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Global Diversity Estimates Need to Acknowledge Species–Area Relationships.

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Title: Global Diversity Estimates Need to Acknowledge Species–Area Relationships.
Authors: Faurby, S.1,2 (AUTHOR) soren.faurby@bioenv.gu.se, Matthews, T. J.3,4 (AUTHOR), Silvestro, D.1,2,5,6 (AUTHOR)
Source: Global Ecology & Biogeography. Jun2026, Vol. 35 Issue 6, p1-10. 10p.
Subjects: Selection bias (Statistics), Extrapolation, Biodiversity, Species diversity, Biodiversity monitoring, Species, Insect-plant relationships
Abstract: Background: Many studies have tried to estimate the number of undescribed species based on the known diversity. These estimates often rely on extrapolation based on data from a limited number of species. Although statistical methods provide accurate inference when generalizing from a random sample, their predictions will be biased when based on a non‐random sample unless the sampling process is explicitly accounted for. Problem: In this paper, we argue that this is a fundamental issue in many estimates of unrecorded biodiversity. We show that the sample of species used in biodiversity extrapolation represents disproportionately common and abundant taxa, which leads to an overestimation of extrapolated diversity. We discuss this issue in the context of three specific cases: estimates of plant‐associated insect diversity, estimates of parasite diversity and estimates of cryptic species diversity. Implications: For the example of plant‐associated insects, we provide an estimate of the magnitude of the error, but insufficient data are currently available to estimate the magnitude of the problem for the other examples. Our findings cast doubt over previous attempts to estimate the number of undescribed species, suggesting that they provide consistent overestimations. [ABSTRACT FROM AUTHOR]
Copyright of Global Ecology & Biogeography is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 194916897
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PubType: Academic Journal
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  Data: Global Diversity Estimates Need to Acknowledge Species–Area Relationships.
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  Data: <searchLink fieldCode="AR" term="%22Faurby%2C+S%2E%22">Faurby, S.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> soren.faurby@bioenv.gu.se</i><br /><searchLink fieldCode="AR" term="%22Matthews%2C+T%2E+J%2E%22">Matthews, T. J.</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Silvestro%2C+D%2E%22">Silvestro, D.</searchLink><relatesTo>1,2,5,6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Global+Ecology+%26+Biogeography%22">Global Ecology & Biogeography</searchLink>. Jun2026, Vol. 35 Issue 6, p1-10. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Selection+bias+%28Statistics%29%22">Selection bias (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Extrapolation%22">Extrapolation</searchLink><br /><searchLink fieldCode="DE" term="%22Biodiversity%22">Biodiversity</searchLink><br /><searchLink fieldCode="DE" term="%22Species+diversity%22">Species diversity</searchLink><br /><searchLink fieldCode="DE" term="%22Biodiversity+monitoring%22">Biodiversity monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Species%22">Species</searchLink><br /><searchLink fieldCode="DE" term="%22Insect-plant+relationships%22">Insect-plant relationships</searchLink>
– Name: Abstract
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  Data: Background: Many studies have tried to estimate the number of undescribed species based on the known diversity. These estimates often rely on extrapolation based on data from a limited number of species. Although statistical methods provide accurate inference when generalizing from a random sample, their predictions will be biased when based on a non‐random sample unless the sampling process is explicitly accounted for. Problem: In this paper, we argue that this is a fundamental issue in many estimates of unrecorded biodiversity. We show that the sample of species used in biodiversity extrapolation represents disproportionately common and abundant taxa, which leads to an overestimation of extrapolated diversity. We discuss this issue in the context of three specific cases: estimates of plant‐associated insect diversity, estimates of parasite diversity and estimates of cryptic species diversity. Implications: For the example of plant‐associated insects, we provide an estimate of the magnitude of the error, but insufficient data are currently available to estimate the magnitude of the problem for the other examples. Our findings cast doubt over previous attempts to estimate the number of undescribed species, suggesting that they provide consistent overestimations. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Global Ecology & Biogeography is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1111/geb.70267
    Languages:
      – Code: eng
        Text: English
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        PageCount: 10
        StartPage: 1
    Subjects:
      – SubjectFull: Selection bias (Statistics)
        Type: general
      – SubjectFull: Extrapolation
        Type: general
      – SubjectFull: Biodiversity
        Type: general
      – SubjectFull: Species diversity
        Type: general
      – SubjectFull: Biodiversity monitoring
        Type: general
      – SubjectFull: Species
        Type: general
      – SubjectFull: Insect-plant relationships
        Type: general
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      – TitleFull: Global Diversity Estimates Need to Acknowledge Species–Area Relationships.
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            NameFull: Matthews, T. J.
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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