The recently increased interest in marine trait-based studies
highlights one general demand – the access to standardized, reference-based
trait information. This demand holds especially true for polar regions, where
the gathering of ecological information is still challenging. The Arctic
Traits Database is a freely accessible online repository
(10.25365/phaidra.49;
https://www.univie.ac.at/arctictraits, last access: 20 February 2019) that fulfils these requests for one important component of
polar marine life, the Arctic benthic macroinvertebrates. It accounts for
(1) obligate traceability of information (every entry is linked to at least
one source), (2) exchangeability among trait platforms (use of most common
download formats), (3) standardization (use of most common terminology and
coding scheme) and (4) user-friendliness (granted by an intuitive
web interface and rapid and easy download options, for the first
time including the option to download a fuzzy coded trait matrix). The combination of
these aspects makes the Arctic Traits Database the currently most
sophisticated online accessible trait platform in (not only) marine ecology
and a role model for prospective databases of other marine compartments or
other (also non-marine) ecosystems. At present the database covers 19 traits
(80 trait categories) and holds altogether 14 242 trait entries for
1911 macro- and megabenthic taxa. Thus, the Arctic Traits Database will
foster and facilitate trait-based approaches in polar regions in the future
and increase our ecological understanding of this rapidly changing system.
Introduction
The interest in trait-based approaches – i.e., such that consider the life
history, morphological, physiological and behavioral characteristics (i.e.,
traits) of species – in the marine realm has been growing tremendously in
the last decades (reviewed in Degen et al., 2018) (Fig. 1). Reasons for the
increasing popularity of these approaches are that they offer a variety of
additional options to solely species-based methods: traits can be analyzed
across wide geographical ranges and across species pools
(Bernhardt-Römermann et al., 2011), and they can be used to calculate a
variety of functional diversity indices (Schleuter et al., 2010), to estimate
functional redundancy (Darr et al., 2014) or as indicators of
ecosystem functioning (Bremner et al., 2006). Given the rapid changes we
observe in many marine regions of the world, and especially in the Arctic
Ocean (Wassmann et al., 2011), the potential to indicate vulnerability to
climate change and biodiversity loss or to estimate climate change effects
on ecosystem functions is another inherent advantage of trait-based
approaches (Foden et al., 2013; Hewitt et al., 2016).
Cumulative number of marine trait-based studies based on
the literature review of 233 studies from the marine realm by Degen et
al. (2018).
Although the methodical diversity and complexity of trait-based approaches
have broadened in the last years (Beauchard et al., 2017; Kleyer et al.,
2012), the underlying data are always species traits. Trait information,
however, is often not easy to find, and its collation requires a time- and
labor-intensive survey of literature, databases, field data, and expert
knowledge. This holds especially true for the polar regions, as ecological
information for many polar marine taxa is still scarce, and only few
publications supplement traceable resources of trait information (e.g.,
Kokarev et al., 2017). An additional obstacle is that existing trait
repositories focus mainly on species from temperate regions. The increasing
variability in terminology that surrounds traits is another challenge, and
recent publications stress the importance of standardization in order to
facilitate meta-analyses and comparison of results (Costello et al., 2015;
Degen et al., 2018). Several online accessible trait databases specialize in
specific taxonomic groups such as fish, polychaetes or copepods, while
others cover a wider part of the marine community (Table 1). The number of
traits included and the form of access varies considerably among the
different repositories. The database for marine copepods (Brun et al., 2017)
contains 14 traits, whereas Fishbase
(http://www.fishbase.org, last access: 20 February 2019),
polytraits (Faulwetter et al., 2014) and BIOTIC
(MarLIN, 2018, http://www.marlin.ac.uk/biotic, last access: 20 February 2019) contain more than 40 traits. Some repositories allow only for online
browsing, while others enable different forms of download that range from
spreadsheets to different matrix formats (Table 1). No traits repository
explicitly comprising polar species has existed so far.
List of marine trait databases or repositories. “Component”
indicates the organism group targeted. “Access options” indicates in which
forms the data can be accessed. References and web links are provided.
ComponentAccess optionsPublication, web linksCopepodaDownload of Excel workbook via PANGAEA, traits provided as original values or binary code (0/1), references per trait provided.Brun et al. (2017); https://doi.pangaea.de/10.1594/PANGAEA.862968PolychaetaDownload of full database or specified subsets in various formats (references and partly original quote and page number provided), online via browsing the Polychaetes ScratchpadFaulwetter et al. (2014); http://polytraits.lifewatchgreece.eu (last access: 20 February 2019) http://polychaetes.lifewatchgreece.eu (last access: 20 February 2019)BenthosDownload of trait information in several matrix formats: as text and for certain traits as binary (0/1) code, also browsing onlineBiological Traits Information Catalogue (BIOTIC); MarLIN (2018), http://www.marlin.ac.uk/biotic(last access: 20 February 2019)FishBrowse online, programmatically via an application programming interface (API) and R package rfishbaseFroese and Pauly (2018) http://www.fishbase.org, version (02/2018) last access: 20 February 2019BenthosBrowse onlineMarine Macrofauna Genus Trait Handbook; http://www.genustraithandbook.org.uk (last access: 27 June 2018)CoralsBrowse online, download as *.csv file, traits provided as original values or text information, references provided.https://coraltraits.org/ (last access: 20 February 2019)Phytoplankton (coastal)Download of Excel workbook, traits provided as original values or binary code (0/1).Klais et al. (2017); https://www.riinaklais.com/phytotraits(last access: 20 February 2019)All marineBrowse onlineMarine Species Traits; http://www.marinespecies.org/traits (last access: 27 June 2018)All marineBrowse onlineSeaLifeBase; http://www.sealifebase.org(last access: 29 June 2018)Fossil groupsBrowse onlineNeogene Marine Biota of Tropical America (NMiTA); http://eusmilia.geology.uiowa.edu(last access: 29 June 2018)All biotaBrowse online, programmatically via an APIEncyclopedia of Life (EoL); http://www.eol.org (last access: 29 June 2018)
With the Arctic Traits Database presented here we aim to investigate some of the
above-mentioned issues for one important compartment of marine life: the
Arctic macro- and megabenthic invertebrates. In order to fulfil the
communities' demand for standardization and comparability, only those traits
and trait categories are included that are most frequently used in topical
publications or which are already provided in freely accessible trait
databases (Table 1). Regarding download options and traceability, we follow
the successful example given in Faulwetter et al. (2014) and provide download
of trait data in different tabular formats (i.e., data in columns, once
following a database-specific format and once following Darwin Core format)
(Wieczorek et al., 2012). The use of these formats guarantees that the
included trait information can be easily shared between trait repositories
and that the content is fully exploitable both by humans and computers. Every
trait code is backed up by at least one reference, and where possible the
original quote and page number are provided. In addition to the above-mentioned
formats, for the first time trait information has also been made available in a
fuzzy-coded and ready-to-use matrix format that can be directly incorporated
into appropriate analysis software.
By providing the Arctic Traits Database to the community of benthic
ecologists, we aim to provide a sound basis for prospective trait-based
approaches in polar regions which will in return aid our overall
understanding of these unique and rapidly changing ecosystems.
Trait terminology as used in the Arctic Traits Database,
BIOTIC, Costello et al. (2015) and in other marine trait-based studies
(i.e., studies reviewed in Degen et al., 2018, list non-exhaustive; see
Appendix 1 of Degen et al., 2018 for total trait list and corresponding
literature references). Be aware that the Arctic Traits Database and BIOTIC only consider benthic taxa, while Costello et al. (2015) and the studies
summarized in “Other” cover all marine groups.
