background-image: url(images/coastal_map.png) background-position: top right background-size: contain class: middle, left # Mapping Ocean Stories ## Dr. Laurie Baker, College of the Atlantic soon Bates College ### Bigelow Laboratory for Ocean Sciences, 14 November, 2024 .footnote[] --- class: middle, left # About me .pull-left[ .center[ <img style="border-radius: 50%;" src="images/laurie_baker.jpg" width="350px"/> ### Dr. Laurie Baker ]] .pull-right[ ### <svg viewBox="0 0 640 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M622.34 153.2L343.4 67.5c-15.2-4.67-31.6-4.67-46.79 0L17.66 153.2c-23.54 7.23-23.54 38.36 0 45.59l48.63 14.94c-10.67 13.19-17.23 29.28-17.88 46.9C38.78 266.15 32 276.11 32 288c0 10.78 5.68 19.85 13.86 25.65L20.33 428.53C18.11 438.52 25.71 448 35.94 448h56.11c10.24 0 17.84-9.48 15.62-19.47L82.14 313.65C90.32 307.85 96 298.78 96 288c0-11.57-6.47-21.25-15.66-26.87.76-15.02 8.44-28.3 20.69-36.72L296.6 284.5c9.06 2.78 26.44 6.25 46.79 0l278.95-85.7c23.55-7.24 23.55-38.36 0-45.6zM352.79 315.09c-28.53 8.76-52.84 3.92-65.59 0l-145.02-44.55L128 384c0 35.35 85.96 64 192 64s192-28.65 192-64l-14.18-113.47-145.03 44.56z"></path></svg> BSc Marine Biology, University of St. Andrews ### <svg viewBox="0 0 640 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M622.34 153.2L343.4 67.5c-15.2-4.67-31.6-4.67-46.79 0L17.66 153.2c-23.54 7.23-23.54 38.36 0 45.59l48.63 14.94c-10.67 13.19-17.23 29.28-17.88 46.9C38.78 266.15 32 276.11 32 288c0 10.78 5.68 19.85 13.86 25.65L20.33 428.53C18.11 438.52 25.71 448 35.94 448h56.11c10.24 0 17.84-9.48 15.62-19.47L82.14 313.65C90.32 307.85 96 298.78 96 288c0-11.57-6.47-21.25-15.66-26.87.76-15.02 8.44-28.3 20.69-36.72L296.6 284.5c9.06 2.78 26.44 6.25 46.79 0l278.95-85.7c23.55-7.24 23.55-38.36 0-45.6zM352.79 315.09c-28.53 8.76-52.84 3.92-65.59 0l-145.02-44.55L128 384c0 35.35 85.96 64 192 64s192-28.65 192-64l-14.18-113.47-145.03 44.56z"></path></svg> Msc Marine Biology, Dalhousie University ### <svg viewBox="0 0 640 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M622.34 153.2L343.4 67.5c-15.2-4.67-31.6-4.67-46.79 0L17.66 153.2c-23.54 7.23-23.54 38.36 0 45.59l48.63 14.94c-10.67 13.19-17.23 29.28-17.88 46.9C38.78 266.15 32 276.11 32 288c0 10.78 5.68 19.85 13.86 25.65L20.33 428.53C18.11 438.52 25.71 448 35.94 448h56.11c10.24 0 17.84-9.48 15.62-19.47L82.14 313.65C90.32 307.85 96 298.78 96 288c0-11.57-6.47-21.25-15.66-26.87.76-15.02 8.44-28.3 20.69-36.72L296.6 284.5c9.06 2.78 26.44 6.25 46.79 0l278.95-85.7c23.55-7.24 23.55-38.36 0-45.6zM352.79 315.09c-28.53 8.76-52.84 3.92-65.59 0l-145.02-44.55L128 384c0 35.35 85.96 64 192 64s192-28.65 192-64l-14.18-113.47-145.03 44.56z"></path></svg> PhD Ecology and Evolution, University of Glasgow ] .center[ [<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg> lauriebaker.rbind.io](https://lauriebaker.rbind.io) [<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"></path></svg> @llbaker1707](https://twitter.com/llbaker1707) [<svg viewBox="0 0 496 512" style="position:relative;display:inline-block;top:.1em;height:1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 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About me .pull-left[ .center[ <img style="border-radius: 50%;" src="images/laurie_baker.jpg" width="350px"/> ### Dr. Laurie Baker ]] .pull-right[ #### <svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M528 0H48C21.5 0 0 21.5 0 48v320c0 26.5 21.5 48 48 48h192l-16 48h-72c-13.3 0-24 10.7-24 24s10.7 24 24 24h272c13.3 0 24-10.7 24-24s-10.7-24-24-24h-72l-16-48h192c26.5 0 48-21.5 48-48V48c0-26.5-21.5-48-48-48zm-16 352H64V64h448v288z"></path></svg> Data Science Lecturer and Head of Faculty, Data Science Campus, Office for National Statistics #### <svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M496 128v16a8 8 0 0 1-8 8h-24v12c0 6.627-5.373 12-12 12H60c-6.627 0-12-5.373-12-12v-12H24a8 8 0 0 1-8-8v-16a8 8 0 0 1 4.941-7.392l232-88a7.996 7.996 0 0 1 6.118 0l232 88A8 8 0 0 1 496 128zm-24 304H40c-13.255 0-24 10.745-24 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style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M496 128v16a8 8 0 0 