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Jelen közleményben a Keszthelyi-hegységben 2014–2017 években tett terepbejárásaim során észlelt nőszőfű-előfordulásokat foglalom össze. A területről tíz nőszőfűfaj rendelkezett irodalmi vagy herbáriumi adatokkal, ezek előfordulását sikerült megerősíteni (Epipactis atrorubens, E. helleborine, E. leptochila, E. microphylla, E. moravica, E. muelleri, E. palustris, E. purpurata, E. nordeniorum, E. voethii) és a hegységre nézve további öt, eddig publikációban nem jelzett faj (Epipactis albensis, E. neglecta, E. peitzii, E. pontica, E. tallosii), illetve egy hibrid (Epipactis ×reinekei) került elő.

Glycidyl esters (GEs) and 3-monochloropropane-1,2-diol esters (3-MCPDEs) are heat-induced contaminants mainly formed during oil refining. Information on the occurrence of these contaminants in pressed oils is still limited. In this study, 16 oilseeds pressed with a screw press and a hydraulic press had extremely low concentrations of GEs and 3-MCPDEs. Seed-roasting at high temperatures was the principal factor that significantly increased contents of GEs and 3-MCPDEs in pressed oils, in which higher precursor levels were observed. Occurrence data of GE and 3-MCPDE concentrations in refined oils (n = 25) and pressed oils (n = 26) marketed in Taiwan showed that hot-pressed oils had higher concentrations than their cold-pressed counterparts, and average concentrations of refined oils were > 10-fold higher than those of pressed oils. Risk assessment using the margin of exposure (MOE) approach indicated the presence of GEs in edible oils was of concern for food safety, especially for people who frequently use refined oils.

Context: Ecological networks are often designed based on the degree of suitability and permeability of land cover classes, as obtained by estimating the statistical relationships between occurrence data and classes coverage using habitat suitability models (HSMs). Considering only the classes coverage, but not their spatial arrangement, frequently prevents HSMs from correctly identifying nodes and connectivity elements. Objectives: We propose a new approach in the design of ecological networks starting from the relationship between occurrence data and both land cover classes coverage and spatial arrangement, as calculated for different simulated species perceptions of the landscape (SSPLs, corresponding to different combinations of classes alternatively assuming the role of nodes, connectivity elements, or matrix). Methods: The approach consists of comparing the ability to explain the observed species occurrence of both the nodes coverage and the connectivity degree provided by both nodes and connectivity elements, calculated for each SSPL. The better performing SSPL will provide information about the land cover classes that should be considered in designing an ecological network for the species, as well as their role in the network. Results: When applied to the Hazel Dormouse in an agricultural landscape in northern Italy, the method proved effective and allowed us to identify woodlands and hedgerows as nodes, and poplar cultivations, biomasses and reforestations as connectivity elements. Conclusions: The proposed method can be adopted to identify nodes and connectivity elements for virtually every species sensitive to fragmentation, and has important practical implications when integrated in landscape management plans developed to guarantee ecological connectivity

Species distribution models are a useful tool and are now often used in many branches of biology, especially when dealing with threatened organisms. In combination with GIS techniques, these models are especially important and valuable for predicting the occurrence of rare species, for example orchids. Orchids are an endangered plant group, protected worldwide. Questions about their conservation are therefore highly discussed, but not all factors affecting their survival and distribution are known. Here we present an example of using SDMs for analysing orchid species occurrence data from the Jeseniky Mountains in the Czech Republic. Our data were analysed using the MaxEnt program, which produces species distribution maps and thus allows the prediction of the potential occurrence of orchids at yet unknown localities. This program also determines the environmental factors affecting species distribution. This is important for the better protection of orchids, because only by knowing these factors can new localities be found or the management plans that are crucial for maintaining orchid localities be improved. We studied the most abundant orchid species in the given region. We determined the most important factors affecting their occurrence and also areas, where new sites are most likely to be discovered and depicted them in potential distribution maps. This approach can help in finding new localities of orchids and in understanding, which environmental factors influence the occurrence of endangered orchids.

The community temperature index (CTI) is increasingly used to identify the impacts of global warming on local biotic communities such as birds, butterflies, and plants. Temperature is one of the main determinants of global ant diversity and local ant assemblages. Therefore, the CTI can be used to identify the relationship between temperature and ant assemblages or to estimate the influence of global warming. This study aimed at finding the relationship between temperature and CTI values of ant assemblages. Ants were surveyed using baits and pitfall traps at six forest sites in South Korea, differing in mean annual temperature (MAT) from 7.4 °C to 12 °C. The national ant data was used to calculate the species temperature index (STI) of each species that was then used to estimate CTI. The CTI values were significantly positively correlated to MAT values, but the slopes of regression models were lower than one (0.43–0.62). The low slope might be partly caused by the bias of local occurrence data: Overestimation of STI of northern species and underestimation of southern species. The slope values varied according to data types (abundance-individuals, abundance-trap, and occurrence).

Transformation products (TPs) of organic micropollutants are still rarely considered in monitoring of wastewater and aquatic environments. For example, occurrence data of ozonated TPs in full-scale wastewater systems is largely lacking. In this study, the efficiency of a suspect screening strategy including 245 previously reported compounds and their TPs was evaluated for assessing the occurrence of different compound classes and their ozonated TPs in wastewater samples collected at different steps of an advanced treatment process including ozonation. After applying blank subtraction and filtering by mass accuracy (5 ppm tolerance), peak height (minimum 1000 counts) and isotopic pattern score (≥ 80%) 189 of the 245 compounds were detected. A decrease in relative concentration levels was observed for parent compounds in wastewater after ozonation and after a subsequent biological treatment process, while formation of tentative TPs after ozonation accompanied by subsequent degradation in a following biological treatment step was found. Plausibility of structural assignments for tentatively identified TPs could be successfully tested by using relative retention time information as comparison criteria. Overall, the screening approach was fast and successful and can be expanded to other compound classes and TPs where reference standards are not readily available.

