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Cited by 139Marine and fisheries researchFish Ecology and Management StudiesFish Biology and Ecology Studies

Effects of temperature on global patterns of tuna and billfish richness

Open access
Boyce, DG, Tittensor, DP, Worm, B·2008·Marine Ecology Progress Series
DOI 10.3354/meps07237
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Abstract

Although tunas and billfishes are of substantial economic importance and conservation concern, global patterns of diversity and distribution remain poorly understood.Many species are highly migratory and able to tolerate a wide thermal range.In the present study, ambient water temperature data for 18 species of tuna and billfish from 190 literature sources were combined according to geographical location.An empirical modelling approach was used to relate temperature tolerances of tunas and billfishes to their global diversity patterns.Mean preferred and tolerated temperature ranges were calculated for each species in the adult and juvenile life stages.Mean tolerance data were then overlaid in order to fit models relating the species richness of tunas and billfishes to ambient water temperature.The best-fit model was used in conjunction with gridded water temperature data to predict global species richness patterns.Cumulative species richness predictions from water temperature data were positively correlated with observed longline-derived richness data (r = 0.577, p < 0.0001).Diversity consistently peaked at intermediate latitudes (10 to 35° N and S) in a manner similar to other pelagic taxa.This analysis provides evidence that the ambient water temperature tolerances of tunas and billfishes can be used to predict broad species richness patterns on a global scale.

AI snapshot

Written from the paper’s full text.

TL;DR

Temperature tolerances compiled for 18 tuna and billfish species predicted global richness patterns that correlated with longline-derived richness, peaking at intermediate latitudes. The best-fit third-order polynomial predicted peak richness at ~22.5°C and at 100 m depth gave the strongest correlation with observed data.

Key findings

  • Cumulative temperature-predicted species richness was positively correlated with rarefied longline-derived richness at 100 m (r = 0.577, p < 0.0001), stronger than at 0 m (r = 0.282) or 50 m (r = 0.420).
  • The best-fit third-order polynomial predicted peak species richness at T_optimum ≈ 22.5°C (r² = 0.978); separately, peak richness was ~21°C for Thunnus (r² = 0.976) and ~24°C for Istiophoridae and Xiphidae (r² = 0.919).
  • Predicted richness peaked at intermediate latitudes (10 to 35° N and S) and declined toward polar and equatorial regions; maximum predicted richness was higher in the Indo-Pacific (11 species, T_optimum ≈ 22°C, r² = 0.978) than the Atlantic (9 species, T_optimum ≈ 21°C, r² = 0.979).
  • Among tunas, body length was positively related to maximum temperature range (r = 0.881, p = 0.0004), but not among billfishes (r = 0.456, p = 0.297); spawning occurred in waters about 5°C warmer than those typically inhabited by juveniles or adults.

Methods

  • Compiled ambient water temperature tolerances and preferences for 18 tuna and billfish species from 190 publications published January 1950 to April 2006, separated by adult, juvenile, and larval life stages where data allowed.
  • Calculated mean temperature tolerances and species richness at 1°C increments, fitted second-, third-, and fourth-order polynomial regressions plus inverse polynomial and Poisson GLMs, and selected the best-fit third-order polynomial using AIC.
  • Predicted global richness from NOAA World Ocean Atlas 2001 mean water temperature at 0, 50, and 100 m on a 5° grid, then compared predictions with rarefied species richness from Japanese pelagic longline logbook data (1952–1999) across 5° × 5° cells (n = 1983 cells), including percentile binning for spatial comparison.

