Literature DB >> 27023900

The Coral Trait Database, a curated database of trait information for coral species from the global oceans.

Joshua S Madin1, Kristen D Anderson2, Magnus Heide Andreasen3, Tom C L Bridge2,4, Stephen D Cairns5, Sean R Connolly2,6, Emily S Darling7, Marcela Diaz1, Daniel S Falster1, Erik C Franklin8, Ruth D Gates8, Aaron Harmer, Mia O Hoogenboom2,6, Danwei Huang9, Sally A Keith3, Matthew A Kosnik1, Chao-Yang Kuo2, Janice M Lough2,4, Catherine E Lovelock10, Osmar Luiz1, Julieta Martinelli1, Toni Mizerek1, John M Pandolfi11, Xavier Pochon12,13, Morgan S Pratchett2, Hollie M Putnam8, T Edward Roberts2, Michael Stat14, Carden C Wallace15, Elizabeth Widman16, Andrew H Baird2.   

Abstract

Trait-based approaches advance ecological and evolutionary research because traits provide a strong link to an organism's function and fitness. Trait-based research might lead to a deeper understanding of the functions of, and services provided by, ecosystems, thereby improving management, which is vital in the current era of rapid environmental change. Coral reef scientists have long collected trait data for corals; however, these are difficult to access and often under-utilized in addressing large-scale questions. We present the Coral Trait Database initiative that aims to bring together physiological, morphological, ecological, phylogenetic and biogeographic trait information into a single repository. The database houses species- and individual-level data from published field and experimental studies alongside contextual data that provide important framing for analyses. In this data descriptor, we release data for 56 traits for 1547 species, and present a collaborative platform on which other trait data are being actively federated. Our overall goal is for the Coral Trait Database to become an open-source, community-led data clearinghouse that accelerates coral reef research.

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Year:  2016        PMID: 27023900      PMCID: PMC4810887          DOI: 10.1038/sdata.2016.17

Source DB:  PubMed          Journal:  Sci Data        ISSN: 2052-4463            Impact factor:   6.444


Background & Summary

Most ecosystems are rich in species that display a wide diversity of characteristics[1] (i.e., traits). One way to make meaningful generalizations from this diversity has been to identify physiological, ecological or functional traits of organisms to infer (e.g., using traits as explanatory variables) patterns of demography, distribution and abundance, and more broadly, ecosystem function and evolution[2]. Moreover, species traits can be used as explanatory variables for the responses of ecosystems to environmental change, as functionally significant traits mediate species’ responses to disturbances[3]. Recently, research has demonstrated the utility of trait-based approaches for understanding the effects of anthropogenic disturbances[4], the provisioning of ecosystem services[5], species distributions[6-8], species composition[9,10], and energetic and ecological trade-offs[11,12]. In seminal papers, compilations of species trait data with broad taxonomic coverage have revealed, for example, a general axis of variation in plants that describes costs and benefits of key chemical, structural and physiological traits[11]; and factors influencing the metabolic rates of organisms[13]. However, such broad-scale insights have been restricted to relatively few taxonomic groups, often due to lack of data, particularly information about the ecological context in which data were collected, when such data do exist. Trait data for stony corals (Cnidaria: Scleractinia) have been collected for more than 100 years and published in many languages. Sufficient data might well exist already for addressing broad-scale hypotheses regarding the ecology and evolution of corals. Although trait compilations are accumulating[4,14-16], and new statistical approaches for analysing such data are emerging[7,12], these datasets are typically gathered for specific traits in isolation to address specific questions which can result in duplication of effort by separate research groups (e.g., Darling et al.[12] and Pratchett et al.[17] both independently compiled growth rate data). Trait data also tend to be gathered rapidly, for instance with means extracted from tables that present a mixture of original data and data collected previously by others (i.e., meta-analyses). Such a rapid assembly of data can result in omission of important contextual information (e.g., local environmental conditions and levels of variation and replication), confusion about the origin of the data, preventing appropriate provenance and credit[18], and the accidental duplication of data points in large datasets. In this data descriptor, we introduce the Coral Trait Database: a curated database of trait information for coral species from the global oceans. The goals of the Coral Trait Database are: (i) to assemble disparate information on coral traits, (ii) to provide unrestricted, open-source access to coral trait data, (iii) to facilitate and encourage the appropriate crediting of original data sources, and (iv) to engage the reef coral research community in the collection and quality control of trait data. We release 56 error-checked, validated and referenced traits, and also provide their context of measurement, together with an online system for transparently and accurately archiving and presenting coral trait data in future research. Our vision is an inclusive and accessible data resource to more rapidly advance the science and management of a sensitive ecosystem at a time of unprecedented environmental change.

Methods

The data are held in the Coral Traits Database (https://coraltraits.org). The database was designed to contain individual-level traits and species-level characteristics and is currently focused on shallow water zooxanthellate (‘reef building’) scleractinian corals. Individual-level traits include any potentially heritable quality of an organism[19,20]. In the database, individual-level traits are accompanied by contextual characteristics, which give information about the environment or situation in which an individual-level trait was measured (e.g., characteristics of the habitat, seawater or an experiment). These contextual variables are important for understanding variation in individual-level traits (e.g., as predictor variables in analyses). For example, if measurement of colony growth rate was measured at a given depth, the latter datum is included to provide important information for the focal measurement. Some individual-level traits have no or little variation (e.g., mode of larval development), and therefore contextual information is not required. Species-level characteristics do not have contextual information because they are characteristics of species as entities (such as geographical range size and maximum depth observed). For simplicity, we use the single term ‘trait’ to refer to individual-level (variant and invariant), species-level (emergent) and contextual (environmental or situational) measurements. Moreover, these traits are grouped into ten use-classes based on various sub-disciplines of reef coral research: biomechanical, conservation, ecological, geographical, morphological, phylogenetic, physiological, reproductive, stoichiometric, and contextual.

Observation and measurements

The database contains two core data tables—Observations and Measurements—each of which has a series of associated tables (Fig. 1). We follow the high-level structure of the Observation and Measurement Ontology[21] in that observations bind related measurements and potentially provide context for other observations.
Figure 1

Overview of the design of the Coral Trait Database.