We monitored the occurrences of giant jellyfish Nemopilema nomurai off Hyogo Prefecture, southwestern Sea of Japan, from 2006 to 2015. Occurrence data were collected from daily by-catch number of medusae at three large-scale set-nets operated in Hyogo Prefecture. In addition, we examined parameters to base predictions of outbreaks of N. nomurai using environmental factors measured at Amarube set-net and by-catch data of a preliminary offshore trawl survey. Annual by-catch number of N. nomurai medusae exceeding ten thousand in the three set-nets was observed in 2006, 2007 and 2009. On the other hand, no medusa was observed in 2014 and 2015, and the annual values were 2–147 in the other five years (2008 and 2010–2013). Salinity measured at the Amarube set-net decreased from June to August or September, and then increased in every year. The first detection time of N. nomurai medusa occurred within one week from the day when the salinity reached a minimum value for the year. It is thought that prediction of the occurrence timing of N. nomurai may become possible in the future by monitoring salinity data. The present study revealed that in the years when large amounts of medusae were caught in the offshore trawl survey, many medusae were also collected in the set-nets. For predicting the amount of N. nomurai medusae impacting coastal areas of Hyogo Prefecture, the use of catch data from offshore trawl surveys will enable early assessment of potential damage to fisheries.

Based on herpetofaunal records, New Mexico is one of the most diverse states in the American Southwest. We visually summarized reptile and amphibian diversity in New Mexico using occurrence data from the past 20 years. We also identified patterns of species richness by county and discuss survey bias as a factor. In general, northwestern counties had the lowest number of species while central and southwestern regions had the highest numbers of species. We also recognized species-rich counties with few to no new county records in the past 20 years as areas that potentially reached survey saturation.

Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on concentration alone, it can be difficult to identify which compounds may be of toxicological concern and should be prioritized for further monitoring, in-depth testing, or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high-throughput screening (HTS) data, such as the ToxCast database, which contains information for over 9000 compounds screened through up to 1100 bioassays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Prioritized bioactivities from the EAR analysis were linked to discrete adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts.

The representatives of the genusCercyonLeach occurring in the Greater Antilles are reviewed. Ten species are recorded, of which five are described here as new:C. gimmelisp. n.(Dominican Republic),C. armatipenissp. n.(Dominican Republic),C. tainosp. n.(Dominican Republic),C. sklodowskaesp. n.(Jamaica) andC. spiniventrissp. n.(Dominican Republic). Diagnoses and detailed distributional data are also provided forC. floridanusHorn, 1890 (distributed in southeastern United States of America and Cayman Islands),C. insularisChevrolat, 1863 (endemic to the Antilles)C. praetextatus(Say, 1825) (widely distributed in the New World incl. Greater Antilles),C. quisquilius(Linnaeus, 1761) (an adventive species of Paleartic origin) andC. nigriceps(Marshall, 1802) (an adventive species probably of Oriental origin).Cercyon armatipenis, C. gimmeli, C. tainoform a group of closely related species only distinguishable by male genitalia and DNA sequences. A key to the Great AntilleanCercyonis provided and important diagnostic characters are illustrated. The larvae ofC. insularisandC. tainowere associated with adults using COI barcode sequences, illustrated and diagnosed. Full occurrence data, additional images and COI barcode sequences were submitted to open access on-line depositories in an effort to provide access to complete data.

Occurrences of the invasive plant species Heracleum sosnowskyi Manden. in the Komi Republic (northeastern part of European Russia) were recorded and published in the Global Biodiversity Information Facility (GBIF http://www.gbif.org) using the RIVR information system (http://ib.komisc.ru/add/rivr/en). RIVR stands for "Rasprostranenie Invasionnyh Vidov Rastenij" [Occurrence of Invasion Plant Species]. This citizen science project aims at collecting occurrence data about invasive plant species with the help of citizen scientists. Information can be added by any user after a simple registration (concept) process. However, the data published in GBIF are provided only by professional scientists. The total study area is approximately 19,000 km2. The GBIF resource contains 10894 H. sosnowskyi occurrence points, each with their geographical coordinates and photographs of the plants in the locus of growth. The preliminary results of species distribution modelling on the territory of European North-East Russia presented.

Poster presentation presented at the 2020 Texas Chapter of the American Fisheries Society annual meeting in Waco, Texas on January 24, 2020., The Fishes of Texas Project (FoTX) (http://fishesoftexas.org) database currently has 124,452 specimen-vouchered occurrence records spanning > 150 years with over 400,000 new records (including non-vouchered sources such as literature, anecdotal, and photo-based) in the process of being imported. Continual data growth prompted creation of new tools to dynamically assess (as the data evolve) the state of data coverage across various dimensions to increase user understanding and accessibility to the data and improve overall utility of the project. We produced species sampling curves, temporal species accumulation graphs, and heat maps of collecting event density over time and space for each river sub-basin within Texas. A QGIS plugin was also created to better assess the suspect status of incoming records. Each type of visualization has basic documentation, easily accessible statistical summaries, flexible queries, and exploration tools to help reveal variations in sampling density over both temporal and spatial dimensions. We highlight here the San Bernard River as an example of a notably under-sampled sub-basin (as indicated by diverse forms of evidence). With addition of future records, these dynamic tools will continue to illustrate taxonomic and spatial sampling deficiencies that in turn will help guide conservation planning.