Arctic Traits DatabaseBIOTICCostello et al. (2015)OtherBody sizeBody sizeBody sizeBody size/length/height, largest radius, biovolume, coverageBody formGrowth form–Body form, body design, body shape, growth form, growth type, functional form group, morphologyFragilityFragility–Fragility, structural robustness, shell strengthSkeleton–SkeletonSkeletal composition/ thickness/material/densitySociabilitySociability–Sociability, schooling, gregariousness, social group size, social behaviorReproductionReproductive typeReproductionReproduction, reproduction type, reproductive method/strategy/type/techniqueLarval developmentDevelopmental mechanism–Larval development, larvae type, larval feeding, larval development location, developmental mode/type/mechanism/techniqueLife spanLife span–Longevity, age, life span, maturity, life duration, generation timeEnvironmental positionEnvironmental position–Environment, environmental position, habitat, vertical distribution, sediment position, living position, life zoneLiving habitLiving habit–Living habit, habit, life habit, life form, habitat, living mode, habitat structureMobility–MobilityMobility, relative mobility, degree of mobility, mobility within sedimentAdult movementMobility/movement–Adult movement, mobility, movement method/type, locomotionFeeding habitFeeding habit–Feeding habit/behavior/method/type/apparatus, resource capture method, trophic mode, oral gape position/height/surface, protrusionTrophic levelTypical food typesDietTrophic level, diet, food type, trophic group, dietary groupBioturbationBioturbation–Bioturbation mode/type/potential, sediment movement/reworking/transport, direction of sediment transport, reworking mode, fecal deposition, irrigationToleranceSalinity–Tolerance, tolerance limits, salinity tolerance, survival salinity/temperature, temperature optimum, thermal affinity, hypoxia tolerance, tolerance to pollutants, ecological group, resilience, condition indexZoogeographyBiogeographic range–Biogeography, geographical range/distribution, range size, native region, median latitudeDepth rangeBiological zoneDepth rangeDepth range/regime, diving depthSubstratum affinitySubstratum affinitySubstratum affinitySubstratum affinity, habitat, habitat preference/type/specificity/complexity, preferred substrate, substrate type, living locationDataTaxon data
The current taxa in the database are a subset of the dataset compiled in the
frame of the “Arctic Traits Project” (Austrian Science Fund FWF, T801-B29),
with a focus on pan-Arctic benthic invertebrate macro- and megafauna. This
dataset comprises species lists from published studies of collaborators
(Blanchard et al., 2013a, b; Grebmeier et al., 2015) but also from
sampling campaigns that are so far unpublished (e.g., field courses of the University Center in Svalbard,
UNIS, 2007–2017). The regional coverage currently comprises the Chukchi Sea
and the Svalbard area. At present, mainly species in the macrofauna size
class have been uploaded.
Trait data
Here, we consider 19 traits and 80 trait categories that reflect the
morphology, life history and the behavior of Arctic benthic invertebrates
(Table 3). All traits are in categorical format; i.e., they belong to one out of
up to six clearly defined trait categories (see Table 3). The three
continuous traits included (body size, life span and depth distribution) are
converted into categories, but the associated text information also assures
accessibility to users in their original numerical or continuous
format.
Detailed information on the 19 biological traits currently
included in the Arctic Traits Database, clustered into morphology traits
(5), life history traits (3) and behavioral traits (11). For every trait
and its categories, the definition as used in the Arctic Traits Database is
given. Abbreviations of each category are given (e.g., S1, S2) as these are
used in files downloaded from the website. The relation of the respective
trait to benthic ecosystem functions or responses (i.e., its role as effect
or response trait) is given via specific examples, and underlying literature
sources are displayed.
MORPHOLOGY Body sizeDefinitionMaximum body size as adult given in millimeters, as individual or colony and excluding appendages. Can be height in rather upright animals (e.g., corals), body width or diameter in rather round animals (e.g., crabs) or body length in elongated animals (e.g., worms).CategoriesS1small<10 mmS2small–medium10–50 mmS3medium50–100 mmS4medium–large100–300 mmS5large>300 mmFunctionSize has a direct effect on productivity, the amount of habitat structuring and facilitation, and it is important for the amount of oxygen and nutrient flux across the sediment–water interface. It correlates with food web structure, trophic levels and energy flow in ecosystems.DetailSmaller animals are faster-growing, usually show a higher productivity and are less affected by trawling as they are more likely to fit through the nets of trawling gear, thus often replacing larger slow-growing fauna in trawl-impacted areas. A clear majority of small-bodied species may be indicative of environments with high instability or be the result of environmental or anthropogenic disturbances. Larger taxa usually show a lower productivity but higher carbon fixation and have a higher effect on fluxes of nutrients, energy and matter. They usually grow slower, reproduce later and are more affected by trawling and other disturbances.ReferencesBolam and Eggleton (2014), Bremner (2008), Costello et al. (2015), Emmerson (2012), Micheli and Halpern (2005), Norkko et al. (2013), van der Linden et al. (2016)Body form DefinitionThe external characteristic of an organism.CategoriesBF1globuloseRound or oval (e.g., sea urchin, sponge, some bivalves)BF2vermiformWorm-likeBF3dorsoventrally compressedSpecies that are flat, or encrusting (e.g., starfish, sponge)BF4laterally compressedThin (e.g., isopods, amphipods, some bivalves)BF5uprighte.g., coral, basket star, spongeFunctionThe body form can be indicative of the ecological role of species in an ecosystem (e.g., if it is habitat-forming) and of its vulnerability to mechanical disturbances (e.g., bottom trawling). Species with an upright body form will be more affected than vermiform or flat ones. Sets restrictions to habitat use and migration capability. Vermiform taxa can be a proxy for litter quality/decomposition.RemarkOften simply a proxy for taxonomy (e.g., vermiform > polychaetes, laterally compressed > amphipods).ReferencesBeauchard et al. (2017), Bolam and Eggleton (2014), Costello et al. (2015), Törnroos and Bonsdorff (2012), Wiedmann et al. (2014)FragilityDefinitionThe degree to which an organism can withstand physical impact. F1fragileLikely to crush, break or crack as a result of physical impact (e.g., brittle star, soft worms, smaller crustaceans, mollusks with thin shells)F2intermediateLiable to suffer minor damage, chips or cracks as a result of physical impacts (e.g., mollusks with thicker shells, animals with harder cuticle like some echinoderms)F3robustUnlikely to be damaged as a result of physical impacts, e.g., hard or tough enough to withstand impact, or leathery or wiry enough to resist impact (e.g., starfish, sponges, tunicates)FunctionDetermines sensitivity to physical disturbance (e.g., bottom trawling) and to predatory aggression. Softer/fragile bodies are more strongly affected by trawling. Indicative of prey accessibility and ease of ingestion.ReferencesBeauchard et al. (2017), Bolam and Eggleton (2014), Weigel et al. (2016)
Continued.
SkeletonDefinitionPresence and type of supporting structures in the animal body.CategoriesSK1calcareousSkeleton material aragonite or calcite (e.g., bivalves)SK2siliceousSkeleton material silicate (e.g., siliceous sponges)SK3chitinousSkeleton material chitin (e.g., arthropods)SK4cuticleNo skeleton but a protective structure like a cuticle (e.g., sea squirts)SK5noneNo form of protective structure (e.g., sea slugs)FunctionIndicates vulnerability (trawling, ocean acidification), resistance to predation (proxy for palatability) and ecosystem engineering (provision of habitat, increased heterogeneity). Large calcifying taxa contribute most to inorganic carbon sequestration.ReferencesCostello et al. (2015), Frid and Caswell (2015, 2016), Spitz et al. (2014)SociabilityDefinitionThe degree to which species aggregate.CategoriesSO1solitarySingle individualSO2gregariousSingle individuals forming groups; growing in clusters (e.g., barnacles)SO3colonialLiving in permanent colonies (e.g., stony corals, Bryozoa, Synascidia)FunctionDetermines sensitivity to physical disturbance (e.g., bottom trawling) and can indicate if a species can increase habitat heterogeneity or is habitat forming. If yes, then it affects habitat creation, nursery, refuge, facilitation and sediment oxygenation.ReferencesBeauchard et al. (2017), Costello et al. (2015)LIFE HISTORY TRAITS ReproductionDefinitionThe way species reproduce, here including information about where fertilization occurs and whether propagules are released or not.CategoriesR1asexualBudding and fission (e.g., sponges, cnidarians)R2sexual – externalFertilization external, eggs and sperm deposited on substrate or released into water (broadcast spawners) (e.g., echinoderms, cnidarians)R3sexual – internalFertilization internal, but no brooding, eggs deposited on substrate, indirect or direct development (e.g., gastropods)R4sexual – broodingFertilization internal or external, eggs or larvae are brooded, indirect or direct development (e.g., amphipods, isopods, echinoderms)FunctionIndicates the ability of a species to disperse, become invasive or recover from a population decline. Can indicate if carbon is transported from the benthic to the pelagic realm or stays locally bound. Animals without a planktonic stage that perform brooding and parental care might have a higher tolerance against some forms of stress (e.g., ocean acidification) but may be more vulnerable to local disturbances (biotic or abiotic).ReferencesBremner (2008), Costello et al. (2015), Lucey et al. (2015)Larval developmentDefinitionLarval development and feeding type.CategoriesLD1pelagic/planktotrophicHigh fecundity, larvae feed and grow in water column, generally pelagic for several weeks (e.g., echinoderms, bivalves)LD2pelagic/lecitotrophicMedium fecundity, larvae with yolk sac, pelagic for short periods (e.g., tunicates)LD3benthic/directLarvae have benthic or direct development (no larval stage, eggs develop into miniature adults)FunctionAbility of a species to disperse, become invasive or recover from a population decline. Indicator of long-term sensitivity (ability to recolonize disturbed areas). Planktonic stages indicate productivity and elemental transport from benthos to pelagos.ReferencesBolam and Eggleton (2014), Cardeccia et al. (2018), Törnroos and Bonsdorff (2012)
Continued.
