Ruhl
Henry A.
Ruhl
Henry A.
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ArticleBioTIME : a database of biodiversity time series for the Anthropocene(John Wiley & Sons, 2018-07-24) Dornelas, Maria ; Antao, Laura H. ; Moyes, Faye ; Bates, Amanda E. ; Magurran, Anne E. ; Adam, Dusan ; Akhmetzhanova, Asem A. ; Appeltans, Ward ; Arcos, Jose Manuel ; Arnold, Haley ; Ayyappan, Narayanan ; Badihi, Gal ; Baird, Andrew H. ; Barbosa, Miguel ; Barreto, Tiago Egydio ; Bässler, Claus ; Bellgrove, Alecia ; Belmaker, Jonathan ; Benedetti-Cecchi, Lisandro ; Bett, Brian J. ; Bjorkman, Anne D. ; Błazewicz, Magdalena ; Blowes, Shane A. ; Bloch, Christopher P. ; Bonebrake, Timothy C. ; Boyd, Susan ; Bradford, Matt ; Brooks, Andrew J. ; Brown, James H. ; Bruelheide, Helge ; Budy, Phaedra ; Carvalho, Fernando ; Castaneda-Moya, Edward ; Chen, Chaolun Allen ; Chamblee, John F. ; Chase, Tory J. ; Collier, Laura Siegwart ; Collinge, Sharon K. ; Condit, Richard ; Cooper, Elisabeth J. ; Cornelissen, Johannes H. C. ; Cotano, Unai ; Crow, Shannan Kyle ; Damasceno, Gabriella ; Davies, Claire H. ; Davis, Robert A. ; Day, Frank P. ; Degraer, Steven ; Doherty, Tim S. ; Dunn, Timothy E. ; Durigan, Giselda ; Duffy, J. Emmett ; Edelist, Dor ; Edgar, Graham J. ; Elahi, Robin ; Elmendorf, Sarah C. ; Enemar, Anders ; Ernest, S. K. Morgan ; Escribano, Ruben ; Estiarte, Marc ; Evans, Brian S. ; Fan, Tung-Yung ; Farah, Fabiano Turini ; Fernandes, Luiz Loureiro ; Farneda, Fabio Z. ; Fidelis, Alessandra ; Fitt, Robert ; Fosaa, Anna Maria ; Franco, Geraldo Antonio Daher Correa ; Frank, Grace E. ; Fraser, William R. ; García, Hernando ; Gatti, Roberto Cazzolla ; Givan, Or ; Gorgone-Barbosa, Elizabeth ; Gould, William A. ; Gries, Corinna ; Grossman, Gary D. ; Gutierrez, Julio R. ; Hale, Stephen ; Harmon, Mark E. ; Harte, John ; Haskins, Gary ; Henshaw, Donald L. ; Hermanutz, Luise ; Hidalgo, Pamela ; Higuchi, Pedro ; Hoey, Andrew S. ; Hoey, Gert Van ; Hofgaard, Annika ; Holeck, Kristen ; Hollister, Robert D. ; Holmes, Richard ; Hoogenboom, Mia ; Hsieh, Chih-hao ; Hubbell, Stephen P. ; Huettmann, Falk ; Huffard, Christine L. ; Hurlbert, Allen H. ; Ivanauskas, Natalia Macedo ; Janík, David ; Jandt, Ute ; Jazdzewska, Anna ; Johannessen, Tore ; Johnstone, Jill F. ; Jones, Julia ; Jones, Faith A. M. ; Kang, Jungwon ; Kartawijaya, Tasrif ; Keeley, Erin C. ; Kelt, Douglas A. ; Kinnear, Rebecca ; Klanderud, Kari ; Knutsen, Halvor ; Koenig, Christopher C. ; Kortz, Alessandra R. ; Kral, Kamil ; Kuhnz, Linda A. ; Kuo, Chao-Yang ; Kushner, David J. ; Laguionie-Marchais, Claire ; Lancaster, Lesley T. ; Lee, Cheol Min ; Lefcheck, Jonathan S. ; Levesque, Esther ; Lightfoot, David ; Lloret, Francisco ; Lloyd, John D. ; Lopez-Baucells, Adria ; Louzao, Maite ; Madin, Joshua S. ; Magnusson, Borgbor ; Malamud, Shahar ; Matthews, Iain ; McFarland, Kent P. ; McGill, Brian ; McKnight, Diane ; McLarney, William O. ; Meador, Jason ; Meserve, Peter L. ; Metcalfe, Daniel J. ; Meyer, Christoph F. J. ; Michelsen, Anders ; Milchakova, Nataliya ; Moens, Tom ; Moland, Even ; Moore, Jon ; Moreira, Carolina Mathias ; Muller, Jorg ; Murphy, Grace ; Myers-Smith, Isla H. ; Myster, Randall W. ; Naumov, Andrew ; Neat, Francis ; Nelson, James A. ; Nelson, Michael Paul ; Newton, Stephen F. ; Norden, Natalia ; Oliver, Jeffrey C. ; Olsen, Esben M. ; Onipchenko, Vladimir G. ; Pabis, Krzysztof ; Pabst, Robert J. ; Paquette, Alain ; Pardede, Sinta ; Paterson, David M. ; Pelissier, Raphael ; Penuelas, Josep ; Perez-Matus, Alejandro ; Pizarro, Oscar ; Pomati, Francesco ; Post, Eric ; Prins, Herbert H. T. ; Priscu, John C. ; Provoost, Pieter ; Prudic, Kathleen L. ; Pulliainen, Erkki ; Ramesh, B. B. ; Ramos, Olivia Mendivil ; Rassweiler, Andrew ; Rebelo, Jose Eduardo ; Reed, Daniel C. ; Reich, Peter B. ; Remillard, Suzanne M. ; Richardson, Anthony J. ; Richardson, J. Paul ; Rijn, Itai van ; Rocha, Ricardo ; Rivera-Monroy, Victor H. ; Rixen, Christian ; Robinson, Kevin P. ; Rodrigues, Ricardo Ribeiro ; Rossa-Feres, Denise de Cerqueira ; Rudstam, Lars ; Ruhl, Henry A. ; Ruz, Catalina S. ; Sampaio, Erica M. ; Rybicki, Nancy ; Rypel, Andrew ; Sal, Sofia ; Salgado, Beatriz ; Santos, Flavio A. M. ; Savassi-Coutinho, Ana Paula ; Scanga, Sara ; Schmidt, Jochen ; Schooley, Robert ; Setiawan, Fakhrizal ; Shao, Kwang-Tsao ; Shaver, Gaius R. ; Sherman, Sally ; Sherry, Thomas W. ; Sicinski, Jacek ; Sievers, Caya ; da Silva, Ana Carolina ; da Silva, Fernando Rodrigues ; Silveira, Fabio L. ; Slingsby, Jasper ; Smart, Tracey ; Snell, Sara J. ; Soudzilovskaia, Nadejda A. ; Souza, Gabriel B. G. ; Souza, Flaviana Maluf ; Souza, Vinícius Castro ; Stallings, Christopher D. ; Stanforth, Rowan ; Stanley, Emily H. ; Sterza, Jose Mauro ; Stevens, Maarten ; Stuart-Smith, Rick ; Suarez, Yzel Rondon ; Supp, Sarah ; Tamashiro, Jorge Yoshio ; Tarigan, Sukmaraharja ; Thiede, Gary P. ; Thorn, Simon ; Tolvanen, Anne ; Toniato, Maria Teresa Zugliani ; Totland, Orjan ; Twilley, Robert R. ; Vaitkus, Gediminas ; Valdivia, Nelson ; Vallejo, Martha Isabel ; Valone, Thomas J. ; Van Colen, Carl ; Vanaverbeke, Jan ; Venturoli, Fabio ; Verheye, Hans M. ; Vianna, Marcelo ; Vieira, Rui P. ; Vrska, Tomas ; Vu, Con Quang ; Vu, Lien Van ; Waide, Robert B. ; Waldock, Conor ; Watts, David ; Webb, Sara ; Wesołowski, Tomasz ; White, Ethan P. ; Widdicombe, Claire E. ; Wilgers, Wilgers ; Williams, Richard ; Williams, Stefan B. ; Williamson, Mark ; Willig, Michael R. ; Willis, Trevor J. ; Wipf, Sonja ; Woods, Kerry D. ; Woehler, Eric ; Zawada, Kyle ; Zettler, Michael L.The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2). BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
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ArticleMajor impacts of climate change on deep-sea benthic ecosystems(University of California Press, 2017-02-23) Sweetman, Andrew K. ; Thurber, Andrew R. ; Smith, Craig R. ; Levin, Lisa A. ; Mora, Camilo ; Wei, Chih-Lin ; Gooday, Andrew J. ; Jones, Daniel O. B. ; Rex, Michael ; Yasuhara, Moriaki ; Ingels, Jeroen ; Ruhl, Henry A. ; Frieder, Christina A. ; Danovaro, Roberto ; Würzberg, Laura ; Baco, Amy R. ; Grupe, Benjamin ; Pasulka, Alexis ; Meyer, Kirstin S. ; Dunlop, Katherine Mary ; Henry, Lea-Anne ; Roberts, J. MurrayThe deep sea encompasses the largest ecosystems on Earth. Although poorly known, deep seafloor ecosystems provide services that are vitally important to the entire ocean and biosphere. Rising atmospheric greenhouse gases are bringing about significant changes in the environmental properties of the ocean realm in terms of water column oxygenation, temperature, pH and food supply, with concomitant impacts on deep-sea ecosystems. Projections suggest that abyssal (3000–6000 m) ocean temperatures could increase by 1°C over the next 84 years, while abyssal seafloor habitats under areas of deep-water formation may experience reductions in water column oxygen concentrations by as much as 0.03 mL L–1 by 2100. Bathyal depths (200–3000 m) worldwide will undergo the most significant reductions in pH in all oceans by the year 2100 (0.29 to 0.37 pH units). O2 concentrations will also decline in the bathyal NE Pacific and Southern Oceans, with losses up to 3.7% or more, especially at intermediate depths. Another important environmental parameter, the flux of particulate organic matter to the seafloor, is likely to decline significantly in most oceans, most notably in the abyssal and bathyal Indian Ocean where it is predicted to decrease by 40–55% by the end of the century. Unfortunately, how these major changes will affect deep-seafloor ecosystems is, in some cases, very poorly understood. In this paper, we provide a detailed overview of the impacts of these changing environmental parameters on deep-seafloor ecosystems that will most likely be seen by 2100 in continental margin, abyssal and polar settings. We also consider how these changes may combine with other anthropogenic stressors (e.g., fishing, mineral mining, oil and gas extraction) to further impact deep-seafloor ecosystems and discuss the possible societal implications.
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ArticleThe Deep Ocean Observing Strategy: addressing global challenges in the deep sea through collaboration(Marine Technology Society, 2022-06-08) Smith, Leslie M. ; Cimoli, Laura ; LaScala-Gruenewald, Diana ; Pachiadaki, Maria G. ; Phillips, Brennan T. ; Pillar, Helen R. ; Stopa, Justin ; Baumann-Pickering, Simone ; Beaulieu, Stace E. ; Bell, Katherine L. C. ; Harden-Davies, Harriet ; Gjerde, Kristina M. ; Heimbach, Patrick ; Howe, Bruce M. ; Janssen, Felix ; Levin, Lisa A. ; Ruhl, Henry A. ; Soule, S. Adam ; Stocks, Karen ; Vardaro, Michael F. ; Wright, Dawn J.The Deep Ocean Observing Strategy (DOOS) is an international, community-driven initiative that facilitates collaboration across disciplines and fields, elevates a diverse cohort of early career researchers into future leaders, and connects scientific advancements to societal needs. DOOS represents a global network of deep-ocean observing, mapping, and modeling experts, focusing community efforts in the support of strong science, policy, and planning for sustainable oceans. Its initiatives work to propose deep-sea Essential Ocean Variables; assess technology development; develop shared best practices, standards, and cross-calibration procedures; and transfer knowledge to policy makers and deep-ocean stakeholders. Several of these efforts align with the vision of the UN Ocean Decade to generate the science we need to create the deep ocean we want. DOOS works toward (1) a healthy and resilient deep ocean by informing science-based conservation actions, including optimizing data delivery, creating habitat and ecological maps of critical areas, and developing regional demonstration projects; (2) a predicted deep ocean by strengthening collaborations within the modeling community, determining needs for interdisciplinary modeling and observing system assessment in the deep ocean; (3) an accessible deep ocean by enhancing open access to innovative low-cost sensors and open-source plans, making deep-ocean data Findable, Accessible, Interoperable, and Reusable, and focusing on capacity development in developing countries; and finally (4) an inspiring and engaging deep ocean by translating science to stakeholders/end users and informing policy and management decisions, including in international waters.
