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The increasing spread of marine non‐indigenous species (NIS) due to the growth in global shipping traffic is causing widespread concern for the ecological and economic impacts of marine bioinvasions. Risk management authorities need tools to identify pathways and source regions of priority concern to better target efforts for preventing NIS introduction. The probability of a successful NIS introduction is affected by the likelihood that a marine species entrained in a transport vector will survive the voyage between origin and destination locations and establish an independently reproducing population at the destination. Three important risk factors are voyage duration, range of environmental conditions encountered during transit and environmental similarity between origin and destination. In this study, we aimed for a globally comprehensive approach to assembling quantifications of source‐destination risk factors from every potential origin to every potential destination. To derive estimates of voyage‐related marine biosecurity risk, we used computer‐simulated vessel paths between pairs of ecoprovinces in the Marine Ecoregions Of the World biogeographic classification system. We used the physical length of each path to calculate voyage duration risk and the cross‐latitudinal extent of the path to calculate voyage path risk. Environmental similarity risk was based on comparing annual average sea surface temperature and salinity within each ecoprovince to those of other ecoprovinces. We derived three separate sets of risk quantifications, one each for voyage duration, voyage path and environmental similarity. Our quantifications can be applied to studies that require source‐destination risk estimates. They can be used separately or combined, depending on the importance of the types of source‐destination risks that might be relevant to particular scientific or risk management questions or applications. The probability of a successful marine bioinvasion is affected by the likelihood that a potentially invasive marine species entrained in a transport vector (e.g., cargo ships) will survive the voyage between origin and destination locations, and establish an independently reproducing population at the destination. Three important risk factors are voyage duration, range of environmental conditions encountered during transit and environmental similarity between origin and destination. In this study, we aimed for a globally comprehensive approach to assembling quantifications of source‐destination risk factors from every potential origin to every potential destination.

Avian influenza (AI) is a highly contagious viral disease affecting both domestic and wild birds, posing a significant threat to poultry farming worldwide. This study aims to analyze the key landscape and population factors associated with H7 avian influenza outbreaks across the Euro-Asian continent and to identify high-risk areas in Russia for the virus’s introduction and subsequent spread. Two models were developed using the Maximum Entropy algorithm (MaxEnt): An introduction model predicting the likelihood of avian influenza presence based on climatic, landscape, wild waterfowl and semiaquatic bird population density data; and a spread model estimating outbreak risk in poultry farms using data on synanthropic birds, poultry flock density, and proximity to wild bird habitats. The first model was trained via maximum likelihood using data from H7 avian influenza outbreaks in Europe (Italy, Germany, France, Denmark, Lithuania, the Netherlands) and Southeast Asia (China, Hong Kong, Taiwan, Japan, Cambodia, North Korea, South Korea, Vietnam). The second model was trained using output from the first model. Specifically, areas with a predicted probability of H7 outbreak between 0.9 and 1.0 were used as occurrence points for the model in Russia. The results demonstrated that both models achieved high predictive reliability for avian influenza outbreaks in the Russian Federation: the introduction model (AUC = 0.855) and the spread model (AUC = 0.993). Areas with a high probability of disease occurrence were identified in the Central, Southern, North Caucasian, and Volga Federal Districts. These findings underscore the necessity of enhanced disease surveillance in these regions, as well as in the border areas of the Ural, Siberian, and Far Eastern Federal Districts. The authors recommend strengthening biosecurity measures, enhancing wild bird monitoring in high-risk areas, and maintaining stocks of relevant vaccines to timely contain the outbreaks.