Limitations

  • The paper states that temperature data were unavailable for any spearfish, 2 tuna species, and sparse for 8 of the studied species, and that detailed effects of water temperature on spawning behavior remain poorly resolved.
  • The paper states that other regionally important factors—such as ocean fronts, reefs, shelf breaks, seamounts, eddies, and productivity—were not taken into account, and that depth mismatches between database temperature records and the 100 m prediction depth, plus variation in vertical distribution and possible tracking-vessel effects, are sources of error.
  • The paper notes that longlining data exclude some coastal areas within Exclusive Economic Zones and that longlining included spearfishes but excluded many smaller tunas included in the present data set; it also reports overprediction in the Atlantic and southern Indian Oceans, which it suggests may relate to exploitation.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3354/meps07237

Cites

38 of 38 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

1 of 57 cited sources checked · 1 supported · 0 flagged

  • Findingown data

    Marlins, sailfishes, and many small tropical tunas (kawakawa, little tunny, and skipjack) were less tolerant of low water temperatures than the larger species of tuna and billfish (bluefin, bigeye, yellowfin, and swordfish).

    “Furthermore, marlins, sailfishes, and many small tropical tunas (kawakawa, little tunny, and skipjack) were less tolerant of low water temperatures than the larger species of tuna and billfish (bluefin, bigeye, yellowfin, and swordfish) (Table 1, Fig. 1A).”
    Quote in the paperSubstantial claim
  • Findingown data

    Total species richness against water temperature was best approximated by a third-order polynomial regression model yielding a predicted peak in species richness at Topt ≈ 22.5°C (r2 = 0.978).

    “Total species richness against water temperature was best approximated by a third-order polynomial regression model yielding a predicted peak in species richness at a water temperature of T optimum ≈ 22.5°C (r 2 = 0.978) (Fig. 2C).”
    Quote in the paperSubstantial claim
  • Findingown data

    The model under-predicted relative species richness in the northwest Atlantic and Pacific Oceans.

    “The model under-predicted relative species richness in the northwest Atlantic and Pacific Oceans (Fig. 4C).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: Rarefaction correctly orders cells in terms of relative species richness.
    • Rests on an assumption: The difference between rarefied and actual (asymptotic) species richness values varies between cells.
    • Rests on an assumption: The Japanese longline data set encompasses the estimated global range of all tuna and billfish species, excluding some coastal areas within individual countries' Exclusive Economic Zones.
  • Findingown data

    Mean temperature preferences for marlins and sailfishes were skewed towards the warmer end of their mean tolerance range.

    “While mean temperature preferences for these species were approximately centred on the mean tolerance range, mean preferences for marlins (5 species) and sailfishes (2 species) were skewed towards the warmer end of their mean tolerance range.”
    Quote in the paperNot a substantial claim
  • Findingown data

    The largest discrepancies between predicted and rarefied percentiles were in mid-latitudinal regions of the Atlantic and Indian Oceans, where the model over-predicted relative species richness.

    “The largest discrepancies were noted for mid-latitudinal regions of the Atlantic and Indian Oceans, where the model appeared to over-predict relative species richness (Fig. 4C).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: Rarefaction correctly orders cells in terms of relative species richness.
    • Rests on an assumption: The difference between rarefied and actual (asymptotic) species richness values varies between cells.
    • Rests on an assumption: The Japanese longline data set encompasses the estimated global range of all tuna and billfish species, excluding some coastal areas within individual countries' Exclusive Economic Zones.
  • Classified as probably not a substantial claim. 16
  • The quote only partly states this claim. 1
  • May combine two claims. 18

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The development of satellite and other tagging technologies has greatly increased our understanding of the distribution patterns of tunas and billfishes.

    “While the development of satellite and other tagging technologies has greatly increased our understanding of the distribution patterns of tunas and billfishes (Sedberry & Loefer 2001, Boustany et al. 2002, Graves et al. 2002, Block et al. 2005), there are still information gaps for particular species.”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites Sedberry & Loefer 2001 source
    • cites Boustany et al. 2002 source
    • cites Graves et al. 2002

  • Probably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.

    Findingnone given

    Correlations between predicted and rarefied species richness tended to strengthen marginally over time.

    “Correlations tended to strengthen marginally over time.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: Rarefaction correctly orders cells in terms of relative species richness.
    • Rests on an assumption: The difference between rarefied and actual (asymptotic) species richness values varies between cells.
    • Rests on an assumption: The Japanese longline data set encompasses the estimated global range of all tuna and billfish species, excluding some coastal areas within individual countries' Exclusive Economic Zones.

