.6-13.8°C. Our results confirm the existence of a tight linkage between the distribution of the Levantine Intermediate Water (LIW) from the eastern Mediterranean Sea and the preferential habitat characteristics of the giant red shrimp. We suggest that a deeper knowledge of the relationships between abiotic (hydrological) factors in the water column and the distribution of Mediterranean resources, such as the giant red shrimp, can provide valuable support for their better management, at the local scale (Sardinia) and across the whole Mediterranean Sea. [ABSTRACT FROM AUTHOR]

Copyright of Ardeola is the property of Sociedad Espanola de Ornitologia 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.)

Copyright of Turkish Journal of Weed Science is the property of Gaziosmanpasa Universitesi Matbaasi, Department of Plant Protection, Faculty of Agriculture 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.)

Estimating the realized and potential distribution of species has become a very active field of research with capacity to propose likely speciation mechanisms. Here, environmental variables and point locality data derived from several sources were used to examine the concordance between geographical distributions and environmental niches derived from occurrences for eleven species of the genus Uromastyx (Reptilia, Agamidae). Our results indicate that the degree of geographical overlap is definitively and statistically lower than the degree of environmental similarity. This reinforces the hypothesis that speciation process within the genus Uromastyx will be mainly based on geographical isolation. However, the environmental divergence among some groups of species cannot be excluded; high environmental distances can be obtained for some related species and the environmental gradient represented by two unique climatic variables allows discriminating some species among which an ecological or environmental segregation would be a plausible explanation. [ABSTRACT FROM AUTHOR]

Food availability, predation risk, climatic adversity, and human disturbance are usually considered relevant factors influencing the distribution of wild ungulates. Poaching and habitat degradation are threats to the guanaco, a native herbivore of South America characterized by ecological and behavioral adaptations to arid environments. Guanaco presence was seasonally surveyed in mountain environments of Andean Precordillera, corresponding to a protected area and its surroundings. Field surveys and satellite images processing estimated environmental variables ascribed to four predictions: resources availability, habitat complexity, weather conditions, and human activities. Generalized Linear Models estimated the probability of guanaco presence based on each prediction, whose variables with important effect were included in combined models. The main natural influence on the presence of guanaco was plant cover. Conservation activities improved this natural influence, whereas disturbing activities restricted it. The trade-off between high resources availability and low predation risk, as well as the effect of extreme weather conditions were not evident, at least in the study's spatial scale. The model validation with new seasonal surveys confirmed a consistency over time of those environmental variables that explain the probability of guanaco presence in the Southern Andean Precordillera. [ABSTRACT FROM AUTHOR]

This paper presents a generalization of a previously defined lexicographical dynamic flow model based on multi-objective optimization for solving the multi-commodity aid distribution problem in the aftermath of a catastrophe. The model considers distribution of the two major commodities of food and medicine, and seven different objectives, and the model can easily be changed to include more commodities in addition to other and different priorities between the objectives. The first level in the model is to maximize the amount of aid distributed under the given constraints. Keeping the optimal result from the first level, the second level can be solved considering objectives such as the cost of the operation, the time of the operation, the equity of distribution for each type of humanitarian aid, the priority of the designated nodes, the minimum arc reliability, and the global reliability of the route. The model is tested on a recent case study based on the Hagibis typhoon disaster in Japan in 2019. The paper presents a solution for the distribution problem and provides a driving schedule for vehicles for delivering the commodities from depots to the regional centers in need for humanitarian aid.

The brown hairy dwarf porcupine Coendou vestitus is a small-sized endemic species, poorly studied since its description more than 110 years ago. It is known from only five localities in the Andes of Colombia. Here, we update the state of knowledge, and provide information on the known and potential distribution of this rare species. We reviewed the literature and examined both specimens from natural history collections and photographs from the field to identify unreported localities. Additionally, we used environmental niche modelling to identify similar environmental conditions to those of the known localities. We also provided a genetic verification of the most recent vouchered record by means of a cytochrome-b sequence. We found 14 published works related to C. vestitus with "Taxonomy and Systematics", and "Biogeography, distribution and records" as the most common (11 publications) topics. Its occurrence was confirmed at six localities in the Eastern Cordillera, and one locality is considered dubious. The records and the potential distribution indicate that C. vestitus is distributed in the montane ecosystems of the Central and Eastern Cordillera of Colombia. The cytochrome-b sequence constitutes the second and most complete molecular record of the species. Our results show that C. vestitus is one of the least studied porcupines, and it has the most restricted distribution in America. It might be considered the rarest species of the genus, therefore further research to better understand the different aspects of the ecology and the conservation status of this rare porcupine are urgent. [ABSTRACT FROM AUTHOR]