1-8 8h-24v12c0 6.627-5.373 12-12 12H60c-6.627 0-12-5.373-12-12v-12H24a8 8 0 0 1-8-8v-16a8 8 0 0 1 4.941-7.392l232-88a7.996 7.996 0 0 1 6.118 0l232 88A8 8 0 0 1 496 128zm-24 304H40c-13.255 0-24 10.745-24 24v16a8 8 0 0 0 8 8h464a8 8 0 0 0 8-8v-16c0-13.255-10.745-24-24-24zM96 192v192H60c-6.627 0-12 5.373-12 12v20h416v-20c0-6.627-5.373-12-12-12h-36V192h-64v192h-64V192h-64v192h-64V192H96z"></path></svg> Assistant Professor, Mathematics, Bates College ] .center[ [<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg> lauriebaker.rbind.io](https://lauriebaker.rbind.io) [<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"></path></svg> @llbaker1707](https://twitter.com/llbaker1707) [<svg viewBox="0 0 496 512" style="position:relative;display:inline-block;top:.1em;height:1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg> @laurielbaker](https://github.com/laurielbaker) ] --- class: middle, left # Research Interests .left-column[ .center[ <img style="border-radius: 5%;" src="images/ecology.png" width="500px"/> ] ] .right-column[ ### Spatial and temporal patterns in human and biological systems ### - Disease spread ### - Animal movement ### - Fisheries management ] --- # Target species in the Chilean longline fishery .pull-left[ .center[ <img style="border-radius: 5%;" src="images/congrio_centolla.jpg" width="700px"/> ] ] .pull-right[ ## Topics ### <svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M327.1 96c-89.97 0-168.54 54.77-212.27 101.63L27.5 131.58c-12.13-9.18-30.24.6-27.14 14.66L24.54 256 .35 365.77c-3.1 14.06 15.01 23.83 27.14 14.66l87.33-66.05C158.55 361.23 237.13 416 327.1 416 464.56 416 576 288 576 256S464.56 96 327.1 96zm87.43 184c-13.25 0-24-10.75-24-24 0-13.26 10.75-24 24-24 13.26 0 24 10.74 24 24 0 13.25-10.75 24-24 24z"></path></svg> **Fisheries Management** ### <svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg> **Spatial Statistics** ] ### <svg viewBox="0 0 352 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M176 80c-52.94 0-96 43.06-96 96 0 8.84 7.16 16 16 16s16-7.16 16-16c0-35.3 28.72-64 64-64 8.84 0 16-7.16 16-16s-7.16-16-16-16zM96.06 459.17c0 3.15.93 6.22 2.68 8.84l24.51 36.84c2.97 4.46 7.97 7.14 13.32 7.14h78.85c5.36 0 10.36-2.68 13.32-7.14l24.51-36.84c1.74-2.62 2.67-5.7 2.68-8.84l.05-43.18H96.02l.04 43.18zM176 0C73.72 0 0 82.97 0 176c0 44.37 16.45 84.85 43.56 115.78 16.64 18.99 42.74 58.8 52.42 92.16v.06h48v-.12c-.01-4.77-.72-9.51-2.15-14.07-5.59-17.81-22.82-64.77-62.17-109.67-20.54-23.43-31.52-53.15-31.61-84.14-.2-73.64 59.67-128 127.95-128 70.58 0 128 57.42 128 128 0 30.97-11.24 60.85-31.65 84.14-39.11 44.61-56.42 91.47-62.1 109.46a47.507 47.507 0 0 0-2.22 14.3v.1h48v-.05c9.68-33.37 35.78-73.18 52.42-92.16C335.55 260.85 352 220.37 352 176 352 78.8 273.2 0 176 0z"></path></svg> What factors influence a fisher's target species (market value, weather, location, time of year) under different management practices? ??? I used catch composition and machine learning to infer a fisher's target species and used generalized additive models to explore the factors influencing target species. --- # Grey seals as bioprobes .pull-left[ .center[ <img style="border-radius: 5%;" src="images/grey_seal.jpg" width="700px"/> ] ] .pull-right[ ## Topics ### <svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M327.1 96c-89.97 0-168.54 54.77-212.27 101.63L27.5 131.58c-12.13-9.18-30.24.6-27.14 14.66L24.54 256 .35 365.77c-3.1 14.06 15.01 23.83 27.14 14.66l87.33-66.05C158.55 361.23 237.13 416 327.1 416 464.56 416 576 288 576 256S464.56 96 327.1 96zm87.43 184c-13.25 0-24-10.75-24-24 0-13.26 10.75-24 24-24 13.26 0 24 10.74 24 24 0 13.25-10.75 24-24 24z"></path></svg> **Ecology** ### <svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg> **Animal Movement** ] ### <svg viewBox="0 0 352 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M176 80c-52.94 0-96 43.06-96 96 0 8.84 7.16 16 16 16s16-7.16 16-16c0-35.3 28.72-64 64-64 8.84 0 16-7.16 16-16s-7.16-16-16-16zM96.06 459.17c0 3.15.93 6.22 2.68 8.84l24.51 36.84c2.97 4.46 7.97 7.14 13.32 7.14h78.85c5.36 0 10.36-2.68 13.32-7.14l24.51-36.84c1.74-2.62 2.67-5.7 2.68-8.84l.05-43.18H96.02l.04 