Dataset Information

Bias and sensitivity in the placement of fossil taxa resulting from interpretations of missing data.

ABSTRACT: The utility of fossils in evolutionary contexts is dependent on their accurate placement in phylogenetic frameworks, yet intrinsic and widespread missing data make this problematic. The complex taphonomic processes occurring during fossilization can make it difficult to distinguish absence from non-preservation, especially in the case of exceptionally preserved soft-tissue fossils: is a particular morphological character (e.g., appendage, tentacle, or nerve) missing from a fossil because it was never there (phylogenetic absence), or just happened to not be preserved (taphonomic loss)? Missing data have not been tested in the context of interpretation of non-present anatomy nor in the context of directional shifts and biases in affinity. Here, complete taxa, both simulated and empirical, are subjected to data loss through the replacement of present entries (1s) with either missing (?s) or absent (0s) entries. Both cause taxa to drift down trees, from their original position, toward the root. Absolute thresholds at which downshift is significant are extremely low for introduced absences (two entries replaced, 6% of present characters). The opposite threshold in empirical fossil taxa is also found to be low; two absent entries replaced with presences causes fossil taxa to drift up trees. As such, only a few instances of non-preserved characters interpreted as absences will cause fossil organisms to be erroneously interpreted as more primitive than they were in life. This observed sensitivity to coding non-present morphology presents a problem for all evolutionary studies that attempt to use fossils to reconstruct rates of evolution or unlock sequences of morphological change. Stem-ward slippage, whereby fossilization processes cause organisms to appear artificially primitive, appears to be a ubiquitous and problematic phenomenon inherent to missing data, even when no decay biases exist. Absent characters therefore require explicit justification and taphonomic frameworks to support their interpretation.

SUBMITTER: Sansom RS

PROVIDER: S-EPMC4380037 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bias and sensitivity in the placement of fossil taxa resulting from interpretations of missing data.

Sansom Robert S RS

Systematic biology 20141127 2

The utility of fossils in evolutionary contexts is dependent on their accurate placement in phylogenetic frameworks, yet intrinsic and widespread missing data make this problematic. The complex taphonomic processes occurring during fossilization can make it difficult to distinguish absence from non-preservation, especially in the case of exceptionally preserved soft-tissue fossils: is a particular morphological character (e.g., appendage, tentacle, or nerve) missing from a fossil because it was ...[more]

PMID: 25432893

Similar Datasets

Project description:BackgroundMissing data are an inevitable challenge in Randomised Controlled Trials (RCTs), particularly those with Patient Reported Outcome Measures. Methodological guidance suggests that to avoid incorrect conclusions, studies should undertake sensitivity analyses which recognise that data may be 'missing not at random' (MNAR). A recommended approach is to elicit expert opinion about the likely outcome differences for those with missing versus observed data. However, few published trials plan and undertake these elicitation exercises, and so lack the external information required for these sensitivity analyses. The aim of this paper is to provide a framework that anticipates and allows for MNAR data in the design and analysis of clinical trials.MethodsWe developed a framework for performing and using expert elicitation to frame sensitivity analysis in RCTs with missing outcome data. The framework includes the following steps: first defining the scope of the elicitation exercise, second developing the elicitation tool, third eliciting expert opinion about the missing outcomes, fourth evaluating the elicitation results, and fifth analysing the trial data. We provide guidance on key practical challenges that arise when adopting this approach in trials: the criteria for identifying relevant experts, the outcome scale for presenting data to experts, the appropriate representation of expert opinion, and the evaluation of the elicitation results.The framework was developed within the POPPI trial, which investigated whether a preventive, complex psychological intervention, commenced early in ICU, would reduce the development of patient-reported post-traumatic stress disorder symptom severity, and improve health-related quality of life. We illustrate the key aspects of the proposed framework using the POPPI trial.ResultsFor the POPPI trial, 113 experts were identified with potentially suitable knowledge and asked to participate in the elicitation exercise. The 113 experts provided 59 usable elicitation questionnaires. The sensitivity analysis found that the results from the primary analysis were robust to alternative MNAR mechanisms.ConclusionsFuture studies can adopt this framework to embed expert elicitation within the design of clinical trials. This will provide the information required for MNAR sensitivity analyses that examine the robustness of the trial conclusions to alternative, but realistic assumptions about the missing data.