The North American planthopper Metcalfa pruinosa (Say, 1830) (Hemiptera: Flatidae) was accidentally introduced into Europe, and subsequently caused economic damage to orchards and vineyards in some South-European countries. In 2003, a mass occurrence of M. pruinosa was discovered in Vienna, followed by new infestations of several sites. A Pest Risk Analysis was conducted, according to the European and Mediterranean Plant Protection Organization decision support scheme for quarantine pests, to evaluate the risk to Austrian agriculture by M. pruinosa. The highest risk of further introduction into Austria arises from trade of deciduous plants infested with M. pruinosa eggs from Italy and France where this pest is common and which are important trading partners of Austria. Entry by vehicle traffic is considered moderately likely. Active spread by flight of adult M. pruinosa is considered significant only for local dispersal. The CLIMEX® program was applied to predict M. pruinosa's potential geographical distribution and to identify areas at risk. In Austria, southern Burgenland and south-east Styria as well as parts of Vienna, Lower and Upper Austria provide the most suitable climate for M. pruinosa's development. Organic production areas in theses regions are especially at risk of being damaged. To prevent economic impact and for long-term control of M. pruinosa, biological control with its natural enemy Neodryinus typhlocybae (Ashmead 1893) (Hymenoptera: Dryinidae) is recommended.

1. The number of alien reptiles and amphibians introduced and established worldwide has increased over the last decades. The legal pet trade is now the dominant pathway by which individuals of these species arrive in their non-native locale. Despite its importance, specific factors of pet trade pathway that influence the release (introduction) of exotic reptiles and amphibians have not yet been examined. 2. We set out to identify broadscale and easily measured biological and economic factors that influence the release of these exotic pets by their owners. We hypothesize that biological factors reflect the cost of care, and economic factors reflect the value that owners place on their pet, both of which can influence the probability when a pet is released. We collected life history and economic data on the 1,722 species of reptiles and amphibians sold within the US as pets over the last 18 years. We also compiled a list of pet trade-attributed releases in the US (i.e., all free-living species regardless of whether they successfully established). We used boosted regression trees to correlate species release status with their life-history traits and economic attributes (r² = 0.51, AUC = 0.89). 3. We found that species with a high probability of being released were imported at higher quantities over our period of record, have a relatively large adult mass and commanded cheaper retail prices. The number imported and price interacted with longevity and adult mass to produce nonlinear increases in release probability. The most important interaction revealed that large-bodied species imported in high quantities have a three times higher release probability compared to largebodied species imported in lower quantities. 4. Policy implications. Our results provide guidance towards targeting exotic pet reptile and amphibian species that are at a high risk of being released. Species that are both prevalent in the pet trade and large-bodied or long-lived have the highest probability of being released. This will aid in developing education and policy solutions aimed at decreasing the rate at which these pets are released, thus curtailing the invasion process before these species can establish and impacts can occur.