43.18zM176 0C73.72 0 0 82.97 0 176c0 44.37 16.45 84.85 43.56 115.78 16.64 18.99 42.74 58.8 52.42 92.16v.06h48v-.12c-.01-4.77-.72-9.51-2.15-14.07-5.59-17.81-22.82-64.77-62.17-109.67-20.54-23.43-31.52-53.15-31.61-84.14-.2-73.64 59.67-128 127.95-128 70.58 0 128 57.42 128 128 0 30.97-11.24 60.85-31.65 84.14-39.11 44.61-56.42 91.47-62.1 109.46a47.507 47.507 0 0 0-2.22 14.3v.1h48v-.05c9.68-33.37 35.78-73.18 52.42-92.16C335.55 260.85 352 220.37 352 176 352 78.8 273.2 0 176 0z"></path></svg> What is the detection efficiency of acoustic tags in the field? What potential is there to use grey seals to sample the marine environment? ??? --- # Grey seals as bioprobes .pull-left[ .center[ <iframe src="https://www.google.com/maps/embed?pb=!1m18!1m12!1m3!1d367544.6964222735!2d-60.215552395501966!3d43.97088868870316!2m3!1f0!2f0!3f0!3m2!1i1024!2i768!4f13.1!3m3!1m2!1s0x4b4689632ca41c27%3A0xfcd36f09136414e!2sSable%20Island!5e0!3m2!1sen!2sus!4v1630508253565!5m2!1sen!2sus" width="560" height="420" style="border:0;" allowfullscreen="" loading="lazy"></iframe> ] ] .pull-right[ ## Topics ### <svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M327.1 96c-89.97 0-168.54 54.77-212.27 101.63L27.5 131.58c-12.13-9.18-30.24.6-27.14 14.66L24.54 256 .35 365.77c-3.1 14.06 15.01 23.83 27.14 14.66l87.33-66.05C158.55 361.23 237.13 416 327.1 416 464.56 416 576 288 576 256S464.56 96 327.1 96zm87.43 184c-13.25 0-24-10.75-24-24 0-13.26 10.75-24 24-24 13.26 0 24 10.74 24 24 0 13.25-10.75 24-24 24z"></path></svg> **Ecology** ### <svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg> **Animal Movement** ] ### <svg viewBox="0 0 352 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M176 80c-52.94 0-96 43.06-96 96 0 8.84 7.16 16 16 16s16-7.16 16-16c0-35.3 28.72-64 64-64 8.84 0 16-7.16 16-16s-7.16-16-16-16zM96.06 459.17c0 3.15.93 6.22 2.68 8.84l24.51 36.84c2.97 4.46 7.97 7.14 13.32 7.14h78.85c5.36 0 10.36-2.68 13.32-7.14l24.51-36.84c1.74-2.62 2.67-5.7 2.68-8.84l.05-43.18H96.02l.04 43.18zM176 0C73.72 0 0 82.97 0 176c0 44.37 16.45 84.85 43.56 115.78 16.64 18.99 42.74 58.8 52.42 92.16v.06h48v-.12c-.01-4.77-.72-9.51-2.15-14.07-5.59-17.81-22.82-64.77-62.17-109.67-20.54-23.43-31.52-53.15-31.61-84.14-.2-73.64 59.67-128 127.95-128 70.58 0 128 57.42 128 128 0 30.97-11.24 60.85-31.65 84.14-39.11 44.61-56.42 91.47-62.1 109.46a47.507 47.507 0 0 0-2.22 14.3v.1h48v-.05c9.68-33.37 35.78-73.18 52.42-92.16C335.55 260.85 352 220.37 352 176 352 78.8 273.2 0 176 0z"></path></svg> What is the detection efficiency of acoustic tags in the field? What potential is there to use grey seals to sample the marine environment? ??? --- # Spread and control of fox rabies in Europe .pull-left[ .center[ <img style="border-radius: 5%;" src="images/rabies_retreat.png" width="700px"/> ] ] .pull-right[ ## Topics ### <svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M327.1 96c-89.97 0-168.54 54.77-212.27 101.63L27.5 131.58c-12.13-9.18-30.24.6-27.14 14.66L24.54 256 .35 365.77c-3.1 14.06 15.01 23.83 27.14 14.66l87.33-66.05C158.55 361.23 237.13 416 327.1 416 464.56 416 576 288 576 256S464.56 96 327.1 96zm87.43 184c-13.25 0-24-10.75-24-24 0-13.26 10.75-24 24-24 13.26 0 24 10.74 24 24 0 13.25-10.75 24-24 24z"></path></svg> **Ecology** ### <svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M201.5 174.8l55.7 55.8c3.1 3.1 3.1 8.2 0 11.3l-11.3 11.3c-3.1 3.1-8.2 3.1-11.3 0l-55.7-55.8-45.3 45.3 55.8 55.8c3.1 3.1 3.1 8.2 0 11.3l-11.3 11.3c-3.1 3.1-8.2 3.1-11.3 0L111 265.2l-26.4 26.4c-17.3 17.3-25.6 41.1-23 65.4l7.1 63.6L2.3 487c-3.1 3.1-3.1 8.2 0 11.3l11.3 11.3c3.1 3.1 8.2 3.1 11.3 0l66.3-66.3 63.6 7.1c23.9 2.6 47.9-5.4 65.4-23l181.9-181.9-135.7-135.7-64.9 65zm308.2-93.3L430.5 2.3c-3.1-3.1-8.2-3.1-11.3 0l-11.3 11.3c-3.1 3.1-3.1 8.2 0 11.3l28.3 28.3-45.3 45.3-56.6-56.6-17-17c-3.1-3.1-8.2-3.1-11.3 0l-33.9 33.9c-3.1 3.1-3.1 8.2 0 11.3l17 17L424.8 223l17 17c3.1 3.1 8.2 3.1 11.3 0l33.9-34c3.1-3.1 3.1-8.2 0-11.3l-73.5-73.5 45.3-45.3 28.3 28.3c3.1 3.1 8.2 3.1 11.3 0l11.3-11.3c3.1-3.2 3.1-8.2 0-11.4z"></path></svg> **Public Health** ### <svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg> **Spatial