(a) The general schema consists of an Observation of a coral colony that is a collection of one or more Measurements associated with the colony. Solid borders represent table associations and dotted borders represent values. Observations have four table associations (contributor, coral species, resource and location) and one value for access (i.e., public or private). Measurements have four table associations (observation, trait, methodology and standard) and five values. (b) An example of an observation where coral growth rate was measured along with two contextual measurements (represented in the database by an eye). All observation-level attributes are required. Required measurement-level attributes are trait, standard, value and value type. Precision details are entered when a value type is not a raw value. Photograph: Emily Darling.

The observation table contains information about the observation of a coral or coral species. Observation-level data must include the Enterer, Species, Location and Resource. Access is an optional variable, and can be controlled by database users entering data for a project that has not yet been published (see https://coraltraits.org/procedures for more information). Observation-level data are the same for all measurements corresponding to the observation. Measurement-level data include the Trait, Value, Standard (measurement unit), Methodology, and estimates of precision (if applicable). The hypothetical example given in Fig. 1b is for growth rate that was measured within the context of a water depth and habitat that were given in the published resource. The Species table provides taxonomy that is regularly updated by the Taxonomy Advisory Board (https://coraltraits.org/procedures) to keep pace with the rapid rate of revision[22-24]. The table contains the valid name for each coral species based largely on the World Register of Marine Species (http://www.marinespecies.org), the major clade (Basal, Robust or Complex[25]), family based on molecular work[26], family based on morphology (following Cairns[27] or Veron[28]), and other names and synonyms.

Data acquisition

All public data in the Coral Trait Database and included in this data descriptor release are linked with published resources, which include peer-reviewed papers, taxonomic monographs and books. The original source of entered data must be included (called the primary resource), even when extracted from secondary compilations (e.g., for the purpose of meta-analyses). Secondary sources can be included optionally, and so the database captures both the original data collector and subsequent data compilers, which allows both to be credited when re-using data. Measurement value types, which can be flexibly added to, currently include: raw, mean, median, maximum, minimum, expert opinion (the view of a single expert), group opinion (the consensus of a group of experts), and model derived. Continuous data are typically means extracted from tables or figures unless raw data are available. When available, aggregate values such as means and medians should be accompanied by the number of replicates and a measure of dispersion (e.g., standard deviation). Means and estimates of dispersion from figures in resources were captured using ImageJ[29]. The data released in this data descriptor have broad taxonomic (Fig. 2), global (Fig. 3) and phylogenetic (Fig. 4) coverage. However, some large data gaps exist, because few species have been comprehensively measured in many locations.
Figure 2

Trait by species matrix, illustrating coverage of trait data are currently available in the Coral Trait Database across the worlds 1547 coral species.

Blue cells correspond with the traits released in this data descriptor. Grey cells correspond with other available data for which thorough error checking is still being conducted.

Figure 3
Figure 4

The phylogenetic coverage of traits in the Coral Trait Database, for the subset of species in the current molecular phylogeny.

As for Fig. 2, blue cells indicate traits for species released in this data descriptor and grey cells indicate other available information in the database, still being federated.

Data Records

A static release of the 56 traits contained in this descriptor is available from the Coral Trait Database (Data Citation 1) and Figshare (Data Citation 2). Details and references for the trait data are summarised in Table 1 (available online only). Up-to-date data can be downloaded directly from the database. However, as validation (see Technical Validation, below) and data entry is ongoing, users are recommended to pull data from the static releases, to ensure results remain consistent as the database is updated. Both static releases and datasets downloaded from the database are accompanied by the primary (and, if applicable, secondary) resource lists for the data, which should be credited wherever feasible.
Table 1

Overview of traits in release 1.1.1, including descriptions, measurement standards, the number of measurements and the references

