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利用自然历史标本馆估计昆虫种群趋势面临的挑战与机遇。

Challenges and opportunities for using natural history collections to estimate insect population trends.

作者信息

Davis Courtney L, Guralnick Robert P, Zipkin Elise F

机构信息

Department of Integrative Biology; Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, Michigan, USA.

Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA.

出版信息

J Anim Ecol. 2023 Feb;92(2):237-249. doi: 10.1111/1365-2656.13763. Epub 2022 Jun 27.

Abstract

Natural history collections (NHC) provide a wealth of information that can be used to understand the impacts of global change on biodiversity. As such, there is growing interest in using NHC data to estimate changes in species' distributions and abundance trends over historic time horizons when contemporary survey data are limited or unavailable. However, museum specimens were not collected with the purpose of estimating population trends and thus can exhibit spatiotemporal and collector-specific biases that can impose severe limitations to using NHC data for evaluating population trajectories. Here we review the challenges associated with using museum records to track long-term insect population trends, including spatiotemporal biases in sampling effort and sparse temporal coverage within and across years. We highlight recent methodological advancements that aim to overcome these challenges and discuss emerging research opportunities. Specifically, we examine the potential of integrating museum records and other contemporary data sources (e.g. collected via structured, designed surveys and opportunistic citizen science programs) in a unified analytical framework that accounts for the sampling biases associated with each data source. The emerging field of integrated modelling provides a promising framework for leveraging the wealth of collections data to accurately estimate long-term trends of insect populations and identify cases where that is not possible using existing data sources.

摘要

自然历史藏品(NHC)提供了丰富的信息,可用于了解全球变化对生物多样性的影响。因此,当当代调查数据有限或无法获取时,利用NHC数据来估计历史时间范围内物种分布的变化和丰度趋势的兴趣与日俱增。然而,博物馆标本的采集并非旨在估计种群趋势,因此可能表现出时空和采集者特定的偏差,这可能严重限制利用NHC数据评估种群动态。在此,我们回顾了利用博物馆记录追踪昆虫长期种群趋势所面临的挑战,包括采样努力中的时空偏差以及年份内和年份间稀疏的时间覆盖范围。我们强调了旨在克服这些挑战的近期方法学进展,并讨论了新出现的研究机会。具体而言,我们研究了在一个统一的分析框架中整合博物馆记录和其他当代数据源(例如通过结构化、设计好的调查以及机会性公民科学项目收集的数据)的潜力,该框架考虑了与每个数据源相关的采样偏差。整合建模这一新兴领域为利用丰富的藏品数据准确估计昆虫种群的长期趋势以及识别使用现有数据源无法做到这一点的情况提供了一个有前景的框架。

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