The alarming current and predicted species extinction rates have galvanized conservationists in their efforts to avoid future biodiversity losses, but for species extinct in the wild, few options exist. We posed the questions, can these species be restored, and, if so, what role can ex situ plant collections (i.e., botanic gardens, germplasm banks, herbaria) play in the recovery of plant genetic diversity? We reviewed the relevant literature to assess the feasibility of recovering lost plant genetic diversity with using ex situ material and the probability of survival of subsequent translocations. Thirteen attempts to recover species extinct in the wild were found, most of which used material preserved in botanic gardens (12) and seed banks (2). One case of a locally extirpated population was recovered from herbarium material. Eight (60%) of these cases were successful or partially successful translocations of the focal species or population; the other 5 failed or it was too early to determine the outcome. Limiting factors of the use of ex situ source material for the restoration of plant genetic diversity in the wild include the scarcity of source material, low viability and reduced longevity of the material, low genetic variation, lack of evolution (especially for material stored in germplasm banks and herbaria), and socioeconomic factors. However, modern collecting practices present opportunities for plant conservation, such as improved collecting protocols and improved cultivation and storage conditions. Our findings suggest that all types of ex situ collections may contribute effectively to plant species conservation if their use is informed by a thorough understanding of the aforementioned problems. We conclude that the recovery of plant species currently classified as extinct in the wild is not 100% successful, and the possibility of successful reintroduction should not be used to justify insufficient in situ conservation. Las alarmantes tasas de extinción actuales y pronosticadas han incitado a los conservacionistas a esforzarse paraevitar las futuras pérdidas de biodiversidad, pero para las especies que ya se encuentran extintas en vida silvestre existen pocas opciones. Nos preguntamos si estas especies pueden ser restauradas, y de ser así, qué papel pueden desempeñar las colecciones ex situ de plantas (es decir, jardines botánicos, bancos de germoplasma, herbarios) en la recuperación de la diversidad genética de las plantas. Revisamos la literatura relevante para evaluar la factibilidad de la recuperación de la diversidad genética perdida y la probabilidad de supervivencia subsecuente de las reubicaciones. Encontramos 13 intentos por recuperar especies extintas en vida silvestre, la mayoría de los cuales usó material preservado en jardines botánicos (12) y en bancos de semillas (2). También hubo un caso de una población eliminada localmente que fue recuperada con material de un herbario. Ocho (60%) de estos casos fueron reubicaciones exitosas o parcialmente exitosas de la especie o población focal; los otros cinco fallaron o era demasiado pronto para poder determinar el resultado. Los factores que limitan el uso de material proveniente de colecciones ex situ para la restauración de la diversidad genética de las plantas en vida silvestre incluyen la escasez de material original, la baja viabilidad y la longevidad reducida del material, la baja variación genética, la falta de evolución (especialmente para el material almacenado en herbarios y bancos de germoplasma) y los factores socioeconómicos. A pesarde esto, las prácticas modernas de colección representanuna oportunidad para la conservación de las plantas, como los protocolos mejorados de recolección y las condiciones acrecentadas de cultivo y almacenamiento. Nuestros hallazgos sugieren que todos los tipos de colecciones ex situ pueden contribuir efectivamente a la conservación de especies de plantas si su uso está respaldado por un entendimiento a fondo de los problemas antes mencionados. Concluimos que la recuperación de especies de plantas que actualmente están clasificadas como extintas en vida silvestre no es 100% exitosa y que la posibilidad de una reintroducción exitosa no debería utilizarse para justificar una conservación in situ insuficiente.

Unauthorized introductions are an ongoing problem for fisheries managers. To understand reasons for the continued spread of nonnative fish species, the pathways of nonnative fish introductions were analyzed from 1961 to 2017 in Wyoming, USA. Unauthorized introductions are those that occurred without oversight of a management agency. The largest source of unauthorized introductions was the deliberate, illegal release of fish by the public at 46% of the 215 introduction events. The next largest source was colonization of new water bodies after initial establishment at 29%. Inadvertent (accidental) stockings (8%) and unknown sources (17%) were the other pathways documented. Management responses consisted of attempts at complete eradication (9%), population reduction (10%), or containment (3%) although in the majority of introductions (79%) no action was taken. The introductions involved 49 taxa but three sport fish constituted 26.5% of all events: brook trout Salvelinus fontinalis, walleye Sander vitreus, and yellow perch Perca flavescens. The prevalence of illegal introductions and the difficulty of eradicating introduced species indicate the continuing need for public education and enforcement efforts. The high frequency whereby species colonize new waterbodies indicates that fish introductions, even those authorized by management agencies, must consider the high probability that species will expand into unintended waterways.

Intrusion detection pretended to be a major technique for revealing the attacks and guarantee the security on the network. As the data increases tremendously every year on the Internet, a single algorithm is not sufficient for the network security. Because, deploying a single learning approach may suffer from statistical, computational and representational issues. To eliminate these issues, this paper combines multiple machine learning algorithms called stacked ensemble learning, to detect the attacks in a better manner than conventional learning, where a single algorithm is used to identify the attacks. The stacked ensemble system has been taken the benchmark data set, NSL-KDD, to compare its performance with other popular machine learning algorithms such as ANN, CART, random forest, SVM and other machine learning methods proposed by researchers. The experimental results show that stacked ensemble learning is a proper technique for classifying attacks than other existing methods. And also, the proposed system shows better accuracy compare to other intrusion detection models.

