The spatial distribution of the subtidal benthic macrofauna and its relationship with environmental factors using geostatistical tools: a case study in Trapandé Bay, southern Brazil

Souza, Fernanda Maria de; Gilbert, Eliandro R.; Camargo, Maurício G.; Pieper, Wagner W.

doi:10.1590/s1984-46702013000100007

Cited by 9 publications

(4 citation statements)

References 23 publications

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“…A similar density observed in Sechura Bay, in Peru, where were collected 1,886 ind.m² (Yupanqui et al, 2007). This result was superior when compared to the density of Trapandé/SP Bay, which presented approximately 170 ind.m² (Souza et al, 2013). In Lagoa dos Patos/RS Bay, the density of capitellids found was around 6,000 ind.m² (Soares et al, 2016), a value considerably higher than that found in this study.…”

Section: Abioticssupporting

confidence: 67%

Composition and seasonal variation of capitellidae from Balneário Camboriú, Santa Catarina, Brazil

Beltrão,

Cunha,

Diehl

2023

RHE

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The objective of this study was to provide information about the structure and composition of the Capitellidae family in Balneário Camboriú, as well as evaluate its space-time variations. Four sampling campaigns were carried out at 16 stations, distributed in the Camboriú River and Balneário Camboriú Bay. A total of 1,769 ind.m² were collected and identified into five taxa: Capitella sp.; Capitella cf. nonatoi; Heteromastus sp., Heteromastus similis and Mediomastus cf. californiensis. The most abundant taxon was M. californiensis, showing the highest number of individuals during autumn, followed by Capitella cf. nonatoi in the summer. The distribution of M. californiensis was more related to the opportunistic habit of the species than to seasonality, while Capitella cf. nonatoi distribution was related to the high concentration of organic matter from the Camboriú River, which may be the result of residents and tourists visiting the city in the summer. These results denote the Capitellidae family bioindicator potential for anthropogenic disturbances.

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Section: Abioticssupporting

confidence: 67%

Composition and seasonal variation of capitellidae from Balneário Camboriú, Santa Catarina, Brazil

Beltrão,

Cunha,

Diehl

2023

RHE

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“…The complexity driving ecological interactions can vary from one area to another within a habitat and can be difficult to model because habitat complexity contributes to ecosystem heterogeneity (de Souza et al, 2013 ). Spatial–temporal interactions of biological, hydrographic, and oceanographic characteristics with seafloor and shoreline topography can be significant ecosystem influences affecting benthic community characteristics, long-term maintenance of benthic energy hotspots, and thus marine animal distributions (Blanchard et al, 2013 ; Buhl-Mortensen et al, 2012 ; Grebmeier et al, 2015 ).…”

Section: Discussionmentioning

confidence: 99%

Benthic studies adjacent to Sakhalin Island, Russia 2015 III: benthic energy density spatial models in the nearshore gray whale feeding area

Blanchard¹,

Ainsworth²,

Gailey³

et al. 2022

Environ Monit Assess

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Energy densities of six dominant benthic groups (Actinopterygii, Amphipoda, Bivalvia, Cumacea, Isopoda, and Polychaeta) and total prey energy were modeled for the nearshore western gray whale feeding area, Sakhalin Island, Russia, as part of a multi-disciplinary research program in the summer of 2015. Energy was modeled using generalized additive mixed models (GAMM) with accommodations for zero-inflation (logistic regression and hurdle models) and regression predictions combined with kriging to interpolate energy densities across the nearshore feeding area. Amphipoda energy density was the highest nearshore and in the south whereas Bivalvia energy density was the highest offshore and in the northern portion of the study area. Total energy was the highest in mid-range distances from shore and in the north. Amphipoda energy density was higher than minimum energy estimates defining gray whale feeding habitats (312–442 kJ/m2) in 13% of the nearshore feeding area whereas total prey energy density was higher than the minimum energy requirement in 49% of the habitat. Inverse distance-weighted interpolations of Amphipoda energy provided a broader scale representation of the data whereas kriging estimates were spatially limited but more representative of higher density in the southern portion of the study area. Both methods represented the general trend of higher Amphipoda energy density nearshore but with significant differences that highlight the value of using multiple methods to model patterns in highly complex environments.

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“…Faunal responses to organic matter concentrations are essentially a response to changes in nutrient pathways, feeding modes and physiological tolerance mechanisms to the decreasing oxygen availability associated with this type of disturbance ( Souza et al, 2013 ; Bon et al, 2021 ). Consequently, organically enriched environments tend to be dominated by more generalist and opportunistic taxa or r-strategist guilds, which are physiologically more resistant to oxygen deprivation ( Pearson & Rosenberg, 1978 ; Cardell, Sardà & Romero, 1999 ; Brauko et al, 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Macrobenthic community responses to multiple environmental stressors in a subtropical estuary

Souza

Gilbert

Brauko

et al. 2021

PeerJ

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We assessed how multi- and univariate models reflect marine environmental health based on macrobenthic community responses to three environmental stressor categories: hydrodynamics, organic enrichment and metal contamination. We then compared the models with the benthic index AMBI (AZTI Marine Biotic Index). Macrobenthic community and physicochemical variables were sampled at 35 sites along Babitonga Bay, a subtropical estuary in Southern Brazil. Distance-based linear modelling identified depth, grain size and organic matter as well as Cu and Zn as key stressors affecting the macrobenthos. Using canonical analysis of principal coordinates (CAP), we developed three multivariate models based on the variability in community composition, creating stress gradients. The metal gradient showed better correlation with the benthic community. Sediment quality indices (Geoaccumulation Index and Contamination Factor) showed a low to moderate contamination status, with higher concentrations for Cr, Ni and Zn at the inner areas of the bay. According to AMBI, Babitonga Bay has a “good” environmental health status, and the AMBI values show stronger correlations with the hydrodynamic and organic enrichment gradients (r = 0.50 and r = 0.47) rather than the metal gradient (r = 0.29). Lumbrineridae polychaetes (not included in the AMBI list) and Scoloplos sp. were negatively related to the metal contamination gradient and were considered sensitive, while Sigambra sp., Magelona papillicornis, the gastropod Heleobia australis and species of the crustacean order Mysida were positively related to the gradient and considered tolerant to higher concentrations of metals in the sediment. Despite the inconsistency in the ecological classification provided by AMBI and its relationship with the metal gradient, our results suggest that the environmental quality was satisfactory for the studied gradients. The metal gradient showed the weakest correlation to AMBI. In such cases, the ecological classification of taxa by the index should be evaluated under the perspective of the action of inorganic genotoxic contaminants represented by metals.

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The spatial distribution of the subtidal benthic macrofauna and its relationship with environmental factors using geostatistical tools: a case study in Trapandé Bay, southern Brazil

Cited by 9 publications

References 23 publications

Composition and seasonal variation of capitellidae from Balneário Camboriú, Santa Catarina, Brazil

Composition and seasonal variation of capitellidae from Balneário Camboriú, Santa Catarina, Brazil

Benthic studies adjacent to Sakhalin Island, Russia 2015 III: benthic energy density spatial models in the nearshore gray whale feeding area

Macrobenthic community responses to multiple environmental stressors in a subtropical estuary

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