MBON Community Practiceshttps://repository.oceanbestpractices.org/handle/11329/8352024-03-29T08:00:29Z2024-03-29T08:00:29ZA Marine Biodiversity Observation Network for Genetic Monitoring of Hard-Bottom Communities (ARMS-MBON).Obst, MatthiasExter, KatrinaAllcock, A. LouiseArvanitidis, ChristosAxberg, AlizzBustamante, MariaCancio, IbonCarreira-Flores, DiegoChatzinikolaou, EvaChatzigeorgiou, GiorgosChrismas, NathanClark, Melody S.Comtet, ThierryDailianis, ThanosDavies, NeilDeneudt, Klaasde Cerio, Oihane DiazFortic, AnaGerovasileiou, VasilisHablutzel, PascalKeklikoglou, KleonikiKotoulas, GeorgiosLasota, RafalLeite, Barbara R.Loisel, StephaneLeveque, LaurentLevy, LirazMalachowicz, MagdalenaMavria, BorutMeyer, ChristopherMortelmans, JonasNorkko, JoannaPade, NicolasPower, Anne MarieRamsak, AndrejaReiss, HenningSolbakken, JosteinStoehr, Peter A.Sundberg, PerThyrring, JacobTroncoso, Jesus S.Viard, FrederiqueWenne, RomanYperifanou, Eleni LoannaZbawicka, MalgorzataPavloudi, Christinahttps://repository.oceanbestpractices.org/handle/11329/21792023-04-16T13:00:38Z2020-01-01T00:00:00ZA Marine Biodiversity Observation Network for Genetic Monitoring of Hard-Bottom Communities (ARMS-MBON).
Obst, Matthias; Exter, Katrina; Allcock, A. Louise; Arvanitidis, Christos; Axberg, Alizz; Bustamante, Maria; Cancio, Ibon; Carreira-Flores, Diego; Chatzinikolaou, Eva; Chatzigeorgiou, Giorgos; Chrismas, Nathan; Clark, Melody S.; Comtet, Thierry; Dailianis, Thanos; Davies, Neil; Deneudt, Klaas; de Cerio, Oihane Diaz; Fortic, Ana; Gerovasileiou, Vasilis; Hablutzel, Pascal; Keklikoglou, Kleoniki; Kotoulas, Georgios; Lasota, Rafal; Leite, Barbara R.; Loisel, Stephane; Leveque, Laurent; Levy, Liraz; Malachowicz, Magdalena; Mavria, Borut; Meyer, Christopher; Mortelmans, Jonas; Norkko, Joanna; Pade, Nicolas; Power, Anne Marie; Ramsak, Andreja; Reiss, Henning; Solbakken, Jostein; Stoehr, Peter A.; Sundberg, Per; Thyrring, Jacob; Troncoso, Jesus S.; Viard, Frederique; Wenne, Roman; Yperifanou, Eleni Loanna; Zbawicka, Malgorzata; Pavloudi, Christina
Marine hard-bottom communities are undergoing severe change under the influence of multiple drivers, notably climate change, extraction of natural resources, pollution and eutrophication, habitat degradation, and invasive species. Monitoring marine biodiversity in such habitats is, however, challenging as it typically involves expensive, non-standardized, and often destructive sampling methods that limit its scalability. Differences in monitoring approaches furthermore hinders inter-comparison among monitoring programs. Here, we announce a Marine Biodiversity Observation Network (MBON) consisting of Autonomous Reef Monitoring Structures (ARMS) with the aim to assess the status and changes in benthic fauna with genomic-based methods, notably DNA metabarcoding, in combination with image-based identifications. This article presents the results of a 30-month pilot phase in which we established an operational and geographically expansive ARMS-MBON. The network currently consists of 20 observatories distributed across European coastal waters and the polar regions, in which 134 ARMS have been deployed to date. Sampling takes place annually, either as short-term deployments during the summer or as long-term deployments starting in spring. The pilot phase was used to establish a common set of standards for field sampling, genetic analysis, data management, and legal compliance, which are presented here. We also tested the potential of ARMS for combining genetic and image-based identification methods in comparative studies of benthic diversity, as well as for detecting non-indigenous species. Results show that ARMS are suitable for monitoring hard-bottom environments as they provide genetic data that can be continuously enriched, re-analyzed, and integrated with conventional data to document benthic community composition and detect non-indigenous species. Finally, we provide guidelines to expand the network and present a sustainability plan as part of the European Marine Biological Resource Centre (www.embrc.eu).
