Quantifying Sedimentary Capture of Biological Information

量化生物信息的沉积捕获：软体动物贝壳组合偏差的荟萃分析Susan M.Kidwell(EAR-0345897)摘要关于海洋生态系统状态的地史信息--即来自沉积岩心的数据早于科学家进行定量研究的时期--提供了独特的机会，以(A)将生态时间序列延伸到过去，从而确定相对较新的环境变化的影响前基线和驱动因素，以及(B)利用过去的地理间隔来测试物种和群落行为的组织原则。然而，为了从沉积记录中提取全部价值，我们需要对生物信息中的死后偏差进行定量评估，特别是在通常的沉积时间平均条件下。用于评估沉积记录捕获的生物数据的主要方法是“活-死”研究，即将骨骼遗骸(这里是海底软体动物的贝壳)的分类组成和数量丰度与当地生物群落进行比较。该项目将使用常规统计学和荟萃分析(沉积地质学和古生态学的新知识)来量化偏差，并对决定数据质量的因素进行排序。需要调查的因素包括(1)内在生物学(例如物种的身体大小、贝壳矿物学、生活习性)、(2)外部环境(例如栖息地类型、水深、纬度)和(3)方法(例如采样工具和时间/空间的密度、用于将样本与沉积物分开的网目大小)。还将明确测试空间尺度的影响(即捕捉环境梯度、单一死亡集合体捕捉区域信息)。这些分析利用了世界各地数十年来在沿海和陆架环境进行的实地调查产生的现有数据，代表了地质、生物和渔业团体过去数百万美元的投资，是改进古生物采样设计和分析方案的重要步骤，特别是对于寻求(A)将地史信息与新生物信息联系起来，或(2)利用死亡集合体取代或增加生物多样性新生物清单的研究。该项目的一个关键方面是通过进一步的文献搜索和从美国沿海水域过去4次非常有价值的生态调查中“拯救”数据来扩大数字数据库。元分析揭示(或揭穿)的模式为现场实验和数值建模提供了新的假设，就像在这个主题的试点工作中已经发生的那样。此外，预计从这项工作中开发的技术(包括被确定为生物数据捕获的关键因素)可以应用于对其他主要群体和环境的评估。

Quantifying Sedimentary Capture of Biological Information: meta-analysis of bias in molluscan shell assemblagesSusan M. Kidwell(EAR-0345897)ABSTRACTGeohistorical information on the state of marine ecosystems - that is, data from sedimentary cores for periods that pre-date quantitative studies by scientists -- provides unique opportunities to (a) extend ecological time-series into the past and thereby identify pre-impact baselines and drivers of relatively recent environmental change, and (b) use past geointervals to test for organizing principles in the behavior of species and communities. To extract full value from sedimentary records, however, we need a quantitative evaluation of post-mortem bias in biological information, particularly under ordinary conditions of sedimentary time-averaging. The primary method used to evaluate bio-data capture by sedimentary records is a "live-dead" study, in which the taxonomic composition and numerical abundances of skeletal remains (here, the shells of benthic mollusks) are compared against the local living community. This project will use both conventional statistics and meta-analysis (new to sedimentary geology and paleoecology) both to quantify bias and to rank factors that determine data quality. Factors to be investigated include (1) intrinsic biology (e.g., species' body size, shell mineralogy, life habit), (2) extrinsic environment (e.g., habitat type, bathymetry, latitude), and (3) methodology (e.g., sampling gear and density in time/space, mesh-size used to separate specimens from sediment). The effects of spatial scaling (i.e., the capture of environmental gradients, the capture of regional information by single death assemblages) will also be tested explicitly. These analyses, using existing data generated from many decades of fieldwork around the world in coastal and shelf settings, and representing millions of dollars of past investment by geological, biological and fisheries groups, are an important step in improving the design of paleobiologic sampling and protocols for analysis, particularly for studies that seek to (a) link geohistorical with neontologic information, or (2) use death assemblages to substitute for or augment neontologic inventories of biodiversity. A key aspect of the project is enlarging of the digital database both by further literature search, and by the "rescue" of data from 4 exceptionally valuable past ecological surveys in US coastal waters. Patterns revealed (or debunked) by meta-analysis provide new hypotheses for field experimentation and numerical modeling, as is already occurring in response to pilot work on this subject. In addition, it is expected that the techniques developed from this work (including factors identified as critical to bio-data capture) can be applied to the evaluation of other major groups and environments.