Fatty acid esters of 3-monochloropropane-1,2-diol (3-MCPD) and glycidol are potentially carcinogenic and/or genotoxic processing contaminants that are formed during the process of edible oil refining. Because of their toxicological properties, the presence of these compounds in refined oils and foods containing these oils, particularly infant formula, poses a potential food safety concern. For this reason, recent research efforts have focussed on the development of methods for the analysis of MCPD and glycidyl esters in infant formula in order to estimate levels of exposure. This work presents occurrence data for 3-MCPD and glycidyl esters in 222 infant formulas purchased in the United States between December 2017 and January 2019. The results of this study show a wide range of contaminant concentrations across four different manufacturers, with average bound 3-MCPD concentrations ranging from 0.035 µg g−1 to 0.63 µg g−1 and average bound glycidol concentrations ranging from 0.019 µg g−1 to 0.22 µg g−1. The data suggest that manufacturers B and C source palm oil produced with mitigation measures, leading to reduced amounts of 3-MCPD and glycidyl esters in their infant formulas. Additionally, comparison with a previously published study in our laboratory of the occurrence of 3-MCPD and glycidyl esters in infant formula purchased in the U.S. between 2013 and 2016 revealed that, since 2016, contaminant concentrations have decreased in products produced by manufacturers A, B, and C, while contaminant amounts in formulas from manufacturer D have slightly increased.

Recently, presence of mineral oil in numerous foods has been detected. The analysis of mineral oil in food is convoluted since it comprises MOSH (saturated hydrocarbons) and variable amounts of mainly alkylated MOAH (aromatic hydrocarbons). Both fractions have a different toxicological profile and therefore they need to be assessed separately. For Belgium, occurrence data are available comprising concentrations of 217 food samples. These data were used, in combination with the 2014/15 Belgian Food Consumption Survey data, in a lower bound scenario to evaluate the dietary exposure of the Belgian population. Exposure to mineral oil was much lower compared to the results previously reported by EFSA and RIVM. The main contributors in Belgium were similar to previous studies (i.e. cereal products and oils), but an important additional contribution of non-alcoholic drinks was identified due to the presence of mineral oil in coffee. However, the concentration of mineral oil was determined from the dry product by applying a dilution factor with transfer rate of 100%, and not in the prepared coffee. This study gives an account of the dietary exposure of the Belgian population to mineral oil for the first time and reports the associated uncertainties.

The blue-green lobe Cnemidophorus lemniscatus, has a wide distribution in the Neotropical region, from Central America to South America through Colombia. A review of the occurrence data of the species reported in the Biodiversity Information System of Colombia (SIB), the World Biodiversity Information Service (GBIF), the database of the Museum of Natural History of the University of Nariño PSO-CZ, the Amphibian and Reptile Catalog of Colombia volume two, published articles and records taken in the field by the authors. A total of 2,516 records were obtained, determining 1,517 as valid, from which a distribution map of the species in Colombia was prepared and comparing with those previously reported, it was determined that C. lemniscatus is currently distributed in 96,87% of the departments of the national territory. An extension is made for 12 departments with records that are around 2,000 meters above sea level in the southwest of the country, this being an altitudinal extension compared to a maximum distribution reported up to 1,500meters above sea level., El lobito verdiazul Cnemidophorus lemniscatus, presenta una amplia distribución en la región Neotropical, desde Centroamérica hasta Suramérica pasando por Colombia. Se realizó una revisión de los datos de ocurrencia de la especie, reportados en el Sistema de Información sobre Biodiversidad de Colombia (SIB), el Servicio mundial de Información sobre Biodiversidad (GBIF), la base de datos del Museo de Historia Natural de la Universidad de Nariño PSO-CZ, el Catálogo de Anfibios y Reptiles de Colombia volumen dos, artículos publicados y registros tomados en campo por los autores. Se obtuvo un total de 2.516 registros, determinando como válidos 1.517, a partir de los cuales se elaboró un mapa de distribución de la especie en Colombia y comparando con los reportados previamente se determinó que C. lemniscatus actualmente se distribuye en el 96,87% de los departamentos del territorio nacional. Se hace una ampliaciónpara 12 departamentos con registros que se encuentran alrededor de los 2.000 msnm en el suroccidente del país, siendo esto una ampliación altitudinal en comparación con una distribución máxima reportada hasta los 1.500 msnm.

The Eyasi Plateau Paleontological Expedition (EPPE) Laetoli specimen database contains 13716 records of plant and animal fossils (ca. 28248 specimens) collected by EPPE field teams working at Laetoli, Tanzania between 1998 and 2005. This dataset is a digital version of the original hard-copy specimen catalog, and it documents the discovery, stratigraphic provenience and taxonomic diversity of Plio-Pleistocene fauna and flora in northern Tanzania between 4.4 Ma and >200 ka. Laetoli is renowned for the discovery of important hominin fossils, including the lectotype for Australopithecus afarensis, one of our early hominin ancestors, the first record of Paranthropus aethiopicus outside Kenya-Ethiopia, and an early record of our own species Homo sapiens. This database is one of the few publicly available palaeoanthropological fossil datasets and serves as an example for expanding open access to primary fossil occurrence data in palaeoanthropology. The taxonomic identifications appearing in this dataset are the original field identifications and are provisional. Any taxonomic analysis employing this dataset should refer to updated taxonomic identifications published by specialists., Measurement(s)fossilTechnology Type(s)digital curationFactor Type(s)taxonomy • geographic locationSample Characteristic - LocationLaetoli Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.10265336