Statistics** ] ### <svg viewBox="0 0 352 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M176 80c-52.94 0-96 43.06-96 96 0 8.84 7.16 16 16 16s16-7.16 16-16c0-35.3 28.72-64 64-64 8.84 0 16-7.16 16-16s-7.16-16-16-16zM96.06 459.17c0 3.15.93 6.22 2.68 8.84l24.51 36.84c2.97 4.46 7.97 7.14 13.32 7.14h78.85c5.36 0 10.36-2.68 13.32-7.14l24.51-36.84c1.74-2.62 2.67-5.7 2.68-8.84l.05-43.18H96.02l.04 43.18zM176 0C73.72 0 0 82.97 0 176c0 44.37 16.45 84.85 43.56 115.78 16.64 18.99 42.74 58.8 52.42 92.16v.06h48v-.12c-.01-4.77-.72-9.51-2.15-14.07-5.59-17.81-22.82-64.77-62.17-109.67-20.54-23.43-31.52-53.15-31.61-84.14-.2-73.64 59.67-128 127.95-128 70.58 0 128 57.42 128 128 0 30.97-11.24 60.85-31.65 84.14-39.11 44.61-56.42 91.47-62.1 109.46a47.507 47.507 0 0 0-2.22 14.3v.1h48v-.05c9.68-33.37 35.78-73.18 52.42-92.16C335.55 260.85 352 220.37 352 176 352 78.8 273.2 0 176 0z"></path></svg> What can we learn about vaccination planning from the successful elimination of rabies in Western Europe? --- # Target species in the Chilean longline fishery .pull-left[ .center[ <img style="border-radius: 5%;" src="images/congrio_centolla.jpg" width="700px"/> ] ] .pull-right[ ## Topics ### <svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M327.1 96c-89.97 0-168.54 54.77-212.27 101.63L27.5 131.58c-12.13-9.18-30.24.6-27.14 14.66L24.54 256 .35 365.77c-3.1 14.06 15.01 23.83 27.14 14.66l87.33-66.05C158.55 361.23 237.13 416 327.1 416 464.56 416 576 288 576 256S464.56 96 327.1 96zm87.43 184c-13.25 0-24-10.75-24-24 0-13.26 10.75-24 24-24 13.26 0 24 10.74 24 24 0 13.25-10.75 24-24 24z"></path></svg> **Fisheries Management** ### <svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg> **Spatial Statistics** ] ### <svg viewBox="0 0 352 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M176 80c-52.94 0-96 43.06-96 96 0 8.84 7.16 16 16 16s16-7.16 16-16c0-35.3 28.72-64 64-64 8.84 0 16-7.16 16-16s-7.16-16-16-16zM96.06 459.17c0 3.15.93 6.22 2.68 8.84l24.51 36.84c2.97 4.46 7.97 7.14 13.32 7.14h78.85c5.36 0 10.36-2.68 13.32-7.14l24.51-36.84c1.74-2.62 2.67-5.7 2.68-8.84l.05-43.18H96.02l.04 43.18zM176 0C73.72 0 0 82.97 0 176c0 44.37 16.45 84.85 43.56 115.78 16.64 18.99 42.74 58.8 52.42 92.16v.06h48v-.12c-.01-4.77-.72-9.51-2.15-14.07-5.59-17.81-22.82-64.77-62.17-109.67-20.54-23.43-31.52-53.15-31.61-84.14-.2-73.64 59.67-128 127.95-128 70.58 0 128 57.42 128 128 0 30.97-11.24 60.85-31.65 84.14-39.11 44.61-56.42 91.47-62.1 109.46a47.507 47.507 0 0 0-2.22 14.3v.1h48v-.05c9.68-33.37 35.78-73.18 52.42-92.16C335.55 260.85 352 220.37 352 176 352 78.8 273.2 0 176 0z"></path></svg> What factors influence a fisher's target species (market value, weather, location, time of year) under different management practices? ??? I used catch composition and machine learning to infer a fisher's target species and used generalized additive models to explore the factors influencing target species. --- class: middle, left # Who is fishing? <img src="slides/figs/fishing_who.png" alt="Plot showing the vessel length and width as boats on a scatter plot where the size of the boat is proportional to the carrying capacity of the vessel" width="65%" style="display: block; margin: auto;" /> --- class: middle, left # How are vessels fishing? <img src="slides/figs/fishing_when.png" alt="Plot showing the distribution of trip length by vessel" width="65%" style="display: block; margin: auto;" /> --- class: middle, left # What are vessels targeting? <img src="images/species_prop.png" alt="Plot showing the distribution of species in the catch by weight by vessel" width="65%" style="display: block; margin: auto;" /> --- class: middle, left # Where are they fishing?