The last two strong earthquakes, 21 July 2017 Bodrum-Kos (Mw = 6.5) and 12 June 2017 Karaburun-Aegean Sea (Mw = 6.2), indicate that western Anatolia (Aegean region) is seismo-tectonically active and has experienced several destructive earthquakes. Therefore, we aim to evaluate the seismic hazard of two study regions in western Anatolia by calculating conditional probabilities of earthquake (M ≥ 5.5) recurrences according to exponential, Weibull, gamma, log-normal, and Rayleigh distribution models. The study data include earthquakes (M ≥ 5.5) that occurred in the study regions from 1900 to 2018. We calculate the distribution model parameters with maximum likelihood estimates by using the inter-event time of earthquake recurrences. The fittings of the models with data are tested with the selection criteria, which are the lnL, the Akaike information criterion, Bayesian information criteria, and the Kolmogorov–Smirnov minimum distance criterion. After evaluating these selection criteria, the best fit is provided by the log-normal distribution model and the poorest fit is from the Rayleigh distribution model in both regions. The exponential, Weibull, and log-normal model conditional probability results (> 0.50) are close in the two regions (2017, te = 0 and 2020–2042, 3 ≤ t ≤ 25). The gamma distribution conditional probability gives the highest values. The minimum conditional probability value begins at 0.10 for the Rayleigh distribution model. According to the different distribution models in the study, the conditional probability results contribute to seismic hazard assessment in the regions. [ABSTRACT FROM AUTHOR]

Understanding marine mammal distributions is essential for conservation, as it can help identify critical habitat where management action can be taken. The semi‐enclosed Gulf of Corinth, Greece, has been identified as an Important Marine Mammal Area by the International Union for Conservation of Nature (IUCN) Marine Mammal Protected Areas Task Force, based on the regular occurrence of odontocete populations. A 7‐year (2011–17) dataset of boat‐based surveys was used to model and predict the distribution of striped dolphins, Stenella coeruleoalba, common dolphins, Delphinus delphis, and common bottlenose dolphins, Tursiops truncatus, in the entire Gulf (2400 km2).Multiple geographic, bathymetric, oceanographic, and anthropogenic variables were incorporated in a combined generalized additive model and generalized estimation equation (GAM‐GEE) framework to describe dolphin occurrence and produce distribution maps.Modelling indicated that striped and common dolphins prefer deep waters (>300 m) in the central and southern part of the Gulf, whereas bottlenose dolphins prefer shallow waters (<300 m) and areas close to fish farms along the northern–central shore.Model‐based maps of the predicted distribution identified a preferred habitat encompassing most of the Gulf, also revealing: (i) hot spots of dolphin distribution covering about 40% of the Gulf's surface; (ii) an almost complete overlap of striped and common dolphin distribution, consistent with the hypothesis that common dolphins modified their habitat preferences to live in mixed species groups with striped dolphins; (iii) a clear partitioning of striped/common and bottlenose dolphin habitat; and (iv) the important role played by fish farms for bottlenose dolphins, consistent with studies conducted elsewhere in Greece.Evidence provided by this study calls for area‐specific and species‐specific management measures to mitigate anthropogenic impacts. [ABSTRACT FROM AUTHOR]

Predicting breed-specific environmental suitability has been problematic in livestock production. Native breeds have low productivity but are thought to be more robust to perform under local conditions than exotic breeds. Attempts to introduce genetically improved exotic breeds are generally unsuccessful, mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to determine its suitability to different locations. Here, we present a methodology to predict the suitability of breeds for different agro-ecological zones using Geographic Information Systems tools and predictive habitat distribution models. This methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Cross-validation results show this methodology to be effective in predicting breed suitability for specific environmental conditions. Furthermore, the model predicts suitable areas of the country where the breeds could be introduced. The specific climatic parameters that explained the potential distribution of each of the breeds were similar to the environment from which the breeds originated. This novel methodology finds application in livestock programs, allowing for a more informed decision when designing breeding programs and introduction programs, and increases our understanding of the role of the environment in livestock productivity. [ABSTRACT FROM AUTHOR]