Life spanDefinitionThe maximum reported life span of the adult stage in years.CategoriesA1short<2 yearsA2medium2–5 yearsA3medium–long5–20 yearsA4long>20 yearsFunctionLong-lived animals are more susceptible to disturbance and need longer to recover (while short-lived species can recover fast and may increase in richness and abundance as disturbance increases). An indicator for population stability over time, carbon fixation, productivity.DetailIndicates the relative investment of energy in somatic rather than reproductive growth and the relative age of sexual maturity. A proxy for relative r and k strategy.ReferencesBolam and Eggleton (2014), Bremner (2008), Cain et al. (2014), Costello et al. (2015)BEHAVIORAL TRAITS Living habitDefinitionThe mode of living, ranging from free-living to tube- or burrow-dwelling to permanently attached.CategoriesLH1free-livingNot limited to any restrictive structure at any time. Able to move freely within and/or on the sedimentsLH2crevice-dwellingAdults are typically cryptic, inhabiting spaces made available by coarse/rock substrate and/or biogenic species or algal holdfastsLH3tube-dwellingTube may be lined with sand, mucus or calcium carbonate; tube can also be in a burrowLH4burrowingSpecies inhabiting permanent or temporary burrows in the sediment or are just burrowing in the sedimentLH5epi-/endozoic or epi-/endophyticLiving on or in other organismsLH6attachedAdherent to a substratumFunctionAttached species are more vulnerable to predation and perturbations (e.g., bottom trawling). Burrowing, crevice and tube dwelling taxa affect sediment biogeochemistry, carbon transport and elemental cycling and are less affected by strong hydrodynamic disturbance, anoxic conditions and water pollution. Tube building can add to local storage of chemicals and waste materials. Microbial processes are facilitated, and microbial biomass is promoted by deep-dwelling fauna. Burrowing and irrigation generally facilitate life of associates. Burrowing or attached living habit can be related to habitat creation and facilitation.ReferencesAller (1983), Bolam and Eggleton (2014), Bremner (2008), Bremner et al. (2006), Costello et al. (2015), Törnroos and Bonsdorff (2012), van der Linden et al. (2016)Adult movementDefinitionType of movement as an adult. CategoriesMV1sessile/noneNo movement as adult (sponge, coral)MV2burrowerMovement in the sediment (e.g., annelids, echinoderms, crustaceans, bivalves)MV3crawlerAn organism that moves along on the substratum via movements of its legs, appendages or muscles (e.g., crabs, snails)MV4swimmer (facultative)Movement above the sediment (e.g., amphipods)FunctionIndicates the dispersal and recolonization potential and the invasiveness of an organism. Related to nutrient cycling (burrowing taxa contribute most to nutrient cycling and regeneration; burrows increase the total sediment surface area available for exchange with the water column), carbon deposition (sessile calcifying taxa), facilitation of microbial and other fauna (either via burrowing or via constructing biogenic habitats) and habitat stability. Swimmers may escape predators and trawling gear.RemarkClosely linked to trait mobility.ReferencesAller (1983), Bremner (2008), Bremner et al. (2006), Costello et al. (2015), Frid and Caswell (2016)
Continued.
MobilityDefinitionDegree or intensity of movement.CategoriesMO1noneNo movement as adult (sponge, coral)MO2lowSlow movement (e.g., anemones, snails)MO3mediumMedium movement (e.g., starfish, brittle stars)MO4highHigh movement, swimmer or fast crawler (e.g., amphipods, shrimp)FunctionSlow- or non-moving species are more vulnerable to predation, perturbations and decrease in food input, while mobile taxa are more flexible and may evade trawl gear or predators. High percentage of non-moving organisms can indicate high amount of food, while high percentage of highly mobile taxa may indicate food patchiness or scarcity. Indicative of dispersal potential and ability to recolonize.ReferencesCostello et al. (2015), Micheli and Halpern (2005), Tyler et al. (2012)Feeding habitDefinitionThe mode of food uptake. CategoriesFH1surface deposit feederActive removal of detrital material from the sediment surface. Includes species which scrape and/or graze algal matter from surfacesFH2subsurface deposit feederRemoval of detrital material from within the sediment matrix (e.g., Echinocardium)FH3filter/suspension feederSponge, coral, hydrozoa, bivalvesFH4opportunist/scavengerAn organism that can use different types of food sources/an organism that feeds on dead organic material (e.g., crabs, whelks)FH5predatorAn organism that feeds by preying on other organisms (e.g., starfish)FH6parasite/commensalAn organism that lives in or on another living organism (the host), from which it obtains food and other requirementsFunctionCan indicate hydrodynamic conditions (suspension feeders in turbulent, deposit feeders in calmer water), carbon transport between pelagos and benthos (suspension feeders) and backwards (predators) and vulnerability (e.g., surface deposit feeders and suspension feeders are more sensitive to trawling). Impacts resource utilization and facilitation (e.g., deposit feeders facilitate microbes that further decompose organic carbon). Affects the depth of oxygen and detritus penetration and can enhance organic matter decomposition and nutrient recycling/regeneration. Control of other species in the assemblage.ReferencesBremner (2008), Bremner et al. (2006), Dolbeth et al. (2009), Frid et al. (2008), Kröncke (1994), Oug et al. (2012), Rosenberg (1995), Tyler et al. (2012), van der Linden et al. (2016)Trophic levelDefinitionRank of an animal according to how many steps it is above the primary producers at the base of the food web.CategoriesTL11Primary producerTL22Primary consumers – herbivore/deposit feeder/suspension feederTL33Secondary consumers – carnivoreTL44Tertiary consumersTL55Quaternary consumers – apex predatorFunctionDetermines the role of an organism in energy transfer within the food web. Control of other species abundance in the assemblage.ReferencesCostello et al. (2015), Micheli and Halpern (2005), Renaud et al. (2011)Substratum affinityDefinitionType of substratum that organisms (preferential) live on.CategoriesSA1softSoft substrata, sand or mudSA2hardHard substrata, rock, gravelSA3biologicalEpizoic or epiphytic lifestyleSA4noneSpecies is hyper-/suprabenthic and has no affinity for a certain substrate, but it might prefer one for hunting/scavenging (this category should not occur too often, as we work with benthos)FunctionCan be used – alongside depth range – for habitat classification. Can depict potential substrate specificity of other traits.ReferencesCostello et al. (2015)
Continued.
BioturbationDefinitionBiogenic modification of sediments through living, movement and feeding habits of organisms.CategoriesB1diffusive mixingSurficial movement of sediment and/or particles, resulting from movement or feeding activities on the surfaceB2surface depositionDeposition of particles at the sediment surface resulting from, e.g., defecation or egestion (pseudofaeces) by, for example, surface-deposit-feeding organisms (e.g., Holothuroidea, bivalves, tubiculous polychaetes)B3conveyor belt transport (upward)Translocation of sediment and/or particulates from depth within the sediment to the surface during subsurface deposit feeding or burrow excavationB4downward (reverse) conveyorThe subduction of particles from the surface to some depth by feeding or defecationB5noneNo bioturbation (e.g., sessile animals on hoard bottom)FunctionImpacts sediment biogeochemistry (oxygen, pH and redox gradients, elemental carbon), organic matter regeneration, nutrient cycling, sediment granulometry, pollutant release, microbial composition, abundance and diversity and in general provision and maintenance of habitats for other organisms.ReferencesChen et al. (2017), Frid et al. (2008), Gogina et al. (2017), Lacoste et al. (2018), Mermillod-Blondin (2011), Pearson (2001), Queirós et al. (2013), Solan et al. (2012)ToleranceDefinitionDegree to which a species reacts to changes in its environment.CategoriesT1lowSpecies reacts sensitive to changes in the environment like organic enrichment, pollution, temperature or salinity changes; AMBI group IT2intermediateSpecies react indifferent or no information available; AMBI group IIT3highSpecies tolerates organic enrichments, pollution, temperature or salinity changes; AMBI groups III–IVFunctionIndicates vulnerability or resistance/resilience of a species towards pollution or climate-change-induced changes in water biogeochemistry.ReferencesBorja et al. (2000), Gusmao (2017), Marchini et al. (2008), Piló et al. (2016)Environmental position DefinitionThe position of the animal relative to the sediment.CategoryEP1infaunaLives in the sedimentEP2epibenthicLives on the surface of the seabedEP3hyperbenthicLiving in the water column but (primarily/occasionally) feeds on the bottom; benthopelagicFunctionAffects carbon fixation and transport within the sediment, between aerobic and anaerobic layers, or from pelagos to benthos. Can indicate facilitation (e.g., for microbial communities in the sediment) and sensitivity to perturbation (e.g., bottom trawling, infauna less affected than epifauna; hyperbenthic taxa might be able to escape). Endobenthic lifestyle affects the sediment biogeochemistry. Epibenthic and shallow-sediment-dwelling taxa are more vulnerable to predation. Hyperbenthic taxa are involved in transport of carbon from benthos to pelagos. ReferencesBolam et al. (2014), Bremner et al. (2008), Frid and Caswell (2016), Törnroos and Bonsdorff (2012)Depth rangeDefinitionSpecies distribution related to water depth.CategoriesDR1shallow0–20 mDR2shelf20–200 m (some shelves can extend to 500 m)DR3shelf slope200–1000 m (sometimes the slope starts deeper, e.g., 500–1000 m)DR4slope basin>1000 mFunctionCan be used – alongside substratum affinity – for habitat classification. Can depict depth distribution of other traits.DetailShallow water and shelf taxa face a higher exposure to predation of marine mammals, to physical disturbances such as iceberg scouring and to coastal processes and pollution.ReferencesCostello et al. (2015), Gutt (2001)
Continued.
