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优化分类学、系统发育和功能多样性的编目和监测。

Optimal inventorying and monitoring of taxonomic, phylogenetic and functional diversity.

机构信息

Centre for Ecology, Evolution and Environmental Changes (cE3c) & CHANGE-Global Change and Sustainability Institute, University of Lisbon, Lisboa, Portugal.

Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History (Luomus), University of Helsinki, Helsinki, Finland.

出版信息

PLoS One. 2024 Jul 31;19(7):e0307156. doi: 10.1371/journal.pone.0307156. eCollection 2024.

Abstract

Comparable data is essential to understand biodiversity patterns. While assemblage or community inventorying requires comprehensive sampling, monitoring focuses on as few components as possible to detect changes. Quantifying species, their evolutionary history, and the way they interact requires studying changes in taxonomic (TD), phylogenetic (PD) and functional diversity (FD). Here we propose a method for the optimization of sampling protocols for inventorying and monitoring assemblages or communities across these three diversity dimensions taking sampling costs into account. We used Iberian spiders and Amazonian bats as two case-studies. The optimal combination of methods for inventorying and monitoring required optimizing the accumulation curve of α-diversity and minimizing the difference between sampled and estimated β-diversity (bias), respectively. For Iberian spiders, the optimal combination for TD, PD and FD allowed sampling at least 50% of estimated diversity with 24 person-hours of fieldwork. The optimal combination of six person-hours allowed reaching a bias below 8% for all dimensions. For Amazonian bats, surveying all the 12 sites with mist-nets and 0 or 1 acoustic recorders was the optimal combination for almost all diversity types, resulting in >89% of the diversity and <10% bias with roughly a third of the cost. Only for phylogenetic α-diversity, the best solution was less clear and involved surveying both with mist nets and acoustic recorders. The widespread use of optimized and standardized sampling protocols and regular repetition in time will radically improve global inventory and monitoring of biodiversity. We strongly advocate for the global adoption of sampling protocols for both inventory and monitoring of taxonomic, phylogenetic and functional diversity.

摘要

比较数据对于理解生物多样性模式至关重要。虽然集合或群落编目需要全面采样,但监测则侧重于尽可能少的组件,以检测变化。量化物种、它们的进化历史以及它们相互作用的方式需要研究分类(TD)、系统发育(PD)和功能多样性(FD)的变化。在这里,我们提出了一种方法,用于优化考虑采样成本的编目和监测集合或群落的采样方案,以实现这三个多样性维度。我们使用伊比利亚蜘蛛和亚马逊蝙蝠作为两个案例研究。编目和监测的最佳方法组合分别需要优化α多样性的累积曲线,并最小化采样和估计β多样性之间的差异(偏差)。对于伊比利亚蜘蛛,TD、PD 和 FD 的最佳组合允许用 24 个人时的实地工作时间采集至少 50%的估计多样性。六种人员时的最佳组合允许在所有维度上达到低于 8%的偏差。对于亚马逊蝙蝠,使用网和 0 或 1 个声学记录器调查所有 12 个地点是几乎所有多样性类型的最佳组合,结果是多样性超过 89%,偏差小于 10%,成本约为三分之一。只有在系统发育α多样性方面,最佳解决方案不太明确,涉及使用网和声学记录器进行调查。优化和标准化采样方案的广泛使用和定期重复将极大地改善全球生物多样性的编目和监测。我们强烈主张全球采用用于编目和监测分类、系统发育和功能多样性的采样方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a994/11290677/bf6131d62e35/pone.0307156.g001.jpg

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