  • May combine two claims.

    Findingown data

    Spawning occurs in waters much warmer (ΔT ≈ 5°C) than those typically inhabited by juveniles or adults, often on the upper fringes of the reported mean adult temperature tolerance range.

    “Results indicated that spawning occurs in waters that are much warmer (ΔT ≈ 5°C) than those typically inhabited by juveniles or adults, and which have temperatures that are often on the upper fringes of the reported mean adult temperature tolerance range; this was the case, for example, in southern and pacific bluefin tunas and albacore tuna (Table 1, Fig. 1).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Maximum predicted and observed global species richness both occurred at intermediate latitudes (10 to 35° N and S), and decreased towards polar and equatorial regions.

    “Diversity consistently peaked at intermediate latitudes (10 to 35° N and S) in a manner similar to other pelagic taxa.”
    • Also stated in: § RESULTS · plain
      “Maximum predicted and observed global species richness both occurred at intermediate latitudes (10 to 35° N and S), and decreased towards polar and equatorial regions.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Rarefaction correctly orders cells in terms of relative species richness.
    • Rests on an assumption: The difference between rarefied and actual (asymptotic) species richness values varies between cells.
    • Rests on an assumption: The Japanese longline data set encompasses the estimated global range of all tuna and billfish species, excluding some coastal areas within individual countries' Exclusive Economic Zones.

  • May combine two claims.

    Findingown data

    Temperature studies were sparse for kawakawa and little tunny and lacking for longtail tuna, blackfin tuna, shortbill spearfish, longbill spearfish, and Mediterranean spearfish.

    “Temperature studies were sparse for kawakawa and little tunny and lacking for longtail tuna Thunnus tonggol, blackfin tuna Thunnus atlanticus, shortbill spearfish Tetrapturus angustirostris, longbill spearfish Tetrapturus pfluegeri and Mediterranean spearfish Tetrapturus pelone.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Total global predicted species richness was strongly related to water temperature, with peak species richness predicted at ~22.5°C (r2 = 0.978, p < 0.0001).

    “Total global predicted species richness was strongly related to water temperature, with peak species richness predicted at ~22.5°C (r 2 = 0.978, p < 0.0001) (Fig. 2C).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    Marlins, sailfishes, and most small tropical tuna species (kawakawa, little tunny, and skipjack tuna) appeared to possess a higher tolerance for warmer waters and a lower tolerance for colder waters.

    “Unsurprisingly, marlins, sailfishes, and most small tropical tuna species (kawakawa, little tunny, and skipjack tuna) appeared to possess a higher tolerance for warmer waters and a lower tolerance for colder waters.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In the Atlantic and Indian Oceans, predicted species richness peaks were more widely distributed, although still occurring at intermediate latitudes (10 to 35° N and S).

    “In the Atlantic and Indian Oceans, predicted species richness peaks were more widely distributed, although still occurring at intermediate latitudes (10 to 35° N and S) (Fig. 4A).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    Data regarding water temperature tolerances and preferences were unavailable for any species of spearfish, 2 species of tunas, and sparse for 8 of the species of tuna and billfish studied here.

    “Data regarding water temperature tolerances and preferences were unavailable for any species of spearfish, 2 species of tunas, and sparse for 8 of the species of tuna and billfish studied here.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    This latitudinal pattern is similar to that previously found for the diversity of tunas and billfishes, as well as foraminifera and other zooplankton groups.

    “This latitudinal pattern is similar to that previously found for the diversity of tunas and billfishes (Worm et al. 2003(Worm et al. , 2005)), as well as foraminifera and other zooplankton groups (Rutherford et al. 1999).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Worm et al. 2003 source
    • cites Worm et al. 2005 source
    • cites Rutherford et al. 1999 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Bigeye tuna are capable of diving to depths of 600 m.