2020-01-01T00:00:00ZSatellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems.Muller-Karger, Frank E.Hestir, ErinAde, ChristianaTurpie, KevinRoberts, Dar A.Siegel, DavidMiller, Robert J.Humm, DavidIzenberg, NoamKeller, MaryMorgan, FrankFrouin, RobertDekker, Arnold G.Gardner, RoyalGoodman, JamesSchaeffer, BlakeFranz, Bryan A.Pahlevan, NimaMannino, Antonio G.Concha, Javier A.Ackleson, Steven G.Cavanaugh, Kyle C.Romanou, AnastasiaTzortziou, MariaBoss, Emmanuel S.Pavlick, RyanFreeman, AnthonyRousseaux, Cecile S.Dunne, JohnLong, Matthew C.Klein, EduardoMcKinley, Galen A.Goes, JoachimLetelier, RicardoKavanaugh, MariaRoffer, MitchellBracher, AstridArrigo, Kevin R.Dierssen, HeidiZhang, XiaodongDavis, Frank W.Best, BenGuralnick, RobertMoisan, JohnSosik, Heidi M.Kudela, RaphaelMouw, Colleen B.Barnard, Andrew H.Palacios, SherryRoesler, CollinDrakou, Evangelia G.Appeltans, WardJetz, Walterhttps://repository.oceanbestpractices.org/handle/11329/20552022-08-21T19:31:39Z2018-01-01T00:00:00ZSatellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems.
Muller-Karger, Frank E.; Hestir, Erin; Ade, Christiana; Turpie, Kevin; Roberts, Dar A.; Siegel, David; Miller, Robert J.; Humm, David; Izenberg, Noam; Keller, Mary; Morgan, Frank; Frouin, Robert; Dekker, Arnold G.; Gardner, Royal; Goodman, James; Schaeffer, Blake; Franz, Bryan A.; Pahlevan, Nima; Mannino, Antonio G.; Concha, Javier A.; Ackleson, Steven G.; Cavanaugh, Kyle C.; Romanou, Anastasia; Tzortziou, Maria; Boss, Emmanuel S.; Pavlick, Ryan; Freeman, Anthony; Rousseaux, Cecile S.; Dunne, John; Long, Matthew C.; Klein, Eduardo; McKinley, Galen A.; Goes, Joachim; Letelier, Ricardo; Kavanaugh, Maria; Roffer, Mitchell; Bracher, Astrid; Arrigo, Kevin R.; Dierssen, Heidi; Zhang, Xiaodong; Davis, Frank W.; Best, Ben; Guralnick, Robert; Moisan, John; Sosik, Heidi M.; Kudela, Raphael; Mouw, Colleen B.; Barnard, Andrew H.; Palacios, Sherry; Roesler, Collin; Drakou, Evangelia G.; Appeltans, Ward; Jetz, Walter
The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the
foundation for important benefits to human societies around the world. These globally distributed
habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction
of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance
spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton
groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically
structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and
algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including
the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat
fragmentation. However, current and planned satellites are not designed to observe the EBVs that
change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat
destruction over scales relevant to human activity. Making these observations requires a new generation
of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the
order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and
10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630,
2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radio-
metric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open
ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization
sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize
sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4
imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity
and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d
repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily.
Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations
are now feasible and are used in various applications.