ISI Document Delivery No.: JQ4GU Times Cited: 1 Cited Reference Count: 39 Jitaru, Petru Ingenbleek, Luc Marchond, Nathalie Laurent, Clemence Adegboye, Abimbola Hossou, Setondji Epiphane Kone, Abdoulaye Zie Oyedele, Awoyinka Dada Kisito, Chabi Sika K. J. Dembele, Yara Koreissi Eyangoh, Sara Verger, Philippe Le Bizec, Bruno Leblanc, Jean-Charles Guerin, Thierry Ingenbleek, Luc/0000-0001-9100-1460 Standard and Trade Development Facility (STDF)Science and Technology Development Fund (STDF) [STDF/PG/303] The project was funded by the Standard and Trade Development Facility (STDF) under grant STDF/PG/303. We would like to remember the late Marie Madeleine Gimou, the initiator of this study. Many thanks also to FAO staff (Renata Clarke, Markus Lipp, Caroline Merten, Blaise Ouattara, Jean Kamanzi, Sekou Hebie, and Alex Nyarko) who supported the Total diet study at various stages of its submission and implementation. The CPC management and various heads of national coordinating institutions of the participating countries, ABSSA (Benin), ANSSA (Mali), and NAFDAC (Nigeria), contributed to the success of this project. The scientific committee members, who provided guidance and validation of the methodology with their valuable experience of implementing total diet studies, are Katie Egan, Peter Furst, Adam Probert, Siswanto, and Christina Tlustos. We are extremely grateful for their support. 1 3 Pergamon-elsevier science ltd Oxford 1873-6750 B; International audience; This paper reports occurrence data related to 30 trace elements in food composite samples from a multi-regional Sub-Saharan Africa Total Diet Study. Herein, 2700 samples grouped in 225 food composite samples corresponding to 13 food groups: cereals, tubers, legumes, vegetables, fruits, nuts/seeds, meat, eggs, fish, milk/dairy, oil/fats, and beverages from eight locations in four countries, namely Benin (Littoral/Borgou), Cameroon (Duala/North), Mali (Bamako/Sikasso), and Nigeria (Lagos/Kano) were prepared as consumed, pooled, and analysed using a validated method based on inductively coupled plasma-mass spectrometry. The occurrence data for Al, As, Cd, Hg, and Pb as regulated by the Codex Alimentarius are discussed herein. Although the levels of As, Cd, Hg, and Pb were above the limit of quantification, they were below the maximum limits set by the Codex in most samples analysed. A distinct feature was observed for cereals and tubers, as they were mostly contaminated with Al and Pb. A pilot study regarding the impact of using artisanal cookware (made from recycled aluminium) on the contamination of food samples was performed. Relevant contamination with Al and Pb when cooking tomato samples from Cameroon and Nigeria using artisanal aluminium cookware was compared to that when cooked using stainless-steel.

Tetrabromobisphenol A (TBBPA) and Hexabromocyclododecanes (HBCDs) are two of the most used BFRs and they have cumulated in the environment. TBBPA and HBCDs in food were determined and their risks were assessed. The analytical method used was validated in different food categories, and the performance parameters were acceptable based on the criteria of AOAC. Fish and cephalopods were contaminated with TBBPA higher than other foods, and fish contained higher levels of HBCDs than other foods. α-HBCD was the predominant diastereomer in fish and meat and had strong correlations with HBCDs in fish and cephalopods. HBCDs accumulated easier than TBBPA in food. People were exposed to TBBPA from 0.125 ng kg−1 b.w. day−1 to 0.284 ng kg−1 b.w. day−1 and HBCDs from 0.353 ng kg−1 b.w. day−1 to 1.006 ng kg−1 b.w. day−1 via food and air. Food mainly contributed to exposure to TBBPA and HBCDs and vegetables were the main contributors for exposure to TBBPA and HBCDs in food. MOEs for the whole population were over 100, and the risks of exposure to TBBPA and HBCDs from food and the environment were of low concern to public health.

Feed samples are frequently contaminated by a wide range of chemically diverse natural products, which can be determined using highly sensitive analytical techniques. Next to already well-investigated mycotoxins, unknown or unregulated fungal secondary metabolites have also been found, some of which at significant concentrations. In our study, 1141 pig feed samples were analyzed for more than 800 secondary fungal metabolites using the same LC-MS/MS method and ranked according to their prevalence. Effects on the viability of the 28 most relevant were tested on an intestinal porcine epithelial cell line (IPEC-J2). The most frequently occurring compounds were determined as being cyclo-(L-Pro-L-Tyr), moniliformin, and enniatin B, followed by enniatin B1, aurofusarin, culmorin, and enniatin A1. The main mycotoxins, deoxynivalenol and zearalenone, were found only at ranks 8 and 10. Regarding cytotoxicity, apicidin, gliotoxin, bikaverin, and beauvericin led to lower IC50 values, between 0.52 and 2.43 &micro, M, compared to deoxynivalenol (IC50 = 2.55 &micro, M). Significant cytotoxic effects were also seen for the group of enniatins, which occurred in up to 82.2% of the feed samples. Our study gives an overall insight into the amount of fungal secondary metabolites found in pig feed samples compared to their cytotoxic effects in vitro.