--- class: # Inspiration <img src="images/cod-ted-ames.png" alt="Map of Cod Spawning Grounds on the Coast of Maine" width="1000" style="display: block; margin: auto;" /> ??? In Maine we have a rich history of collecting and sharing local ecological knowledge. Ted Ames collected and analyzed stories from 61- to 94-year-old Maine fishermen to show where cod had historically spawned and been caught along the coast of Maine and used this in addition to catch records to study movements of Atlantic cod. --- # Mapping Ocean Stories .pull-left[ .center[ <img style="border-radius: 5%;" src="images/student_class.jpeg" width="600px"/> ] ] .pull-right[ #### <svg viewBox="0 0 640 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M622.34 153.2L343.4 67.5c-15.2-4.67-31.6-4.67-46.79 0L17.66 153.2c-23.54 7.23-23.54 38.36 0 45.59l48.63 14.94c-10.67 13.19-17.23 29.28-17.88 46.9C38.78 266.15 32 276.11 32 288c0 10.78 5.68 19.85 13.86 25.65L20.33 428.53C18.11 438.52 25.71 448 35.94 448h56.11c10.24 0 17.84-9.48 15.62-19.47L82.14 313.65C90.32 307.85 96 298.78 96 288c0-11.57-6.47-21.25-15.66-26.87.76-15.02 8.44-28.3 20.69-36.72L296.6 284.5c9.06 2.78 26.44 6.25 46.79 0l278.95-85.7c23.55-7.24 23.55-38.36 0-45.6zM352.79 315.09c-28.53 8.76-52.84 3.92-65.59 0l-145.02-44.55L128 384c0 35.35 85.96 64 192 64s192-28.65 192-64l-14.18-113.47-145.03 44.56z"></path></svg> Collaboration with the Island Institute, Maine Sea Grant, The First Coast, College of the Atlantic, and Bates College. #### <svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M256 32C114.52 32 0 146.496 0 288v48a32 32 0 0 0 17.689 28.622l14.383 7.191C34.083 431.903 83.421 480 144 480h24c13.255 0 24-10.745 24-24V280c0-13.255-10.745-24-24-24h-24c-31.342 0-59.671 12.879-80 33.627V288c0-105.869 86.131-192 192-192s192 86.131 192 192v1.627C427.671 268.879 399.342 256 368 256h-24c-13.255 0-24 10.745-24 24v176c0 13.255 10.745 24 24 24h24c60.579 0 109.917-48.098 111.928-108.187l14.382-7.191A32 32 0 0 0 512 336v-48c0-141.479-114.496-256-256-256z"></path></svg> Series of oral history and audio storytelling projects, courses, and exhibits. <div class="figure" style="text-align: center"> <img src="images/stonington_soundwalk.jpeg" alt="Stonington Soundwalk map by Kristina Buckley © 2023" width="450" /> <p class="caption">Stonington Soundwalk map by Kristina Buckley © 2023</p> </div> ] ### <svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M576 240c0-23.63-12.95-44.04-32-55.12V32.01C544 23.26 537.02 0 512 0c-7.12 0-14.19 2.38-19.98 7.02l-85.03 68.03C364.28 109.19 310.66 128 256 128H64c-35.35 0-64 28.65-64 64v96c0 35.35 28.65 64 64 64h33.7c-1.39 10.48-2.18 21.14-2.18 32 0 39.77 9.26 77.35 25.56 110.94 5.19 10.69 16.52 17.06 28.4 17.06h74.28c26.05 0 41.69-29.84 25.9-50.56-16.4-21.52-26.15-48.36-26.15-77.44 0-11.11 1.62-21.79 4.41-32H256c54.66 0 108.28 18.81 150.98 52.95l85.03 68.03a32.023 32.023 0 0 0 19.98 7.02c24.92 0 32-22.78 32-32V295.13C563.05 284.04 576 263.63 576 240zm-96 141.42l-33.05-26.44C392.95 311.78 325.12 288 256 288v-96c69.12 0 136.95-23.78 190.95-66.98L480 98.58v282.84z"></path></svg> **Goal:** To Amplify the Voices of Maine's Coastal Communities ??? --- class: # Mapping Ocean Stories <iframe width="960" height="505" src="https://www.youtube.com/embed/__oa_9Gugmg?si=pthIL7fCYvOLtdeW" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe> --- class: # Mapping Ocean Stories Goals <img src="images/mos_goals.png" width="880" /> --- class: # Mapping Ocean Stories Timeline ### Began with 2017 class *Mapping Ocean Stories* and 2020 class created the Mt. Desert Island Historical Fisheries Atlas. ### <svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M256 32C114.52 32 0 146.496 0 288v48a32 32 0 0 0 17.689 28.622l14.383 7.191C34.083 431.903 83.421 480 144 480h24c13.255 0 24-10.745 24-24V280c0-13.255-10.745-24-24-24h-24c-31.342 0-59.671 12.879-80 33.627V288c0-105.869 86.131-192 192-192s192 86.131 192 192v1.627C427.671 268.879 399.342 256 368 256h-24c-13.255 0-24 10.745-24 24v176c0 13.255 10.745 24 24 24h24c60.579 0 109.917-48.098 111.928-108.187l14.382-7.191A32 32 0 0 0 512 336v-48c0-141.479-114.496-256-256-256z"></path></svg> March 2023 received a grant to further develop two key outputs: Maine Sound + Story and the Maine Historical Fisheries Atlas (MHFA). ### 1. Develop a coding scheme for spatial data mentioned in interviews ### 2. Build a hub site to host the Maine Historical Fisheries Atlas ### 3. Use text analysis to support the spatial coding process --- class: center <figure> <img src="images/workflow.png" alt="Diagram of the Interview to Spatial Coding Analysis Workflow" width="800" height="600"> <figcaption>Figure 1. Diagram of the Mapping Ocean Stories Data Analysis Workflow.