Responses of multimetric indices to disturbance are affected by index construction features

扰动(地质) 索引(排版) 环境科学 地理 生态学 计算机科学 生物 万维网 古生物学
作者
Renata Ruaro,Éder André Gubiani,André Andrian Padial,James R. Karr,Robert M. Hughes,Roger Paulo Mormul
出处
期刊:Environmental Reviews [Canadian Science Publishing]
标识
DOI:10.1139/er-2023-0098
摘要

Multimetric indices (MMIs) are used worldwide to assess the ecological conditions of aquatic and terrestrial ecosystems. Different criteria and approaches are used to construct MMIs, resulting in widely different indices. Therefore, scientists, managers, and policymakers sometimes question whether such MMIs are useful for biomonitoring and bioassessment programs. Crucial design issues for biomonitoring programs include MMI responsiveness, the bioindicator group used, survey design, field sampling methods, level of taxonomic resolution, metric selection and scoring, and reference condition identification. We performed a meta-analysis on MMI development and applications worldwide to analyze the response of MMIs to different disturbance factors and to determine the degree to which MMI construction features influence their responsiveness to anthropogenic disturbances. We used the Web of Science database to find articles that applied an MMI and related MMI values to an environmental stressor, and we extracted data from 157 articles. We performed random-effects modeling to estimate the overall effect of MMI responses to disturbance and used subgroup analysis to analyze the extent to which the effect sizes varied as a function of different MMI construction features. We found that reference condition criteria had the major effect on MMI responses to disturbance. The environmental disturbance type, the number of metrics, and the ecosystem type to which MMIs were applied contributed more weakly to effect size variance. The general response of MMIs to disturbance was little affected by the bioindicator group, taxonomic resolution, the metric selection criteria, or scoring method. These findings have important implications for designing biomonitoring programs, including developing and improving cost-effective biological indices, because they could enhance MMI development and application protocols.

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