Class Name Description Standard Default unit Categories Category descriptions Measurements References
N/A denotes not applicable.        
BiomechanicalColony shape factorA dimensionless measure of mechanical vulnerability to hydrodynamic disturbance (see Madin and Connolly 2006). Colony shape factor is a function of colony size, and therefore each observation should also include a colony size measurement. Currently published data is only available for three species.DimensionlessN/AN/AN/A1158 [30]
Larval swimming speedThe swimming speed, typically the maximum, of coral larvae.Speedmm s−1 N/AN/A394 [31–40]
Skeletal densityThe material density of coral skeleton. Porosity measurements can be converted to density by multiplying the reciprocal of porosity by the maximum density of aragonite (2.94 g cm^−3).Densityg cm−3 N/AN/A378 [16,17,41–74]
Skeletal micro-densityThe fine-scale specific gravity of the material from which coral skeleton is constructed (Bucher et al. 1998, following terminology from Barnes & Devereux 1988). Micro-density should be closer to the density of solid aragonite (~2.96 g cm^−3) than to typical bulk densities, because it does not capture corallite voids (i.e., porosity).Densityg cm−3 N/AN/A9 [45]
Substrate attachmentWhether or not individuals attach to substrates, including reef, rock and wood.CategoryN/AattachedunattachedbothAttached to the substratumNot attached to the substratumFound both attached and unattached to the substratum1464 [28,75–77]
ConservationIUCN Red List categoryRed list categories are from Delbeek et al. (2009) as compiled by Carpenter et al. (2009).CategoryN/AVULCNTDDCRENVulnerableLeast concernNear threatenedData deficientCritically endangeredEndangered818 [4,78]
EcologicalAbundance GBRThe typical local abundance of species when found on the Great Barrier Reef, Australia. Data were extracted from textual descriptions in Veron (1996) by Diaz and Madin (2011).CategoryN/ArareuncommoncommonTypically rare where foundTypically uncommon where foundTypically common where found400 [79,80]
Abundance worldThe typical local abundance of species from Veron (2000). It is suspected that many species listed as rare are abundant at some localities. Furthermore, as Bridge et al. (2013) point out, some are abundant at depth.CategoryN/ArareuncommoncommonTypically rare where foundTypically uncommon where foundTypically common where found823 [4,28,78,81–84]
Depth lowerThe maximum (deepest) observed depth of a species. Data are a mix of individual-level local observations and species-level global estimates based on expert opinion.LengthmN/AN/A1214 [4,78,85–105]
Depth upperThe minimum (shallowest) observed depth of a species. Data are a mix of individual-level local observations and species-level global estimates based on expert opinion.LengthmN/AN/A1147 [4,78,87,89,95,97–99,102–105]
Generation timeThe average age of mothers in populations. This characteristic has only been empirically estimated for three species as far as we know ([Babcock 1991](/resources/273)). Values in Carpenter et al. (2008) are unreliable and we advise against using them.DurationyearsN/AN/A3 [106]
Life history strategyLife history strategies broadly capture the various investments in growth, reproduction, and survivorship that differentiate species.Categorycatcompetitiveweedystress-tolerantgeneralistEfficient at using resources and can dominate communities in productive environmentsOpportunistically colonize recently disturbed habitatsAdvantageous traits in chronically harsh environmentsDo well in habitats where competition is limited by low levels of stress and disturbance143 [12]
Water clarity preferencePreferred water clarity environment. Derived from preferred habitat textual descriptions, mostly from Veron and Stafford-Smith (2002), and published in Diaz and Madin (2011).CategoryN/AbothclearturbidFound in both clear and turbid water environmentsFound predominantly in clear water environmentsFound predominantly in turbid water environments933 [28,79,81,83]
Wave exposure preferencePreferred hydrodynamic exposure environment. Derived from preferred habitat textual descriptions, mostly from Veron and Stafford-Smith (2002), and published in Diaz and Madin (2011).CategoryN/AprotectedbroadexposedFound predominantly in sheltered environmentsFound in both sheltered and exposed wave environmentsFound predominantly in exposed wave environments933 [28,79,83]
GeographicalEastern-most range edgeEastern-most edge of a species range given as longitude, typically calculated from shapefiles. May also include one-off published observations. Not to be confused with eastern-most longitude relative to Greenwich. The value that results in the greatest range extent is used when species are synonymized.LongitudedegN/AN/A709 [107]
Geographical regionPresence in broad ocean and geographical regions.BinomialN/AIndian OceanWestern and Central PacificWestern AtlanticEastern PacificEastern AtlanticSubantarctic and AntarcticN/A2316 [14,27]
Indo-Pacific faunal provincePresence in the eleven Indo-Pacific faunal provinces established in Keith et al. (2013).CategoryN/AAfrica-IndiaAndaman-Nicobar IslandsAustralianFiji-Caroline IslandsHawaii-Line IslandsIndonesianJapan-VietnamPersian GulfPolynesiaRed SeaTonga-SamoaN/A3814 [7]
Northern-most range edgeNorthern-most edge of a species range given as latitude, typically calculated from shapefiles. May also include one-off published observations. The value that results in the greatest range extent is used when species have been synonymized.Latitudedecimal degreeN/AN/A709 [107]
Ocean basinThe ocean basin in which a species is found. Indian and Pacific Oceans are grouped as ‘pacific.’CategoryN/ApacificatlanticPresent in the Indo-PacificPresent in the Atlantic1494 [14,27]
Range sizeGeographic range size of species calculated from shapefiles. Be aware that there are different definitions of range size. For example, Veron (2000) range sizes are the sum of ecoregion sizes in which a species occurs; whereas, Hughes et al. (2013) range sizes capture the full extent of a species and so will be larger than Veron (2000) range sizes. Largest range size is used when species are synonymized.Areakm2 N/AN/A1477 [28,107]
Southern-most range edgeSouthern-most edge of a species range given as latitude, typically calculated from shapefiles. May also include one-off published observations. The value that results in the greatest range extent is used when species have been synonymized.Latitudedecimal degreeN/AN/A709 [107]
Western-most range edgeWestern-most edge of a species range given as longitude, typically calculated from shapefiles. May also include one-off published observations. Not to be confused with western-most longitude relative to Greenwich. The value that results in the greatest range extent is used when species have been synonymized.Longitudedecimal degreeN/AN/A709 [107]
MorphologicalColonialityWhether mature individuals of a species are colonial, solitary or either colonial or solitary (both).CategoryN/AcolonialsolitarybothMature individuals are colonialMature individuals are solitaryMature individuals can be either colonial or solitary1613 [28,77]
Colony maximum diameterThe maximum diameter of a colony. At this stage, most maximum diameters have been extracted from monographs. However, new published records of large colonies should also be entered.LengthcmN/AN/A537 [28,75,80,83,84,108–128]
Corallite width maximumThe maximum typical corallite width, axial corallite width or valley size.LengthmmN/AN/A733 [28,77,81,121,129–133]
Corallite width minimumThe minimum typical corallite width, axial corallite width or valley size.LengthmmN/AN/A688 [28,77,81,121,129–133]
Growth form typicalThe growth form (morphology) of a species as derived from text descriptions in Veron (2000). The ‘typical’ growth form is given for each species, rather than all forms that might be observed in the field.CategoryN/Aencrustinglaminarsubmassivemassivecolumnarbranching_closedbranching_opentables_or_platesdigitatecorymbosehispidoseencrusting_long_uprightsOverlaying the substratumThin sheets often forming whorlsNot quite massiveSolid with similar shape in all directionForming columnsBranches in clusters or tuftsBranches of similar length given off at similar anglesColony outline in the shape of a table i.e., a top with one central leg or side-attached tableEncrusting with regular short upright branchesFlat topped clumpsOpen-branched except with a second type of branch given off at regular intervalsOverlaying the substratum with long branches773 [28]