Project description:Pterosaurs, a Mesozoic group of flying archosaurs, have become a focal point for debates pertaining to the impact of sampling biases on our reading of the fossil record, as well as the utility of sampling proxies in palaeodiversity reconstructions. The completeness of the pterosaur fossil specimens themselves potentially provides additional information that is not captured in existing sampling proxies, and might shed new light on the group's evolutionary history. Here we assess the quality of the pterosaur fossil record via a character completeness metric based on the number of phylogenetic characters that can be scored for all known skeletons of 172 valid species, with averaged completeness values calculated for each geological stage. The fossil record of pterosaurs is observed to be strongly influenced by the occurrence and distribution of Lagerstätten. Peaks in completeness correlate with Lagerstätten deposits, and a recovered correlation between completeness and observed diversity is rendered non-significant when Lagerstätten species are excluded. Intervals previously regarded as potential extinction events are shown to lack Lagerstätten and exhibit low completeness values: as such, the apparent low diversity in these intervals might be at least partly the result of poor fossil record quality. A positive correlation between temporal patterns in completeness of Cretaceous pterosaurs and birds further demonstrates the prominent role that Lagerstätten deposits have on the preservation of smaller bodied organisms, contrasting with a lack of correlation with the completeness of large-bodied sauropodomorphs. However, we unexpectedly find a strong correlation between sauropodomorph and pterosaur completeness within the Triassic-Jurassic, but not the Cretaceous, potentially relating to a shared shift in environmental preference and thus preservation style through time. This study highlights the importance of understanding the relationship between various taphonomic controls when correcting for sampling bias, and provides additional evidence for the prominent role of sampling on observed patterns in pterosaur macroevolution.

Project description:BACKGROUND:Spatial conservation prioritisation (SCP) is a set of computational tools designed to support the efficient spatial allocation of priority areas for conservation actions, but it is subject to many sources of uncertainty which should be accounted for during the prioritisation process. We quantified the sensitivity of an SCP application (using software Zonation) to possible sources of uncertainty in data-poor situations, including the use of different surrogate options; correction for sampling bias; how to integrate connectivity; the choice of species distribution modelling (SDM) algorithm; how cells are removed from the landscape; and two methods of assigning weights to species (red-list status or prediction uncertainty). Further, we evaluated the effectiveness of the Egyptian protected areas for conservation, and spatially allocated the top priority sites for further on-the-ground evaluation as potential areas for protected areas expansion. RESULTS:Focal taxon (butterflies, reptiles, and mammals), sampling bias, connectivity and the choice of SDM algorithm were the most sensitive parameters; collectively these reflect data quality issues. In contrast, cell removal rule and species weights contributed much less to overall variability. Using currently available species data, we found the current effectiveness of Egypt's protected areas for conserving fauna was low. CONCLUSIONS:For SCP to be useful, there is a lower limit on data quality, requiring data-poor countries to improve sampling strategies and data quality to obtain unbiased data for as many taxa as possible. Since our sensitivity analysis may not generalise, conservation planners should use sensitivity analyses more routinely, particularly relying on more than one combination of SDM algorithm and surrogate group, consider correction for sampling bias, and compare the spatial patterns of predicted priority sites using a variety of settings. The sensitivity of SCP to connectivity parameters means that the responses of each species to habitat loss are important knowledge gaps.

Dataset Information

Bias and sensitivity in the placement of fossil taxa resulting from interpretations of missing data.

Publications

Bias and sensitivity in the placement of fossil taxa resulting from interpretations of missing data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets