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update: Species–area curves and the estimation of extinction rates - eScholarship

Jan Beck

Published 2012 in Frontiers of biogeography

ABSTRACT

news and update ISSN 1948‐6596 update Species–area curves and the estimation of extinction rates The species–area relationship (SAR) is one of the longest‐known, most intuitive and empirically best ‐proven patterns of biodiversity (Arrhenius 1921). Various authors determined theoretically that the SAR can be approximated as a power‐law function (i.e., S = cA z where S is species richness, A is area and c and z are constants; Preston 1962, May 1975, Harte et al. 1999), with z ≈ 0.25 in continen‐ tal areas but higher when dispersal barriers are involved (e.g., ‘island species–area relationship’). Empirical data suggested lower z in continental areas (0.13‐0.18) and values up to 0.35 for island systems (Rosenzweig 1995). Dengler (2009) re‐ cently came to the conclusion that the power law fits empirical data best in most cases (see also Dengler & Odeland 2010). Various authors ob‐ served further systematic variations of z, such as when considering spatial scale or sampling design (Plotkin et al. 2001, Scheiner 2006, Tjorve 2006, Dengler 2009). Kinzig & Harte (2000) pointed out the difference between SAR and the endemics– area curve (EAR), which considers only species endemic to a part of the region under analysis. So what could He & Hubbell (2011) report that was so novel and generally relevant about SARs to merit recent publication in Nature? Since area seems always to affect biodiver‐ sity, no matter what taxon, system or scale, SARs have frequently been used to estimate species richness loss resulting from anthropogenic habitat destruction, i.e. extinction rates in a conservation context. The loss of a certain amount of area leads to fewer species existing in a region – at least some regional extinctions occur – and the shape of the SAR has typically been used to retrieve quantitative estimates of how many species will go (regionally) extinct. Providing empirical evidence for the extinc‐ tion of a species is challenging and estimating ex‐ tinction rates across a community even more so (Ladle et al. 2011, this issue). Yet this is needed for many conservation applications, such as schemes for offsetting biodiversity loss (Curran et al. 2011) or, not least, for political argument. It is therefore not surprising that SAR‐based estimates of extinc‐ tion have been welcome despite critical studies that often found lower extinction rates than pre‐ dicted (e.g., Kinzig & Harte 2000). It was argued, reasonably, that on top of imminent extinction in some species, others will be doomed to future extinction because of reductions in their popula‐ tion size, and that this ‘extinction debt’ explains apparent misfits. Other sources of uncertainty of the SAR‐based estimates are the (often false) as‐ sumption of a completely inhospitable matrix be‐ tween remaining habitat patches (Koh & Ghazoul 2010) or the use of default slope values (z) in the absence of system‐specific fitted data. He & Hubbell (2011) pointed out that a backward interpolation of SARs is a flawed con‐ cept of measuring extinction rates (see also Kinzig & Harte 2000). This is because the area gain needed to encounter the first individual of a new species (which shapes the SAR) is always smaller than the area loss needed to remove the last indi‐ vidual. To show this, they formulated both as spa‐ tially explicit sampling processes (SAR for first en‐ counters, EAR for last encounters). They con‐ cluded that SAR‐derived estimates of imminent extinction will always be too high, unless individu‐ als are randomly distributed (i.e., no aggregated occurrence of individuals within a species), which is an unrealistic assumption. He & Hubbell (2011) also showed that the EAR is a good predictor of empirical extinction rates even if no spatial aggre‐ gation is modelled, which offers an alternative (but a more challenging one) for estimating imme‐ diate extinction of endemics from area loss. He & Hubbell (2011) clearly acknowledged that there is an anthropogenic extinction crisis and that habitat loss causes extinction. Further‐ more, they did not claim that small population sizes of remaining species could not lead to fur‐ ther, lagged extinction (in He & Hubbell’s view, EARs model only imminent extinction – and so do SARs, but wrongly). Despite this, He & Hubbell (2011) already anticipated that pointing out this error in estimating extinctions would not be frontiers of biogeography 3.3, 2011 — © 2011 the authors; journal compilation © 2011 The International Biogeography Society

PUBLICATION RECORD

  • Publication year

    2012

  • Venue

    Frontiers of biogeography

  • Publication date

    2012-04-12

  • Fields of study

    Biology, Environmental Science

  • Identifiers
    DOI 10.21425/F5FBG12415
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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