ZoogeographyDefinitionSpatial distribution of a species in relation to commonly used zoogeographic regions. CategoriesZ1arcticConfined to Arctic regions.Z2arctic-borealArctic, subarctic and North Atlantic/North Pacific distribution.Z3borealNorth Atlantic and/or North Pacific distribution; potentially subarctic regions such as southern Barents Sea or Bering Sea.Z4cosmopoliteCosmopolite distributionFunctionIndicates vulnerability (arctic species may be more vulnerable to changes than species with an arctic-boreal or cosmopolite distribution) or potential of a species to become invasive.ReferencesFetzer (2004), Fetzer and Arntz (2008), Piepenburg (2000), Weslawski et al. (2003)
The choice of which traits to include in the database is based on the
following considerations: (1) trait information should be available for and
applicable to all benthic taxa (Costello et al., 2015); (2) traits used in
previous studies and databases should be favored to enable comparisons across
studies (Degen et al., 2018); and (3) the traits should be usable across a
wide geographical area (Bremner et al., 2006). In order to fulfil this last
precondition, the trait body size is provided as the “maximum body size as
adult” (see also Table 3). While clearly a trade-off in regard to the
detection of intraspecific plasticity, it enables the use of this trait
across large spatial scales.
Recent trait-based studies emphasize the importance of standardized traits
and trait terminology to ensure that data can be integrated more easily in
the future (Costello et al., 2015; Degen et al., 2018; Faulwetter et al.,
2014). To meet these requirements of the scientific community, the Arctic
Traits Database includes 7 of the 10 traits prioritized in Costello et
al. (2015): depth range, substratum affinity, mobility,
skeleton, diet, body size and reproduction (Table 3). The
remaining three traits emphasized in Costello et al. (2015) – taxonomic
identity, environment and geography – are not included. For taxonomic
traits, every species in the database is bidirectionally deep linked (i.e.,
connected via a hyperlink) to the World Register of Marine Species (WoRMS
Editorial Board, 2017; http://www.marinespecies.org/, last access: 20 February 2019). For more detailed biogeographic information we
refer users to the Global Biodiversity Information System (GBIF;
http://www.gbif.org/, last access: 29 June 2018) or the
Ocean Biogeographic Information System (OBIS;
http://www.iobis.org, last access: 27 June 2018). We do
include, however, the trait “zoogeography”, which enables a differentiation
between typical arctic and boreal or cosmopolitan taxa. Of the 19 traits used
here, 17 are also identical to those used by the BIOTIC database
(MarLIN 2006, Table 1), one of the most comprehensive databases on biological
traits of marine organisms. BIOTIC also includes the trait “salinity”. We
cover salinity preferences within the trait “tolerance”, which also accounts for temperature and pollution tolerance (see Table 3 for details).
Traits we include in addition are “skeleton”, and “mobility” (i.e., the
relative degree of movement). Although physiological traits are of high
interest in trait-based studies, we do not include them as they are not
easily retrieved for many (arctic) benthic taxa (one of the preconditions for
inclusion in the database as stated above). In addition, physiological traits
(e.g., growth rate, respiration rate, ingestion rate) depend on body mass and
temperature (Brown et al., 2004), which can vary tremendously among Arctic
regions, contradicting the consideration that the trait information provided should be usable
across a wide geographical area.
One common approach to the use of traits is as indicators of ecosystem functions
(effect traits) or of changes in the environment (response traits)
(Hooper et al., 2005). An overview of how each
of the 19 traits that are currently included in the database may relate to
ecosystem functions or respond to environmental changes or pressures is given
in Table 3.
Explanation of fuzzy codes as used in the Arctic Traits
Database.
FuzzyExplanationcode3Taxon has total and exclusive affinity for a certain trait category; all other categories do not apply and must be coded with “0”.2Taxon has a high affinity for a certain trait category, but other categories can occur with equal (2) or lower (1) affinity.1Taxon has a low affinity for a certain trait category.0Taxon has no affinity for a certain trait category.Sources of trait information
Sources of trait information are research papers, books, databases and online
repositories (Table 1) but also grey literature such as cruise reports.
Trait information can also result from on-site measurements (e.g., for the
trait body size) or personal observations or be transmitted via communication
with experts for a specific taxonomic group. In any case, the source is
indicated as precisely as possible, for published literature with a complete
reference and DOI (if available), and in the case of expert communication, the name
and contact details of the respective expert are given. Wherever possible the
original quote from literature and page numbers are given to ensure the
traceability of the provided trait information. Although literature sources
targeting the Arctic are used preferably (and for exclusively Arctic species
are the only option), we do not restrict source information for arctic-boreal or cosmopolite taxa to stem from Arctic regions. This bears the risk that the
assigned trait information is not accurate, as polar taxa might differ in
their expression of certain traits from their relatives at lower latitudes
(Degen et al., 2018). However, this is an issue that is not resolved for now, as
trait information from the high latitudes is often scarce, and the user is
recommended to consider the source of trait information when interpreting
results.
Fuzzy coding of traits
The fuzzy coding procedure indicates to what extent a taxon exhibits each
trait category (Chevenet et al., 1994). This method has the advantage that it
enables us to analyze diverse kinds of biological information derived from a
variety of sources (as those included in the Arctic Traits Database; see
Sect. 2.3), and that also intermediate scenarios (i.e., when a taxon does not
clearly fall into one category or the other) can be accounted for (Chevenet
et al., 1994). We use the 0–3 coding scheme (details in Table 4 above) as it
is the most widely used (which facilitates comparisons and exchange of trait
information) and provides a compromise between binary codes and many graduations that are not
clearly delineated (Degen et al., 2018).
Two coding examples for the trait “Feeding habit”, which
has six trait categories (FH1–FH6; see also Table 3). Species 1 is a
surface deposit feeder but can switch from facultative to suspension feeding,
while species 2 is an exclusive suspension feeder.
While the coding might be pretty straightforward for some traits and taxa,
in some cases a decision might not be drawn so easily. As one of the clearer
cases, we point out the coding of the trait “body size” for the starfish
Crossaster papposus. A literature reference states that the body
size can range “up to 340 mm in diameter” (Hayward and Ryland, 2012,
p. 668). This size fits into the category “large” (S5, >300 mm); thus
the taxon is coded “3” for this size class, and “0” for all other
categories (S1–S4). The trait “mobility” is trickier. A literature
reference (Himmelman and Dutil, 1991, p. 68) states the following:
“Crossaster papposus and Solaster endeca are highly
mobile; large individuals can cover distances of more than 5 meters in 12
hours”. Here we have to keep in mind that the particular reference frame in
this publication is subtidal sea stars in the northern Gulf of St. Lawrence
(west Atlantic). The reference of the Arctic Traits Database however is the
entire community of benthic invertebrates, and the trait category “high mobility” is defined
here for taxa which are “swimmers or fast crawlers”, such as some amphipods
and shrimp (see Table 2). Accordingly, the correct coding for C. papposus in the reference system of the Arctic Traits Database is the
category “medium” mobility (MO3). Users of the Arctic Traits Database
should bear this reference system in mind when only downloading the fuzzy
coded trait data and aiming to apply it to another reference system. But as
the detailed literature quote that leads to the coding of a trait is always
provided (see Sect. 2.3), the trait information can easily be adjusted by the
user.
This is how the above example would appear in the matrix
downloaded from the Arctic Traits Database. In the download matrix format
species are rows, trait categories are columns and the fuzzy codes are the
values. Due to the database structure zero codes (“0”) are only displayed
when they are backed up by a specific reference (e.g., for the trait category
LH3/tube dwelling: “No species within the family Polynoidae is
tubiculous”).
