20230425 16565700 1.0 ISO19139 007 ENBS_Sample_Locations -1321907.353000 -253181.326800 576846.258700 1781234.229900 1 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) Albers_Conic_Equal_Area <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.1.0'><WKT>PROJCS[&quot;Albers_Conic_Equal_Area&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Albers&quot;],PARAMETER[&quot;false_easting&quot;,0.0],PARAMETER[&quot;false_northing&quot;,0.0],PARAMETER[&quot;central_meridian&quot;,-154.0],PARAMETER[&quot;standard_parallel_1&quot;,55.0],PARAMETER[&quot;standard_parallel_2&quot;,65.0],PARAMETER[&quot;latitude_of_origin&quot;,50.0],UNIT[&quot;Meter&quot;,1.0]]</WKT><XOrigin>-13752200</XOrigin><YOrigin>-8948200</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem> 150000000 5000 20230425 16571000 FALSE 20230425 16571000 <p>NOAA Fisheries and its partners conduct fisheries-independent surveys in 8 regions in the US (Northeast, Southeast, Gulf of Mexico, West Coast, Gulf of Alaska, Bering Sea, Aleutian Islands, Hawai’i Islands). These surveys are designed to collect information on the seasonal distribution, relative abundance, and biodiversity of fish and invertebrate species found in U.S. waters. Over 900 species of fish and invertebrates have been identified in these surveys.</p> Eastern and Northern Bering Sea Sample Locations 2023-04-01T00:00:00 vector digital data Timothy J Haverland NMFS Office of Science and Technology GIS App Developer tim.haverland@noaa.gov 1315 East West Highway Silver Spring MD 20910-3282 US 301-427-8137 301-713-4137 Eastern and Northern Bering Sea Sample Locations 2010 to 2022 -177.880044 -161.598786 66.024291 59.506421 1 2010-01-01T00:00:00 2022-12-31T00:00:00 Melissa Ann Karp NMFS/OST/AMD Fisheries Science Coordinator melissa.karp@noaa.gov 1315 East West Hwy, Bldg. SSMC3 Silver Spring MD 20910-3282 US 301-427-8202 Eastern and Northern Bering Sea2010 to 2022distributionseasonal distributionfishinvertebratesclimate changefishery-independent surveysecological dynamicsoceansbiosphereearth sciencespecies/population interactionsaquatic sciencesfisheriesrange changes distribution, seasonal distribution, fish, invertebrates, climate change, fishery-independent surveys, ecological dynamics, oceans, biosphere, earth science, species/population interactions, aquatic sciences, fisheries, range changes These data were created as part of the DisMAP project to enable visualization and analysis of changes in fish and invertebrate