Daniel E Ruzzante, Gregory R McCracken, Dylan J Fraser, John MacMillan, Colin Buhariwalla, Joanna Mills Flemming
{"title":"有效大小(N ̂ e $$ {\\hat{N}}_e $$)的时间变异性确定了标记再捕获与近亲标记再捕获对种群丰度估计之间差异的潜在来源。","authors":"Daniel E Ruzzante, Gregory R McCracken, Dylan J Fraser, John MacMillan, Colin Buhariwalla, Joanna Mills Flemming","doi":"10.1111/1755-0998.14047","DOIUrl":null,"url":null,"abstract":"<p><p>Although efforts to estimate effective population size, census size and their ratio in wild populations are expanding, few empirical studies investigate interannual changes in these parameters. Hence, we do not know how repeatable or representative many estimates may be. Answering this question requires studies of long-term population dynamics. Here we took advantage of a rich dataset of seven brook trout (Salvelinus fontinalis) populations, 5 consecutive years and 5400 individuals genotyped at 33 microsatellites to examine variation in estimates of effective and census size and in their ratio. We first estimated the annual effective number of breeders ( <math> <semantics> <mrow><mover><mi>N</mi> <mo>̂</mo></mover> </mrow> <annotation>$$ \\hat{N} $$</annotation></semantics> </math> <sub>b</sub>) using individuals aged 1+. We then adjusted these estimates using two life history traits, to obtain <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>b</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{b(adj2)} $$</annotation></semantics> </math> and subsequently, <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> following Waples et al. (2013). <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> was estimated for the years 2014 to 2019. Census size was estimated by mark recapture using double-pass electrofishing ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> ) (years 2014-2018) as well as by the Close Kin Mark Recapture approach ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> ) (years 2015-2017). Within populations, annual variation in <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> (ratio of maximum to minimum <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> ) ranged from 1.6-fold to 58-fold. Over all 7 populations, the median annual variation in <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> was around 5-fold. These results reflect important interannual changes in the variance in reproductive success and more generally in population dynamics. Within population <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> varied between years by a (median) factor of 2.7 with a range from 2 to 4.3. Thus, estimated effective size varied nearly twice as much as did estimated census size. Our results therefore suggest that, at least in small populations like those examined in the present study, any single annual estimate of <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> is unlikely to be representative of long-term dynamics. At least 3-4 annual estimates may be required for an estimate of contemporary effective size to be truly representative. We then compared <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> to <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> . For five of the seven populations, the estimates of population abundance based on mark recapture ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> ) were indistinguishable from those based on close kin mark recapture ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> ). The two populations with discordant <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> and <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> exhibited extremely low <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> <mo>/</mo> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{e(adj2)}/{\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> ratios and the largest annual variation in <math> <semantics> <mrow> <msub> <mover><mrow><mspace></mspace> <mi>N</mi></mrow> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{\\ N}}_{e(adj2)} $$</annotation></semantics> </math> (58-fold and 35.4-fold respectively). These results suggest that sampling effort in these two streams may have been insufficient to properly capture the genetic diversity of the entire population and that individuals sampled were not representative of the population. Our study further validates CKMR as a method for estimating abundance in wild populations and it demonstrates how knowledge of the temporal variation in <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mi>e</mi></msub> </mrow> <annotation>$$ {\\hat{N}}_e $$</annotation></semantics> </math> can be used to identify potential sources of discrepancies between <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> and <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> .</p>","PeriodicalId":211,"journal":{"name":"Molecular Ecology Resources","volume":" ","pages":"e14047"},"PeriodicalIF":5.5000,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"<ArticleTitle xmlns:ns0=\\\"http://www.w3.org/1998/Math/MathML\\\">Temporal Variability in Effective Size ( <ns0:math> <ns0:semantics> <ns0:mrow> <ns0:msub><ns0:mover><ns0:mi>N</ns0:mi> <ns0:mo>̂</ns0:mo></ns0:mover> <ns0:mi>e</ns0:mi></ns0:msub> </ns0:mrow> <ns0:annotation>$$ {\\\\hat{N}}_e $$</ns0:annotation></ns0:semantics> </ns0:math> ) Identifies Potential Sources of Discrepancies Between Mark Recapture and Close Kin Mark Recapture Estimates of Population Abundance.