FH1FH2FH3FH4FH5FH6Species 121Species 23
Screenshots of the start page of the Arctic Traits
Database. Toolbar of the public page with the login button for the registered
user (a) and toolbar in the area for registered users (b).
Screenshot of the taxon page of the asteroid Crossaster papposus selected
from the classification tree on the left.
There will always be a certain degree of subjectivity related to the fuzzy
coding procedure. To find out how strong the coding might differ among
scientists, a small experiment was performed at the Arctic Traits Workshop in Vienna
(December 2016) (Degen et al., 2018). Participants coded 27
trait categories of three common Arctic benthic species and found the final
trait matrices to be to 83 % identical. We are confident that the
sophisticated structure of the Arctic Traits Database (see Sect. 3) and the information and instructions provided will support a more consistent coding
of benthic traits in the future.
Screenshot of data completeness.
Database
In order to collect trait information and to disseminate it among users, a
web-based database was created. The database features a public interface
(Sect. 3.1) and an entry interface that is only accessible for registered
collaborators (Supplement). The public interface (Fig. 2a) allows
the traits and references to be browsed online (“Data per taxon” in the top menu bar), background
information to be viewed (“About” and “Trait definitions”) and either the entire species, trait and literature information or
specified subsets to be downloaded in several formats (“Download data”) (see Sect. 3.1).
Registered collaborators – i.e., those users that actively contribute trait
information to the Arctic Traits Database – can access the interactive part
of the database via the login button on the public page (Fig. 2a). This
access offers additional options (Fig. 2b): browsing the existing information
also by trait (“Traits” in the top menu bar), uploading new taxa, trait
and source information or adding trait information, references and comments
to already existing taxa in the database (“Taxa”). As several users can
work on the same taxa, a flagging system is used to highlight and discuss
potentially conflicting sources and opinions.
List of fields returned by the Arctic Traits Database
when “Data as columns” (*.csv) is chosen as an export option from the
download section.
Column labelColumn descriptionTaxonThe taxon for which the information was recorded.AuthorThe author and year of the Taxon for which the information was recorded.RankRank of the taxon for which the information was recorded.Valid taxonCurrently accepted name of the Taxon (as stored in the Arctic Traits Database – information might not be up to date with the WoRMS or the latest taxonomic literature in some cases). Users should check all taxa against WoRMS before use. If Taxon is currently accepted, this field contains the same value as Taxon.Valid authorCurrently accepted name of the Author (as stored in the Arctic Traits Database – information might not be up to date with the WoRMS or the latest taxonomic literature in some cases). Users should check all taxa against WoRMS before use. If Taxon is currently accepted, this field contains the same value as Author.Taxonomic statusThe status of the use of the Taxon (e.g., objective synonym, subjective synonym) as stored in the Arctic Traits database.Source of synonymyLiterature reference for synonymy of taxon (if present).Parent taxonThe Taxon's direct parent in the taxonomic classification (as stored in the Arctic Traits Database).TraitThe biological trait for which information is available (e.g., “Feeding habit”).CategoryThe subcategory of the Trait for which information is available (e.g., “Predator”).Category abbreviationAn abbreviated version of the often verbose trait category – useful as a label in further analyses of the data (e.g., FH6).TraitvalueDescribes the affinity of the Taxon to the Category. Values range from 0 to 3: “0”: no affinity for a certain trait category; “1”: low affinity for a certain trait category; “2”: high affinity for a certain trait category, but other categories can occur with equal (2) or lower (1) affinity; “3”: total and exclusive affinity for a certain trait category.ReferenceLiterature reference leading to the assignment of the Traitvalue to the Category for the Taxon.DOIDigital Object Identifier (where available) of the Reference.Value creatorPerson who assigned the Traitvalue to the Category for the Taxon, supported by a Reference.Value creation dateDate and time when the above information was entered into the database.Value modified byPerson who last modified the Traitvalue. Empty if no modifications were done.Value modification dateDate and time when the Traitvalue was last modified. If no modification was done since the first entry, this has the same value as Value creation date.Text excerptA quotation of the original text passage from the literature source that led to the assignment of assignment of the Category/Traitvalue to the Taxon. Empty if information has not been recorded yet.Text excerpt creatorPerson who entered the Text excerpt. Only present if Text excerpt is present.Text excerpt creation dateDate and time when the Text excerpt was entered into the database. Only present if Text excerpt is present.Text excerpt modified byPerson who last modified the Text excerpt. Empty if no modifications were done.Text excerpt modification dateDate and time when the Text excerpt was last modified. If no modification has been done since the first entry, this has the same value as Text excerpt creation date.
List of fields returned by the Arctic Traits Database
when “Darwin Core” is chosen as an export option from the download section.
Darwin Core does not provide the same granularity as the “Data as columns”
format. The output file consequently contains fewer details.
Column labelColumn descriptionscientificNameThe taxon for which the information was recordedscientificNameAuthorshipThe author and year of the taxon for which the information was recordedtaxonRankRank of the taxon for which the information was recorded.acceptedNameUsageCurrently accepted name and authorship of the scientificName (as stored in the Arctic Traits Database – information might not be up to date with the latest taxonomic literature in some casesTaxonomic statusThe status of the use of the scientificName (e.g., objective synonym, subjective synonym) as stored in the Arctic Traits Database. Empty if scientificName is the currently accepted name.MeasurementOrFactTrait name and trait category, separated by a colon (e.g., Size:small)measurementValueValue from 0 to 3, describing the affinity of the taxon to a trait category. Coding of values as described in Table 7 “Traitvalue”.dcterms:bibliographicCitationFull literature reference (including DOI where present) supporting the trait information for the current taxon.measurementRemarksA quotation of the original text passage containing the trait information for the current taxonmeasurementDeterminedByPerson who entered the trait information for this taxon into the database.measurementDeterminedDateDate the trait information was entered into the database or last modified.
A screenshot from the fuzzy coded trait matrix returned by
the Arctic Traits Database when the “Data in matrix format” is chosen as
export option from the download section. Species are rows
(“Valid_name” refers to the currently accepted taxonomy in
WoRMS), and abbreviated trait categories are columns. For abbreviations of trait
categories, see Table 3. Due to the database structure, zero codes (“0”) are
not displayed (see Table 6).
Taxonomic data coverage. “Other ranks” include higher
taxonomic levels and intermediate ranks.
The “References”, “Statistics” and “Tools” sections are equally only
accessible for registered users (Fig. 2b; Supplement). Every scientist
working in the field of Arctic benthic ecology aiming to share trait
information can become a registered user by getting in touch with the editor
and retrieving a user login. Credit to the registered collaborators is given
in the “About” section on the public site and also on taxon pages after
each trait entry they conduct. A detailed manual for registered users is
provided in the Supplement to this publication or can alternatively be
accessed via the public web interface (“About”). Collaborators who want to
share trait information without registering on the database can alternatively
be provided with an upload template xls.
Public access and download options
The public access enables the database to be browsed online and the
complete set of data as well as the bibliography or specified subsets to be downloaded. Taxon
traits can be visually inspected online via the “Data per taxon” button
from the top menu bar and “Browse taxa” or “Search taxa”. Taxa can be
browsed and selected via the taxonomic tree, as indicated for the asteroid
Crossaster papposus in Fig. 3. Alternatively, the “Search taxa”
panel allows a specific taxon to be typed in and searched.
The completeness of trait information can be inspected via “Data
completeness” (Fig. 4), equally accessible via “Data per taxon” on the top
menu bar. This option shows an alphabetic list of all taxa in the database
for which trait information is available. The bar on the right side indicates
the information coverage for each taxon and trait; the blue color indicates that
trait information is present.
Scheme visualizing the taxon entries per trait (bar
chart), the number of taxa per phylum (brackets) and the data coverage per
trait per phylum (dot plot).
Relative amount (%) of trait source types.
The download section can be accessed via the “Download data” button on the
top menu bar (Figs. 2a, 3, 4). Download is enabled in three different
computer readable formats: (1) as data in columns (*.csv) (Table 7), (2) in
Darwin Core format (Table 8) and (3) as a fuzzy coded trait matrix, which some
users might prefer (see Sect. 2.4 and Fig. 5). Also, the entire bibliography
is available for download. Before the download commences the user is asked
whether to download (a) all data in the database, (b) only data for an
uploaded list of taxon names, (c) only data for an uploaded list of AphiaIDs,
or (d) only the data selected from a classification tree. In the last option,
entire phyla or sub-groups can be easily selected from the tree. By default,
all 19 traits are exported, but if the user is interested only in one or a
few specific traits, the option to select these from the total list of 19
traits is available. As the fuzzy coded trait matrix (download option 3)
contains only the fuzzy codes per trait category but no literature sources,
we recommend also downloading the data in columns (download option 1) for
the same taxa, for which the detailed source per species and trait category is
included. Details on the structure of the first two download options are
given above in Tables 7 and 8. A screenshot from a downloaded fuzzy coded trait
matrix is shown in Fig. 5. The database can also be accessed programmatically
via a REST API (documented at
https://www.univie.ac.at/arctictraits/download-api, last access: 20 February 2019).