Acrylamide is a contaminant that can form in certain plant-based foods during high-temperature cooking. From 2011-2015, the Food and Drug Administration conducted extensive sampling and analyses of acrylamide in foods, as a follow-up to surveys from 2002-2006. We compared acrylamide occurrence data and exposure estimates based on 2011-2015 data with data and exposure estimates from 2002-2006. Acrylamide levels in selected food categories generally did not decrease significantly in 2011-2015 compared with 2002-2006. However, significant decreases in acrylamide concentrations were observed for potato chips and crackers, which may be related to the availability and use of mitigation techniques for reducing acrylamide in foods. Mean dietary intake for those 2 years and older based on 2011-2015 data was 0.36 µg/kg bw/day, comparable to the 0.44 µg/kg bw/day reported by FDA in 2006. French fries and potato products, breakfast cereal, cookies, potato chips, and crackers continue to be the greatest contributors to dietary intake of acrylamide. Infant snack foods were identified as an important contributor to acrylamide intake relative to infant jarred foods. The continued presence of acrylamide in food suggests that manufacturers and governments should continue to pursue efforts to reduce acrylamide in foods that are important contributors to acrylamide intake.

Mitsubishi Aircraft Corporation is performing the full-scale fatigue testing (FSFT) for Mitsubishi Reginal Jet (MRJ) type certification. Main objective of this test is to show freedom from wide spread fatigue damage (WFD) during the life of aircraft and establish Limit of Validity (LOV). Prior to the test, WFD susceptible structures are defined based on the stress distributions and structure configurations, and they are fully covered by this test. Test duration of FSFT is 240,000 flights (3 × DSG of 80,000 flights). The flight-by-flight loading spectrum is newly designed for MRJ and its loads occurrence data was verified by flight test data. Furthermore, to reduce the test duration, low loads omission was applied based on the results of some spectrum verification tests. During fatigue test, scheduled inspection consistent with MRJ maintenance program is planned.

Tree pests can cause rapid and widespread damage, reducing the economic value of plants, production, in the case of fruit trees, and their role in mitigating climate change. There are several diseases that affect trees, including, for example, pine tree nematode (PWN), trunk fungal diseases, or Xylella fastidiosa (Xf).Mapping of diseased plants based on visual or automatic analysis of remote sensing data could be a useful support for in situ investigation planning. However, there is a clear need for better modeling methods to elaborate potential critical scenarios in order to early detect diseases (e.g. Xf) in host plants.Maxent (Maximum Entropy) has proved powerful when modeling species with available scarce presence-only occurrence data. The purpose is to predict potential distributions or explore expanding distributions. In this work we applied the Maxent model comparing local modeling results with worldwide cases towards a more comprehensive analysis of potential pest risk zones.

Taxonomic revisions contain crucial biodiversity data in the material examined sections for each species. In entomology, material examined lists minimally include the collecting locality, date of collection, and the number of specimens of each collection event. Insect species might be represented in taxonomic revisions by only a single specimen or hundreds to thousands of specimens. Furthermore, revisions of insect genera might treat small genera with few species or include tens to hundreds of species. Summarizing data from such large and complex material examined lists and revisions is cumbersome, time-consuming, and prone to errors. However, providing data on the seasonal incidence, abundance, and collecting period of species is an important way to mobilize primary biodiversity data to understand a species’s occurrence or rarity. Here, we present SpOccSum (Species Occurrence Summary)—a tool to easily obtain metrics of seasonal incidence from specimen occurrence data in taxonomic revisions. SpOccSum is written in Python (Python Software Foundation 2019) and accessible through the Anaconda Python/R Data Science Platform as a Jupyter Notebook (Kluyver et al. 2016). The tool takes a simple list of specimen data containing species name, locality, date of collection (preferably separated by day, month, and year), and number of specimens in CSV format and generates a series of tables and graphs summarizing: number of specimens per species, number of specimens collected per month, number of unique collection events, as well as earliest, and most recent collecting year of each species. number of specimens per species, number of specimens collected per month, number of unique collection events, as well as earliest, and most recent collecting year of each species. The results can be exported as graphics or as csv-formatted tables and can easily be included in manuscripts for publication. An example of an early version of the summary produced by SpOccSum can be viewed in Tables 1, 2 from Markee and Dikow (2018). To accommodate seasonality in the Northern and Southern Hemispheres, users can choose to start the data display with either January or July. When geographic coordinates are available and species have widespread distributions spanning, for example, the equator, the user can itemize particular regions such as North of Tropic of Cancer (23.5˚N), Tropic of Cancer to the Equator, Equator to Tropic of Capricorn, and South of Tropic of Capricorn (23.5˚S). Other features currently in development include the ability to produce distribution maps from the provided data (when geographic coordinates are included) and the option to export specimen occurrence data as a Darwin-Core Archive ready for upload to the Global Biodiversity Information Facility (GBIF).

Prediction of crime occurrences is of great significance for underlying criminal risk reduction and public security improvement. In all kinds of crime events, robbery is a more serious and noticeable one that threatens our everyday life. Different kinds of robbery events have different characteristics, and therefore their predictability varies. Previous studies mainly focus on forecast of all kinds of crime events at a fixed spatiotemporal scale, however, special predictability comparison between different robbery events at multiple scales is insufficient. In this paper, we use LSTM to capture long-short space-time dependencies of robbery events, and explore the predictability differences of three kinds of robbery crimes at different spatial and temporal scales. Daily crime occurrence data of Atlanta, US, from 2009 to 2017, and crime data of Baltimore, US, from 2011 to 2016, are respectively used in experiments, and the correlation coefficient between the predicted value and the true value is used to evaluate the model performance. Three robbery events, including commercial robbery, pedestrian robbery, as well as residence robbery, are compared. Experimental results show that the predictability of these three kinds of robbery events differs from each other and varies across different cities. In Atlanta, the commercial robbery is more predictable than that of the residential robbery and pedestrian robbery, with a higher correlation coefficient up to about 0.75. While in Baltimore, the predictability of residential robbery and commercial robbery achieves up to about 0.9, much higher than that of pedestrian robbery. In addition, experiments demonstrate different degree of predictability changes of three robbery events as the spatiotemporal scale changes, reflecting the different geographical distribution characteristics of the three robbery events.

Nickel (Ni) is a silvery‐white, hard, ductile metal existing in oxidation states; in biological systems, Ni2+ is the prevalent form. All analytical results used to estimate animal dietary exposure were reported as Ni', without providing information on specific chemical species. Considering the data provided by Member states, among FoodEx level 1 feed categories, the highest mean Ni levels were measured in ‘Minerals and products derived thereof’ (n = 72). High mean Ni concentrations were also observed in ‘Compound feed’ (n = 516), in particular in complementary feeds for fattening cattles, unspecified complementary feed and complementary feeds for fattening pigs. Within grains used as feed (n = 597), the highest mean Ni concentrations were measured in oats. In addition, Ni concentrations in hydrogenated vegetable oils/fats were reported by industry. Exposure to Ni in livestock and companion animals varied according to the animal species. When considering the diets with hydrogenated vegetable oils/fats based on the reported Ni concentrations, the mean exposures varied between 6.0 μg Ni/kg body weight (bw) per day in cats and 79 μg Ni/kg bw per day in laying hens and the high exposure levels varied between 11 μg Ni/kg bw per day in cats and 127 μg Ni/kg bw per day in rabbits. The mean exposure estimates considering the maximum concentration of Ni assumed from good manufacturing practice in hydrogenated vegetable oils/fats (50 mg Ni/kg) varied between 27 μg Ni/kg bw per day in cats and 255 μg Ni/kg bw per day in rabbits; for the high concentration scenarios, exposures varied between 30 μg Ni/kg bw per day and 307 μg Ni/kg bw per day in the same species. The estimated exposures to Ni are in line with the one reported in the 2015 EFSA opinion, using a worst‐case scenario. When estimating exposure with a realistic scenario, using the reported Ni concentration in hydrogenated vegetable oils/fats, the exposure of livestock and companion animals is lower (approximately from 1.5 to 6 times, depending on the species) than the 2015 assessment.

This study produced a dataset containing information on moss occurrences in the territory of Yugyd Va National Park, located in the Subpolar and Northern Urals, European North-East Russia. The dataset summarises occurrences noted by long-term bryological explorations in remote areas of the Subpolar and Northern Urals from 1943 to 2015 and from studies published since 1915. The dataset consists of 4,120 occurrence records. The occurrence data were extracted from herbarium specimen labels (3,833 records) and data from published literature (287 records). Most of the records (4,104) are georeferenced. A total of 302 moss taxa belonging to 112 genera and 36 families are reported herein to occur in Yugyd Va National Park. The diversity of bryophytes in this National Park has not yet been fully explored and further exploration will lead to more taxa. A total of 4,120 moss occurrences records in the territory of Yugyd Va National Park were published.

The genus Runcinioides is revised, including the redescription of R. argenteus Mello-Leitão, 1929 and R. litteratus (Piza, 1933). The male of R. litteratus is described and illustrated for the first time and Misumenops paranensis (Mello-Leitão, 1932) is here considered a junior synonym of R. argenteus. The known geographic distribution of both species is expanded with the inclusion of new occurrence data. Runcinioides pustulatus Mello-Leitão, 1929 and Runcinioides souzai Soares, 1942 are not related to the other species of the genus, and provisionally considered as incertae sedis.

1.Key features of the fossil record that present challenges for integrating palaeontological and phylogenetic datasets include (i) non‐uniform fossil recovery, (ii) stratigraphic age uncertainty and (iii) inconsistencies in the definition of species origination and taxonomy. 2.We present an r package FossilSim that can be used to simulate and visualise fossil data for phylogenetic analysis under a range of flexible models. The package includes interval‐, environment‐ and lineage‐dependent models of fossil recovery that can be combined with models of stratigraphic age uncertainty and species evolution. 3.The package input and output can be used in combination with the wide range of existing phylogenetic and palaeontological r packages. We also provide functions for converting between FossilSim and paleotree objects. 4. Simulated datasets provide enormous potential to assess the performance of phylogenetic methods and to explore the impact of using fossil occurrence databases on parameter estimation in macroevolution., Methods in Ecology and Evolution, 10 (6), ISSN:2041-210X, ISSN:2041-2096

This article found mistakes and misunderstandings regarding the collection of occurrence data of antibiotics in surface freshwater from the previous literature. These mistakes and misunderstandings were corrected to avoid the propagation of inaccurate information in the scientific literature.

This work presents occurrence data for fatty acid esters of 3-chloro-1,2-propanediol (3-MCPD) and glycidol in 98 infant formula samples purchased in the United States. These contaminants are considered potentially carcinogenic and/or genotoxic, making their presence in refined oils and foods a potential health risk. Recently, attention has focused on methodology to quantify MCPD and glycidyl esters in infant formula for risk-assessment purposes. Occurrence data for 3-MCPD and glycidyl esters were produced using a procedure for extracting fat from infant formula and an LC-MS/MS method for analysing fat extracts for intact esters. Infant formulas were produced by seven manufacturers, five of which use palm oil and/or palm olein in their formulations. In formulas containing palm/palm olein, concentrations for bound 3-MCPD and glycidol ranged from 0.021 to 0.92 mg kg–1 (ppm) and from

The present study reports the occurrence data of 3 macrofungi and 47 vascular plant taxa, collected in Zalaegerszeg-Botfa between 2006 and 2017. These new data provide valuable additional information to the distribution map of the studied species. The spatial and abundance information of both protected and non-protected species can contribute to the future biodiversity monitoring activities in order to asses and mitigate the human impact upon natural plant communities and semi-natural habitats.

