Development of a benthic multimetric index for the Serra da Bocaina bioregion in Southeast Brazil

Abstract

Brazil faces a challenge to develop biomonitoring tools to be used in water quality assessment programs, but few multimetric indices were developed so far. This study is part of an effort to test and implement programs using benthic macroinvertebrates as bioindicators in Rio de Janeiro State. Our aim was first to test the Multimetric Index for Serra dos Órgãos (SOMI) for a different area -Serra da Bocaina (SB) -in the same ecoregion. We sampled 27 streams of different sizes and altitudes in the SB region. Despite the environmental similarities, results indicated biological differences between reference sites of the two regions. Considering these differences, we decided to develop an index specific for the SB region, the Serra da Bocaina Multimetric Index (MISB). We tested twenty-two metrics for sensitivity to impairment and redundancy, and six metrics were considered valid to integrate the MISB: Family Richness, Trichoptera Richness, % Coleoptera, % Diptera, IBE-IOC index, EPT / Chironomidae ratio. A test of the MISB in eleven sites indicated it was more related to land-use and water physico-chemical parameters than with altitude or stream width, being a useful tool for the monitoring and assessment of streams in the bioregion.Keywords: biomonitoring, macroinvertebrates, freshwater ecoregions, watershed management, stream ecology. Desenvolvimento de um índice multimétrico bentônico para a bioregião da Serra da Bocaina no Sudeste do BrasilResumo O Brasil enfrenta o desafio de desenvolver ferramentas de biomonitoramento para serem utilizadas em programas de avaliação da qualidade de águas, porém poucos índices multimétricos foram construídos para esta finalidade. Este estudo faz parte de um esforço para testar e implementar programas de biomonitoramento utilizando macroinvertebrados bentônicos como bioindicadores no Estado do Rio de Janeiro. Nosso objetivo foi primeiro testar se as métricas que compõem o Índice Multimétrico da Serra dos Órgãos (SOMI) eram válidas para serem aplicadas em um área diferente -Serra da Bocaina (SB) -pertencente à mesma ecoregião. Nós amostramos 27 riachos de diferentes tamanhos e altitudes na região da Serra da Bocaina. Apesar das similaridades ambientais, os resultados indicaram haver diferenças entre locais de referencia nas duas regiões. Considerando tais diferenças, nós desenvolvemos um índice específico para região da SB, denominado de Índice Multimétrico da Serra da Bocaina (IMSB). Testamos vinte e duas métricas quanto à sensibilidade e redundância. Seis métricas foram consideradas válidas para integrar o IMSB: Riqueza de Famílias, Riqueza de Trichoptera, % Coleoptera, % Diptera, índice IBE-IOC e Taxa EPT / Chironomidae. O teste do IMSB indicou que o índice estava mais relacionado aos parâmetros físicos e químicos da água e ao uso da terra do que com a altitude ou largura dos rios. Assim, consideramos uma ferramenta útil para monitorar e avaliar riachos na bioregião estudada.Palavras-chave: biomonitoramento, macroinvertebrados, ecoregiões de água doce, manejo de bacia hid...

Developing and applying a macroinvertebrate‐based multimetric index for urban rivers in the Niger Delta, Nigeria

“…Most of the sensitive metrics were in the abundance and composition measures. The abundance and composition metrics are widely recognized as being sensitive to pollution and therefore often integrated into multimetric indices (Baptista et al, ; Gieswein et al, ; Huang et al, ; Lu et al, ; Melo, Stenert, Dalzochio, & Maltchik, ).…”

“…The inadequacies of physicochemical monitoring alone have necessitated the complementary use of biological monitoring (i.e., biomonitoring) tools and approaches (Arimoro, Ikomi, Nwadukwe, Eruotor, & Edegbene, ; Bonada et al, ; Serra, Graca, Doledec, & Feio, ). Biomonitoring tools/approaches widely used include single biotic indices (e.g., South African Scoring System version 5, Dickens & Graham, ) functional feeding group (FFG; e.g., Akamagwuna, Mensah, Nnadozie, & Oghenekaro, ; Baptista et al, ; Lakew & Moog, ; Ntislidou, Lazaridou, Tsiaoussi, & Bobori, ), multivariate approaches (e.g., Chowdhury, Gallardo, & Aldridge, ; Gieswein et al, ; Oliveira, Mugnai, Pereira, Souza, & Baptista, ), and multimetric indices (e.g., Bonada et al, ; Edegbene et al, ; Mereta et al, ; Monaghan & Soares, ). Of these approaches, the multimetric indices have been shown to perform extremely well particularly because they integrate information and data from multiple dimension of aquatic biota and the ecosystem as a whole (Bonada et al, ).…”

Advances in Watershed Science and Assessment

“…The presence of standing water interacts with the radar signal V. Klemas and A. Pieterse differently depending on the dominant vegetation type/structure [20] as well as the biomass and condition of vegetation [126,127]. In areas of open water without vegetation, specular reflection occurs and a dark signal (weak or no return) is observed [128].…”

“…PCA is commonly used to aggregate individual stressor variables into a comprehensive index of impairment. Metrics and indices can then be evaluated as to the strength of their correlation with this aggregate stressor index [124,127,128]. Tests of whether metrics differ significantly from reference conditions provide binary results regarding whether a metric classifies sites correctly.…”

“…When only a few sites are available, index accuracy may be validated by analyzing for correlations of index scores with stressor gradients, which requires fewer validation sites. This approach is especially useful in highly developed landscapes where there are few reference sites [127,142]. Index accuracy is often prioritized over other performance characteristics, although more thorough validation strategies also evaluate precision [21,106,143].…”