Growth form VeronThe growth form (morphology) of a species as derived from text descriptions in Veron (2000). Species can have more than one growth form, and therefore captures some degree of morphological plasticity.CategoryN/Aencrustinglaminarsubmassivemassivecolumnarbranching_closedbranching_opentables_or_platesdigitatecorymbosehispidoseencrusting_long_uprightsOverlaying the substratumThin sheets often forming whorlsNot quite massiveSolid with similar shape in all directionForming columnsBranches in clusters or tuftsBranches of similar length given off at similar anglesColony outline in the shape of a table i.e., a top with one central leg or side-attached tableEncrusting with regular short upright branchesFlat topped clumpsOpen-branched except with a second type of branch given off at regular intervalsOverlaying the substratum with long branches1168 [28]
Growth form WallaceThe growth form (morphology) of a species as derived from text descriptions in Wallace (2012). Species may, but tend not to, have more than one growth form.CategoryN/Aarborescentarborescent_tablescorymbosecaespitosecaespitose_corymbosehispidoseencrustingelkhorncuneiformtables_or_platesBranches of similar length given off at a similar angles. Open branchingOpen branched tablesFlat topped clumpsBranches in clusters or tufts. Closed branchingFlat topped closed branching clumpsArborescent except with a second type of branch given off at regular intervals around the primary branchAdhering to or overlaying the substratumBranches in the shape of the horns of an ElkBranches shaped like a wedgeColony outline in the shape of a table, i.e., a top with one central leg or pedicle, may be side-attached table122 [77]
Growth outline typeWhether or not a colony tends to approach a predictable outline. This trait was included in Wallace et al. (2012), and so has been measured mostly for Acropora.CategoryN/AIndeterminatedeterminateColony grows apparently without any intrinsic restrictionColony grows to a more or less predictable outline119 [77]
Polyps per areaThe number of polyps found in a given colony surface area.Densityunits cm−2 N/AN/A55 [16,70,72,106,121,129,131–147]
PhylogeneticGenus fossil ageDate of the first palaeontological occurrence of morphologically defined genera based on the published literature.Million years agomyaN/AN/A3799 [7,28,148–150]
Genus fossil stageThe geochronological unit of the first palaeontological occurrence of morphologically defined genera based on the published literature.CategoryN/ARecent, Eocene, Oligocene, Miocene, Ypresian, Miocene middle, Cretaceous Lower, Aptian, Jurassic Upper, Eocene middle, Cretaceous Upper, Turonian, Cretaceous, Cretaceous upper, Pleistocene, Priabonian, Cretaceous middle, Pliocene, Barremian, Neocomian, Chattian, Thanetian, Danian, Kimmeridgian, Miocene upper, Burdigalian, Oligocene middle, Rupelian upper, Tortonian, Cenomanian, Pleistocene-?Oligocene, Miocene Lower, Aquitanian, Eocene-Cretaceous, Pliocene-Pleistocene, Palaeocene, Rupelian, BathonianN/A2335 [28,149,150]
Species age phylogenyThis is the phylogenetic tip length based on a phylogeny of 1547 species reconstructed using supertree and MCMC methods, incorporating molecular, morphological and taxonomic data.Million years agomyaN/AN/A1461 [151]
PhysiologicalCalcification rateThe rate at which aragonite is laid down per unit of skeletal surface area. When using this data, be aware that this trait is measured in numerous ways.Percent per year% yr−1 N/AN/A320 [16,17,41,43,46,48,50,53,54,63,67,70–72,74,152–170]
Dark respirationThe rate of oxygen consumption measured in the darkness per unit of skeletal surface area. Values may include both light enhanced dark respiration and dark acclimated dark respiration.Rateμmol O2 cm−2 h−1 N/AN/A46 [16,138,139,144,152,157,171–179]
Gross photosynthesisThe rate of oxygen production measured in the light per unit of skeletal surface area. This includes oxygen consumption due to light respiration.Rateμmol O2 cm−2 h−1 N/AN/A37 [16,138,139,144,152,157,171–173,175–179]
Growth rateTypically, the yearly extension for branching and massive corals, or simple linear extension. Growth rate is sometimes measured using different dimensions (e.g., diameter and radius) or over shorter periods of time (e.g., month), which are indicated by measurement standards and methodologies, and so values may need to be standardised before comparisons among measurements can be made.Extension rate (linear)mm yr−1 N/AN/A1297 [12,16,17,41,43,46,48,50,51,53,54,56,57,59,61–63,65–68,70–74,106,113,138,169,170,180–316]
Mitotic indexThe percentage of cells in the paired stage of cell division.Percent%N/AN/A31 [16,317–322]
Protein biomassThe amount or biomass of protein per unit of skeletal surface area.Densitymg cm−2 N/AN/A32 [16,138,139,171,179,323–329]
Symbiodinium cladeThe genetic identity of Symbiodinium found in coral tissue at the clade level (broad level of major symbiont taxa). This is typically identified using regions of the nuclear ribosomal DNA, but other regions are also used.CategoryN/AA, B, C, D, F, G, H, IN/A3147 [15,330–379]
Symbiodinium densityThe number of symbiont cells per unit of skeletal surface area.Densityunits cm−2 N/AN/A4062 [16,164,171,320,380–393]
Symbiodinium subcladeThe genetic identity of Symbiodinium found in coral tissue at the level below clade, but usually above species. This is typically identified using the nuclear ribosomal DNA Internal Transcribed Spacer region (ITS2), but other markers are also used.CategoryN/AN/AN/A3068 [15,76,330–338,340–345,347–365,367–379]
Tissue thicknessThe distance from the external surface to the internal surface of the coral tissue.LengthmmN/AN/A59 [16,72,273,306,388,394]
ZooxanthellateIs the species zooxanthellate?CategoryN/AzooxanthellateazooxanthellatebothContain zooxanthellae within their tissuesDon't contain zooxanthellae within their tissuesSometimes contain zooxanthellae within their tissues1548 [27,28,75,76,78,91,395–420]
ReproductiveMode of larval developmentThe mode of larval development classified as either a brooder, where fertilization is internal and colonies release planulae larvae, or a broadcast spawner, where gametes are release for external fertilization and the planulae develops in the plankton.CategoryN/Abothbrooderspawnerindividual colonies both brood and spawnFertilization internalFertilization external814 [14,32,35,84,120,141,146,234,235,421–523]
Oocyte size at maturityThe diameter of mature oocytes in a population. Determined by histology or dissection or measuring the size of eggs once released from the colony in broadcast spawners.LengthμmN/AN/A133 [234,423,425,428,436,441,448,460,478–480,483,484,493,494,498,500,510,519,521,524–530]
Propagule size on releaseThe size of eggs or planula larvae on release.LengthμmN/AN/A67 [423,425,428,478,480,483,484,493,510,512,525,528–531]
Sexual systemEach polyp of the population having gametes of only one sex (either male or female) at maturity (gonochore); one or more polyps of the population having both male and female gametes at maturity (hermaphrodite).CategoryN/AgonochorehermaphroditeOnly one sex in all polypsBoth sexes in at least one polyp1153 [14,35,84,141,146,234,235,422–429,432,436,438–443,445–449,451–454,456–458,460,461,463–469,471,472,476–481,483–489,492–513,515–523,525,532–550]
Symbiodinium sp. in propagulesWhether or not mature eggs or larvae contain Symbiodinium sp. at the time of release from the parent. Typically determined by eye, rarely by histology or fluorescent microscopy, which are required for confirmation.BinomialN/AyesnoSymbiodinium sp. in propagulesNo Symbiodinium sp. in propagules818 [14,120,146,234,235,424–427,429,436,438,440,441,444,447,451,453,455,456,458,460,466,468,473,474,476,479,483,484,488,489,493–501,505,511,512,517,522,525,535,538,541,549,551–555]
StoichiometricChlorophyll aThe amount of chlorophyll a in coral tissue, typically given per unit surface area.Densityμg cm−2 N/AN/A110 [16,144,171,179,215,222,323,328,329,383,388,389,556–571]
Lipid contentThe amount of lipid is tissue.Densitymg cm−2 N/AN/A13 [16,325–328,385,572]
Nitrogen concentrationThe amount of nitrogen in tissue.Percent%N/AN/A131 [573]
Phosphorus concentrationThe amount of phosphorus in tissue.Percent%N/AN/A142 [573]
RNA:DNA ratioThe relative quantities of RNA and DNA.Ratiox:yN/AN/A80 [573]
Total biomassThe dry weight of holobiont tissue, typically reported as mass per unit of skeletal surface area of a colony.Densitymg cm−2 N/AN/A3867 [16,138,139,157,325,327,328,389,392,560,564,574,575]