Database specification
The website runs on an Apache 2.2. server, and the database is implemented in
MySQL 5. PHP 5 is used as the scripting language. Web technologies used are
HTML4, CSS and JavaScript/Jquery. A code package to create such a web-based
trait database including a README file with instructions for installation is
provided at figshare;
10.6084/m9.figshare.7491869.
ResultsTaxonomic data coverage
At present, the database contains 1911 Arctic marine benthic invertebrate
taxa. Thereof 686 are on species level, 516 are on genus level and 274 are on family
level. The remaining 435 taxa are higher taxonomic levels or intermediate
ranks. The largest taxonomic group in the database at present stage are the
Arthropoda with 557 taxa (186 entries on species level), followed by the
Annelida with 489 taxa (218 entries on species level) and the Mollusca with
418 taxa (146 entries on species level) (Fig. 6).
Trait data coverage
At present, the database contains 19 traits and 80 trait categories, with currently 14 242 entries of trait information in
total. The trait for which
most entries exist is “Skeleton” (1837 entries), followed by
“Reproduction” (1328 entries) and “Body form” (1151 entries) (Fig. 7).
The phylum with most entries is the Annelida (6130 entries, 43 %),
followed by Arthropoda (2968 entries, 21 %) and Mollusca (2177 entries,
15 %). Regarding the taxonomic level, most trait information was added on
the species level (48 %), less on the genus (25 %) and family level
(17 %).
Bibliography
The Arctic Traits Database currently includes 394 sources of trait
information. Thereof 66 % are scientific papers, 11 % are books, 10 %
are web pages and 4 % are expert communications and personal observations
(“Other”). Theses, book sections and reports each make up around 3 %.
Most sources were used for the phyla Echinodermata and Annelida (33 %
each), followed by Arthropoda (29 %).
Discussion
Although the Arctic Traits Database is still growing as new taxa and trait
information are added, certain trends in data completeness or scarceness,
respectively, have become apparent (Fig. 7). Thus, the database is not only a
valuable tool for collecting and providing information but also for pointing
out in which areas more research might be needed. Regarding the 19 traits included at
the present stage, it shows that our knowledge on, e.g., the life span of many
Arctic benthic species is still limited (information only for <5 % of
species). This lack of data on species longevity is astonishing, as polar
taxa are traditionally depicted as slow-growing and long-lived compared to
their relatives from lower latitudes. Accordingly, one might have expected
that more studies and measurements are available for a variety of Arctic
taxa, which is not the case for many groups. Other traits that are currently
underrepresented are trophic level (<8 %) and tolerance (<13 %).
Regarding our interest in identifying knowledge gaps, a special strength of the
database is the implemented flagging system (described in detail in the
Supplement). As registered users continue to upload trait information,
more “conflicts” – i.e., cases in which the sources or observations added by
different users point towards different trait categories – may also arise. Such
cases are then indicated by a red flag and can be easily filtered.
Monitoring and statistical evaluation of these cases will grant important
information on where conflicts exist and for which taxa or traits future
research is needed. Such evaluation will also aid in identifying which traits
are more robust (i.e., are never flagged) and which show a higher plasticity
(frequent flagging). This kind of information is of tremendous value as it
can aid the choice as to which traits to include in prospective trait-based
studies. Apart from clearly diverging source information, different
levels of experience or customs in fuzzy coding might also lead to red flags in
the system. Here the editorial team will take care of consistency by
solving the conflicts according to the database standard and through that also
fostering a standardized way of coding within the community. In addition,
repetitively occurring discrepancies in the coding of certain traits might
also point towards a need for revision of these trait categories or their
definitions, or maybe even the adding of a new trait, in that way improving
the quality of the database.
In addition to the knowledge gaps surrounding certain traits discussed above, the data coverage among taxonomic groups also varies considerable (Fig. 7).
This potentially mirrors the sampling design of the underlying datasets. Some
taxonomic groups such as the polychaetes clearly dominate many benthic
soft-bottom communities, while other taxa such as the shrimp/Caridea are
highly mobile and might be permanently undersampled with sampling gear like
grabs, box corers or bottom trawls (Eleftheriou and McIntyre, 2007). This
points toward the need of also including datasets derived from video and still
image analysis in the future development of the database. These methods –
despite certain disadvantages (discussed in Degen et al., 2018, their
supplementary material, file 3) – have the great benefit that traits of hard-bottom
communities can also be analyzed, ecosystems which are at present underrepresented in the Arctic Traits Database.
Data availability
The Arctic Traits Database is hosted at the University of
Vienna (Austria) and can be accessed via
https://www.univie.ac.at/arctictraits/ (last access: 20 February 2019) (10.25365/phaidra.49; Degen and Faulwetter, 2018). A
code package to create a web-based trait database including a README file
with instructions for installation is provided at figshare;
10.6084/m9.figshare.7491869 (Faulwetter and Degen, 2018).
Conclusions
The Arctic Traits Database provides an easy accessible and sound knowledge
base of traits of Arctic benthic invertebrates and will thus facilitate
prospective trait-based studies for a variety of benthic ecologists at all
career stages. Its sophisticated structure accounts for the most commonly
raised demands for contemporary trait databases: (1) obligate traceability of
information (every entry is linked to at least one source);
(2) exchangeability among platforms (use of most common download formats);
(3) standardization (use of most common terminology and coding scheme); and
last but not least (4) user-friendliness (granted by an intuitive
web interface and rapid and easy download options). The combination of these
aspects makes the Arctic Traits Database a cutting-edge tool for (not only)
the marine realm and a role model for prospective databases.
The supplement related to this article is available online at: https://doi.org/10.5194/essd-11-301-2019-supplement.
Author contributions
RD designed the project and performed the trait data collection. SF
performed database and web page development and design. RD prepared the
manuscript with contributions from SF.
Competing interests
The authors declare that they have no
conflict of interest.
