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3,015 results for “occurrence”
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Sweden
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Swedish Food Agency</p> <p>OCC-CHEMMON2021 – Swedish Food Agency</p> <p>OCC-CHEMMON2022 – Swedish Food Agency</p> <p>OCC-CHEMMON2023 – Swedish Food Agency</p> <p>OCC-CHEMMON2024 – Swedish Food Agency</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Norway
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, and 2023, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2023 – Institute of Marine Research</p> <p>OCC-CHEMMON2023 – Norwegian Institute of Bioeconomy Research</p> <p>OCC-CHEMMON2024 – Institute of Marine Research</p> <p>OCC-CHEMMON2024 – Norwegian Institute of Bioeconomy Research</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Latvia
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Institute of Food Safety, Animal Health and Environment</p> <p>OCC-CHEMMON2021 – Institute of Food Safety, Animal Health and Environment</p> <p>OCC-CHEMMON2022 – Institute of Food Safety, Animal Health and Environment</p> <p>OCC-CHEMMON2023 – Institute of Food Safety, Animal Health and Environment</p> <p>OCC-CHEMMON2024 – Institute of Food Safety, Animal Health and Environment</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Slovakia
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – State Veterinary and Food Institute, National Agricultural and Food Centre – Food Research Institute</p> <p>OCC-CHEMMON2021 – State Veterinary and Food Institute, National Agricultural and Food Centre – Food Research Institute</p> <p>OCC-CHEMMON2022 – State Veterinary and Food Institute, National Agricultural and Food Centre – Food Research Institute; National Agricultural and Food Centre – Food Research Institute</p> <p>OCC-CHEMMON2023 – State Veterinary and Food Institute, National Agricultural and Food Centre – Food Research Institute; National Agricultural and Food Centre – Food Research Institute</p> <p>OCC-CHEMMON2024 – State Veterinary and Food Institute, National Agricultural and Food Centre – Food Research Institute; National Agricultural and Food Centre – Food Research Institute</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Austria
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Austrian Agency for Health and Food Safety</p> <p>OCC-CHEMMON2021 – Austrian Agency for Health and Food Safety</p> <p>OCC-CHEMMON2022 – Austrian Agency for Health and Food Safety</p> <p>OCC-CHEMMON2023 – Austrian Agency for Health and Food Safety</p> <p>OCC-CHEMMON2024 – Austrian Agency for Health and Food Safety</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Greece
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Hellenic Food Authority, Ministry of Rural Development and Food</p> <p>OCC-CHEMMON2021 – Hellenic Food Authority, Ministry of Rural Development and Food</p> <p>OCC-CHEMMON2022 – Hellenic Food Authority, Ministry of Rural Development and Food</p> <p>OCC-CHEMMON2023 – Hellenic Food Authority, Ministry of Rural Development and Food</p> <p>OCC-CHEMMON2024 – Hellenic Food Authority, Ministry of Rural Development and Food</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Malta
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in the ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Ministry for Health</p> <p>OCC-CHEMMON2021 – Ministry for Health</p> <p>OCC-CHEMMON2022 – Ministry for Health</p> <p>OCC-CHEMMON2023 – Ministry for Health</p> <p>OCC-CHEMMON2024 – Ministry for Health</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Ireland
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Food Safety Authority of Ireland, Marine Institute, Department of Agriculture, Food and the Marine</p> <p>OCC-CHEMMON2021 – Food Safety Authority of Ireland</p> <p>OCC-CHEMMON2022 – Food Safety Authority of Ireland</p> <p>OCC-CHEMMON2023 – Food Safety Authority of Ireland; Department of Agriculture, Environment and Rural Affairs</p> <p>OCC-CHEMMON2024 – Food Safety Authority of Ireland; Department of Agriculture, Environment and Rural Affairs</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Italy
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’. </p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Ministry of Health</p> <p>OCC-CHEMMON2021 – Ministry of Health</p> <p>OCC-CHEMMON2022 – Ministry of Health</p> <p>OCC-CHEMMON2023 – Ministry of Health</p> <p>OCC-CHEMMON2024 – Ministry of Health</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Finland
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Finnish Food Authority</p> <p>OCC-CHEMMON2021 – Finnish Food Authority</p> <p>OCC-CHEMMON2022 – Finnish Food Authority</p> <p>OCC-CHEMMON2023 – Finnish Food Authority; Finnish Customs</p> <p>OCC-CHEMMON2024 – Finnish Food Authority; Finnish Customs</p>
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Bulgaria