distributions. This survey points layer provides information on both the locations where species are caught in several NOAA Fisheries surveys and the amount (i.e., biomass weight catch per unit effort, standardized to kg/ha) of each species that was caught at each location. Information on species distributions is of paramount importance for understanding and preparing for climate-change impacts, and plays a key role in climate-ready fisheries management. The Sample Locations were produced by NMFS OST in partnership with OceanAdapt at Rutgers University <p>***No Warranty*** The user assumes the entire risk related to its use of these data. NMFS is providing these data "as is" and NMFS disclaims any and all warranties, whether express or implied, including (without limitation) any implied warranties of merchantability or fitness for a particular purpose. No warranty expressed or implied is made regarding the accuracy or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. It is strongly recommended that careful attention be paid to the contents of the metadata file associated with these data to evaluate dataset limitations, restrictions or intended use. In no event will NMFS be liable to you or to any third party for any direct, indirect, incidental, consequential, special or exemplary damages or lost profit resulting from any use or misuse of these data.</p> Esri ArcGIS 13.1.0.41833 Eastern Bering Sea, Northern Bering Sea, Alaska 2010 to 2022 dataset /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCACFAMgDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3Gs+z trnTNMkWS5m1CddzgvhWc9Qo7D0qe8tDd+Ti4mh8qUSfumxux/CfUUy/u57X7P5Fm9z5syxvtbHl qerH2FbHIRS6tDZ6INS1KNrNAgaVH+YoTxg4zU8KW9zpii0Ijt5oso0Y24DDqPTrTdRvLC1gRNQe NY53EKq4yHY8AYpupaYuoaabJLia0QlcPbnawCkHAPbpigCIWV5p+gi006YTXUSbY5Lskhjn+Iir X2hrbTftN9tV44t83l5YAgZOO5qHUv7Sjs4xpYgecOob7QTgp/F071JqGoWum2nn3smyIsqE7S3L HAHHuaNgGw3dlPpaXSssVrOuQX+T73r6E5pbLTbfTdO+x2C+RGAdnJbBPfnrSajZaffWQt9Qiie2 LLhJDgZ7U++iun06WLT5Y4LkriJ3Xcq/h9KAItNivbPSI01Cf7XdopLyIuN5ycYH5VFY6uX0Malq UP8AZ4AJkWU42DOBn9KszzXFnpTzGM3VxFFuKRjb5jAdB6ZqKa/tF0MX2poLe3MavKk4zszjgj6k UAWLOW1ubdbq0KNFMN4dBw3vUOm6ZHppuiksshuZ2nYyHOCew9uKnaGGayMK/LA6bR5Z24UjtjpU SWRtdJFlaSshSLy4pJDuIOMAn1oAXT7e6topVu7s3LNKzIxULtUnhePSk027ubuKV7qya0ZZWRFZ w25QeG49aS3S5sNGRZ5HvbmGH5mAwZWA/rT473Glre3UTW/7rzJI25KcZI49KAGabqNrqUUs9qG2 pK0blk2ksvB+tR6faaWLy71CwWJp522Tyxvuyy9jzgYq1a3EF3ZR3MGDBMgdSRjIPOaZYWNnYW5j sYkjhdzIQnQk9TQBDZafNa6lf3Ul5LMlyylIm+7EAMYHPc81oVT0ywOnWrQtcy3BMjPvlOTyc4+g