Technical Validation

The database is curated on a voluntary basis, which includes a Managerial Board, Editorial Board, Taxonomy Advisory Board and Database Administrator (https://coraltraits.org/procedures). Database Contributors who add data for a new trait are typically asked to be that trait’s editor. Quality control of data and editorial procedures include: Contributor approval: Database users must request permission to become a database contributor, and any observations entered by the contributor are associated with their user account. Editorial approval: Once a contributor enters an observation of a coral trait, an email is sent automatically to the editor of that trait. The editor must approve the observation to remove the ‘pending’ flag from the observation record. User feedback: Data issues can be reported for any observation using a simple form. Editors are automatically emailed if an issue with one of their traits is reported. Duplicate detection: Measurements with the same value, resource, location and species are flagged for confirmation. Outlier detection: Frequency histograms are generated in real time when loading trait pages. Outliers can be detected visually (e.g., a very large value for continuous data or a category that has one or few associated measurements for categorical data).

Usage Notes

The data release is a compressed folder containing two files: A csv-formatted data file containing all publicly available observation and measurement data, which includes contextual data. A csv-formatted resource file containing all the resources (primary and secondary) that correspond with the data. Users are expected to cite the data correctly using these resources. An example for extracting and reshaping release data for analysis can found online (https://coraltraits.org/procedures).

Additional Information

Table 1 is only available in the online version of this paper. How to cite this article: Madin, J. S. et al. The Coral Trait Database, a curated database of trait information for coral species from the global oceans. Sci. Data 3:160017 doi: 10.1038/sdata.2016.17 (2016).
  83 in total

1.  The relative significance of host-habitat, depth, and geography on the ecology, endemism, and speciation of coral endosymbionts in the genus Symbiodinium.

Authors:  J Christine Finney; Daniel Tye Pettay; Eugenia M Sampayo; Mark E Warner; Hazel A Oxenford; Todd C LaJeunesse
Journal:  Microb Ecol       Date:  2010-05-26       Impact factor: 4.552

2.  Ecological consequences of major hydrodynamic disturbances on coral reefs.

Authors:  Joshua S Madin; Sean R Connolly
Journal:  Nature       Date:  2006-11-23       Impact factor: 49.962

3.  Bleaching susceptibility and mortality of corals are determined by fine-scale differences in symbiont type.

Authors:  E M Sampayo; T Ridgway; P Bongaerts; O Hoegh-Guldberg
Journal:  Proc Natl Acad Sci U S A       Date:  2008-07-21       Impact factor: 11.205

4.  Taxonomic homogenization of woodland plant communities over 70 years.

Authors:  Sally A Keith; Adrian C Newton; Michael D Morecroft; Clive E Bealey; James M Bullock
Journal:  Proc Biol Sci       Date:  2009-07-22       Impact factor: 5.349

5.  Coral host transcriptomic states are correlated with Symbiodinium genotypes.

Authors:  M K DeSalvo; S Sunagawa; P L Fisher; C R Voolstra; R Iglesias-Prieto; M Medina
Journal:  Mol Ecol       Date:  2010-02-08       Impact factor: 6.185

6.  Differential effects of copper on three species of scleractinian corals and their algal symbionts (Symbiodinium spp.).

Authors:  G K Bielmyer; M Grosell; R Bhagooli; A C Baker; C Langdon; P Gillette; T R Capo
Journal:  Aquat Toxicol       Date:  2010-01-04       Impact factor: 4.964

7.  Genetic divergence across habitats in the widespread coral Seriatopora hystrix and its associated Symbiodinium.

Authors:  Pim Bongaerts; Cynthia Riginos; Tyrone Ridgway; Eugenia M Sampayo; Madeleine J H van Oppen; Norbert Englebert; Francisca Vermeulen; Ove Hoegh-Guldberg
Journal:  PLoS One       Date:  2010-05-27       Impact factor: 3.240

8.  Coral reef growth in the galapagos: limitation by sea urchins.

Authors:  P W Glynn; G M Wellington; C Birkeland
Journal:  Science       Date:  1979-01-05       Impact factor: 47.728

9.  Echinophyllia tarae sp. n. (Cnidaria, Anthozoa, Scleractinia), a new reef coral species from the Gambier Islands, French Polynesia.

Authors:  Francesca Benzoni
Journal:  Zookeys       Date:  2013-07-24       Impact factor: 1.546

10.  A pre-zygotic barrier to hybridization in two con-generic species of scleractinian corals.

Authors:  Andrew H Baird; Vivian R Cumbo; Joana Figueiredo; Saki Harii
Journal:  F1000Res       Date:  2013-09-20
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  39 in total

1.  Molecular convergence and positive selection associated with the evolution of symbiont transmission mode in stony corals.