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ArticleGlobal observing needs in the deep ocean(Frontiers Media, 2019-03-29) Levin, Lisa A. ; Bett, Brian J. ; Gates, Andrew R. ; Heimbach, Patrick ; Howe, Bruce M. ; Janssen, Felix ; McCurdy, Andrea ; Ruhl, Henry A. ; Snelgrove, Paul V. R. ; Stocks, Karen ; Bailey, David ; Baumann-Pickering, Simone ; Beaverson, Chris ; Benfield, Mark C. ; Booth, David J. ; Carreiro-Silva, Marina ; Colaço, Ana ; Eblé, Marie C. ; Fowler, Ashley M. ; Gjerde, Kristina M. ; Jones, Daniel O. B. ; Katsumata, Katsuro ; Kelley, Deborah S. ; Le Bris, Nadine ; Leonardi, Alan P. ; Lejzerowicz, Franck ; Macreadie, Peter I. ; McLean, Dianne ; Meitz, Fred ; Morato, Telmo ; Netburn, Amanda ; Pawlowski, Jan ; Smith, Craig R. ; Sun, Song ; Uchida, Hiroshi ; Vardaro, Michael F. ; Venkatesan, Ramasamy ; Weller, Robert A.The deep ocean below 200 m water depth is the least observed, but largest habitat on our planet by volume and area. Over 150 years of exploration has revealed that this dynamic system provides critical climate regulation, houses a wealth of energy, mineral, and biological resources, and represents a vast repository of biological diversity. A long history of deep-ocean exploration and observation led to the initial concept for the Deep-Ocean Observing Strategy (DOOS), under the auspices of the Global Ocean Observing System (GOOS). Here we discuss the scientific need for globally integrated deep-ocean observing, its status, and the key scientific questions and societal mandates driving observing requirements over the next decade. We consider the Essential Ocean Variables (EOVs) needed to address deep-ocean challenges within the physical, biogeochemical, and biological/ecosystem sciences according to the Framework for Ocean Observing (FOO), and map these onto scientific questions. Opportunities for new and expanded synergies among deep-ocean stakeholders are discussed, including academic-industry partnerships with the oil and gas, mining, cable and fishing industries, the ocean exploration and mapping community, and biodiversity conservation initiatives. Future deep-ocean observing will benefit from the greater integration across traditional disciplines and sectors, achieved through demonstration projects and facilitated reuse and repurposing of existing deep-sea data efforts. We highlight examples of existing and emerging deep-sea methods and technologies, noting key challenges associated with data volume, preservation, standardization, and accessibility. Emerging technologies relevant to deep-ocean sustainability and the blue economy include novel genomics approaches, imaging technologies, and ultra-deep hydrographic measurements. Capacity building will be necessary to integrate capabilities into programs and projects at a global scale. Progress can be facilitated by Open Science and Findable, Accessible, Interoperable, Reusable (FAIR) data principles and converge on agreed to data standards, practices, vocabularies, and registries. We envision expansion of the deep-ocean observing community to embrace the participation of academia, industry, NGOs, national governments, international governmental organizations, and the public at large in order to unlock critical knowledge contained in the deep ocean over coming decades, and to realize the mutual benefits of thoughtful deep-ocean observing for all elements of a sustainable ocean.
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ArticleThe distribution of benthic biomass in hadal trenches : a modelling approach to investigate the effect of vertical and lateral organic matter transport to the seafloor(Elsevier, 2015-02-19) Ichino, Matteo C. ; Clark, Malcolm R. ; Drazen, Jeffrey C. ; Jamieson, Alan ; Jones, Daniel O. B. ; Martin, Adrian P. ; Rowden, Ashley A. ; Shank, Timothy M. ; Yancey, Paul H. ; Ruhl, Henry A.Most of our knowledge about deep-sea habitats is limited to bathyal (200–3000 m) and abyssal depths (3000–6000 m), while relatively little is known about the hadal zone (6000–11,000 m). The basic paradigm for the distribution of deep seafloor biomass suggests that the reduction in biomass and average body size of benthic animals along depth gradients is mainly related to surface productivity and remineralisation of sinking particulate organic carbon with depth. However, there is evidence that this pattern is somewhat reversed in hadal trenches by the funnelling of organic sediments, which would result in increased food availability along the axis of the trenches and towards their deeper regions. Therefore, despite the extreme hydrostatic pressure and remoteness from the pelagic food supply, it is hypothesized that biomass can increase with depth in hadal trenches. We developed a numerical model of gravitational lateral sediment transport along the seafloor as a function of slope, using the Kermadec Trench, near New Zealand, as a test environment. We propose that local topography (at a scale of tens of kilometres) and trench shape can be used to provide useful estimates of local accumulation of food and, therefore, patterns of benthic biomass. Orientation and steepness of local slopes are the drivers of organic sediment accumulation in the model, which result in higher biomass along the axis of the trench, especially in the deepest spots, and lower biomass on the slopes, from which most sediment is removed. The model outputs for the Kermadec Trench are in agreement with observations suggesting the occurrence of a funnelling effect and substantial spatial variability in biomass inside a trench. Further trench surveys will be needed to determine the degree to which seafloor currents are important compared with the gravity-driven transport modelled here. These outputs can also benefit future hadal investigations by highlighting areas of potential biological interest, on which to focus sampling effort. Comprehensive exploration of hadal trenches will, in turn, provide datasets for improving the model parameters and increasing predictive power.