2018-01-01T00:00:00ZBest practices for implementing the STAVIRO underwater video protocol. [VIDEO]Pelletier, DominiqueCadé, FlorentPearlman, JayLara-Lopez, AnaRoos, Davidhttps://repository.oceanbestpractices.org/handle/11329/19392023-11-27T16:01:01Z2022-01-01T00:00:00ZBest practices for implementing the STAVIRO underwater video protocol. [VIDEO]
Pelletier, Dominique; Cadé, Florent; Pearlman, Jay; Lara-Lopez, Ana; Roos, David
Essential Biodiversity variables (EBV) related to benthic habitats and high trophic levels such as fish communities must be measured at fine scale but monitored and assessed at spatial scales that are relevant for policy and management actions. Local scales, such as individual marine parks, are important for assessing anthropogenic impacts, and conservation-related and fisheries management actions, while reporting on the conservation status of biodiversity to formulate national and international policies requires much broader scales. Measurements must account for the fact that coastal habitats and fish communities are heterogeneously distributed locally and at larger scales. Assessments based on in situ monitoring generally suffer from poor spatial replication and limited geographical coverage, which is challenging for area-wide assessments. Requirements for appropriate monitoring comprise cost-efficient and standardized observation protocols and data formats, spatially-scalable and versatile data workflows, data that comply with the FAIR (Findable, Accessible, Interoperable and Reusable) principles, while minimizing the environmental impact of measurements. This panoramic unbaited video technique was developed in 2007 to survey both fishes and benthic habitats in a cost-efficient manner, and with minimal effect on biodiversity. It can be deployed in areas where low underwater visibility is not a permanent or major limitation. The technique was consolidated and standardized and has been successfully used in varied settings over the last twelve years. We operationalized the EBV workflow by documenting the field protocol, survey design, image post-processing, EBV production and data curation. The STAVIRO’s proven track-record of utility and cost-effectiveness indicates that it should be considered by other researchers for future applications.
2022-01-01T00:00:00ZA standardized workflow based on the STAVIRO unbaited underwater video system for monitoring fish and habitat essential biodiversity variables in coastal areas.Pelletier, DominiqueRoos, DavidBouchoucha, MarcSchohn, ThomasRoman, WilliamGonson, CharlesBockel, ThomasCarpentier, LilianePreuss, BastienPowell, AbigailGarcia, JessicaGaboriau, MatthiasCade, FlorentRoyaux, ColineLe Bras, YvanReecht, Yveshttps://repository.oceanbestpractices.org/handle/11329/19192022-05-24T08:40:31Z2021-01-01T00:00:00ZA standardized workflow based on the STAVIRO unbaited underwater video system for monitoring fish and habitat essential biodiversity variables in coastal areas.
Pelletier, Dominique; Roos, David; Bouchoucha, Marc; Schohn, Thomas; Roman, William; Gonson, Charles; Bockel, Thomas; Carpentier, Liliane; Preuss, Bastien; Powell, Abigail; Garcia, Jessica; Gaboriau, Matthias; Cade, Florent; Royaux, Coline; Le Bras, Yvan; Reecht, Yves
Essential Biodiversity variables (EBV) related to benthic habitats and high trophic levels such as fish communities must be measured at fine scale but monitored and assessed at spatial scales that are relevant for policy and management actions. Local scales, such as individual marine parks, are important for assessing anthropogenic impacts, and conservation-related and fisheries management actions, while reporting on the conservation status of biodiversity to formulate national and international policies requires much broader scales. Measurements must account for the fact that coastal habitats and fish communities are heterogeneously distributed locally and at larger scales. Assessments based on in situ monitoring generally suffer from poor spatial replication and limited geographical coverage, which is challenging for area-wide assessments. Requirements for appropriate monitoring comprise cost-efficient and standardized observation protocols and data formats, spatially-scalable and versatile data workflows, data that comply with the FAIR (Findable, Accessible, Interoperable and Reusable) principles, while minimizing the environmental impact of measurements.