q2SFGTQtEAE4Gaos2e9TM5Y+1MIG05Fc1WalojaMWgWnqMsAKZGCQMVbji2DJ6moii0P7e1MeVUH PGabLKqL1/8Ar1VCvLyTxTc7DuWCdze1FOUDbRUPuIq3dlNcX1lcR3kkKW7szxKOJQRjBoM97/bA g+zKbEwljPu5D5+7j6U9bWYam90byUwtGEFsQNgOfvZxnP40JdStqUlqbSVYkjDi4JGxif4R3zXc cw25nsDe21ncmNriQmSBHXJJXkkfSkv7KW8e1Md3LbrDMJHEf/LQAH5T7U+K5srq9ljjeOS5tTh8 DJjz2zSCyf8AtY3pupSnleWLfPyA5zu+tAEeoz6hDPZLY2qTJJMFuGZseXH3I96mu7q0t/JS6dR5 0gSMMM7m7Co1k1D+2XjaKL+z/JBWTPz+ZnkfTFKt/aS6nJp4bdcwoJWUr90Hoc+tADr/AE601OKO O7iEixyLKgJ6MOhqHVLfUp0hOm3kVu6PucSxbxIPTrx9addada315bTyPIJrRtyeXKV69mA6j60T R6i2r27xTxLYKjedGUy7N2wewoYC397PZJbmOylumllWN/Kx8gPVjnsKXULuwt444tQkiWO4cRqs oyHbsKQ6hjWRp32eYkw+d5235Bzjbn1oludOn1BdPmeF7tVEyxOMkD+8KAF1LTodU02WxmaRIpAA TE21hggjBHTpSX8F4dMaHTZ0iuQFCSSjcAARnPrxmk1DSotRntJnmnje1l81PKfbk+h9RRqEeoyS 2hsZ4okWXNwJFzvTHQe9DAfeXU1lZCVbaS6lBVTHCBkknBPPbvRf39vp1ibm7JWLIUjGTknAGPxp mo309lJaiGxlulml2SGMj90MfeNJqGq2FhcWlteSBXu3KRArkEjH5dRRcCe6FsbJ47hljgddhy20 YPGM9qbHYQwaaLC23QxLH5abTyo9QT3puo21jewJa36o8cjgqjtjcw5GPyo1C0mvFgWG8e28uZZG 2Dl1HVfoaAJbK2FlYwW3mvIIkCb5DlmwOpPrRKctjtinzH5duDyO1VwmB1OayqysrGkFrcWms3y/ WnEnpSEEiudo1ERtv8WKVp2yMnIFMYE9BTSpHWpbaQrsk3eY+f0qeMZQgevSq0YyeMVaaRI1GOKc fMaDJHGOaKq/aJRITsVk7c4NFFhXQukafJpmnpbS3s12yknzZjljk9KXT76W9Nz5lnNbCKZo183/ AJaAfxD2NKDcWGkZcve3EMWSQAGlYD09TUljcvd2MVzJbyWzOu4xSfeT2Ndy7HOJaXNndNO1o8Ts khSUp1DjqD71SSSLSdQdbvUJJG1C4/0eJxnZx90e1XbL7HJCbiyEJjnO8yRAYc+uR1qjapDY3MNr fXqXN/LLLLbeYuGCnJwvoAOKQFywkvpBOb2GKLErCIRtncnYn3qSCa2ufMeB45CGKOyYPI6g/Ssq x/tEsdW1SRrcJAytZp8yjDE7/c4xT7O8+2LZXWix27afNI5uCRsYHnkD13dc0JgW7fSrS31KfUIl ZbidQsp3nDY6HHTNOtob1L+7kuLhHtn2+REq4KADnJ75pt1qUNrqVnZOkxkui2xlTKjaMnce1O02 K9htNuoTpPPvY7kXAxngflQhjra9+03V1B5E0f2dgu91wr5Gcqe4plvPp95fTmAxSXVq3lSsF+ZC RnGaNNv31CGSR7Oe12SMgWYYLAfxD2NS2klnN5slo0TZkKyNHjlhwc470xELaajayupfaJw6xeV5 Qf8AdkZzkj1pfL1D+2DIZof7O8nAi2/P5meufTFLZ6ZBZXV3cRGUvdOHkDyFgCB2B6UWkd+l5eNd XEUlu7L9mREwyLjnce/NFgGfbbr+3PsRsX+y+T5gus/LuzjbilfULVtZTTHjZp/J89SUyoGcdfWn 2l3LcXF1HJZywLC4VHcjEoxnK+1FtfQXV5dQRo4ktmCOzJgHIzwe9ADLzT7HULy1kuAGntH82LD4 Kk8ZxVY+H4Dri6sLm6EwYnYJPkIKhcY9OM/Wp10zTm1ltTSNftyp5Turnp6EZxT1sJBrDX5vJyhi 8sW2R5Y5zux60reQFxgSpA61VPHFW6hkjUAnnNTUjcuErER/WlpB6mlrlZsVpL2OKUxurZHcDNL9 rgZthfDdMEU+S2hmOZI1Y+pHNRtYwkDAZcdNrGgBbe4jL5Rg+B0BqV2Mh6BRUUFuIFIB3E9WbGam I4yTU20sKwgVVGSaKaF3E56UUJAOvbuawsVlW2kvJdyIUiGCckAn2A61NdXdtZxK91KkaOwjBfoS TgCoJL64TWYbJbCR7eSNna6DDahHRSPepp57QTRW1w8XmSnMcb4yxHPA9q7znF+ypDZG2tAtsoQr H5agBPcDpVFbKaz02Od411LVLaAqkzKFaQ9xntmp9VsZtQtUhhuntiJUdmTqyqwJX8cUajc3lsbZ bOy+0mSVUkO/aI07sfWgCjdSW+mSDXtTu5rVTAsMlvv3RKxPoB1ycZq7JHLcytB5cQ02WA5dGKvu PpjoMd6qrBZaTeTNd30kn9pTqIorhtyhuyoO1PayudVsLi01ZViUz5jNtIVLIrArk9unIpAGneRY rJo1rJNJNaxBlM+W4OcfN3q1HNc2uk+ffqr3EcZaRYFJBI7KKZqTXTWM0OmTwxXwA8tphleozn8M 0+7vXsbOOV7eW4csqMtuu4gnv9KewEi3sX9ni9lDQxeX5rCQYKDGeRTNOSy+yLNYRxrBP++BjXAb dzu/GnX1xZ29ozXzxpA5CN5nQ7uMfjSz2cU2nyWS5hiaMxjyvl2jGOPSgCPTdPXTbZoVuJ5wXL7p 33Nz2+lM0z+01tJDqhgafexUQAgbew570slrcwaMbWwmAuI4tkMk3zcgYBb1p1zPd2ektMtuby6j jBMUZ2+Y3fGelADdNv5r20ea5sZrJlYjZMQSQO/HapNP1Gz1S2NxZTrNEGKFl9R1FJc6hFZaW9/d hookjDyA8lfapbYQfZUa2RFhcblCLgYPPShAQWWnWdncXVxbIBJdPvmbcTkgY/CmaZpj6a90Wvri 5SaXzEWZt3lew9qm0/SbXTI5I7KPy0lkMjAsW+Y9epNXTGMdTU80S1TkMpDhuKUgg4NC4Dc9Kbel 0JLWzGtCuM9MVEFViQvP1olfe/HQU0EjoawclfU1a7CUhpaSsigJAHNR5Ln2qTbnrzRwKTQAOBRS ZFFAEjXLLfpb/ZpSjRlzOANikH7p96qvqFhLr6aayLJexwmdSVB2LnHXsTV7dlcVEkUf2gy+WgmI 279o3Y9M16HKzl5hktpcPqdvdJeyJBGrLJb7QVkyODnqCDQ13OurR2gs5DA8Rc3IPyqwI+U+5p0U N2uoTyyXQe1dVEUOwAoR1O7vmmQXk8up3NrJYyxRRBTHcEgrLnrj6VIxz3Vk+pJYyNG12qeckbDL Bem4elNvdNhvrm0mkkmR7WTzEEchXJ6YOOo9qLe70+61C4jgeJ7u2wkuF+ZAeQM+lKdNgOrjUt0n niHydu87Nuc/d6Z96NwIdSt9RmurRrKaCOBXzcB0yzr6A9qeZltby2haKYtcFlGwFkTAJyT2p+L/ APtbdvh/s/ycbcHf5mev0xSi/VtWbTxDNuWISmXZ8nXGM+tADbyfTzcW1jeNC0twxMMMgB3lecge 3WnajYLqNusLTSwhZFkzE2CcHOPpTXOnT6rHG/kvf26F0BwXjVuCR6A0XWnLdahZXhuJozaliI0b CvuGPmHejcB2oLfNFELB4lk81d5kGRsz82Pem6lfS2EcLRWc100kyxlYv4QerH2FJcRak2qWj29x Cliob7RGyZdzj5cHtTp7yeLUrW1SylkimVy9wpG2LGMA/XP6UAGo3llaQIL9kEU8iwgOuQzN0GKt ZWNQMhR0Haqs93Yi+gsJ5IjcyAyRROMk7e4+lM1TT7LVI4bW8Y8SCZFWTaSVOfxFAGgGK/Snbxnr VO9t5LqARxXUlswcNvjxk4PTnsag1ie+tbAzadbLczq65jJ6rnnHviplFblqbRosctx6UlIpyoJB GR0PalqkrKxLd3cgkXa2QODTKnkTcOKj8t/SuedN30NYyVtRlBHA4+tSCE9zTnXEeB25pKnK12Pn RDSH60uD6U1s5A7etZlAQccUUqIzndkBaKfKxgZCCeablnBAYqSMAjqPemAepzUoAPI7V6bSPOTb JLKGS3s4oZp2nkRcNK4ALH1OKbZXMl1Czy2stuRIyBZMZIBwG+h60+WVobSSVYmlZELCNerEDoKh gvt2kpfXkLWn7vzJI5DzHxkg1jsb9BbGawvBJd2Rhk3sUeWMD5ivGCe+KLTT4bO5u7iN5Ge6cO4d 8gEDHA7UuntZyWUctgIvs0g3oYgApzzniksLCLTbU28DOV3M+ZGLHJOetIBtkNRF1efbWgNv5g+z eWDuC453e+adaXv2ue6i+zzRfZ5PL3SLgScZyvqKj0r+0k04HVTE10GYnyRwRnj8cVJpl+NSsUuh BNAHJ+SZdrDBx0oQDbddOn1Ce6t1he7j/wBHlkUDcMc7SfxBpV09V1d9Q8+cs0Qi8ov+7ABzkD1p bFbFkkubEQlZ3LvJFj526ZJHU8YpLKwWymu5RNLIbmXzCJGyE4AwPQcUANVdR/tp2aSL+zfJAVAP n8zPXPpinJeyvq0tmbSVYo4w4uD9xif4R70lh/aPnXn24xeX53+jeX18vA6++c060u5bme6jktJY Fhk2I79JRjqPagBPtGnyat9nLQtqEUW8Lj51QnGc9hnFJLptlcarBfyJuu7dCsbbj8obrxTrS5sb yWeW1eKSSNvJldOoI/hJ9qbHp9qNWl1JCxuGiELYf5cA56etG4DLvTDdapY3wu54vsu790hwsm4Y +b17U66fUV1SxW2jjaybf9pZvvLwNuP1py2Ug1d703UpjaERi3z8gOc7vrSqL7+1XLGL7B5Q2AD5 9+efwxQA24v5IdTtbRbOeRJgxadR8kePX60651G3tLu1tpSwkumZY8KSMgZOT2pkd9M+tTWJtXWG OFZBOfusSSCv1GP1pYtSt59Vm09Uk8+BQ7M0ZC4Po1FwJpry2t54IJpkSWclYkY4LkcnFPl835TG V4PIPeq00Gn3GqQPKInvbdWeIFvmRW4Jx/WrtMCr9omDsvlKxB5CtzUqSs7bWiZeM5NKYIi+8oN2 c5qQDJAobBJ3Hh1281EwUtvwA3pTsEMdtRO6kAhgT71zNnWO3EnaeR3zRSKA56jHrmikBQVm9M1a gYZIIqsoB5UmrMY6GvRnseZDcj1O6m0/Tpbm3tXupUA2wp1bmprie3igBu3jjjchP3hABJ4A5qG8 vDb3NrCLeaXz3KF41yI+M5b0FNlnsLq9GmzBJZ1UTiN0yAAeG9M5FYM3H3enQ3mnSWJZ4YXAUeQ2 wr9CKWWK4ttKaKybzLiOLbEZmzuYDjcabqWnLqUcKGeWIxTLKDG2M47H1FN1U6mIYf7LWEyGZRJ5 vaPuR70mMdPdzWGkG6uYXnmjjBkjtlLFj32jqale9t4rD7ZcOIINgdmm+XaD656U2/vk0+3WZ4pp Qzqm2GMsck46DtVC8gT7RcrrF7DJp17tghtJUAG49s9yaLgX7K1s7ayWKxjjit2BZRFwOecjFM0+ wOm6cLWKeSZl3FXnbcckk8+1U5I7jUY9Q0n7PNY2yRrHBdRuAWyP4cdMUj6g00d5pWl3CtqtpEvz XCnbk9CT3pXQF+2a8g0wNe7JrpEJcQDhjzwM/hTdO1D7dpUV9LBJbb1LNHLwyAE9fypLi6urTR3n +z/a7yKIFoIDje+OgzUlzewWmmteXxEEKoGk387c9j+eKYCadLY3NqLvTzE0M7F98YwHOcEn34pu naZaacLg2ikC4maaQli2WPX6fSpbeG2jsUjt0SO2KfKEG0AHn+tM0/ToNM09LO13CJM7SzZPJJ6/ U0AFnZyW1xeSPcyTCeXzFV+kY2gbR7cZ/GiyN8ZLr7YIgnmnyNnXZgdffrSWFpNY6csD3Ml1Ku4+ bKeWySQD9M4/CjTXvm0yN9RijS8+YukRyOpxj8MUIBNPvZ7uS7WazktxBMY0L/8ALVR/EPaiw1S2 1Ga7jg3FrWYwyZXA3AdvWn2NzNc2KT3Ns9rId26JzkrgkDp6gZ/Gm6be2moWQu7P/UyM3zbduSCQ T+YoAWCOwlv57qBYGu1AhlkXBYY52k/j0pq6dCNYbURJIZjCISm/5AM5zj1pdPhsEjlm09YNk0jP I8OCHfOCSR3yKLTTbezury5h3mS7cPJubIyBjj06UAXKRuFJ9KpWljNb6je3Ul5LMlwV2RN92IAY wKsyeYQcYx7daL6DI/PflV4U96jVC/AHNTrHgEuPwqRRjpWCpt/Eauemhz9xLPa3DQLOSFIABIzz 9aK3JLeKfl413epFFEqLvoJT01KSNjiraN8vPFUlODUwk4WvQkrnDF2HG7f+0Vtfs0xUxGTz8fJn ONufWnpdWh1BrUSxfbBHvMefmC56/SrCMGUYqpA+nXOoTyQeRJeQfupXUAunfaTXOzoQ64sBPqFp d+fKht93yK3yvkY5FMum1L+0rNbVIPsZ3faWcncOONv40LpoTWH1EXFxl4whhLny+O+31pQ+oHWW QxxjThACHz8xkz0x6YpDFub/AOz6haWgtp5PtBb94i5WPAzlj29KoQ6eGiS1166t72U3Jmtg6hSM cgAdyOauS6jm/m0+GGU3K25mV2Q+WT0A3dM5rPSW2ujbyajbQPrlnAZhApBkXI52/Xj9KTAlUXes aekl2lzpktvcb2SNs+YF+nVTUkd6+qWMF7ozxBZJR5jTxkEoCQwx1zVZy0sFp4g1Frmw+yRPJLaB 8ryP4gOpAq67XV49jJa+T/Z0qMbhZFIcqV+XA7e9CAik+x6VM9/a2cs8uoTokr2439iAx9AKt6ne WVlaA37KIZXEWGXcGLdBiobUWmkm00q0tphC6uyMiFkTBydzdiSeKlvJ9P8AtNrZXhiaadi8EbjO 4rySPpkUdAJL2zgvLCWznyIJUMbBTt4PoabNZk6U9lbTPAfJ8qOVTlk4wD9RTdT0211SCO3ut2xZ FkUK+07l5FGqWlxe2qxW121q4kVmdRklQckfjTAfIl3DpZS3ZZrtIsI0vAdgOppXmng01p5IfMuE i3NFFzuYDoPxpmpG/FvH/ZyxNKZVD+YeAmfmP1xSanfSafaCeK0lum3qpjiGSATjP4UAOivh/ZS3 1zE9uPK82SNx8ycZIPuKLa5tJdMS7iKJaPH5gLDaAp5yfSk1PULXTLFrm8JEAIU4Xd1OOlOv1shp 8sd80Udoy7H8xgq4PGM0AFhbWVvYpHYRxR2rAuoiwFO7kkY9c5pNN0630qzFrah/KDFhvYseTnqa