Jelen közleményünk annak a sorozatnak a harmadik része, melynek célja a Magyarország edényes növényfajainak elterjedési atlasza térképeinek kiegészítése, főként aktuális előfordulási adatokkal. Ezúttal 558 edényes taxon előfordulási adatait közöljük az ország szinte egész területéről (mintegy 186 flóratérképezési kvadrátból), de legnagyobb számban az Északi-középhegységből. Az adatok között ritkább őshonos taxonok (például Marsilea quadrifolia, Salicornia prostrata, Stellaria palustris, Potentilla patula, Althaea cannabina, Lythrum tribracteatum, Ajuga laxmannii, Plantago schwarzenbergiana, Alisma gramineum, Gagea bohemica, G. szovitsii), ritka, vagy legalábbis adathiányos idegenhonos fajok (például Chorispora tenella, Thladiantha dubia, Senecio vernalis) mellett országosan elterjedt, de többé-kevésbé alulreprezentált fajok (például Scleranthus annuus, Vicia hirsuta, V. lathyroides) esetében is közöljük az Atlasz térképeihez képest újnak bizonyuló lelőhelyeket. A legközönségesebb fajok esetében a lelőhelyek részletezése nélkül csupán KEF-kódokat adunk meg.

Accurate avalanche occurrence data are of crucial importance for avalanche forecasting, since recent avalanching provides direct evidence on snowpack instability. We therefore explore how avalanche activity data obtained through seismic monitoring can be used for avalanche forecasting. By visually inspecting data from a seismic sensor deployed in an avalanche starting zone, we obtained three avalanche catalogues for two entire winters and one period of 10 days with intense wet-snow avalanche activity. Avalanche activity was clustered in time for all catalogues, and diurnal periodicity was clearly present during spring. In winter, when dry-snow avalanches predominantly release, rather weak long-term correlations on the order of several days were found between past and future avalanche activity. We investigated the performance of a simple model to predict future avalanches based on past avalanche activity. Model performance was better in spring than in winter, especially for very short time scales of up to 3h , and for time scales around 24 h. Furthermore, the performance of our very simple model was comparable to the performance of more sophisticated models to forecast wet-snow avalanche release based on meteorological input variables. While it is clear that for operational avalanche forecasting automatic avalanche detection still has to be developed, overall this work shows that avalanche activity data obtained through seismic monitoring would yield very valuable data for wet-snow avalanche forecasting.

Species range and climate change risk are often assessed using species distribution models (SDM) that model species niche from presence points and environmental variables and project it in space and time. These presence points frequently originate from occurrence data downloaded from public biodiversity databases, but such data are known to suffer from high biases. There is thus a need to find alternative sources of information to train these models. In this regard, expert-based range maps such as those provided by the International Union for Conservation of Nature (IUCN) have the potential to be used as a source of species presence in a SDM workflow. Here, I compared the predictions of SDM built using true occurrences provided by GBIF or iNaturalist, or using pseudo-occurrences sampled from IUCN expert-based range maps, in current and future climate. I found that the agreement between both types of SDM did not depend on the spatial resolution of environmental data but instead were affected by the number of points sampled from range maps and even more by the spatial congruence between input data. A strong agreement between occurrence data and range maps resulted in very similar SDM outputs, which suggests that expert knowledge can be a valuable alternative source of data to feed SDM and assess potential range shifts when the only available occurrences are biased or fragmentary.

Although it is known that emerging contaminants are widespread all over the globe, there is a gap of information about their distribution in some geographical areas, such as Latin America. The present bibliographic work reviews the available literature about the presence of organic emerging contaminants in Latin American freshwater and marine biota between 2002 and 2016 and includes 23 works from Argentina, Brazil, Chile, Colombia, Mexico, and Nicaragua. In particular, the present review provides an overview of the occurrence of continuously present contaminants such as pharmaceuticals, personal care products, and pyrethroid insecticides, as well as the new groups of persistent organic pollutants, the halogenated flame retardants and the perfluoroalkyl substances. A wide overview is provided, considering not only occurrence data but also effects and potential transfer through the food chain. Environ Toxicol Chem 2017;36:1716-1727. © 2016 SETAC.

Enchodontoidei are extinct marine teleost fishes with a long temporal range and a wide geographic distribution. We propose here to apply Parsimony Analysis of Endemicity (PAE), Track Analysis and Brooks Parsimony Analysis (BPA) to analyze the distributional patterns of these fishes during the Late Cretaceous. Matrices were built according to their respective geological age in the Late Cretaceous. The occurrence data of enchodontoids produced consistent results for the Cenomanian, Turonian, and Santonian. The generalized track found for the Cenomanian (GT 1) can be associated to oceanic currents, whereas for the Turonian the generalized tracks (GT 2, GT 3 and GT 4) were associated with eutrophication/sedimentation effects. During the Santonian, the third Oceanic Anoxic Event (OAE 3) promoted vicariant events that could explain the generalized track found therein (GT 5). The BPA recovered the area formed by Middle East and Europe, which is congruent with GT 1 and GT 5.

LIAS gtm, a new platform of the LIAS lichen information system, is presented. It allows for the visualization of phenotypic traits via geographic heatmapping of relative trait frequencies (RTFs) based on data derived from GBIF (occurrence data) and from LIAS light (taxon description data). The data are combined and referred to defined geographic areas of interest. Exemplarily, LIAS gtm provides distribution patterns of a selection of single, dual or multiple traits. The data are visualized for two lichen record hotspots, Scandinavia and Australia. Detailed technical information is provided on the platform web site itself.