This paper describes a standardized workflow based on remote underwater video that aims to assess fishes (at species and community levels) and habitat-related EBVs in coastal areas. This panoramic unbaited video technique was developed in 2007 to survey both fishes and benthic habitats in a cost-efficient manner, and with minimal effect on biodiversity. It can be deployed in areas where low underwater visibility is not a permanent or major limitation. The technique was consolidated and standardized and has been successfully used in varied settings over the last twelve years. We operationalized the EBV workflow by documenting the field protocol, survey design, image post-processing, EBV production and data curation. Applications of the workflow are illustrated here based on some 4500 observations (fishes and benthic habitats) in the Pacific, Indian and Atlantic Oceans, and Mediterranean Sea. The STAVIRO’s proven track-record of utility and cost-effectiveness indicates that it should be considered by other researchers for future applications.
2021-01-01T00:00:00ZWebenizing Condition Reports: Communicating Data-Driven Ecosystem Indicators in a Visually Engaging and Interactive Online Platform.Spector, PikeBest, BenRaganathan, JaiMurray, TylarBrown, JenniferCaldow, ChrisCanonico, GabrielleDeVogelaere, Andrewhttps://repository.oceanbestpractices.org/handle/11329/18912022-03-10T00:58:00Z2021-01-01T00:00:00ZWebenizing Condition Reports: Communicating Data-Driven Ecosystem Indicators in a Visually Engaging and Interactive Online Platform.
Spector, Pike; Best, Ben; Raganathan, Jai; Murray, Tylar; Brown, Jennifer; Caldow, Chris; Canonico, Gabrielle; DeVogelaere, Andrew
The compilation and release of data-driven reports is one of the core functions of natural
resource agencies and offices that support scientific investigations. Often, these reports contain
data and synthesis related to an ecosystem’s “state” or the status and trends of driving forces
and the related condition of ecological indicators. These reports are often data and text rich and
may be difficult for non-technical audiences to interpret. Further, because these reports may
take years to compile and finalize, the data presented may be outdated by the time they are
published. Status and trend reports, such as condition reports released by the Office of National
Marine Sanctuaries, may need to target a wide swath of technical and non-technical audiences
as stakeholders with interests in a national marine sanctuary’s resources. Here, we introduce the
webenized condition report (WebCR) as a digital companion to the published technical
condition report (and similar reports) for increasing stakeholder engagement and accessibility
while fostering timely understanding of ecosystem status and trends. The WebCR, built using
open-source software, combines artwork depicting ecosystems, habitats, species, and human
uses with related, data-driven content in the form of figures containing static or interactive
charts, maps, and accompanying captions. The intuitive visual navigation combined with timely
updates using a free and reproducible back-end system means that data providers and end users
all benefit from this novel framework. Through an iterative process combined with stakeholder
engagement, the WebCR has been made to specifically target the needs of a broad audience,
including resources managers, educators, academic researchers and the general public. The
WebCR’s design is fully realized across a range of habitats and ecosystems, and can be applied
broadly to disparate use cases. Here we describe the motivation for the WebCR, elements of its
framework, a suite of examples for reuse elsewhere, the WebCR for Channel Islands National
Marine Sanctuary, and next steps in a development pathway
2021-01-01T00:00:00ZBiological Observation Data Standardization - A Primer for Data Managers.Benson, AbigailLaScala-Gruenewald, DianaMcGuinn, RobertSatterthwaite, ErinBeaulieu, StaceBiddle, MathewdeWitt, LynnMcKinzie, MeganMontes, EnriqueMoustahfid, HassanMuller-Karger, FrankMurray, TylarVan de Putte, Antonhttps://repository.oceanbestpractices.org/handle/11329/18522022-01-19T21:00:41Z2021-01-01T00:00:00ZBiological Observation Data Standardization - A Primer for Data Managers.
