Assessing the suitability of a one-time sampling event for close-kin mark-recapture: A caribou case study

IF 2.3 2区 生物学 Q2 ECOLOGY
Brandon D. Merriell, Micheline Manseau, Paul J. Wilson
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Abstract

Abundance estimation is frequently an objective of conservation and monitoring initiatives for threatened and other managed populations. While abundance estimation via capture–mark–recapture or spatially explicit capture–recapture is now common, such approaches are logistically challenging and expensive for species such as boreal caribou (Rangifer tarandus), which inhabit remote regions, are widely dispersed, and exist at low densities. Fortunately, the recently developed ‘close-kin mark–recapture’ (CKMR) framework, which uses the number of kin pairs obtained within a sample to generate an abundance estimate, eliminates the need for multiple sampling events. As a result, some caribou managers are interested in using this method to generate an abundance estimate from a single, non-invasive sampling event for caribou populations. We conducted a simulation study using realistic boreal caribou demographic rates and population sizes to assess how population size and the proportion of the population surveyed impact the accuracy and precision of single-survey CKMR-based abundance estimates. Our results indicated that abundance estimates were biased and highly imprecise when very small proportions of the population were sampled, regardless of the population size. However, the larger the population size, the smaller the required proportion of the population surveyed to generate both accurate and reasonably precise estimates. Additionally, we also present a case study in which we used the CKMR framework to generate annual female abundance estimates for a small caribou population in Jasper National Park, Alberta, Canada, from 2006 to 2015 and compared them to existing published capture–mark–recapture-based estimates. Both the accuracy and precision of the annual CKMR-based abundance estimates varied across years and were sensitive to the proportion of pairwise kinship comparisons which yielded a mother–offspring pair. Taken together, our study demonstrates that it is possible to generate CKMR-based abundance estimates from a single sampling event for small caribou populations, so long as a sufficient sampling intensity can be achieved.

Abstract Image

评估近亲标记重捕一次性采样活动的适宜性:驯鹿案例研究。
丰度估计通常是濒危种群和其他受管理种群的保护和监测计划的目标。虽然通过捕获-标记-再捕获或空间显式捕获-再捕获来估算种群数量的方法现在很常见,但对于像北方驯鹿(Rangifer tarandus)这样居住在偏远地区、分布广泛且密度较低的物种来说,这种方法在后勤方面具有挑战性,而且成本高昂。幸运的是,最近开发的 "近亲标记-再捕获"(CKMR)框架利用在样本中获得的近亲对数来生成丰度估计值,因此无需多次取样。因此,一些驯鹿管理者有兴趣使用这种方法,对驯鹿种群进行单次非侵入性采样,以得出丰度估计值。我们使用现实的北方驯鹿人口统计率和种群规模进行了模拟研究,以评估种群规模和调查种群比例如何影响基于 CKMR 的单次调查丰度估计的准确性和精确性。我们的结果表明,无论种群规模如何,如果采样的种群比例非常小,丰度估计值就会出现偏差且非常不精确。然而,种群规模越大,要获得准确和合理的估计值,所需的调查种群比例就越小。此外,我们还介绍了一项案例研究,在该研究中,我们使用 CKMR 框架为加拿大阿尔伯塔省贾斯珀国家公园的一个小型驯鹿种群生成了 2006 年至 2015 年的年度雌性丰度估计值,并将其与现有公布的基于捕获-标记-再捕获的估计值进行了比较。基于 CKMR 的年度丰度估计的准确度和精确度在不同年份有所不同,并且对产生母子配对的成对亲缘关系比较的比例很敏感。总之,我们的研究表明,对于小型驯鹿种群,只要能达到足够的采样密度,就有可能通过单次采样得出基于 CKMR 的丰度估计值。
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来源期刊
CiteScore
4.40
自引率
3.80%
发文量
1027
审稿时长
3-6 weeks
期刊介绍: Ecology and Evolution is the peer reviewed journal for rapid dissemination of research in all areas of ecology, evolution and conservation science. The journal gives priority to quality research reports, theoretical or empirical, that develop our understanding of organisms and their diversity, interactions between them, and the natural environment. Ecology and Evolution gives prompt and equal consideration to papers reporting theoretical, experimental, applied and descriptive work in terrestrial and aquatic environments. The journal will consider submissions across taxa in areas including but not limited to micro and macro ecological and evolutionary processes, characteristics of and interactions between individuals, populations, communities and the environment, physiological responses to environmental change, population genetics and phylogenetics, relatedness and kin selection, life histories, systematics and taxonomy, conservation genetics, extinction, speciation, adaption, behaviour, biodiversity, species abundance, macroecology, population and ecosystem dynamics, and conservation policy.
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