    “For example, bigeye tuna are capable of diving to depths of 600 m (Hanamoto 1987, Brill & Lutcavage 2001)”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Hanamoto 1987

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Brill & Lutcavage 2001

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    Several species maintain warm brains, and many larger species of tuna (albacore, bigeye, yellowfin, and bluefins) conserve heat in their viscera.

    “For instance, several species maintain warm brains, and many larger species of tuna (albacore, bigeye, yellowfin, and bluefins) conserve heat in their viscera.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Block & Stevens 2001 source

  • May combine two claims.

    Interpretationreasoning

    Tunas generally are found in more temperate waters, migrate further and dive deeper than billfishes (except swordfish).

    “Accordingly, tunas generally are found in more temperate waters, migrate further and dive deeper than billfishes (except swordfish).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The improvement in fit in more recent decades is potentially the result of more accurate empirical richness estimates due to the greater geographic distribution and magnitude of fishing effort by the Japanese longlining fleet in these decades.

    “The improvement in fit in more recent decades is potentially the result of more accurate empirical richness estimates due to the greater geographic distribution and magnitude of fishing effort by the Japanese longlining fleet in these decades.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: More recent decades have more accurate empirical richness estimates due to greater geographic distribution and magnitude of fishing effort by the Japanese longlining fleet.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Second-, third-, and fourth-order polynomial linear regression models were checked for fit using AIC values after testing assumptions of normality and homogeneity of variance.

    “Second-, third-, and fourth-order polynomial linear regression models were fitted to these data and checked for fit using Akaike Information Criterion (AIC) values, after testing assumptions of normality and homogeneity of variance.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Northern bluefin are known to undertake trans-Atlantic migrations spanning a wide range of thermal habitats.

    “and northern bluefin are known to undertake trans-Atlantic migrations spanning a wide range of thermal habitats (Block et al. 2005).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Block et al. 2005 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The difference between predicted and longlining-derived global species diversity peaks may be related to variation in sampling methods, sampling depth, or other unmeasured covariates.

    “This difference may be related to variation in sampling methods, sampling depth, or other unmeasured covariates.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    While temperature may be among the best global predictors for the distribution of these species, other factors are regionally important.

    “While temperature may be among the best global predictors for the distribution of these species, other factors are regionally important (Worm et al. 2005).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Worm et al. 2005 source

  • May combine two claims.

    Premisecitation

    Marlins and sailfishes are predominantly epipelagic, remaining largely within the upper mixed layer, with occasional dives as deep as 200 m.

    “Marlins and sailfishes are predominantly epipelagic, remaining largely within the upper mixed layer (Brill et al. 1993), with occasional dives as deep as 200 m (Block et al. 1992).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Brill et al. 1993 source
    • cites Block et al. 1992 source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationcitation

    Given that tunas generally possess greater heterothermic capacities relative to billfishes, these results are consistent with previous studies.

    “Given that tunas generally possess greater heterothermic capacities relative to billfishes (Dickson 1995), these results are consistent with previous studies.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Dickson 1995 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Spawning behaviour of tunas and billfishes that prefer very warm waters may also account for the fact that optimal water temperature was lower in this study compared with longlining records, which may target spawning aggregations.

    “Spawning behaviour of tunas and billfishes that prefer very warm waters may also account for the fact that optimal water temperature was lower in this study compared with longlining records, which may target spawning aggregations.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Body size may limit the thermal range for tunas but not billfishes.

    “suggesting that body size may limit the thermal range for tunas but not billfishes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Previous work on freshwater ectothermic fish species and other tunas found increased physiological temperature tolerance with increased body size.

    “This finding is consistent with previous work on freshwater ectothermic fish species (Magnuson et al. 1979) and other tunas (Barkley et al. 1978, Sharp 1978), which found increased physiological temperature tolerance with increased body size.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Magnuson et al. 1979 source
    • cites Barkley et al. 1978

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Sharp 1978 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Northern bluefin tuna can dive to depths in excess of 1000 m, encountering an exceptionally wide thermal range.