Benson, Abigail; LaScala-Gruenewald, Diana; McGuinn, Robert; Satterthwaite, Erin; Beaulieu, Stace; Biddle, Mathew; deWitt, Lynn; McKinzie, Megan; Montes, Enrique; Moustahfid, Hassan; Muller-Karger, Frank; Murray, Tylar; Van de Putte, Anton
Lots of standards exist for use with biological data but navigating them can be difficult for data managers who are new to them. The Earth Science Information Partners (ESIP) Biological Data Standards Cluster developed this primer for managers of biological data to provide a quick, easy resource for navigating a selection of the standards that exist. The goal of the primer is to spread awareness about existing standards and is intended to be shared online and at conferences to increase the adoption of standards for biological data and make them FAIR.
2021-01-01T00:00:00ZOptimizing large-scale biodiversity sampling effort: toward an unbalanced survey design.Montes, EnriqueLefcheck, Jonathan S.Guerra-Castro, EdlinKlein, EduardoKavanaugh, Maria T.de Azevedo Mazzuco, Ana CarolinaBigatti, GregorioCordeiro, Cesar A.M.M.Simoes, NunoMacaya, Erasmo C.Moity, NicolasLondoño-Cruz, EdgardoHelmuth, BrianChoi, FrancisSoto, Eulogio H.Miloslavich, PatriciaMuller-Karger, Frank E.https://repository.oceanbestpractices.org/handle/11329/18362022-01-04T16:33:57Z2021-01-01T00:00:00ZOptimizing large-scale biodiversity sampling effort: toward an unbalanced survey design.
Montes, Enrique; Lefcheck, Jonathan S.; Guerra-Castro, Edlin; Klein, Eduardo; Kavanaugh, Maria T.; de Azevedo Mazzuco, Ana Carolina; Bigatti, Gregorio; Cordeiro, Cesar A.M.M.; Simoes, Nuno; Macaya, Erasmo C.; Moity, Nicolas; Londoño-Cruz, Edgardo; Helmuth, Brian; Choi, Francis; Soto, Eulogio H.; Miloslavich, Patricia; Muller-Karger, Frank E.
Acquiring marine biodiversity data is difficult, costly, and timeconsuming,
making it challenging to understand the distribution and abundance of life
in the ocean. Historically, approaches to biodiversity sampling over large geographic
scales have advocated for equivalent effort across multiple sites to minimize comparative
bias. When effort cannot be equalized, techniques such as rarefaction have been
applied to minimize biases by reverting diversity estimates to equivalent numbers of
samples or individuals. This often results in oversampling and wasted resources or
inaccurately characterized communities due to undersampling. How, then, can we better
determine an optimal survey design for characterizing species richness and community
composition across a range of conditions and capacities without compromising
taxonomic resolution and statistical power? Researchers in the Marine Biodiversity
Observation Network Pole to Pole of the Americas (MBON Pole to Pole) are surveying
rocky shore macroinvertebrates and algal communities spanning ~107° of latitude
and 10 biogeographic ecoregions to address this question. Here, we apply existing techniques
in the form of fixed-coverage subsampling and a complementary multivariate
analysis to determine the optimal effort necessary for characterizing species richness
and community composition across the network sampling sites. We show that oversampling
for species richness varied between ~20% and 400% at over half of studied
areas, while some locations were undersampled by up to 50%. Multivariate error analysis
also revealed that most of the localities were oversampled by several-fold for benthic
community composition. From this analysis, we advocate for an unbalanced sampling
approach to support field programs in the collection of high-quality data, where preliminary
information is used to set the minimum required effort to generate robust values
of diversity and composition on a site-to-site basis. As part of this recommendation,
we provide statistical tools in the open-source R statistical software to aid researchers in
implementing optimization strategies and expanding the geographic footprint or sampling
frequency of regional biodiversity survey programs.
