Accounting for Uncertainties in Biodiversity Estimations: A New Methodology and Its Application to the Mesopelagic Sound Scattering Layer of the High Arctic

Abstract

Measures of biological diversity (biodiversity) are important for monitoring the state of ecosystems. Several indices and methods are used to describe biodiversity from field observations. Marine faunal biodiversity is often quantified based on analysis of samples collected using a trawl during research surveys. To monitor spatial and temporal changes in biodiversity between surveys, samples are generally collected from a series of stations. Inference regarding changes in biodiversity must account for uncertainties in the estimation of the values for the different biodiversity indices used. Estimation for a single station is affected by spatial-temporal variation in the species composition in the area and by uncertainty due to the finite sample size taken by the trawl. Therefore, variation between stations needs to be accounted for when estimating uncertainty for values of different indices during a survey as total or as mean for the survey. Herein, we present a method based on nested bootstrapping that accounts for uncertainties in the estimation of various indices and which can be used to infer changes in biodiversity. Application of this methodology is demonstrated using data collected in the mesopelagic sound scattering layer in the high Arctic.

Impacts on biodiversity from codend and fisher selection in bottom trawl fishing

“…To estimate the uncertainty (Efron percentile 95% confidence intervals; Efron, 1982) of the above-mentioned indices the method presented by Herrmann et al (2022) was used (see Appendix A for details).…”

“…The difference D (Herrmann et al, 2022) was applied for pair-wise comparisons of each index, i) between the various units of analysis (T, E, R, D, L) of each codend, and ii) for the same unit of analysis between the tested codends (see Appendix A for details).…”

“…To estimate the uncertainty of each index according to the method presented by Herrmann et al (2022), in each haul, the uncertainty of the finite number N j [see equation ( 1)] was estimated by using a resampling method with replacement (Chernick, 2008) and by performing 1000 resamplings, which gave a population of 1000 values for each indicator. These values can be used to estimate the Efron percentile 95% confidence intervals (Efron, 1982) for each indicator for each haul j.…”

“…For the pair-wise comparison of an index O, the difference D for an index between two units x and y was estimated as presented by Herrmann et al (2022):…”

“…This section provides a description of the different indices used for the of the biodiversity in each unit of analysis. All these analyses were implemented using the software tool SELNET (Herrmann et al, 2012;Herrmann et al, 2013;Herrmann et al, 2022).…”