The Flora-On dataset currently includes 253,310 occurrence records for the class Embryopsidae (vascular plants), comprising data collated via the platform http://flora-on.pt/ relating to observation records of vascular plants across mainland Portugal. Observations are uploaded directly to the database primarily by experienced botanists and naturalists, typically on a weekly basis, and consist of geo-referenced data points for species (or infraspecific taxa) along with their date of observation and phenological state. The Flora-On project aims to compile and make publicly accessible chorological, ecological, morphological and photographic information for the entire vascular flora of Portugal. The project’s website offers powerful query and visualization capabilities, of which we highlight the probabilistic bioclimatic and phenological queries which operate based on the empirical density distributions of species in those variables. Flora-On was created and continues to be maintained by volunteers who are Associate members of Sociedade Portuguesa de Botânica (Botanical Society of Portugal). Given its focus on research-grade and current data, the Flora-On project represents a significant contribution to the knowledge of the present distribution and status of the Portuguese flora.

Estimating absence locations of a species is important in conservation biology and conservation planning. For instance, using reliable absence as much as presence information, species distribution models can enhance their performance and produce more accurate predictions of the distribution of a species. Unfortunately, estimating reliable absence locations is difficult and often requires a deep knowledge of the species’ distribution and of its abiotic and biotic environmental preferences and tolerance. In this paper, we propose a methodology to reconstruct reliable absence information from presence-only information, and the conditions that those presence-only data have to meet to make this possible. Large species occurrence data collections (otherwise called occurrence datasets) contain high quality and expert-reviewed species observation records from scientific surveys. These surveys can be used to retrieve species presence locations, but they also record places where the species in their target list were not observed. Although these absences could be simply due to sampling variation, it is possible to intersect many of these reports to estimate true absence locations, i.e. those due to habitat unsuitability or geographical hindrances. In this paper, we present a method to generate reliable absence locations of this type for marine species, using scientific surveys reports contained in the Ocean Biogeographic Information System (OBIS), an authoritative species occurrence dataset. Our method spatially aggregates information from surveys focussing on the same target species. It detects absence locations for a given species as those locations in which repeated surveys (that included the species of interest in their target list) reported information only on other species. We qualitatively demonstrate the reliability of our method using distribution records of the Atlantic cod as a case study. Additionally, we quantitatively estimate its performance using another authoritative large species occurrence dataset, the Global Biodiversity Information Facility (GBIF). We also demonstrate that our approach has higher accuracy and presents complementary behaviour with respect to another method using environmental envelopes. Our process can support species distribution models (as well as other types of models, e.g. climate change models) by providing reliable data to presence/absence approaches. It can manage regional as well as global scale scenarios and runs within a collaborative e-Infrastructure (D4Science) that publishes it as-a-Service, allowing biologists to reproduce, repeat and share experimental results.

This article describes a method for detecting synecological optima of bryophytes and the possibility of their use in phytoindication of ecological conditions of the biotope. Bryophytes may take a significant part in plant communities, they have the ability to accumulate heavy metals, they can be used to determine the degree of the anthropogenic load and of the formation of forest communities. All this makes them excellent bioindicators, which can give an almost complete description of the plant community. But to do this it is necessary to know the environmental optima of mosses. At the moment, there are sparse data on the environmental characteristics of the bryophytes, it is not always clear how these characteristics were obtained. Currently, there are several ways to determine the environmental optima of the bryophytes based on the occurrence data and the projective cover of mosses. These methods use L.G. Ramenskiy's scales for vascular plants, these scales are extrapolated to bryophytes. Using our experience in defining synecological optima of lichen, we offer a graphical method for identifying ecological optimum of the bryophytes in which A.L. Bellegard's ecomorph scales are applied in the modification of N.M. Matveev (for the forest-steppe zone) and D.N. Tsyganov (for the coniferous-deciduous forest subzone). The essence of this method is the plotting of a graph of the quantitative characteristics of a particular moss depending on the environmental factors. For this you need to carry out phytoindication of the biotope community by using vascular plants and determine the average cover of moss or vitality of this moss.

A fire weather index (FWI) is developed using wildfire occurrence data and Automated Surface Observing System weather observations within a subregion of the northeastern United States (NEUS) from 1999 to 2008. Average values of several meteorological variables, including near-surface temperature, relative humidity, dewpoint, wind speed, and cumulative daily precipitation, are compared on observed wildfire days with their climatological average (“climatology”) using a bootstrap resampling approach. Average daily minimum relative humidity is significantly lower than climatology on wildfire occurrence days, and average daily maximum temperature and average daily maximum wind speed are slightly higher on wildfire occurrence days. Using the potentially important weather variables (relative humidity, temperature, and wind speed) as inputs, different formulations of a binomial logistic regression model are tested to assess the potential of these atmospheric variables for diagnosing the probability of wildfire occurrence. The FWI is defined using probabilistic output from the preferred binomial logistic regression configuration. Relative humidity and temperature are the only significant predictors in the binomial logistic regression. The binomial logistic regression model is reliable and has more probabilistic skill than climatology using an independent verification dataset. Using the binomial logistic regression output probabilities, an FWI is developed ranging from 0 (minimum potential) to 3 (high potential) and is verified independently for two separate subdomains within the NEUS. The climatology of the FWI reproduces observed fire occurrence probabilities between 1999 and 2008 over a subdomain of the NEUS.