Acknowledgements
The authors wish to thank all collaborators that support the Artic Traits
Project, especially Bodil Bluhm, Jackie Grebmeier, Lauren Sutton, Dieter
Piepenburg and Arny Blanchard. This work was supported by the Austrian
Science Fund (FWF; T 801-B29) to Renate
Degen.Edited by: David Carlson
Reviewed by: two anonymous referees
ReferencesAller, R. C.: The importance of the diffusive permeability of animal burrow
linings in determining marine sediment chemistry, J. Mar. Res., 41, 299–322,
10.1357/002224083788520225, 1983.Beauchard, O., Veríssimo, H., Queirós, A. M., and Herman, P. M. J.:
The use of multiple biological traits in marine community ecology and its
potential in ecological indicator development, Ecol. Indic., 76, 81–96,
10.1016/j.ecolind.2017.01.011, 2017.Bernhardt-Römermann, M., Gray, A., Vanbergen, A. J., Bergès, L.,
Bohner, A., Brooker, R. W., Bergès, L., Bohner, A., Brooker, R. W., De
Bruyn, L., De Cinti, B., Dirnböck, T., Grandin, U., Hester, A. J., Kanka,
R., Klotz, S., Loucougaray, G., Lundin, L., Matteucci, G., Mészáros,
I., Oláh, V., Preda, E., Prévosto, B., Pykälä, J., Schmidt,
W., Taylor, M. E., Vadineanu, A., Waldmann, T., and Stadler, J.: Functional
traits and local environment predict vegetation responses to disturbance: a
pan-European multi-site experiment, J. Ecol., 99, 777–787,
10.1111/j.1365-2745.2011.01794.x, 2011.Blanchard, A. L., Parris, C. L., Knowlton, A. L., and Wade, N. R.: Benthic
ecology of the northeastern Chukchi Sea. Part I. Environmental
characteristics and macrofaunal community structure, 2008–2010, Cont. Shelf
Res., 67, 52–66, 10.1016/j.csr.2013.04.021, 2013a.Blanchard, A. L., Parris, C. L., Knowlton, A. L., and Wade, N. R.: Benthic
ecology of the northeastern Chukchi Sea. Part II. Spatial variation of
megafaunal community structure, 2009–2010, Cont. Shelf Res., 67, 67–76,
10.1016/j.csr.2013.04.031, 2013b.Bolam, S. G. and Eggleton, J. D.: Macrofaunal production and biological
traits: Spatial relationships along the UK continental shelf, J. Sea Res.,
88, 47–58, 10.1016/j.seares.2014.01.001, 2014.Borja, A., Franco, J., and Pérez, V.: A Marine Biotic Index to Establish
the Ecological Quality of Soft-Bottom Benthos Within European Estuarine and
Coastal Environments, Mar. Pollut. Bull., 40, 1100–1114,
2000.Bremner, J.: Species' traits and ecological functioning in marine
conservation and management, J. Exp. Mar. Biol. Ecol., 366, 37–47,
10.1016/j.jembe.2008.07.007, 2008.Bremner, J., Rogers, S. I., and Frid, C. L. J.: Methods for describing
ecological functioning of marine benthic assemblages using biological traits
analysis (BTA), Ecol. Indic., 6, 609–622, 10.1016/j.ecolind.2005.08.026,
2006.Brown, J. H., Gillooly, J. F., Allen, A. P., Van Savage, M., and West, G. B.:
Toward a metabolic theory of ecology, Ecology, 85, 1771–1789, 2004.Brun, P., Payne, M. R., and Kiørboe, T.: A trait database for marine
copepods, Earth Syst. Sci. Data, 9, 99–113,
10.5194/essd-9-99-2017, 2017.Cain, M. L., Bowman, W. D., and Hacker, S. D.: Ecology, 3rd Edn., Sinauer
Associates, 2014.Cardeccia, A., Marchini, A., Occhipinti-Ambrogi, A., Galil, B., Gollasch,
S., Minchin, D., Naršcius, A., Olenin, S., and Ojaveer, H.: Assessing
biological invasions in European Seas: Biological traits of the most
widespread non-indigenous species, Estuar. Coast. Shelf S., 201, 17–28,
10.1016/j.ecss.2016.02.014, 2018.Chen, X., Andersen, T. J., Morono, Y., Inagaki, F., Jørgensen, B. B., and
Lever, M. A.: Bioturbation as a key driver behind the dominance of Bacteria
over Archaea in near-surface sediment, Sci. Rep.-UK, 7, 1–14,
10.1038/s41598-017-02295-x, 2017.Chevenet, F., Dolédec, S., and Chessel, D.: A fuzzy coding approach for
the analysis of long-term ecological data, Freshwater Biol., 31, 295–309,
10.1111/j.1365-2427.1994.tb01742.x, 1994.Costello, M. J., Claus, S., Dekeyzer, S., Vandepitte, L., Tuama, É.
Ó., Lear, D., and Tyler-Walters, H.: Biological and ecological traits of
marine species, PeerJ, 3, e1201, 10.7717/peerj.1201, 2015.Darr, A., Gogina, M., and Zettler, M. L.: Functional changes in benthic
communities along a salinity gradient- a western Baltic case study, J. Sea
Res., 85, 315–324, 10.1016/j.seares.2013.06.003, 2014.Degen, R. and Faulwetter, S.: The Arctic Traits Database,
10.25365/phaidra.49, 2018.Degen, R., Aune, M., Bluhm, B. A., Cassidy, C., Kedra, M., Kraan, C.,
Vandepitte, L., Wlodarska-Kowalczuk, M., Zhulay, I., Albano, P. G., Bremner,
J., Grebmeier, J. M., Link, H., Morata, N., Nordström, M. C., Shojaei, M.
G., Sutton, L., and Zuschin, M.: Trait-based approaches in rapidly changing
ecosystems: A roadmap to the future polar oceans, Ecol. Indic., 91, 722–736,
10.1016/j.ecolind.2018.04.050, 2018.Dolbeth, M., Teixeira, H., Marques, J. C., and Pardal, M. Â.: Feeding
guild composition of a macrobenthic subtidal community along a depth
gradient, Sci. Mar., 73, 225–237, 10.3989/scimar.2009.73n2225, 2009.Eleftheriou, A. and McIntyre, A.: Methods for the Study of Marine
Benthos, 3rd Edn., Blackwell Science Ltd., 2007.Emmerson, M. C.: The importance of body size, abundance, and food-web
structure for ecosystem functioning, in: Marine Biodiversity and Ecosystem
Functioning: Frameworks, methodologies, and integration, edited by: Solan,
M., Aspden, R. J., and Paterson, D. M., Oxford University Press, Oxford, 240
pp., 2012.Faulwetter, S. and Degen, R.: Code for a web-based biological traits database,
10.6084/m9.figshare.7491869, 2018.Faulwetter, S., Markantonatou, V., Pavloudi, C., Papageorgiou, N.,
Keklikoglou, K., Chatzinikolaou, E., Pafilis, E., Chatzigeorgiou, G.,
Vasileiadou, K., Dailianis, T., Fanini, L., Koulouri, P., and Arvanitidis,
C.: Polytraits: A database on biological traits of marine polychaetes,
Biodivers. Data J., 2, e1024, 10.3897/BDJ.2.e1024, 2014.
Fetzer, I.: Reproduction strategies and distribution of larvae and juveniles of benthic soft-bottom invertebrates in the Kara Sea (Russian Arctic), PhD
thesis, University of Bremen, Germany, 242 pp., 2004.Fetzer, I. and Arntz, W. E.: Reproductive strategies of benthic
invertebrates in the Kara Sea (Russian Arctic): Adaptation of reproduction
modes to cold water, Mar. Ecol. Prog. Ser., 356, 189–202,
10.3354/meps07271, 2008.Foden, W. B., Butchart, S. H. M., Stuart, S. N., Vié, J. C.,
Akçakaya, H. R., Angulo, A., DeVantier, L. M., Gutsche, A., Turak, E.,
Cao, L., Donner, S. D., Katariya, V., Bernard, R., Holland, R. A., Hughes, A.
F., O'Hanlon, S. E., Garnett, S. T., Sekercioglu, Ç. H., and Mace, G. M.:
Identifying the world's most climate change vulnerable species: a systematic
trait-based assessment of all birds, amphibians and corals, edited by:
Lavergne, S., PLoS One, 8, e65427, 10.1371/journal.pone.0065427, 2013.Frid, C. L. J. and Caswell, B. A.: Is long-term ecological functioning
stable: The case of the marine benthos?, J. Sea Res., 98, 15–23,
10.1016/j.seares.2014.08.003, 2015.Frid, C. L. J. and Caswell, B. A.: Does ecological redundancy maintain
functioning of marine benthos on centennial to millennial time scales?, Mar.
Ecol., 37, 392–410, 10.1111/maec.12297, 2016.Frid, C. L. J., Paramor, O. A. L., Brockington, S., and Bremner, J.:
Incorporating ecological functioning into the designation and management of
marine protected areas, edited by: Davenport, J., Burnell, G., Cross, T.,
Emmerson, M., McAllen, R., Ramsay, R., and Rogan, E., Hydrobiologia, 606,
69–79, 10.1007/978-1-4020-8808-7_7, 2008.Froese, R. and Pauly, D. (Eds.): FishBase, World Wide Web electronic
publication, available at: http://www.fishbase.org (last access: 20 February 2019), version (02/2018),
2018.Gogina, M., Morys, C., Forster, S., Gräwe, U., Friedland, R., and
Zettler, M. L.: Towards benthic ecosystem functioning maps: Quantifying
bioturbation potential in the German part of the Baltic Sea, Ecol. Indic.,
73, 574–588, 10.1016/j.ecolind.2016.10.025, 2017.Grebmeier, J., Bluhm, B., Cooper, L., Denisenko, S., Iken, K., Kedra, M., and
Serratos, C.: Time-Series Benthic Community Composition and Biomass and
Associated Environmental Characteristics in the Chukchi Sea During the
RUSALCA 2004–2012 Program, Oceanography, 28, 116–133,
10.5670/oceanog.2015.61, 2015.Gusmao, J. B.: Sediments and Functional Traits?: Applying a Functional Trait
Approach To Assess Marine Macrobenthic Function, Univeridade Federal do
Parana, 2017.Gutt, J.: On the direct impact of ice on marine benthic communities, a
review, Polar Biol., 24, 553–564, 10.1007/s003000100262, 2001.Hayward, P. J. and Ryland, J. S. (Eds.): Handbook of the marine fauna of North-West
Europe, Oxford University Press, Oxford, New York, Tokyo, 2012.Hewitt, J. E., Norkko, J., Kauppi, L., Villnäs, A., Norkko, A., and
Peters, D. P. C.: Species and functional trait turnover in response to
broad-scale change and an invasive species, Ecosphere, 7, e01289,
10.1002/ecs2.1289, 2016.Himmelman, J. H. and Dutil, C.: Distribution, population structure and
feeding of subtidal seastars in the northern Gulf of St. Lawrence, Mar. Ecol.