dJZ28mmtZY2WzReUAhxhSMcH6UjWQTSzY20jQgQ+VHIDkpxgH60AN02xewgkje6luC8rSbpTkjJz gewpkEl5bRXs+pSQmJHZ4vKU5WIDv6nrTktbq20UWsFxvuo4NiTS85cDAJ/GnRC9XS1WYxPfCLDE Z2F8fyzQAafdSXsJuCiiB8NAwJyyEdSD0PtSWOofbpbpBbzRLby+UGkXAkwOSvtRbS3i6RHLc2yi 8EOXhjYY34+6DTrG4nn06G4u7Y207JueHO4ofTI60ICRrqBbtLVpVE7qXVM8lR1NFVbLUYb3S01U 200K+WzBZY/3gUe3XnHSii6AhpyHnHrRRXWzkLURxiiGCCG4mlihRJJiDIyjBcj1oorGS1NovQSz sRaS3Ugmmk+0SeZtkbITjGF9BVPRtUm1G81WKVEVbS58lNvcYB5oorF6NI1LGrPcLpsxtJhBOGUL IU3gfMM8cdsiqOu3kGjfZdU+xRT3ckiWvmfdYK3XnB9OlFFEtrjNFLST+0Zbp7qR4ZYggtmA2KfU e5qkLyW58SXekvs+yLaBsAYYljg859KKKGBfsbWDT7aOxtkKwwqAoLEnH1NTtFG0qStGpkQEKxHK 564ooqhEFxp1tdXtrdzIWmtSxiO4/LuGDx3pl5DcSXtlJFdtFGjt5sQUESgjgE9sdaKKVgKuq6nP Z6tpFrEF2XczpISOcBc8fjV+4ufIlt02bvOk2ZzjHBP9KKKSerAmdVddrqGU9iM1De2NtqNsbe7h WaEkEo3QkUUVQEepabBqlkbScyLGSD+7baeDkc0zWLae702SC2vJLSRyB50YyyjPOKKKTQEHiC6u dP0GWa1kCzrtVXdd3UgZxS+ItTl0bw9d6hEivJCgIDdCcgf1ooqZOyYDtQ1RrHw++peUHZYlk2Zw CTjv+NWzc4sPtOz/AJZh9ufbOKKKd9QJY33xq2MZGcUUUVQH/9k= gov.noaa.nmfs.inport: 20230401 John F Kennedy NMFS Office of Science and Technology GIS Specialist john.f.kennedy@noaa.gov 1315 East West Highway Silver Spring MD 20910-3282 301-427-8149 301-713-4137 Sample Locations The survey points layers were created by conducting several processing steps of the raw fishery-independent survey catch-per-unit effort data, using R and Python scripts to clean and standardize the datasets. The data processing workflow, as well as information on the original sources of the data, are provided in detail in the below Sources and Process Steps. Data for Eastern and Northern Bering Sea Sample Locations 2010 to 2022 was downloaded from https://www.fisheries.noaa.gov/alaska/commercial-fishing/alaska-groundfish-bottom-trawl-survey-data Alaska Fisheries Science Center Bottom Trawl Survey 2023-04-01T00:00:00 The data was obtained from the above sources as raw survey data. Please refer to the original source for detailed metadata information on each survey. 2023-04-01T00:00:00 Melissa Ann Karp NMFS/OST/AMD Fisheries Science Coordinator melissa.karp@noaa.gov 1315 East West Hwy, Bldg. SSMC3 Silver Spring MD 20910-3282 US 301-427-8202 The raw survey data was then processed using an R script, which combined the individual files collected for each regional survey into one dataset with standardized names and units across all regions, and removing unnecessary columns. During this processing step, decisions where made to in some cases trim a regions data to either eliminate certain years or strata based on evaluation of survey coverage for those years or strata. 