    “Northern bluefin tuna, for example, can dive to depths in excess of 1000 m, encountering an exceptionally wide thermal range (Block et al. 2005).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Block et al. 2005 source

  • May combine two claims.

    Premisecitation

    A recent assessment from the United Nations Food and Agriculture Organization indicated that 4 major tuna species (albacore, Atlantic and southern bluefin, and bigeye tunas) are overexploited or depleted in the Atlantic Ocean, whereas in the Indian and Pacific Oceans only 2 species are listed as fully exploited or depleted.

    “This is supported by a recent assessment from the United Nations Food and Agriculture Organization (Maguire et al. 2006), which indicated that 4 major tuna species (albacore, Atlantic and southern bluefin, and bigeye tunas) are overexploited or depleted in the Atlantic Ocean, whereas in the Indian and Pacific Oceans only 2 species are listed as fully exploited or depleted.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Maguire et al. 2006

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Variation between the depth at which database temperature information was recorded and that used to predict ranges (100 m) is another possible source of error.

    “Variation between the depth at which database temperature information was recorded and that used to predict ranges (100 m) is another possible source of error.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data

    The ability to accurately identify key oceanographic variables, such as temperature, that underlie large-scale tuna and billfish range distributions may have implications for conservation and management.

    “The ability to accurately identify key oceanographic variables, such as temperature, that underlie large-scale tuna and billfish range distributions may have implications for conservation and management.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Oceanic fronts and eddies frequently attract tunas and billfishes, likely because they can enhance and concentrate local productivity.

    “Similarly, oceanic fronts and eddies frequently attract tunas and billfishes (Sund et al. 1981, Laurs et al. 1984, Fiedler & Bernard 1987, Santos 1994), likely because they can enhance and concentrate local productivity (Wolanski & Hamner 1988, Oschlies & Garçon 1998).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Sund et al. 1981
    • cites Laurs et al. 1984 source
    • cites Fiedler & Bernard 1987 source

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Study design and conductnone given

    As mean water temperature is not related to the occurrence of these habitat features, their effects on tuna and billfish abundance and richness have not been taken into account in this analysis.

    “As mean water temperature is not related to the occurrence of these habitat features, their effects on tuna and billfish abundance and richness have not been taken into account in this analysis.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Mean water temperature is not related to the occurrence of ocean fronts, reefs, shelf breaks and seamounts.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Bigeye tuna catch rates as a function of depth vary with latitude in the eastern tropical Pacific, possibly relating to zonal currents.

    “For example, bigeye tuna catch rates as a function of depth have been shown to vary with latitude in the eastern tropical Pacific, possibly relating to zonal currents (Hanamoto 1974).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Hanamoto 1974

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationown data

    The analysis allows prediction of the occurrence of tuna and billfish diversity hotspots and the effects of variation in temperature on those features, e.g. through the El Niño Southern Oscillation or gradual ocean warming.

    “It allows prediction of the occurrence of tuna and billfish diversity hotspots and the effects of variation in temperature on those features, e.g. through the El Niño Southern Oscillation or gradual ocean warming.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The rarefied species richness derived from Japanese longlining data (1990-1999) accurately reflects true tuna and billfish species richness.
    • Rests on an assumption: Temperature at 100 m depth is an adequate predictor of tuna and billfish species richness despite vertical variation.
31 of 31

  • The authors state this as an assumption.

    Rarefaction correctly orders cells in terms of relative species richness.

    “Although we assumed that rarefaction correctly orders cells in terms of relative species richness, the difference between rarefied and actual (asymptotic) species richness values varies between cells.”

  • The paper relies on this without support.

    The difference between rarefied and actual (asymptotic) species richness values varies between cells.

    “Although we assumed that rarefaction correctly orders cells in terms of relative species richness, the difference between rarefied and actual (asymptotic) species richness values varies between cells.”

  • The paper relies on this without support.

    The Japanese longline data set encompasses the estimated global range of all tuna and billfish species, excluding some coastal areas within individual countries' Exclusive Economic Zones.

    “The longlining data set encompasses the estimated global range of all tuna and billfish species, excluding some coastal areas within individual countries' Exclusive Economic Zones.”

  • The paper relies on this without support.

    More cold-tolerant Thunnus spp. and swordfish are capable of diving to depths well below 200 m, where temperatures are much lower.

    “In contrast, the more coldtolerant Thunnus spp.and swordfish are capable of diving to depths well below 200 m, where temperatures are much lower.”

  • The paper relies on this without support.

    These species maintain elevated deep muscle temperatures which enable them to remain active in colder waters.

    “These species maintain elevated deep muscle temperatures which enable them to remain active in colder waters.”

  • The paper relies on this without support.

    100 m is the most common depth at which longline hooks are set.

    “The improvement in fit with increasing water depth is best explained by the fact that 100 m is the most common depth at which longline hooks are set, resulting in the best fit against empirical longline data.”

  • The paper relies on this without support.

    More recent decades have more accurate empirical richness estimates due to greater geographic distribution and magnitude of fishing effort by the Japanese longlining fleet.

    “The improvement in fit in more recent decades is potentially the result of more accurate empirical richness estimates due to the greater geographic distribution and magnitude of fishing effort by the Japanese longlining fleet in these decades.”

  • The paper relies on this without support.

    Longlining data included spearfishes Tetrapturus spp. but excluded many smaller tunas (kawakawa, little tunny, and slender tuna), all of which are included in the present data set.

    “Furthermore, longlining data included spearfishes Tetrapturus spp.but excluded many smaller tunas (kawakawa, little tunny, and slender tuna), all of which are included in the present data set; such variation may also be partly responsible for discrepancies.”

  • The paper relies on this without support.

    Mean water temperature is not related to the occurrence of ocean fronts, reefs, shelf breaks and seamounts.

    “As mean water temperature is not related to the occurrence of these habitat features, their effects on tuna and billfish abundance and richness have not been taken into account in this analysis.”

  • The paper relies on this without support.

    Subsurface tracking methods accurately record ambient water temperature regardless of depth.

    “Such methods accurately record ambient water temperature regardless of depth.”

  • The paper relies on this without support.

    The rarefied species richness derived from Japanese longlining data (1990-1999) accurately reflects true tuna and billfish species richness.

    “Linear regression fit of predicted species richness at 100 m depth against rarefied species richness from longlining data (1990-1999).”

  • The paper relies on this without support.

    The temperature tolerances and preferences compiled from various sources are accurate and representative for each species.

    “Data regarding water temperature tolerances and preferences were unavailable for any species of spearfish, 2 species of tunas, and sparse for 8 of the species of tuna and billfish studied here.”

  • The paper relies on this without support.

    Temperature at 100 m depth is an adequate predictor of tuna and billfish species richness despite vertical variation.

    “Using temperature at 100 m to predict patterns of richness when temperature information was gathered at a range of depths will likely not completely capture distribution patterns.”

  • The paper relies on this without support.

    The 18 species studied represent global tuna and billfish richness.

    “cumulative (all 18 species, all oceans)”
14 of 14

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Temperature and oxygen affect important biological processes and thus determine the spatial distribution of tunas.

    “Temperature and oxygen affect important biological processes and thus determine the spatial distribution of tunas (Barkley et al., 1978;Boyce et al., 2008;Brill, 1994;Strama et al., 2012).”

    From Global habitat preferences of commercially valuable tuna (2015) · cites this paper as Boyce et al., 2008

    The Introduction links physiological temperature tolerance to tuna range boundaries and identifies temperature as a strong predictor of distribution. It mentions oxygen content only as a factor hypothesized to correlate with abundance and distribution; it does not establish that oxygen affects biological processes and thereby determines tuna distribution. The cited claim states that relationship more definitively than this paper does. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • In the case of albacore, our quotient analysis results for temperature preference (up to and beyond 20oC) are comparable to those of Hazen et al. (2013), while our GAM results suggest somewhat lower preferred values (around 15oC), more in line with Boyce et al. (2008) and Lan et al. (2012).