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<span><a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a></span>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2020 – Risk Assessment Center on Food Chain</p> <p>OCC-CHEMMON2021 – Risk Assessment Center on Food Chain</p> <p>OCC-CHEMMON2022 – Risk Assessment Center on Food Chain</p> <p>OCC-CHEMMON2023 – Risk Assessment Center on Food Chain</p> <p>OCC-CHEMMON2024 – Risk Assessment Center on Food Chain</p>
Occurrence Record Dataset from "Depth Matters for Marine Biodiversity"
<p>This is the final occurrence record dataset produced for the manuscript "Depth Matters for Marine Biodiversity". Detailed methods for the creation of the dataset, below, have been excerpted from Appendix I: Extended Methods. Detailed citations for the occurrence datasets from which these data were derived can also be foud in Appedix I of the manuscript.</p> <p><span>We first assembled a list of all recognized species of fishes from the orders Scombiformes</span><span> (Betancur-R et al., 2017)</span><span>, Gadiformes, and Beloniformes by accessing FishBase</span><span> (Boettiger et al., 2012; Froese & Pauly, 2017)</span><span> and the Ocean Biodiversity Information System (OBIS; </span><span>OBIS, 2022; Provoost & Bosch, 2019)</span><span> through queries in R</span><span> (R Core Team, 2021)</span><span>. Species were considered Atlantic if their FishBase distribution or occurrence records on OBIS included any area within the Atlantic or Mediterranean major fishing regions as defined by the Food and Agriculture Organization of the United Nations (FAO Regions 21, 27, 31, 34, 37, 41, 47, and 48;</span><span> FAO, 2020)</span><span>. The database query script can be found on the project code repository (</span><a href="https://github.com/hannahlowens/3DFishRichness/blob/main/1_OccurrenceSearch.R"><span>https://github.com/hannahlowens/3DFishRichness/blob/main/1_OccurrenceSearch.R</span></a><span>). We then curated the list of names to resolve discrepancies in taxonomy and known distributions through comparison with the Eschmeyer Catalog of Fishes</span><span> (Eschmeyer & Fricke, 2015)</span><span> , accessed in September of 2020, as our ultimate taxonomic authority. The resulting list of species was then mapped onto the Global Biodiversity Information Facility’s backbone taxonomy</span><span> (Chamberlain et al., 2021; GBIF.org, 2020a)</span><span> to ensure taxonomic concurrence across databases (Supplementary Table 1). The final taxonomic list was used to download occurrence records from OBIS</span><span> (OBIS, 2022)</span><span> and GBIF</span><span> (GBIF.org, 2020b)</span><span> in R through <em>robis</em></span><span> (Provoost & Bosch, 2019)</span><span> and <em>occCite</em></span><span> (Owens et al., 2021)</span><span>. </span></p> <p><span><span> </span>For each species, duplicate points were removed from two- and three-dimensional species occurrence datasets separately, and inaccurate depth records were removed from 3D datasets (all records with and without depth information were retained for the 2D dataset). Depth records were based on the “depth” field in both the GBIF and OBIS datasets, which define the field as “depth below the surface in meters”. We chose this value over incorporating information from “minimumDepthInMeters” and “maximumDepthInMeters” because more records contained information from the “depth” field than either of the two other fields (although when these fields were both supplied, “depth” appears to have been often, but not always, derived by calculated the mean between minimum and maximum depth). We also initially included the “depthAccuracy” field from both datasets but did not ultimately use this field as it was not complete enough to be useful. Instead, we determined depth inaccuracy based on extreme statistical outliers (values greater than 2 or less than -2 when occurrence depths were centered and scaled), depths that exceeded bathymetry at occurrence coordinates, and occurrence depths far outside known depth ranges obtained from FishBase, Eschmeyer’s Catalog of Fishes, and/or congeneric depth ranges in the dataset. Once the resulting data were mapped and curated to remove records with putatively spurious coordinates, under-sampled regions and species were augmented with data from publicly available digital museum collection databases not served through OBIS or GBIF, as well as a literature search. Finally, for datasets with more than 20 points remaining after data curation, occurrence data were downsampled to the resolution of the environmental data; that is, to 1 point per 1 degree grid cell in the 2D dataset, and to one point per depth slice per 1 degree grid cell in the 3D dataset. </span></p> <p> </p> <p>References:</p> <p>Betancur-R, R., Wiley, E. O., Arratia, G., Acero, A., Bailly, N., Miya, M., Lecointre, G., & Ortí, G. (2017). Phylogenetic classification of bony fishes. <em>BMC Evolutionary Biology</em>, <em>17</em>(1), 162. <a href="https://doi.org/10.1186/s12862-017-0958-3">https://doi.org/10.1186/s12862-017-0958-3</a></p> <p>Boettiger, C., Lang, D. T., & Wainwright, P. C. (2012). rfishbase: exploring, manipulating and visualizing FishBase data from R. <em>Journal of Fish Biology</em>, <em>81</em>(6), 2030–2039. <a href="https://doi.org/10.1111/j.1095-8649.2012.03464.x">https://doi.org/10.1111/j.1095-8649.2012.03464.x</a></p> <p>Chamberlain, S., Barve, V., McGlinn, D., Oldoni, D., Desmet, P., Geffert, L., & Ram, K. (2021). <em>rgbif: Interface to the Global Biodiversity Information Facility API</em>. <a href="https://CRAN.R-project.org/package=rgbif">https://CRAN.R-project.org/package=rgbif</a></p> <p>Eschmeyer, & Fricke, W. N. &. (2015). Taxonomic checklist of fish species listed in the CITES Appendices and EC Regulation 338/97 (Elasmobranchii, Actinopteri, Coelacanthi, and Dipneusti, except the genus Hippocampus). <em>Catalog of Fishes, Electronic Version</em>. Accessed September, 2020. <a href="https://www.calacademy.org/scientists/projects/eschmeyers-catalog-of-fishes">https://www.calacademy.org/scientists/projects/eschmeyers-catalog-of-fishes</a></p> <p>FAO. (2020). <em>FAO Major Fishing Areas</em>. United Nations Fisheries and Aquaculture Division. <a href="https://www.fao.org/fishery/en/collection/area">https://www.fao.org/fishery/en/collection/area</a></p> <p>Froese, R., & Pauly, D. (2017). <em>FishBase</em>. Accessed September, 2022. www.fishbase.org</p> <p>GBIF.org. (2020a). <em>GBIF Backbone Taxonomy</em>. Accessed September, 2020. GBIF.org</p> <p>GBIF.org. (2020b). <em>GBIF Occurrence Download</em>. Accessed November, 2020. <a href="https://doi.org/10.15468">https://doi.org/10.15468</a></p> <p>OBIS. (2020). <em>Ocean Biodiversity Information System. Intergovernmental Oceanographic Commission of UNESCO</em>. Accessed November, 2020. www.obis.org</p> <p>Owens, H. L., Merow, C., Maitner, B. S., Kass, J. M., Barve, V., & Guralnick, R. P. (2021). occCite: Tools for querying and managing large biodiversity occurrence datasets. <em>Ecography</em>, <em>44</em>(8), 1228–1235. <a href="https://doi.org/10.1111/ecog.05618">https://doi.org/10.1111/ecog.05618</a></p> <p>Provoost, P., & Bosch, S. (2019). <em>robis: R Client to access data from the OBIS API</em>. <a href="https://cran.r-project.org/package=robis">https://cran.r-project.org/package=robis</a></p> <p>R Core Team. (2021). <em>R: A Language and Environment for Statistical Computing</em>. <a href="https://www.R-project.org/">https://www.R-project.org/</a></p>
JSTOR plant type specimens linked to GBIF occurrences
<p>A mapping between URLs for type specimens in JSTOR Global Plants and the corresponding occurrence in the Global Biodiversity Information Facility (GBIF).</p><p>Guide to fields:</p><ul><li><strong>doi</strong>: JSTOR identifier</li><li><strong>code</strong>: Barcode:</li><li><strong>gbif</strong>: GBIF occurrence id</li><li><strong>occurrenceUrl</strong>: URL to specimen in original herbarium database</li><li><strong>occurrenceID</strong>: occurrenceID stored in GBIF</li><li><strong>title</strong>: Title of specimen in JSTOR</li><li><strong>resource_type</strong>: Type of resource</li><li><strong>canonical</strong>: Canonical taxonomic name</li><li><strong>stored_under_name</strong>: Taxonomic name specimen is stored under</li><li><strong>type_status</strong>: What kind of type</li><li><strong>family</strong>: Family plant species belongs to</li><li><strong>collector</strong>: Collector</li><li><strong>date</strong>: Date of collection</li><li><strong>country</strong>: Country of collection</li><li><strong>herbarium</strong>: Herbarium where specimen is stored</li><li><strong>names</strong>: All taxonomic names associated with specimen as JSON array</li><li><strong>url</strong>: JSTOR URL</li><li><strong>thumbnailUrl</strong>: URL to thumbnail of image in JSTOR</li></ul>
EFSA Opinion Update of risks for animal health related to the presence of ochratoxin A (OTA) in feed: Annexes on Occurrence data in feed submitted to EFSA
<p>Annexes to EFSA's Update Opinion on the risks for animal health related to the presence of OTA in feed. Annex B includes the occurrence data in feed extracted from EFSA Data Warehouse for the period from 2012 to 2021. Annex C contains the occurrence data expressed in dry matter following analysis and cleansing of the dataset as detailed in EFSA's Opinion. Annex D lists the samples of 'Compound feed' and other feed materials except forage expressed in whole weight. The number of samples across some of the feed categories differ among the two annex C and D because in few cases the moisture content was not reported (and no assumption on the moisture could be done), precluding the conversion of the analytical results to either whole weight or dry matter. </p>
Fig.ç4.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, leg 2, dorsal view; B, leg 3, dorsal view; C, leg 4, dorsal view; D, leg 5, ventral view. Scale bars: 0.1 mm. in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species
Fig.ç4.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, leg 2, dorsal view; B, leg 3, dorsal view; C, leg 4, dorsal view; D, leg 5, ventral view. Scale bars: 0.1 mm.
