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利用调查、历史采集数据和物种分布模型评估历史鱼类群落组成。

Assessing historical fish community composition using surveys, historical collection data, and species distribution models.

机构信息

Texas Natural History Collections, University of Texas, Austin, Texas, United States of America.

出版信息

PLoS One. 2011;6(9):e25145. doi: 10.1371/journal.pone.0025145. Epub 2011 Sep 22.

Abstract

Accurate establishment of baseline conditions is critical to successful management and habitat restoration. We demonstrate the ability to robustly estimate historical fish community composition and assess the current status of the urbanized Barton Creek watershed in central Texas, U.S.A. Fish species were surveyed in 2008 and the resulting data compared to three sources of fish occurrence information: (i) historical records from a museum specimen database and literature searches; (ii) a nearly identical survey conducted 15 years earlier; and (iii) a modeled historical community constructed with species distribution models (SDMs). This holistic approach, and especially the application of SDMs, allowed us to discover that the fish community in Barton Creek was more diverse than the historical data and survey methods alone indicated. Sixteen native species with high modeled probability of occurrence within the watershed were not found in the 2008 survey, seven of these were not found in either survey or in any of the historical collection records. Our approach allowed us to more rigorously establish the true baseline for the pre-development fish fauna and then to more accurately assess trends and develop hypotheses regarding factors driving current fish community composition to better inform management decisions and future restoration efforts. Smaller, urbanized freshwater systems, like Barton Creek, typically have a relatively poor historical biodiversity inventory coupled with long histories of alteration, and thus there is a propensity for land managers and researchers to apply inaccurate baseline standards. Our methods provide a way around that limitation by using SDMs derived from larger and richer biodiversity databases of a broader geographic scope. Broadly applied, we propose that this technique has potential to overcome limitations of popular bioassessment metrics (e.g., IBI) to become a versatile and robust management tool for determining status of freshwater biotic communities.

摘要

准确确立基线条件对于成功管理和生境恢复至关重要。我们展示了一种强大的能力,可以稳健地估计历史鱼类群落组成,并评估美国德克萨斯州中部城市化巴顿溪流域的现状。2008 年对鱼类进行了调查,并将所得数据与鱼类出现的三种信息来源进行了比较:(i)博物馆标本数据库和文献检索中的历史记录;(ii)15 年前进行的几乎相同的调查;以及(iii)使用物种分布模型(SDM)构建的历史群落模型。这种整体方法,特别是 SDM 的应用,使我们发现巴顿溪的鱼类群落比历史数据和调查方法单独指示的更为多样化。在流域内具有高模型出现概率的 16 种本地物种未在 2008 年的调查中发现,其中 7 种未在任何调查或任何历史收藏记录中发现。我们的方法使我们能够更严格地确定开发前鱼类动物群的真实基线,然后更准确地评估趋势并提出有关驱动当前鱼类群落组成的因素的假设,以便更好地为管理决策和未来的恢复工作提供信息。像巴顿溪这样较小的城市化淡水系统通常具有相对较差的历史生物多样性清单,并且伴随着长期的改变历史,因此土地管理者和研究人员倾向于应用不准确的基线标准。我们的方法通过使用源自更大、更丰富的生物多样性数据库的 SDM 来解决该限制,这些数据库具有更广泛的地理范围。我们广泛地提出,该技术有可能克服流行生物评估指标(例如 IBI)的局限性,成为确定淡水生物群落状况的多功能且强大的管理工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d95a/3178614/b4488c8b10d3/pone.0025145.g001.jpg

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