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Four Reasons to Question the Accuracy of a Biotic Index; the Risk of Metric Bias and the Scope to Improve Accuracy.

ABSTRACT: Natural ecological variability and analytical design can bias the derived value of a biotic index through the variable influence of indicator body-size, abundance, richness, and ascribed tolerance scores. Descriptive statistics highlight this risk for 26 aquatic indicator systems; detailed analysis is provided for contrasting weighted-average indices applying the example of the BMWP, which has the best supporting data. Differences in body size between taxa from respective tolerance classes is a common feature of indicator systems; in some it represents a trend ranging from comparatively small pollution tolerant to larger intolerant organisms. Under this scenario, the propensity to collect a greater proportion of smaller organisms is associated with negative bias however, positive bias may occur when equipment (e.g. mesh-size) selectively samples larger organisms. Biotic indices are often derived from systems where indicator taxa are unevenly distributed along the gradient of tolerance classes. Such skews in indicator richness can distort index values in the direction of taxonomically rich indicator classes with the subsequent degree of bias related to the treatment of abundance data. The misclassification of indicator taxa causes bias that varies with the magnitude of the misclassification, the relative abundance of misclassified taxa and the treatment of abundance data. These artifacts of assessment design can compromise the ability to monitor biological quality. The statistical treatment of abundance data and the manipulation of indicator assignment and class richness can be used to improve index accuracy. While advances in methods of data collection (i.e. DNA barcoding) may facilitate improvement, the scope to reduce systematic bias is ultimately limited to a strategy of optimal compromise. The shortfall in accuracy must be addressed by statistical pragmatism. At any particular site, the net bias is a probabilistic function of the sample data, resulting in an error variance around an average deviation. Following standardized protocols and assigning precise reference conditions, the error variance of their comparative ratio (test-site:reference) can be measured and used to estimate the accuracy of the resultant assessment.

SUBMITTER: Monaghan KA

PROVIDER: S-EPMC4938548 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Four Reasons to Question the Accuracy of a Biotic Index; the Risk of Metric Bias and the Scope to Improve Accuracy.

Monaghan Kieran A KA

PloS one 20160708 7

Natural ecological variability and analytical design can bias the derived value of a biotic index through the variable influence of indicator body-size, abundance, richness, and ascribed tolerance scores. Descriptive statistics highlight this risk for 26 aquatic indicator systems; detailed analysis is provided for contrasting weighted-average indices applying the example of the BMWP, which has the best supporting data. Differences in body size between taxa from respective tolerance classes is a ...[more]

PMID: 27392036

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Project description:BackgroundThe database we introduce is a pivotal component of the LIFE SNAILS project (Support and Naturalisation in Areas of Importance for Land Snails). This initiative is dedicated to safeguarding three endangered species of terrestrial molluscs, specifically, two snails (Oxychilusagostinhoi Martins 1981 and Leptaxisminor Backhuys, 1975) and a semi-slug (Plutoniaangulosa (Morelet, 1860)), all of which are single island endemics from Santa Maria Island and face significant threats towards their populations.In this study, we established a comprehensive database derived from a long-term arthropod monitoring campaign utilising SLAM (Sea, Land, Air, Malaise) traps. Although molluscs were not the primary focus, our findings serve as a credible proxy for evaluating the overall habitat quality for endemic invertebrates, with arthropods serving as principal indicators. From September to December of 2022, a total of 11 SLAM traps were installed and monitored monthly in eleven sites of mixed forests of Santa Maria Island.New informationBased on the 33 available samples (11 sites x 3 sampling periods), we recorded a total of 118 taxa of arthropods (of which 94 were identified at species or subspecies level), belonging to three classes, 14 orders and 62 families. From the 94 identified taxa, a total of 21 species were endemic, 31 native non-endemic, 32 introduced and 10 indeterminate. We also provide additional information of the habitat quality (Index of Biotic Integrity), including general habitat and dominant species composition.We registered three new records to the Island, the native bug Piezodoruslituratus (Fabricius, 1794) (Hemiptera, Pentatomidae), the Azorean endemic beetle Phloeosinusgillerforsi Bright, 1987 (Coleoptera, Curculionidae) and the exotic ant Hypoponerapunctatissima (Roger, 1859) (Hymenoptera, Formicidae) and one new record for the Azores Archipelago, the native beetle Cephenniumvalidum Assing & Meybohm, 2021 (Coleoptera, Staphylinidae, Scydmaeninae).This publication not only contributes to the conservation of highly threatened endemic molluscs, through an assessment of habitat quality, based on arthropod communities and habitat description (e.g. native or exotic vegetation), but also provides an updated inventory of arthropods from Santa Maria Island.

Project description:PurposeFor stereotactic radiosurgery (SRS), accurate evaluation of dose-volume metrics for small structures is necessary. The purpose of this study was to compare the DVH metric capabilities of five commercially available SRS DVH analysis tools (Eclipse, Elements, Raystation, MIM, and Velocity).MethodsDICOM RTdose and RTstructure set files created using MATLAB were imported and evaluated in each of the tools. Each structure set consisted of 50 randomly placed spherical targets. The dose distributions were created on a 1-mm grid using an analytic model such that the dose-volume metrics of the spheres were known. Structure sets were created for 3, 5, 7, 10, 15, and 20 mm diameter spheres. The reported structure volume, V100% [cc], and V50% [cc], and the RTOG conformity index and Paddick Gradient Index, were compared with the analytical values.ResultsThe average difference and range across all evaluated target sizes for the reported structure volume was - 4.73%[-33.2,0.2], 0.11%[-10.9, 9.5], -0.39%[-12.1, 7.0], -2.24%[-21.0, 1.3], and 1.15%[-15.1,0.8], for TPS-A through TPS-E, respectively. The average difference and range for the V100%[cc] (V20Gy[cc]) was - 0.4[-24.5,9.8], -2.73[-23.6, 1.1], -3.01[-23.6, 0.6], -3.79[-27.3, 1.3], and 0.26[-6.1,2.6] for TPS-A through TPS-E, respectively. For V50%[cc](V10Gy[cc]) in TPS-A through TPS-E the average and ranger were - 0.05[-0.8,0.4], -0.18[-1.2, 0.5], -0.44[-1.4, 0.3], -0.26[-1.8, 2.6], and 0.09[-1.4,2.7].ConclusionThis study expanded on the previously published literature to quantitatively compare the DVH analysis capabilities of software commonly used for SRS plan evaluation and provides freely available and downloadable analytically derived set of ground truth DICOM dose and structure files for the use of radiotherapy clinics. The differences between systems highlight the need for standardization and/or transparency between systems, especially when evaluating plan quality for multi-institutional clinical trials.

Dataset Information

Four Reasons to Question the Accuracy of a Biotic Index; the Risk of Metric Bias and the Scope to Improve Accuracy.

Publications

Four Reasons to Question the Accuracy of a Biotic Index; the Risk of Metric Bias and the Scope to Improve Accuracy.

Similar Datasets

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