2021-01-01T00:00:00ZPublishing DNA-derived data through biodiversity data platforms. version 1.0.Andersson, A.F.Bissett, A.Finstad, A.G.Fossøy, F.Grosjean, M.Hope, M.Jeppesen, T.S.Kõljalg, U.Lundin, D.Nilsson, R.N.Prager, M.Svenningsen, C.Schigel, D.https://repository.oceanbestpractices.org/handle/11329/17262021-09-24T21:08:59Z2020-01-01T00:00:00ZPublishing DNA-derived data through biodiversity data platforms. version 1.0.
Andersson, A.F.; Bissett, A.; Finstad, A.G.; Fossøy, F.; Grosjean, M.; Hope, M.; Jeppesen, T.S.; Kõljalg, U.; Lundin, D.; Nilsson, R.N.; Prager, M.; Svenningsen, C.; Schigel, D.
When genetic information is used to describe or classify a taxon, most users will foresee its use in
the context of molecular ecology or phylogenetic research. It is important to realize that a sequence
with coordinates and a timestamp is a valuable biodiversity occurrence which is useful in a much
broader context than its original purpose. To realize this potential, DNA-derived data needs to be
discoverable through biodiversity data platforms. This guide will teach you the principles and
approaches of exposing “sequences with dates and coordinates” in the context of broader
biodiversity data. The guide covers choices of particular schemas and terms, common pitfalls and
good practice, without going into platform-specific details. It will benefit anyone interested in better
exposure of DNA-derived data through general biodiversity data platforms, including national
biodiversity portals.
2020-01-01T00:00:00ZAdvancing Marine Biological Observations and Data Requirements of the Complementary Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) Frameworks.Muller-Karger, Frank E.Miloslavich, PatriciaBax, Nicholas J.Simmons, SamanthaCostello, Mark J.Pinto, Isabel SousaCanonico, GabrielleTurner, WoodyGill, MichaelMontes, EnriqueBest, Benjamin D.Pearlman, JayHalpin, PatrickDunn, DanielBenson, AbigailMartin, Corinne S.Weatherdon, Lauren V.Appeltans, WardProvoost, PieterKlein, EduardoKelble, Christopher R.Miller, Robert J.Chavez, Francisco P.Iken, KatrinChiba, SanaeObura, DavidNavarro, Laetitia M.Pereira, Henrique M.Allain, ValerieBatten, SoniaBenedetti-Checchi, LisandroDuffy, J. EmmettKudela, Raphael M.Rebelo, Lisa-MariaShin, YunneGeller, Garyhttps://repository.oceanbestpractices.org/handle/11329/13402020-05-26T22:48:30Z2018-01-01T00:00:00ZAdvancing Marine Biological Observations and Data Requirements of the Complementary Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) Frameworks.
Muller-Karger, Frank E.; Miloslavich, Patricia; Bax, Nicholas J.; Simmons, Samantha; Costello, Mark J.; Pinto, Isabel Sousa; Canonico, Gabrielle; Turner, Woody; Gill, Michael; Montes, Enrique; Best, Benjamin D.; Pearlman, Jay; Halpin, Patrick; Dunn, Daniel; Benson, Abigail; Martin, Corinne S.; Weatherdon, Lauren V.; Appeltans, Ward; Provoost, Pieter; Klein, Eduardo; Kelble, Christopher R.; Miller, Robert J.; Chavez, Francisco P.; Iken, Katrin; Chiba, Sanae; Obura, David; Navarro, Laetitia M.; Pereira, Henrique M.; Allain, Valerie; Batten, Sonia; Benedetti-Checchi, Lisandro; Duffy, J. Emmett; Kudela, Raphael M.; Rebelo, Lisa-Maria; Shin, Yunne; Geller, Gary
Measurements of the status and trends of key indicators for the ocean and
marine life are required to inform policy and management in the context of
growing human uses of marine resources, coastal development, and climate change.