2023-04-01T00:00:00 Melissa Ann Karp NMFS/OST/AMD Fisheries Science Coordinator melissa.karp@noaa.gov 1315 East West Hwy, Bldg. SSMC3 Silver Spring MD 20910-3282 US 301-427-8202 no missing features Reviewed by project staff 2023-04-01T00:00:00 Reviewed by project staff 1 https://services2.arcgis.com/C8EMgrsFcRFL6LrL/arcgis/rest/services/ENBS_Sample_Locations_20230401/FeatureServer ArcGIS REST Services Eastern and Northern Bering Sea Sample Locations 20230401 Sample Locations Feature Service Esri ArcGIS 13.1.0.41833 NOAA Geoplatform Feature Service Timothy J Haverland NMFS Office of Science and Technology GIS App Developer tim.haverland@noaa.gov 1315 East West Highway Silver Spring MD 20910-3282 US 301-427-8137 301-713-4137 True Timothy J Haverland EPSG 6.18.3(9.3.1.2) Sample Locations Attribute Table Sample Locations DisMAP Feature Class 244024 OBJECTID Internal feature number. Esri Sequential unique whole numbers that are automatically generated. OBJECTID OID 4 0 0 Shape Feature geometry. Esri Coordinates defining the features. Shape Geometry 0 0 0 DatasetCode Dataset Code String 20 0 0 Dataset Code DisMAP Dataset Code Region Region String 40 0 0 Region DisMAP Region SummaryProduct Summary Product String 10 0 0 Summary Product DisMAP Summary Product Season Season String 5 0 0 Season Season Season SampleID Sample ID String 20 0 0 Sample ID DisMAP Sample ID Year Year Integer 4 0 0 Year DisMAP Year StdTime StdTime Date 8 0 0 StdTime DisMAP StdTime Species Species String 40 0 0 Species DisMAP Species WTCPUE WTCPUE Double 8 0 0 WTCPUE DisMAP WTCPUE MapValue Map Value Double 8 0 0 Map Value DisMAP Map Value TransformUnit Transform Unit String 30 0 0 Transform Unit DisMAP Transform Unit CommonName Common Name String 30 0 0 Common Name DisMAP Common Name SpeciesCommonName Species Common Name String 60 0 0 Species Common Name DisMAP Species Common Name CommonNameSpecies Common Name Species String 60 0 0 Common Name Species DisMAP Common Name Species CoreSpecies Core Species String 5 0 0 Core Species DisMAP Core Species Stratum Stratum String 20 0 0 Stratum DisMAP Stratum StratumArea Stratum Area Double 8 0 0 Stratum Area DisMAP Stratum Area Latitude Latitude Double 8 0 0 Latitude DisMAP Latitude Longitude Longitude Double 8 0 0 Longitude DisMAP Longitude Depth Depth Double 8 0 0 Depth DisMAP Depth 244024 Simple FALSE 244024 TRUE FALSE