\",\"authors\":\"Daniel E Ruzzante, Gregory R McCracken, Dylan J Fraser, John MacMillan, Colin Buhariwalla, Joanna Mills Flemming\",\"doi\":\"10.1111/1755-0998.14047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Although efforts to estimate effective population size, census size and their ratio in wild populations are expanding, few empirical studies investigate interannual changes in these parameters. Hence, we do not know how repeatable or representative many estimates may be. Answering this question requires studies of long-term population dynamics. Here we took advantage of a rich dataset of seven brook trout (Salvelinus fontinalis) populations, 5 consecutive years and 5400 individuals genotyped at 33 microsatellites to examine variation in estimates of effective and census size and in their ratio. We first estimated the annual effective number of breeders ( <math> <semantics> <mrow><mover><mi>N</mi> <mo>̂</mo></mover> </mrow> <annotation>$$ \\\\hat{N} $$</annotation></semantics> </math> <sub>b</sub>) using individuals aged 1+. We then adjusted these estimates using two life history traits, to obtain <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>b</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{b(adj2)} $$</annotation></semantics> </math> and subsequently, <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> following Waples et al. (2013). <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> was estimated for the years 2014 to 2019. Census size was estimated by mark recapture using double-pass electrofishing ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> ) (years 2014-2018) as well as by the Close Kin Mark Recapture approach ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> ) (years 2015-2017). Within populations, annual variation in <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> (ratio of maximum to minimum <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> ) ranged from 1.6-fold to 58-fold. Over all 7 populations, the median annual variation in <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> was around 5-fold. These results reflect important interannual changes in the variance in reproductive success and more generally in population dynamics. Within population <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> varied between years by a (median) factor of 2.7 with a range from 2 to 4.3. Thus, estimated effective size varied nearly twice as much as did estimated census size. Our results therefore suggest that, at least in small populations like those examined in the present study, any single annual estimate of <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{e(adj2)} $$</annotation></semantics> </math> is unlikely to be representative of long-term dynamics. At least 3-4 annual estimates may be required for an estimate of contemporary effective size to be truly representative. We then compared <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> to <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> . For five of the seven populations, the estimates of population abundance based on mark recapture ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> ) were indistinguishable from those based on close kin mark recapture ( <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> ). The two populations with discordant <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> and <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> exhibited extremely low <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> <mo>/</mo> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{e(adj2)}/{\\\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> ratios and the largest annual variation in <math> <semantics> <mrow> <msub> <mover><mrow><mspace></mspace> <mi>N</mi></mrow> <mo>̂</mo></mover> <mrow><mi>e</mi> <mfenced><mrow><mi>adj</mi> <mn>2</mn></mrow> </mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{\\\\ N}}_{e(adj2)} $$</annotation></semantics> </math> (58-fold and 35.4-fold respectively). These results suggest that sampling effort in these two streams may have been insufficient to properly capture the genetic diversity of the entire population and that individuals sampled were not representative of the population. Our study further validates CKMR as a method for estimating abundance in wild populations and it demonstrates how knowledge of the temporal variation in <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mi>e</mi></msub> </mrow> <annotation>$$ {\\\\hat{N}}_e $$</annotation></semantics> </math> can be used to identify potential sources of discrepancies between <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mi>MR</mi></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(MR)} $$</annotation></semantics> </math> and <math> <semantics> <mrow> <msub><mover><mi>N</mi> <mo>̂</mo></mover> <mrow><mi>c</mi> <mfenced><mtext>CKMR</mtext></mfenced> </mrow> </msub> </mrow> <annotation>$$ {\\\\hat{N}}_{c(CKMR)} $$</annotation></semantics> </math> .</p>\",\"PeriodicalId\":211,\"journal\":{\"name\":\"Molecular Ecology Resources\",\"volume\":\" \",\"pages\":\"e14047\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2024-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Ecology Resources\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1111/1755-0998.14047\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Ecology Resources","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1111/1755-0998.14047","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