Authors:  Groves B Dixon; Carly D Kenkel
Journal:  Proc Biol Sci       Date:  2019-04-24       Impact factor: 5.349

2.  The Whole-Genome Sequence of the Coral Acropora millepora.

Authors:  Hua Ying; David C Hayward; Ira Cooke; Weiwen Wang; Aurelie Moya; Kirby R Siemering; Susanne Sprungala; Eldon E Ball; Sylvain Forêt; David J Miller
Journal:  Genome Biol Evol       Date:  2019-05-01       Impact factor: 3.416

3.  Combining agent-based, trait-based and demographic approaches to model coral-community dynamics.

Authors:  Jason Pither; Lael Parrott; Bruno Sylvain Carturan; Jean-Philippe Maréchal; Corey Ja Bradshaw
Journal:  Elife       Date:  2020-07-23       Impact factor: 8.140

4.  Biogeographical disparity in the functional diversity and redundancy of corals.

Authors:  Mike McWilliam; Mia O Hoogenboom; Andrew H Baird; Chao-Yang Kuo; Joshua S Madin; Terry P Hughes
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-05       Impact factor: 11.205

5.  Local and regional controls of phylogenetic structure at the high-latitude range limits of corals.

Authors:  Brigitte Sommer; Eugenia M Sampayo; Maria Beger; Peter L Harrison; Russ C Babcock; John M Pandolfi
Journal:  Proc Biol Sci       Date:  2017-08-30       Impact factor: 5.349

Review 6.  Open Science principles for accelerating trait-based science across the Tree of Life.

Authors:  Rachael V Gallagher; Daniel S Falster; Brian S Maitner; Roberto Salguero-Gómez; Vigdis Vandvik; William D Pearse; Florian D Schneider; Jens Kattge; Jorrit H Poelen; Joshua S Madin; Markus J Ankenbrand; Caterina Penone; Xiao Feng; Vanessa M Adams; John Alroy; Samuel C Andrew; Meghan A Balk; Lucie M Bland; Brad L Boyle; Catherine H Bravo-Avila; Ian Brennan; Alexandra J R Carthey; Renee Catullo; Brittany R Cavazos; Dalia A Conde; Steven L Chown; Belen Fadrique; Heloise Gibb; Aud H Halbritter; Jennifer Hammock; J Aaron Hogan; Hamish Holewa; Michael Hope; Colleen M Iversen; Malte Jochum; Michael Kearney; Alexander Keller; Paula Mabee; Peter Manning; Luke McCormack; Sean T Michaletz; Daniel S Park; Timothy M Perez; Silvia Pineda-Munoz; Courtenay A Ray; Maurizio Rossetto; Hervé Sauquet; Benjamin Sparrow; Marko J Spasojevic; Richard J Telford; Joseph A Tobias; Cyrille Violle; Ramona Walls; Katherine C B Weiss; Mark Westoby; Ian J Wright; Brian J Enquist
Journal:  Nat Ecol Evol       Date:  2020-02-17       Impact factor: 15.460

7.  Deficits in functional trait diversity following recovery on coral reefs.

Authors:  Mike McWilliam; Morgan S Pratchett; Mia O Hoogenboom; Terry P Hughes
Journal:  Proc Biol Sci       Date:  2020-01-08       Impact factor: 5.349

8.  Linking dimensions of data on global marine animal diversity.

Authors:  Thomas J Webb; Bart Vanhoorne
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-11-02       Impact factor: 6.237

9.  Social-environmental drivers inform strategic management of coral reefs in the Anthropocene.

Authors:  Emily S Darling; Tim R McClanahan; Joseph Maina; Georgina G Gurney; Nicholas A J Graham; Fraser Januchowski-Hartley; Joshua E Cinner; Camilo Mora; Christina C Hicks; Eva Maire; Marji Puotinen; William J Skirving; Mehdi Adjeroud; Gabby Ahmadia; Rohan Arthur; Andrew G Bauman; Maria Beger; Michael L Berumen; Lionel Bigot; Jessica Bouwmeester; Ambroise Brenier; Tom C L Bridge; Eric Brown; Stuart J Campbell; Sara Cannon; Bruce Cauvin; Chaolun Allen Chen; Joachim Claudet; Vianney Denis; Simon Donner; Nur Fadli; David A Feary; Douglas Fenner; Helen Fox; Erik C Franklin; Alan Friedlander; James Gilmour; Claire Goiran; James Guest; Jean-Paul A Hobbs; Andrew S Hoey; Peter Houk; Steven Johnson; Stacy D Jupiter; Mohsen Kayal; Chao-Yang Kuo; Joleah Lamb; Michelle A C Lee; Jeffrey Low; Nyawira Muthiga; Efin Muttaqin; Yashika Nand; Kirsty L Nash; Osamu Nedlic; John M Pandolfi; Shinta Pardede; Vardhan Patankar; Lucie Penin; Lauriane Ribas-Deulofeu; Zoe Richards; T Edward Roberts; Ku'ulei S Rodgers; Che Din Mohd Safuan; Enric Sala; George Shedrawi; Tsai Min Sin; Patrick Smallhorn-West; Jennifer E Smith; Brigitte Sommer; Peter D Steinberg; Makamas Sutthacheep; Chun Hong James Tan; Gareth J Williams; Shaun Wilson; Thamasak Yeemin; John F Bruno; Marie-Josée Fortin; Martin Krkosek; David Mouillot
Journal:  Nat Ecol Evol       Date:  2019-08-12       Impact factor: 19.100