Two synergistic efforts identify specific priority variables for monitoring: Essential
Ocean Variables (EOVs) through the Global Ocean Observing System (GOOS),
and Essential Biodiversity Variables (EBVs) from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (see Data Sheet 1 in Supplementary
Materials for a glossary of acronyms). Both systems support reporting against
internationally agreed conventions and treaties. GOOS, established under the auspices
of the Intergovernmental Oceanographic Commission (IOC), plays a leading role in
coordinating global monitoring of the ocean and in the definition of EOVs. GEO
BON is a global biodiversity observation network that coordinates observations to
enhance management of the world’s biodiversity and promote both the awareness
and accounting of ecosystem services. Convergence and agreement between these
two efforts are required to streamline existing and new marine observation programs
to advance scientific knowledge effectively and to support the sustainable use and
management of ocean spaces and resources. In this context, the Marine Biodiversity
Observation Network (MBON), a thematic component of GEO BON, is collaborating with
GOOS, the Ocean Biogeographic Information System (OBIS), and the Integrated Marine
Biosphere Research (IMBeR) project to ensure that EBVs and EOVs are complementary,
representing alternative uses of a common set of scientific measurements. This work is
informed by the Joint Technical Commission for Oceanography and Marine Meteorology
(JCOMM), an intergovernmental body of technical experts that helps international
coordination on best practices for observing, data management and services, combined
with capacity development expertise. Characterizing biodiversity and understanding its
drivers will require incorporation of observations fromtraditional andmolecular taxonomy,
animal tagging and tracking efforts, ocean biogeochemistry, and ocean observatory
initiatives including the deep ocean and seafloor. The partnership between large-scale
ocean observing and product distribution initiatives (MBON, OBIS, JCOMM, and GOOS)
is an expedited, effective way to support international policy-level assessments (e.g.,
the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services
or IPBES), along with the implementation of international development goals (e.g., the
United Nations Sustainable Development Goals).
2018-01-01T00:00:00ZEssential biodiversity variables for mapping and monitoring species populations.Jetz, WalterMcGeoch, Melodie A.Guralnick, RobertFerrier, SimonBeck, JanCostello, Mark J.Fernandez, MiguelGeller, Gary N.Keil, PetrMerow, CoryMeyer, CarstenMuller-Karger, Frank E.Pereira, Henrique M.Regan, Eugenie C.Schmeller, Dirk S.Turak, Erenhttps://repository.oceanbestpractices.org/handle/11329/13232020-05-05T22:48:31Z2019-01-01T00:00:00ZEssential biodiversity variables for mapping and monitoring species populations.
Jetz, Walter; McGeoch, Melodie A.; Guralnick, Robert; Ferrier, Simon; Beck, Jan; Costello, Mark J.; Fernandez, Miguel; Geller, Gary N.; Keil, Petr; Merow, Cory; Meyer, Carsten; Muller-Karger, Frank E.; Pereira, Henrique M.; Regan, Eugenie C.; Schmeller, Dirk S.; Turak, Eren
Species distributions and abundances are undergoing rapid changes worldwide. This highlights the significance of reliable,
integrated information for guiding and assessing actions and policies aimed at managing and sustaining the many functions
and benefits of species. Here we synthesize the types of data and approaches that are required to achieve such an integration
and conceptualize ‘essential biodiversity variables’ (EBVs) for a unified global capture of species populations in space and time.
The inherent heterogeneity and sparseness of raw biodiversity data are overcome by the use of models and remotely sensed
covariates to inform predictions that are contiguous in space and time and global in extent. We define the species population
EBVs as a space–time–species–gram (cube) that simultaneously addresses the distribution or abundance of multiple species,
with its resolution adjusted to represent available evidence and acceptable levels of uncertainty. This essential information
enables the monitoring of single or aggregate spatial or taxonomic units at scales relevant to research and decision-making.
When combined with ancillary environmental or species data, this fundamental species population information directly underpins
a range of biodiversity and ecosystem function indicators. The unified concept we present links disparate data to downstream
uses and informs a vision for species population monitoring in which data collection is closely integrated with models
and infrastructure to support effective biodiversity assessment.
2019-01-01T00:00:00Z