Prog. Ser., 76, 61–72, 10.3354/meps076061, 1991.Hooper, D. U., Chapin, F. S., Ewel, J. J., Hector, A., Inchausti, P.,
Lavorel, S., Lawton, J. H., Lodge, D. M., Loreau, M., Naeem, S., Schmid, B.,
Setälä, H., Symstad, A. J., Vandermeer, J., and Wardle, D. A.:
Effects of biodiversity on ecosystem functioning: A consensus of current
knowledge, Ecol. Monogr., 75, 3–35, 10.1890/04-0922, 2005.Klais, R., Norros, V., Lehtinen, S., Tamminen, T., and Olli, K.: Community
assembly and drivers of phytoplankton functional structure, edited by:
Carrington, E., Funct. Ecol., 31, 760–767, 10.1111/1365-2435.12784,
2017.Kleyer, M., Dray, S., Bello, F., Lepš, J., Pakeman, R. J., Strauss, B.,
Thuiller, W., and Lavorel, S.: Assessing species and community functional
responses to environmental gradients: Which multivariate methods?, edited by:
Wildi, O., J. Veg. Sci., 23, 805–821, 10.1111/j.1654-1103.2012.01402.x,
2012.Kokarev, V. N., Vedenin, A. A., Basin, A. B., and Azovsky, A. I.: Taxonomic
and functional patterns of macrobenthic communities on a high-Arctic shelf: A
case study from the Laptev Sea, J. Sea Res., 129, 61–69,
10.1016/j.seares.2017.08.011, 2017.Kröncke, I.: Macrobenthos composition, abundance and biomass in the
Arctic Ocean along a transect between Svalbard and the Makarov Basin, Polar
Biol., 14, 519–529, 10.1007/BF00238221, 1994.Lacoste, É., Piot, A., Archambault, P., McKindsey, C. W., and Nozais, C.:
Bioturbation activity of three macrofaunal species and the presence of
meiofauna affect the abundance and composition of benthic bacterial
communities, Mar. Environ. Res., 136, 62–70,
10.1016/j.marenvres.2018.02.024, 2018.Lucey, N. M., Lombardi, C., DeMarchi, L., Schulze, A., Gambi, M. C., and
Calosi, P.: To brood or not to brood: Are marine invertebrates that protect
their offspring more resilient to ocean acidification?, Sci. Rep.-UK, 5,
12009, 10.1038/srep12009, 2015.Marchini, A., Munari, C., and Mistri, M.: Functions and ecological status of
eight Italian lagoons examined using biological traits analysis (BTA), Mar.
Pollut. Bull., 56, 1076–1085, 10.1016/j.marpolbul.2008.03.027, 2008.MarLIN: BIOTIC – Biological Traits Information Catalogue, Marine Life
Information Network, Plymouth, Marine Biological Association of the United
Kingdom, available at: http://www.marlin.ac.uk/biotic/, last access: 18 April
2018.Mermillod-Blondin, F.: The functional significance of bioturbation and
biodeposition on biogeochemical processes at the water–sediment interface in
freshwater and marine ecosystems, J. N. Am. Benthol. Soc., 30, 770–778,
10.1899/10-121.1, 2011.Micheli, F. and Halpern, B. S.: Low functional redundancy in coastal marine
assemblages, Ecol. Lett., 8, 391–400, 10.1111/j.1461-0248.2005.00731.x,
2005.Norkko, A., Villnäs, A., Norkko, J., Valanko, S., and Pilditch, C.: Size
matters: implications of the loss of large individuals for ecosystem
function, Sci. Rep.-UK, 3, 2646, 10.1038/srep02646, 2013.Oug, E., Fleddum, A., Rygg, B., and Olsgard, F.: Biological traits analyses
in the study of pollution gradients and ecological functioning of marine soft
bottom species assemblages in a fjord ecosystem, J. Exp. Mar. Biol. Ecol.,
432, 94–105, available at:
http://apps.webofknowledge.com/full_record.do?product=CCC&search_mode=GeneralSearch&qid=7&SID=W29TQeqCuCsBtQBk9hp&page=1&doc=9
(last access: 28 April 2016), 2012.Pearson, T. H.: Functional group ecology in soft-sediment marine benthos:
the role of bioturbation, Oceanogr. Mar. Biol., 39, 78–94, 2001.Piepenburg, D.: Arctic Brittle Stars (Echinodermata: Ophiuroidea), Oceanogr.
Mar. Biol., 38, 189–256, 2000.Piló, D., Ben-Hamadou, R., Pereira, F., Carriço, A., Pereira, P.,
Corzo, A., Gaspar, M. B., and Carvalho, S.: How functional traits of
estuarine macrobenthic assemblages respond to metal contamination?, Ecol.
Indic., 71, 645–659, 10.1016/j.ecolind.2016.07.019, 2016.The Polychaetes Scratchpad: available at:
http://polychaetes.lifewatchgreece.eu/, last access: 27 June
2018Queirós, A. M., Birchenough, S. N. R., Bremner, J., Godbold, J. A.,
Parker, R. E., Romero-Ramirez, A., Reiss, H., Solan, M., Somerfield, P. J.,
Van Colen, C., Van Hoey, G., and Widdicombe, S.: A bioturbation
classification of European marine infaunal invertebrates, Ecol. Evol., 3,
3958–3985, 10.1002/ece3.769, 2013.Renaud, P., Tessmann, M., Evenset, A., and Christensen, G.: Benthic food-web
structure of an Arctic fjord (Kongsfjorden, Svalbard), Mar. Biol. Res., 7,
13–26, 10.1080/17451001003671597, 2011.Rosenberg, R.: Benthic marine fauna structured by hydrodynamic procesess and
food availability, Neth. J. Sea. Res., 34, 303–317, 1995.Schleuter, D., Daufresne, M., Massol, F., and Argillier, C.: User's guide to
functional diversity indices, Ecol. Monogr., 80, 448–469,
10.1890/08-2225.1, 2010.Solan, M., Aspden, R. J., and Paterson, D. M. (Eds.): Marine biodiversity &
ecosystem functioning, 1st Edn., Oxford University Press, Oxford, 2012.Spitz, J., Ridoux, V., and Brind'Amour, A.: Let's go beyond taxonomy in diet
description: Testing a trait-based approach to prey-predator relationships,
J. Anim. Ecol., 83, 1137–1148, 10.1111/1365-2656.12218, 2014.Törnroos, A. and Bonsdorff, E.: Developing the multitrait concept for
functional diversity: Lessons from a system rich in functions but poor in
species, Ecol. Appl., 22, 2221–2236, 10.1890/11-2042.1, 2012.Tyler, E. H. M., Somerfield, P. J., Berghe, E. Vanden, Bremner, J., Jackson,
E., Langmead, O., Palomares, M. L. D., and Webb, T. J.: Extensive gaps and
biases in our knowledge of a well-known fauna: Implications for integrating
biological traits into macroecology, Global Ecol. Biogeogr., 21, 922–934,
10.1111/j.1466-8238.2011.00726.x, 2012.van der Linden, P., Marchini, A., Dolbeth, M., Patrício, J.,
Veríssimo, H., and Marques, J. C.: The performance of trait-based
indices in an estuarine environment, Ecol. Indic., 61, 378–389,
10.1016/j.ecolind.2015.09.039, 2016.Wassmann, P., Duarte, C. M., Agustí, S., and Sejr, M. K.: Footprints of
climate change in the Arctic marine ecosystem, Glob. Change Biol., 17,
1235–1249, 10.1111/j.1365-2486.2010.02311.x, 2011.Weigel, B., Blenckner, T., and Bonsdorff, E.: Maintained functional diversity
in benthic communities in spite of diverging functional identities, Oikos,
125, 1421–1433, 10.1111/oik.02894, 2016.Weslawski, J., Wlodarska-Kowalczuk, M., and Legezynska, J.: Occurrence of
soft bottom macrofauna along the depth gradient in High Arctic, 79 N, Polar
Res., 24, 73–88, 2003.Wieczorek, J., Bloom, D., Guralnick, R., Blum, S., Döring, M., Giovanni,
R., Robertson, T., and Vieglais, D.: Darwin core: An evolving
community-developed biodiversity data standard, LoS ONE, 7, e29715, 10.1371/journal.pone.0029715,
2012.
Wiedmann, M., Aschan, M., Certain, G., Dolgov, A., Greenacre, M.,
Johannesen, E., Planque, B., and Primicerio, R.: Functional diversity of the
Barents Sea fish community, Mar. Ecol. Prog. Ser., 495, 205–218,
10.3354/meps10558, 2014.WoRMS Editorial Board: World Register of Marine Species: available at:
http://www.marinespecies.org/ (last access: 20 February 2019),
10.14284/170, 2017.