Quantifying Sedimentary Capture of Biological Information

生物信息的沉积捕获定量：软体动物壳组合偏差的荟萃分析。Kidwell关于海洋生态系统状况的地史资料-即科学家进行定量研究之前时期的沉积岩芯数据-提供了独特的机会，可（a）将生态时间序列延伸到过去，从而确定影响前基线和相对较新的环境变化驱动因素，以及（B）使用过去的地理间隔来测试物种和群落行为中的组织原则。 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，特别是在沉积时间平均的普通条件下。 用于评价通过沉积记录获取生物数据的主要方法是“活-死”研究，即将骨骼遗骸（此处指底栖软体动物的壳）的分类组成和数量丰度与当地生物群落进行比较。 该项目将使用传统的统计和元分析（新的沉积地质学和古生态学），既量化偏差，并确定数据质量的因素排名。 待研究的因素包括（1）内在生物学（例如，物种的体型，贝壳矿物学，生活习性），（2）外部环境（例如，生境类型、水深测量、纬度），以及（3）方法（例如，取样装置和时间/空间密度，用于从沉积物中分离样品的网目尺寸）。 空间缩放的影响（即，环境梯度的捕获、通过单一死亡组合捕获区域信息）也将被明确地测试。 这些分析利用了世界各地几十年来在沿海和大陆架环境中进行实地考察所产生的现有数据，代表了地质、生物和渔业团体过去数百万美元的投资，是改进古生物取样和分析方案设计的重要一步，特别是对于那些寻求（a）将地质历史学与新生物学信息联系起来，或（2）使用死亡组合来替代或增加生物多样性的新生物学清单。 该项目的一个关键方面是通过进一步的文献检索和“拯救”美国沿海沃茨4个非常有价值的过去生态调查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，正如已经发生的对这一主题的试点工作。此外，预计从这项工作中发展出来的技术（包括被确定为对生物数据采集至关重要的因素）可用于评价其他主要群体和环境。

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.