10.  The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project.

Authors:  Lawrence N Hudson; Tim Newbold; Sara Contu; Samantha L L Hill; Igor Lysenko; Adriana De Palma; Helen R P Phillips; Tamera I Alhusseini; Felicity E Bedford; Dominic J Bennett; Hollie Booth; Victoria J Burton; Charlotte W T Chng; Argyrios Choimes; David L P Correia; Julie Day; Susy Echeverría-Londoño; Susan R Emerson; Di Gao; Morgan Garon; Michelle L K Harrison; Daniel J Ingram; Martin Jung; Victoria Kemp; Lucinda Kirkpatrick; Callum D Martin; Yuan Pan; Gwilym D Pask-Hale; Edwin L Pynegar; Alexandra N Robinson; Katia Sanchez-Ortiz; Rebecca A Senior; Benno I Simmons; Hannah J White; Hanbin Zhang; Job Aben; Stefan Abrahamczyk; Gilbert B Adum; Virginia Aguilar-Barquero; Marcelo A Aizen; Belén Albertos; E L Alcala; Maria Del Mar Alguacil; Audrey Alignier; Marc Ancrenaz; Alan N Andersen; Enrique Arbeláez-Cortés; Inge Armbrecht; Víctor Arroyo-Rodríguez; Tom Aumann; Jan C Axmacher; Badrul Azhar; Adrián B Azpiroz; Lander Baeten; Adama Bakayoko; András Báldi; John E Banks; Sharad K Baral; Jos Barlow; Barbara I P Barratt; Lurdes Barrico; Paola Bartolommei; Diane M Barton; Yves Basset; Péter Batáry; Adam J Bates; Bruno Baur; Erin M Bayne; Pedro Beja; Suzan Benedick; Åke Berg; Henry Bernard; Nicholas J Berry; Dinesh Bhatt; Jake E Bicknell; Jochen H Bihn; Robin J Blake; Kadiri S Bobo; Roberto Bóçon; Teun Boekhout; Katrin Böhning-Gaese; Kevin J Bonham; Paulo A V Borges; Sérgio H Borges; Céline Boutin; Jérémy Bouyer; Cibele Bragagnolo; Jodi S Brandt; Francis Q Brearley; Isabel Brito; Vicenç Bros; Jörg Brunet; Grzegorz Buczkowski; Christopher M Buddle; Rob Bugter; Erika Buscardo; Jörn Buse; Jimmy Cabra-García; Nilton C Cáceres; Nicolette L Cagle; María Calviño-Cancela; Sydney A Cameron; Eliana M Cancello; Rut Caparrós; Pedro Cardoso; Dan Carpenter; Tiago F Carrijo; Anelena L Carvalho; Camila R Cassano; Helena Castro; Alejandro A Castro-Luna; Cerda B Rolando; Alexis Cerezo; Kim Alan Chapman; Matthieu Chauvat; Morten Christensen; Francis M Clarke; Daniel F R Cleary; Giorgio Colombo; Stuart P Connop; Michael D Craig; Leopoldo Cruz-López; Saul A Cunningham; Biagio D'Aniello; Neil D'Cruze; Pedro Giovâni da Silva; Martin Dallimer; Emmanuel Danquah; Ben Darvill; Jens Dauber; Adrian L V Davis; Jeff Dawson; Claudio de Sassi; Benoit de Thoisy; Olivier Deheuvels; Alain Dejean; Jean-Louis Devineau; Tim Diekötter; Jignasu V Dolia; Erwin Domínguez; Yamileth Dominguez-Haydar; Silvia Dorn; Isabel Draper; Niels Dreber; Bertrand Dumont; Simon G Dures; Mats Dynesius; Lars Edenius; Paul Eggleton; Felix Eigenbrod; Zoltán Elek; Martin H Entling; Karen J Esler; Ricardo F de Lima; Aisyah Faruk; Nina Farwig; Tom M Fayle; Antonio Felicioli; Annika M Felton; Roderick J Fensham; Ignacio C Fernandez; Catarina C Ferreira; Gentile F Ficetola; Cristina Fiera; Bruno K C Filgueiras; Hüseyin K Fırıncıoğlu; David Flaspohler; Andreas Floren; Steven J Fonte; Anne Fournier; Robert E Fowler; Markus Franzén; Lauchlan H Fraser; Gabriella M Fredriksson; Geraldo B Freire; Tiago L M Frizzo; Daisuke Fukuda; Dario Furlani; René Gaigher; Jörg U Ganzhorn; Karla P García; Juan C Garcia-R; Jenni G Garden; Ricardo Garilleti; Bao-Ming Ge; Benoit Gendreau-Berthiaume; Philippa J Gerard; Carla Gheler-Costa; Benjamin Gilbert; Paolo Giordani; Simonetta Giordano; Carly Golodets; Laurens G L Gomes; Rachelle K Gould; Dave Goulson; Aaron D Gove; Laurent Granjon; Ingo Grass; Claudia L Gray; James Grogan; Weibin Gu; Moisès Guardiola; Nihara R Gunawardene; Alvaro G Gutierrez; Doris L Gutiérrez-Lamus; Daniela H Haarmeyer; Mick E Hanley; Thor Hanson; Nor R Hashim; Shombe N Hassan; Richard G Hatfield; Joseph E Hawes; Matt W Hayward; Christian Hébert; Alvin J Helden; John-André Henden; Philipp Henschel; Lionel Hernández; James P Herrera; Farina Herrmann; Felix Herzog; Diego Higuera-Diaz; Branko Hilje; Hubert Höfer; Anke Hoffmann; Finbarr G Horgan; Elisabeth Hornung; Roland Horváth; Kristoffer Hylander; Paola Isaacs-Cubides; Hiroaki Ishida; Masahiro Ishitani; Carmen T Jacobs; Víctor J Jaramillo; Birgit Jauker; F Jiménez Hernández; McKenzie F Johnson; Virat Jolli; Mats Jonsell; S Nur Juliani; Thomas S Jung; Vena Kapoor; Heike Kappes; Vassiliki Kati; Eric Katovai; Klaus Kellner; Michael Kessler; Kathryn R Kirby; Andrew M Kittle; Mairi E Knight; Eva Knop; Florian Kohler; Matti Koivula; Annette Kolb; Mouhamadou Kone; Ádám Kőrösi; Jochen Krauss; Ajith Kumar; Raman Kumar; David J Kurz; Alex S Kutt; Thibault Lachat; Victoria Lantschner; Francisco Lara; Jesse R Lasky; Steven C Latta; William F Laurance; Patrick Lavelle; Violette Le Féon; Gretchen LeBuhn; Jean-Philippe Légaré; Valérie Lehouck; María V Lencinas; Pia E Lentini; Susan G Letcher; Qi Li; Simon A Litchwark; Nick A Littlewood; Yunhui Liu; Nancy Lo-Man-Hung; Carlos A López-Quintero; Mounir Louhaichi; Gabor L Lövei; Manuel Esteban Lucas-Borja; Victor H Luja; Matthew S Luskin; M Cristina MacSwiney G; Kaoru Maeto; Tibor Magura; Neil Aldrin Mallari; Louise A Malone; Patrick K Malonza; Jagoba Malumbres-Olarte; Salvador Mandujano; Inger E Måren; Erika Marin-Spiotta; Charles J Marsh; E J P Marshall; Eliana Martínez; Guillermo Martínez Pastur; David Moreno Mateos; Margaret M Mayfield; Vicente Mazimpaka; Jennifer L McCarthy; Kyle P McCarthy; Quinn S McFrederick; Sean McNamara; Nagore G Medina; Rafael Medina; Jose L Mena; Estefania Mico; Grzegorz Mikusinski; Jeffrey C Milder; James R Miller; Daniel R Miranda-Esquivel; Melinda L Moir; Carolina L Morales; Mary N Muchane; Muchai Muchane; Sonja Mudri-Stojnic; A Nur Munira; Antonio Muoñz-Alonso; B F Munyekenye; Robin Naidoo; A Naithani; Michiko Nakagawa; Akihiro Nakamura; Yoshihiro Nakashima; Shoji Naoe; Guiomar Nates-Parra; Dario A Navarrete Gutierrez; Luis Navarro-Iriarte; Paul K Ndang'ang'a; Eike L Neuschulz; Jacqueline T Ngai; Violaine Nicolas; Sven G Nilsson; Norbertas Noreika; Olivia Norfolk; Jorge Ari Noriega; David A Norton; Nicole M Nöske; A Justin Nowakowski; Catherine Numa; Niall O'Dea; Patrick J O'Farrell; William Oduro; Sabine Oertli; Caleb Ofori-Boateng; Christopher Omamoke Oke; Vicencio Oostra; Lynne M Osgathorpe; Samuel Eduardo Otavo; Navendu V Page; Juan Paritsis; Alejandro Parra-H; Luke Parry; Guy Pe'er; Peter B Pearman; Nicolás Pelegrin; Raphaël Pélissier; Carlos A Peres; Pablo L Peri; Anna S Persson; Theodora Petanidou; Marcell K Peters; Rohan S Pethiyagoda; Ben Phalan; T Keith Philips; Finn C Pillsbury; Jimmy Pincheira-Ulbrich; Eduardo Pineda; Joan Pino; Jaime Pizarro-Araya; A J Plumptre; Santiago L Poggio; Natalia Politi; Pere Pons; Katja Poveda; Eileen F Power; Steven J Presley; Vânia Proença; Marino Quaranta; Carolina Quintero; Romina Rader; B R Ramesh; Martha P Ramirez-Pinilla; Jai Ranganathan; Claus Rasmussen; Nicola A Redpath-Downing; J Leighton Reid; Yana T Reis; José M Rey Benayas; Juan Carlos Rey-Velasco; Chevonne Reynolds; Danilo Bandini Ribeiro; Miriam H Richards; Barbara A Richardson; Michael J Richardson; Rodrigo Macip Ríos; Richard Robinson; Carolina A Robles; Jörg Römbke; Luz Piedad Romero-Duque; Matthias Rös; Loreta Rosselli; Stephen J Rossiter; Dana S Roth; T'ai H Roulston; Laurent Rousseau; André V Rubio; Jean-Claude Ruel; Jonathan P Sadler; Szabolcs Sáfián; Romeo A Saldaña-Vázquez; Katerina Sam; Ulrika Samnegård; Joana Santana; Xavier Santos; Jade Savage; Nancy A Schellhorn; Menno Schilthuizen; Ute Schmiedel; Christine B Schmitt; Nicole L Schon; Christof Schüepp; Katharina Schumann; Oliver Schweiger; Dawn M Scott; Kenneth A Scott; Jodi L Sedlock; Steven S Seefeldt; Ghazala Shahabuddin; Graeme Shannon; Douglas Sheil; Frederick H Sheldon; Eyal Shochat; Stefan J Siebert; Fernando A B Silva; Javier A Simonetti; Eleanor M Slade; Jo Smith; Allan H Smith-Pardo; Navjot S Sodhi; Eduardo J Somarriba; Ramón A Sosa; Grimaldo Soto Quiroga; Martin-Hugues St-Laurent; Brian M Starzomski; Constanti Stefanescu; Ingolf Steffan-Dewenter; Philip C Stouffer; Jane C Stout; Ayron M Strauch; Matthew J Struebig; Zhimin Su; Marcela Suarez-Rubio; Shinji Sugiura; Keith S Summerville; Yik-Hei Sung; Hari Sutrisno; Jens-Christian Svenning; Tiit Teder; Caragh G Threlfall; Anu Tiitsaar; Jacqui H Todd; Rebecca K Tonietto; Ignasi Torre; Béla Tóthmérész; Teja Tscharntke; Edgar C Turner; Jason M Tylianakis; Marcio Uehara-Prado; Nicolas Urbina-Cardona; Denis Vallan; Adam J Vanbergen; Heraldo L Vasconcelos; Kiril Vassilev; Hans A F Verboven; Maria João Verdasca; José R Verdú; Carlos H Vergara; Pablo M Vergara; Jort Verhulst; Massimiliano Virgilio; Lien Van Vu; Edward M Waite; Tony R Walker; Hua-Feng Wang; Yanping Wang; James I Watling; Britta Weller; Konstans Wells; Catrin Westphal; Edward D Wiafe; Christopher D Williams; Michael R Willig; John C Z Woinarski; Jan H D Wolf; Volkmar Wolters; Ben A Woodcock; Jihua Wu; Joseph M Wunderle; Yuichi Yamaura; Satoko Yoshikura; Douglas W Yu; Andrey S Zaitsev; Juliane Zeidler; Fasheng Zou; Ben Collen; Rob M Ewers; Georgina M Mace; Drew W Purves; Jörn P W Scharlemann; Andy Purvis
Journal:  Ecol Evol       Date:  2016-12-16       Impact factor: 2.912

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