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Organic enrichment and structure of macrobenthic communities in the glacial Baker Fjord, Northern Patagonia, Chile

Published online by Cambridge University Press:  07 April 2011

Eduardo Quiroga*
Affiliation:
Pontificia Universidad Católica de Valparaíso (PUCV), Escuela de Ciencias del Mar, Casilla 1020, Valparaíso, Chile
Paula Ortiz
Affiliation:
Centro de Investigación en Ecosistemas de la Patagonia (CIEP), Bilbao 449, Coyhaique, Chile
Dieter Gerdes
Affiliation:
Alfred Wegener Institute for Polar and Marine Research, Columbusstrasse, D-27568 Bremerhaven, Germany
Brian Reid
Affiliation:
Centro de Investigación en Ecosistemas de la Patagonia (CIEP), Bilbao 449, Coyhaique, Chile
Soraya Villagran
Affiliation:
Centro de Investigación en Ecosistemas de la Patagonia (CIEP), Bilbao 449, Coyhaique, Chile
Renato Quiñones
Affiliation:
Centro de Investigación Oceanográfica en el Pacífico Sur-Oriental (COPAS), Universidad de Concepción, Casilla 160-C, Concepción, Chile
*
Correspondence should be addressed to: E. Quiroga, Pontificia Universidad Católica de Valparaíso (PUCV), Escuela de Ciencias del Mar, Casilla 1020, Valparaíso, Chile email: eduardo.quiroga@ucv.cl
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Abstract

In this study we describe community parameters such as densities, biomasses, species composition, feeding modes and normalized biomass size-spectra (NBSS) of macrobenthic invertebrate communities from three stations located in the Baker Fjord obtained on four seasonal campaigns in 2008 and 2009. The macrobenthic communities were dominated by small-bodied polychaetes (Paraonidae, Capitellidae and Cirratulidae) characterized by continuous year-round breeding, short life-spans, and fast turnover rates, which in turn regulated the standing stock in the communities. Principal component analysis and multiple-regression analysis demonstrate the distribution of macrobenthic communities in the study area to be mainly controlled by few local environmental conditions. Macrofaunal densities, diversity and feeding modes were significantly correlated with the total organic carbon (TOC; R2 = 0.74; P < 0.001) and chlorophyll-a (Chl-a; R2 = 0.55; P < 0.05) content in the sediments. This study also suggests that feeding modes and NBSS can be used to detect and follow possible changes caused by natural perturbations such as glacial lake outburst floods or anthropogenic stressors associated with ecological impacts generated by the construction and operation of hydroelectric power stations in the Baker River.

Information

Type
Research Article
Copyright
Copyright © Marine Biological Association of the United Kingdom 2011
Figure 0

Fig. 1. Map of sampling stations.

Figure 1

Fig. 2. (A) Discharge of water into the Baker River between July 2007 to July 2009, measured by the hydro-meteorological Colonia Station (47°160S 73°130W) and (B) estimated suspended sediment load.

Figure 2

Table 1. List of stations and sediment parameters.

Figure 3

Fig. 3. Taxonomic composition of macrofauna (A), feeding modes (B), mean density (C), mean biomass (D), rarefaction (E) and dominance (F) curves for macrofauna sampled at three stations in the Baker Fjord.

Figure 4

Fig. 4. Non-metric multidimensional scaling ordination plots of macrofauna sampled in the study area. The multivariate index of dispersion (MID) reflects relative within-station variability among samples.

Figure 5

Table 2. Species list of the total macrofauna, mean densities with standard deviation (SD), and dominance values (%); pooled data from all sampling campaigns dominance values (%); pooled data from all sampling campaigns.

Figure 6

Table 3. Macrofaunal community parameters obtained from three stations in the Baker Fjord; no data available for Station S1 in the September campaign 2008.

Figure 7

Fig. 5. Normalized biomass size-spectra plots of the macrofauna obtained at three stations in the study area. The equation parameters, the squared correlation coefficient (r2), the standard error of the slopes (SEslope) and the P values are indicated for all data sets in each regression.

Figure 8

Fig. 6. Principal component analysis (PCA) of environmental variables in the study area. Z, depth; Sand, % sand; Clay, % clay; TOM, total organic matter; TOC, total organic carbon; Chl-a, chlorophyll-a; Phaeop, phaeopigment; CPE, chloroplastic pigment equivalent; Q, freshwater input.

Figure 9

Table 4. Summarized results of the multiple-regression analysis of community data versus environmental parameters.