</figcaption> </figure> ??? The database is designed to record spatial, categorical, observational, and temporal information about each activity. --- # Biographical Mapping Interviews .pull-left[ <img src="images/mos-bio-map.jpg" width="550" /> ] .pull-right[Natalie Springuel (Maine Sea Grant) and MOS Class with David Thomas in Islesford, Little Cranberry] --- # Digitizing the Biographical Mapping Interview <center> <video width="800" height="500" controls> <source src="media/Spatial_Data_Editor_Demo.mp4" type="video/mp4"> <source src="media/Spatial_Data_Editor_Demo.ogg" type="video/ogg"> Your browser does not support the video tag. </video> </center> --- class: center # Maine Historical Fisheries Atlas <img src="images/mos-data-entry.png" alt="Spatial Data Entry System" width="500" style="display: block; margin: auto;" /> **Demo** [MOS Hub Site](https://mos-data-coagis.hub.arcgis.com) --- class: center # Digitized Locations <img src="images/toby-scallops.png" alt="Scallop Dragging" width="800" style="display: block; margin: auto;" /> --- class: center # Spatial Data from Oral History Archives .pull-left[ <img src="images/mos-archives.png" width="1600" /> [Maine Sound + Story](https://mainesoundandstory.com/) ] .pull-right[ <div class="figure"> <img src="images/mainesound_story.png" alt="Photo of Herbert Carter Jr." width="3571" /> <p class="caption">Photo of Herbert Carter Jr.</p> </div> #### ~500 oral histories from historical societies, The First Coast, and student-led interviews. #### 1970s to present ] --- class: center # Spatial Data from Oral History Archives .center[ <iframe src="https://mainesoundandstory.com/record/josh-kane/" width="940" height="456" frameBorder="0"></iframe> ] [Josh Kane Interview](https://mainesoundandstory.com/record/josh-kane/) --- class: center # Oral History Transcript .center[ <iframe src="https://mainesoundandstory.s3.us-east-2.amazonaws.com/wp-content/uploads/2023/09/24154031/Kane_Josh_06.22.2023.pdf" width="940" height="456" frameBorder="0"></iframe> ] [Josh Kane Interview Transcript](https://mainesoundandstory.s3.us-east-2.amazonaws.com/wp-content/uploads/2023/09/24154031/Kane_Josh_06.22.2023.pdf) --- # Spatial Data: Audio transcripts <font size="6"> "But we would go up and <strong>fish the channels, which is on the other side of Long [Porcupine] and you could always fish all the way up to Bald Rock and then back to the [southern?]</strong>. You could tow up and down through there and catch a couple of hundred an hour of shrimp on a good day, a couple hundred pounds an hour. So some of the best fishing I’d ever seen was just on that side of that island, just like a whole bunch of boats going back and forth. And shrimp were–it was a lot of shrimp."* </font> .footnote[Kane, Josh, Frenchman Bay Oral History Project, June 22nd, 2023, by Camden Hunt, 22 pages, Maine Sound and Story. Online: https://mainesoundandstory.s3.us-east-2.amazonaws.com/wp-content/uploads/2023/09/24154031/Kane_Josh_06.22.2023.pdf (Last Accessed: 03/18/2024).] --- # Using Text Analysis for Interview Processing ### - Read in the transcript and identify speakers ### - Identify relevant sections for spatial coding ### - Identify information related to key questions --- class: center # Spatial Coding Tool .center[ <iframe src="https://laurie-the-student-baker.shinyapps.io/CodingSpatialMentions/" width="940" height="456" frameBorder="0"></iframe> ] [Josh Kane Interview Transcript](https://mainesoundandstory.s3.us-east-2.amazonaws.com/wp-content/uploads/2023/09/24154031/Kane_Josh_06.22.2023.pdf) --- # Expanding the Spatial Glossary <div class="figure" style="text-align: center"> <img src="images/mos-spatial-glossary.png" alt="Spatial Glossary" width="800" /> <p class="caption">Spatial Glossary</p> </div> Sources of Spatial Data: NOAA Charts, GNIS, Public **Demo:** [MOS Spatial Glossary](https://mos-data-coagis.hub.arcgis.com/apps/a6c101ea5fc643bbb3c7067a0b8d86a4) --- class: left # Where we are now .pull-left[ <img src="images/where_now_101.png" alt="Map with Polygons" width="900" style="display: block; margin: auto;" /> ] .pull-right[ .center[ # **101** ## MS+S Coded Interviews # **18** ## Biographical Mapping Interviews ] ] --- class: left # Future Work ### - Continue to develop data collection and text analysis processes ### - Understand spatial semantics in the marine environment ### - Share the Spatial Glossary and Data Query with others ### - Further develop the uncertainty quantification and spatial classification schemes ### - Explore the potential for Large Language Models --- # Thank You! .left-column[ **College of the Atlantic, Maine Sea Grant, Island Institute, Haley Ward, and Rhumbline Maps**: - Natalie Springuel (Maine Sea Grant) - Todd Little-Siebold, Delphine DeMaisy, Will Draxler, Ilham Santoso, Linnea Goh, Asy Xaytouthor (College of the Atlantic) - Galen Koch (The First Coast/College of the Atlantic/Island Institute) - Ben Meader '10 (Haley Ward) - Nick Battista (Island Institute) **Funding Support:** - The Fund for Maine Islands - The Maine Community Foundation ] .right-column[ **MOS Outputs** .center[ <img src="images/mos-linktree.png" width="150" /> ] - [From the Sea Up](https://www.islandinstitute.org/stories/podcast/) - [Coastal Conversations WERU](https://seagrant.umaine.edu/coastal-conversations-radio-program/) - [Maine Sound + Story Archive:](www.mainesoundandstory.com) - [The First Coast Exhibits](www.thefirstcoast.org) - [Maine Historical Fisheries Atlas](https://mos-data-coagis.hub.arcgis.com/). ] --- class: inverse, center, middle # Additional slides ??? --- # Text Analysis In Practice - packages ``` r library(pdftools) # read in pdf library(tidyverse) # data wrangling and visualization library(tidytext) # text analysis library(stopwords) # stop words ``` --- # In Practice - reading in the transcript ``` r kane_full_text <- pdftools::pdf_text(pdf = "../data/Kane_Josh_06.22.2023.pdf") # convert text to string kane_full_text <- toString(kane_full_text) # convert text to character lines kane <- read_lines(kane_full_text) kane <- tibble(kane) kane <- kane %>% rename(text = kane) %>% filter(text != "") %>% mutate(interview_section = if_else(str_detect(text, pattern = "0:00:00"), "main", NA)) %>% fill(interview_section, .direction = "down") %>% filter(interview_section == "main") ``` --- # In Practice - identifying speakers ``` r kane <- kane %>% mutate(initials = str_extract(text, pattern = "[A-Z]{1,3}\\:")) %>% mutate(initials = str_replace(initials, pattern = ":", replacement = "")) %>% fill(initials, .direction = "down") %>% filter(is.na(initials) == FALSE) %>% mutate(text = str_replace_all(text, "[A-Z]{1,3}:", "")) %>% mutate(group = cumsum(initials != lag(initials, default = ""))) kane <- kane %>% group_by(initials, group) %>% summarise(text = str_c(text, collapse = " ")) %>% mutate(text = str_squish(text)) %>% ungroup() %>% arrange(group) ``` --- # Text Analysis Steps --- # Transcript Text
--- # Searching for locations code ``` r locations <- "bar harbor|Bar Harbor|Frenchman|frenchman|bay|Bay|porcupine|Porcupine|island|Island|Bar|bar" kane %>% filter(initials == "JK") %>% filter(str_detect(text, pattern = locations)) %>% DT::datatable() ``` --- # Searching for locations
--- # Searching for species code ``` r species <- "shrimp|Shrimp|Halibut|halibut|Lobster|lobster|Pogies|pogies|Menhayden|menhayden" kane %>% filter(initials == "JK") %>% filter(str_detect(text, pattern = species)) %>% DT::datatable() ``` --- # Searching for species
--- # Breaking down into words ``` r kane %>% unnest_tokens(word, text, token='words') ``` ``` ## # A tibble: 8,732 × 3 ## initials group word ## <chr> <int> <chr> ## 1 JK 1 basically ## 2 CH 2 that’s ## 3 CH 2 great ## 4 CH 2 perfect ## 5 CH 2 so ## 6 CH 2 then ## 7 CH 2 we ## 8 CH 2 can ## 9 CH 2 go ## 10 CH 2 ahead ## # ℹ 8,722 more rows ``` --- # Parts of Speech ``` r kane %>% unnest_tokens(word, text, token='words') %>% inner_join(parts_of_speech, relationship = "many-to-many") ``` ``` ## # A tibble: 19,502 × 4 ## initials group word pos ## <chr> <int> <chr> <chr> ## 1 JK 1 basically Adverb ## 2 CH 2 great Adjective ## 3 CH 2 great Adverb ## 4 CH 2 great Noun ## 5 CH 2 perfect Adjective ## 6 CH 2 perfect Noun ## 7 CH 2 perfect Verb (usu participle) ## 8 CH 2 perfect Verb (transitive) ## 9 CH 2 so Noun ## 10 CH 2 so Adverb ## # ℹ 19,492 more rows ``` --- # Prepositions and parts of speech ``` r kane %>% unnest_tokens(word, text, token='words') %>% inner_join(parts_of_speech, relationship = "many-to-many") %>% filter(pos == "Preposition") %>% count(word) %>% arrange(desc(n)) ``` ``` ## # A tibble: 48 × 2 ## word n ## <chr> <int> ## 1 of 202 ## 2 to 187 ## 3 a 173 ## 4 in 118 ## 5 but 99 ## 6 up 74 ## 7 for 57 ## 8 on 57 ## 9 like 53 ## 10 out 47 ## # ℹ 38 more rows ``` --- class: center # Spatial Classification Scheme <figure> <img src="images/spatial_classification_scheme.png" alt="Diagram" width="650" height="450"> <figcaption>Figure 4. Spatial classification scheme by geomethod.</figcaption> </figure> --- # Spatial Data: Biographical Mapping Interviews <div class="figure" style="text-align: center"> <img src="images/fb-jp-ex.jpeg" alt="Spatial Interview: Frenchman Bay Coding Example 1" width="500" /> <p class="caption">Spatial Interview: Frenchman Bay Coding Example 1</p> </div> --- # Spatial Data: Map Overlay <div class="figure" style="text-align: center"> <img src="images/fb-jp-map-overlay-opaque.png" alt="Spatial Interview: Frenchman Bay Coding Example" width="800" /> <p class="caption">Spatial Interview: Frenchman Bay Coding Example</p> </div> --- # Spatial Data: Digitization <div class="figure" style="text-align: center"> <img src="images/fb-jp-ex-polygon-large.png" alt="Spatial Interview: Frenchman Bay Coding Example" width="800" /> <p class="caption">Spatial Interview: Frenchman Bay Coding Example</p> </div> --- # Spatial Data: Audio transcripts <font size="6"> "But we would go up and <strong>fish the channels, which is on the other side of Long [Porcupine] and you could always fish all the way up to Bald Rock and then back to the [southern?]</strong>. You could tow up and down through there and catch a couple of hundred an hour of shrimp on a good day, a couple hundred pounds an hour. So some of the best fishing I’d ever seen was just on that side of that island, just like a whole bunch of boats going back and forth. And shrimp were–it was a lot of shrimp."* </font> .footnote[Kane, Josh, Frenchman Bay Oral History Project, June 22nd, 2023, by Camden Hunt, 22 pages, Maine Sound and Story. Online: https://mainesoundandstory.s3.us-east-2.amazonaws.com/wp-content/uploads/2023/09/24154031/Kane_Josh_06.22.2023.pdf (Last Accessed: 03/18/2024).] --- # Shrimp Tow: Referential <div class="figure" style="text-align: center"> <img src="images/shrimp_trawl_large.png" alt="Shrimp Tow" width="600" /> <p class="caption">Shrimp Tow</p> </div> --- class: center # Database Structure .left-column[ <figure> <img src="images/database_structure.png" alt="Diagram" width="650" height="450"> <figcaption>Figure 2. MOS - Database Basic Structure.</figcaption> </figure> ] .right-column[ ## - Who? ## - What? ## - Where? ## - When? ] ??? Spatial activities are categorized by coders by their domain, subdomain, and observation type to create a set of standardized observations that can be reliably compared later using queries, summaries, and other systematic methods (Figure 3). --- class: center # Project Codebook <figure> <img src="images/codebook.png" alt="Diagram" width="700" height="475"> <figcaption>Figure 3. Subset of the codebook showing the domain, subdomain, and data fields.</figcaption> </figure> ??? The spatial information for each activity is then classified by the geomethod and type of spatial information conveyed (Figure 4). - **Domain** Activity Classification (Fisheries, Aquaculture, Recreation) - **Subdomain** Subcategorization and specificity for observations (e.g. by species for fishing) --- # Future Work: Marine Prepositions <div class="figure" style="text-align: center"> <img src="images/prepositions.jpeg" alt="Prepositions" width="600" /> <p class="caption">Prepositions</p> </div> - Understanding prepositions in a marine context.