    “In the case of albacore, our quotient analysis results for temperature preference (up to and beyond 20ºC) are comparable to those of Hazen et al. (2013), while our GAM results suggest somewhat lower preferred values (around 15ºC), more in line with Boyce et al. (2008) and Lan et al. (2012).”

    From Global habitat preferences of commercially valuable tuna (2015) · cites this paper as Boyce et al. (2008)

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • There have been several studies using alternative techniques, datasets and models, providing comprehensive descriptions of the habitat preferences of tunas in the past.

    “There have been several studies using alternative techniques, datasets and models, providing comprehensive descriptions of the habitat preferences of tunas in the past (see Boyce et al., 2008;Brill, 1994;Brill and Lutcavage, 2001;Sund et al., 1981).”

    From Global habitat preferences of commercially valuable tuna (2015) · cites this paper as Boyce et al., 2008

    The Abstract and Database sections describe a study that compiled temperature preferences and tolerances for tuna and billfish species from 190 publications and used an empirical model to predict global richness patterns. This supports citing Boyce et al. as an example of a study using datasets and modelling to examine tuna preferences, but its focus is thermal preferences, not comprehensive habitat preferences more broadly. The supplied copy gives no page numbers for these passages. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Temperature is a key factor in determining the distributions of adult tuna.

    “Temperature is a key factor in determining the distributions of adult tuna (Worm et al. 2005, Boyce et al. 2008, Tittensor et al. 2010), as well as of larvae (present study).”

    From Worldwide distributions of tuna larvae: revisiting hypotheses on environmental requirements for spawning habitats (2014) · cites this paper as Boyce et al. 2008

  • Temperature preferences provided in Boyce et al. (2008) are comparable to those provided in this study.

    “For example, temperature preferences provided in Boyce et al. (2008) are comparable to those provided in this study.”

    From Global habitat preferences of commercially valuable tuna (2015) · cites this paper as Boyce et al. (2008)

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Cumulative model peaks below its reported optimum

    Major

    The stated cumulative polynomial reaches its maximum at approximately 21.6°C, not the reported ~22.5°C.

  • Billfish model peaks below its reported optimum

    Major

    The stated billfish polynomial reaches its maximum at approximately 22.6°C, not the reported ~24°C.

2 of 2

Cites

Flagged first, then by citations

1 of the 39 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Santos AM (1994) Satellite oceanography applications to the swordfish fishery off Portugal's continental west coast. MSc thesis, University of Lisbon

Cited by

Sorted by citations

Related

Authors
Boyce, D., Tittensor, D., & Worm, B.
Venue
Marine Ecology Progress Series
Publisher
Inter-Research Science Center
Published
2008-02-26
Volume
355
Pages
267-276
ISSN
  • 0171-8630 (ISSN-L)
  • 1616-1599
DOI
10.3354/meps07237
OpenAlex
W2139585483
Semantic Scholar
4c1b29b2614cfd624d64adbf059bc75f329e09bb
Cited by
139
References
39
Citations by year
2026: 8 · 2025: 8 · 2024: 10 · 2023: 7 · 2022: 4 · 2021: 10 · 2020: 9 · 2019: 11 · 2018: 9 · 2017: 7 · 2016: 8 · 2015: 7 · 2014: 6 · 2013: 4 · 2012: 8
FWCI
6.78
Type
journal article
Language
en
Open access
Locations
Marine Ecology Progress Series (publishedVersion)
Funders
  • Alfred P. Sloan Foundation
  • National Oceanic and Atmospheric Administration
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Marine and fisheries research
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
  • Life Sciences › Agricultural and Biological Sciences › Aquatic Science › Fish Biology and Ecology Studies
Keywords
tuna, billfish, species richness, water temperature, heat tolerance, thermal preference, latitudinal diversity gradient, species distribution, pelagic fish, longline survey, global biodiversity patterns

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-16.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-16.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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