Fig.ç3.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, maxilla, dorsal view; B, maxilliped, dorsal view; C, sternal furca, dorsal view; D, leg 1, ventral view; E, exopod of leg 1 enlarged, ventral view. Scale bars: 0.1 mm. in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species
Fig.ç3.C aligus longiramus sp. nov., holotype, female (KMNH IvR 500,511). A, maxilla, dorsal view; B, maxilliped, dorsal view; C, sternal furca, dorsal view; D, leg 1, ventral view; E, exopod of leg 1 enlarged, ventral view. Scale bars: 0.1 mm.
Fig.ç2.A, Caligus latigenitalis Shiino, 1954, male (KMNH IvR 500, 510), habitus, dorsal view; B–F. Caligus longiramus sp. nov., holotype, female (KMNH IvR 500, 511): B, habitus, dorsal view; C, caudal rami, dorsal view; D, antennule, ventral view; E, antenna, postantennal process, and maxillule, ventral view; F, mandible. Scale bars: 1 mm (A, B); 0.1 mm (C–F). in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species
Fig.ç2.A, Caligus latigenitalis Shiino, 1954, male (KMNH IvR 500, 510), habitus, dorsal view; B–F. Caligus longiramus sp. nov., holotype, female (KMNH IvR 500, 511): B, habitus, dorsal view; C, caudal rami, dorsal view; D, antennule, ventral view; E, antenna, postantennal process, and maxillule, ventral view; F, mandible. Scale bars: 1 mm (A, B); 0.1 mm (C–F).
Fig.ç1.C ollection sites of pelagic caligids including 3 stations in Japanese waters (St. 2–4, 2010) and 1 station in the Gulf of ffiailand (St. 1, 2006). in Occurrence of Caligid Copepods (Crustacea) in Plankton Samples Collected from Japan and Ŋailand, with the Description of a New Species
Fig.ç1.C ollection sites of pelagic caligids including 3 stations in Japanese waters (St. 2–4, 2010) and 1 station in the Gulf of ffiailand (St. 1, 2006).
Figure 2 in Occurrence of Quesada gigas on Schizolobium amazonicum trees in Maranhão and Pará States, Brazil
Figure 2. Exit holes of Quesada gigas (A), plants of Schizolobium amazonicum with symptoms of attack by this insect (B) and trap to capture nymphs (C).
Data from: Integrated species distribution models to account for sampling biases and improve range wide occurrence predictions
<p><strong><span>Aim</span></strong></p> <p><span>Species distribution models (SDMs) that integrate presence-only and presence-absence data offer a promising avenue to improve information on species' geographic distributions. The use of such 'integrated SDMs' on a species range-wide extent has been constrained by the often-limited presence-absence data and by the heterogeneous sampling of the presence-only data. Here, we evaluate integrated SDMs for studying species ranges with a novel expert range map-based evaluation. We build a new understanding about how integrated SDMs address issues of estimation accuracy and data deficiency and thereby offer advantages over traditional SDMs.</span></p> <p><strong><span>Location</span></strong></p> <p><span>South and Central America.</span></p> <p><strong><span>Time period</span></strong></p> <p><span>1979-2017.</span></p> <p><strong><span>Major taxa studied</span></strong></p> <p><span>Hummingbirds.</span></p> <p><strong><span>Methods</span></strong></p> <p><span>We build integrated SDMs by linking two observation models – one for each data type – to the same underlying spatial process.</span> <span>We validate SDMs with two schemes: i) cross-validation with presence-absence data and ii) comparison with respect to the species' whole range as defined with IUCN range maps. We also compare models relative to the estimated response curves and compute the association between the benefit of the data integration and the number of presence records in each data set.</span></p> <p><strong><span>Results</span></strong></p> <p><span>The integrated SDM accounting for the spatially varying sampling intensity of the presence-only data was one of the top-performing models in both model validation schemes. Presence-only data alleviated overly large niche estimates, and data integration was beneficial compared to modelling solely presence-only data for species that had few presence points when predicting the species' whole range. On the community level, integrated models improved the species richness prediction.</span></p> <p><strong><span>Main conclusions</span></strong></p> <p><span>Integrated SDMs combining presence-only and presence-absence data are successfully able to borrow strengths from both data types and offer improved predictions of species' ranges. Integrated SDMs can potentially alleviate the impacts of taxonomically and geographically uneven sampling and to leverage the detailed sampling information in presence-absence data.</span></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.