Aim Biological invasions threaten biodiversity globally. Large‐scale studies of non‐native plant species invasiveness typically focus on identifying ecological differences between naturalized and invasive species that account for their spread from sites of initial establishment (i.e., invasion success). However, invasive species differ widely in the magnitude of their impacts, suggesting the characteristics that favour invasion success might not necessarily predict the consequences of that invasion. Here we test whether those factors that increase the probability of plant species invasion also explain the severity of impacts. Location China. Methods We compiled a database of the invasiveness, biogeographic origins, life history traits, and introduction history for 538 non‐native plants in China and modelled differences in (a) naturalized and invasive species; (b) the spatial extent of invasion; and, (c) the severity of invasion impacts among successful invaders. Results Invasion success and the spatial extent of invasion shared similar influencing factors. However, these clearly differed from the predictors of severe invasion impacts. Unintentionally introduced non‐native plants with shorter life cycles and longer residence times were more likely to become invasive and to invade a larger area, while taller plants introduced from the Americas tended to have more severe impacts on the native ecosystems of China. Main Conclusions These results illustrate the different roles of introduction history, biogeographical origin and biological traits in determining the invasion success and spatial extent of invasion versus the severity of invasive species impacts. We suggest that factors associated with evolutionary adaptation and population expansion might determine invasion success and extent, while traits related to the relative competitive ability of invasive species determine the severity of impacts. Identifying specific characteristics of species that distinguish among successful invaders most likely to result in more severe impacts could help with planning more effective interventions.

Significance Because of the globalization of trade and travel, worldwide invasion rates are high. A potential driver of the global acceleration of new invasions is the so-called bridgehead effect, in which initial invasive populations serve as the source of additional invasions via secondary introductions. However, the frequency and overall importance of secondary introductions remain largely unknown. Using a remarkable dataset, spanning nearly 100 years (1914–2013), of ant interceptions at air and maritime ports in the United States and New Zealand, we found that most ant introductions arise via secondary transport via intermediate regions. Our analyses also reveal positive feedback between the introduction and establishment stages of the invasion process via secondary introductions acting as a critical driver of increasing global invasion rates.

With the origin of smart homes, smart cities, and smart everything, smart phones came up as an area of magnificent growth and development. These devices became a part of daily activities of human life. This impact and growth have made these devices more vulnerable to attacks than other devices such as desktops or laptops. Text messages or SMS (Short Text Messages) are a part of smartphones through which attackers target the users. Smishing (SMS Phishing) is an attack targeting smartphone users through the medium of text messages. Though smishing is a type of phishing, it is different from phishing in many aspects like the amount of information available in the SMS, the strategy of attack, etc. Thus, detection of smishing is a challenge in the context of the minimum amount of information shared by the attacker. In the case of smishing, we have short text messages which are often in short forms or in symbolic forms. A single text message contains very few smishing-related features, and it consists of abbreviations and idioms which makes smishing detection more difficult. Detection of smishing is a challenge not only because of features constraint but also due to the scarcity of real smishing datasets. To differentiate spam messages from smishing messages, we are evaluating the legitimacy of the URL (Uniform Resource Locator) in the message. We have extracted the five most efficient features from the text messages to enable the machine learning classification using a limited number of features. In this paper, we have presented a smishing detection model comprising of two phases, Domain Checking Phase and SMS Classification Phase. We have examined the authenticity of the URL in the SMS which is a crucial part of SMS phishing detection. In our system, Domain Checking Phase scrutinizes the authenticity of the URL. SMS Classification Phase examines the text contents of the messages and extracts some efficient features. Finally, the system classifies the messages using Backpropagation Algorithm and compares results with three traditional classifiers. A prototype of the system has been developed and evaluated using SMS datasets. The results of the evaluation achieved an accuracy of 97.93% which shows the proposed method is very efficient for the detection of smishing messages.