尽管估算野生种群有效种群数量、普查规模及其比例的工作正在扩大,但很少有实证研究调查这些参数的年际变化。因此,我们不知道许多估计值的可重复性或代表性如何。要回答这个问题,需要对长期种群动态进行研究。在这里,我们利用了一个包含 7 个溪鳟(Salvelinus fontinalis)种群、连续 5 年、5400 个个体、33 个微卫星基因分型的丰富数据集,来研究有效种群规模和普查种群规模的估计值及其比例的变化。我们首先使用 1 岁以上的个体估算了繁殖者的年有效数量(N ̂ $\hat{N} $$ b)。然后,我们利用两种生活史特征对这些估计值进行调整,得出 N ̂ b adj 2 $$ {\hat{N}}_{b(adj2)} $$,随后按照 Waples 等人(2013 年)的方法得出 N ̂ e adj 2 $$ {\hat{N}}_{e(adj2)} $$。 N ̂ e adj 2 $$ {\hat{N}}_{e(adj2)}$ 是 2014 年至 2019 年的估计值。普查规模是通过使用双通电鱼的标记再捕法(N ̂ c MR $$ {\hat{N}}_{c(MR)} $$ )(2014-2018年)以及近亲标记再捕法(N ̂ c CKMR $$ {\hat{N}}_{c(CKMR)} $$ )(2015-2017年)估算的。在种群内部,N ̂ e adj 2 $$ {\hat{N}}_{e(adj2)} $$ (最大 N ̂ e adj 2 $$ {\hat{N}}_{e(adj2)} $$ 与最小 N ̂ e adj 2 $$ {\hat{N}}_{e(adj2)} $ 之比)的年变化范围从 1.6 倍到 58 倍不等。在所有 7 个种群中,N ̂ e adj 2 $$ {\hat{N}}_{e(adj2)}$ 的年变化中位数约为 5 倍。这些结果反映了繁殖成功率差异的重要年际变化,以及更普遍的种群动态变化。种群内 N ̂ c MR $$ {\hat{N}}_{c(MR)}$ 在不同年份的变化系数(中位数)为 2.7,范围在 2 到 4.3 之间。因此,估计有效规模的变化几乎是估计普查规模变化的两倍。因此,我们的结果表明,至少在本研究考察的小型种群中,任何单一的 N ̂ e adj 2 $$ {\hat{N}}_{e(adj2)}$ 的年度估计值都不太可能代表长期动态。至少需要 3-4 个年度估计值才能真正代表当代有效规模的估计值。然后,我们将 N ̂ c MR $$ {\hat{N}}_{c(MR)}$ 与 N ̂ c CKMR $$ {\hat{N}}_{c(CKMR)}$ 进行了比较。对于 7 个种群中的 5 个种群,基于标记重捕的种群丰度估计值(N ̂ c MR $$ {\hat{N}}_{c(MR)} $$)与基于近亲标记重捕的种群丰度估计值(N ̂ c CKMR $$ {\hat{N}}_{c(CKMR)} $$)无法区分。N ̂ c MR $$ {\hat{N}}_{c(MR)}$ 和 N ̂ c CKMR $ {\hat{N}}_{c(CKMR)}$ 不一致的两个种群表现出极低的 N ̂ e adj2 / N ̂ c MR $$ {\hat{N}}_{e(adj2)}/{\hat{N}}_{c(MR)}$ 的比率和 N ̂ e adj 2 $$ {\hat{ N}}_{e(adj2)}$ 的年度变化最大(58-.倍和 35.4 倍)。这些结果表明,在这两条溪流中的取样工作可能不足以正确捕获整个种群的遗传多样性,而且所取样的个体在种群中不具有代表性。我们的研究进一步验证了 CKMR 作为估算野生种群丰度的方法的有效性,并证明了如何利用 N ̂ e $$ {\hat{N}}_e $ 的时间变化知识来识别 N ̂ c MR $$ {\hat{N}}_{c(MR)}$ 与 N ̂ c CKMR $$ {\hat{N}}_{c(CKMR)}$ 之间差异的潜在来源。
Temporal Variability in Effective Size ( N̂e$$ {\hat{N}}_e $$ ) Identifies Potential Sources of Discrepancies Between Mark Recapture and Close Kin Mark Recapture Estimates of Population Abundance.
Although efforts to estimate effective population size, census size and their ratio in wild populations are expanding, few empirical studies investigate interannual changes in these parameters. Hence, we do not know how repeatable or representative many estimates may be. Answering this question requires studies of long-term population dynamics. Here we took advantage of a rich dataset of seven brook trout (Salvelinus fontinalis) populations, 5 consecutive years and 5400 individuals genotyped at 33 microsatellites to examine variation in estimates of effective and census size and in their ratio. We first estimated the annual effective number of breeders ( b) using individuals aged 1+. We then adjusted these estimates using two life history traits, to obtain and subsequently, following Waples et al. (2013). was estimated for the years 2014 to 2019. Census size was estimated by mark recapture using double-pass electrofishing ( ) (years 2014-2018) as well as by the Close Kin Mark Recapture approach ( ) (years 2015-2017). Within populations, annual variation in (ratio of maximum to minimum ) ranged from 1.6-fold to 58-fold. Over all 7 populations, the median annual variation in was around 5-fold. These results reflect important interannual changes in the variance in reproductive success and more generally in population dynamics. Within population varied between years by a (median) factor of 2.7 with a range from 2 to 4.3. Thus, estimated effective size varied nearly twice as much as did estimated census size. Our results therefore suggest that, at least in small populations like those examined in the present study, any single annual estimate of is unlikely to be representative of long-term dynamics. At least 3-4 annual estimates may be required for an estimate of contemporary effective size to be truly representative. We then compared to . For five of the seven populations, the estimates of population abundance based on mark recapture ( ) were indistinguishable from those based on close kin mark recapture ( ). The two populations with discordant and exhibited extremely low ratios and the largest annual variation in (58-fold and 35.4-fold respectively). These results suggest that sampling effort in these two streams may have been insufficient to properly capture the genetic diversity of the entire population and that individuals sampled were not representative of the population. Our study further validates CKMR as a method for estimating abundance in wild populations and it demonstrates how knowledge of the temporal variation in can be used to identify potential sources of discrepancies between and .
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