3 resultados para multivariate analysis of covariance

em Aquatic Commons


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Using data collected simultaneously from a trawl and a hydrophone, we found that temporal and spatial trends in densities of juvenile Atlantic croaker (Micropogonias undulatus) in the Neuse River estuary in North Carolina can be identified by monitoring their sound production. Multivariate analysis of covariance (MA NCOVA) revealed that catch per unit of effort (CPUE) of Atlantic croaker had a significant relationship with the dependent variables of sound level and peak frequency of Atlantic croaker calls. Tests of between-subject correspondence failed to detect relationships between CPUE and either of the call parameters, but statistical power was low. Williamson’s index of spatial overlap indicated that call detection rate (expressed by a 0–3 calling index) was correlated in time and space with Atlantic croaker CPUE. The correspondence between acoustic parameters and trawl catch rates varied by month and by habitat. In general, the calling index had a higher degree of overlap with this species’ density than did the received sound level of their calls. Classification and regression tree analysis identified calling index as the strongest correlate of CPUE. Passive acoustics has the potential to be an inexpensive means of identifying spatial and temporal trends in abundance for soniferous fish species.

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Fish assemblage structure of Maryland's coastal lagoon complex was analyzed for spatial and seasonal patterns for the period 1991-2000. Data was made available by Maryland Department of Natural Resources from their MD Coastal Bays Finfish Survey. Dominant species from separate trawl and wiw surveys included blue crab Callinectes sapidus (erroneously included here as a "fish" due to its dominance and commercial importance), bay anchovy Anchoa mitchilli, spot Leiostomous xanthurus, silver perch Bairdiella ehrysoura, and Atlantic menhaden Brevwrtia tyrannus. Ninety-four fish species were identified in the two surveys, a diversity substantially higher than other survey records for Middle Atlantic Bight estuarine and lagoon systems (richness=26 to 78 species). Total species richness for the trawl survey was highest in Chincoteague and lowest in Assawoman and Sinepuxent. On the other hand, mean richness per tow (-area) and related Shannon Weiner Diversity Index were significantly higher in the northern two bays (Assawoman and Isle of Wight Bays) than in the two southern bays (Chincoteague or Sinepuxent Bays). For the seine survey, effort-adjusted diversity indices were significantly lower for Chincoteague Bay than for the other three bays. Higher relative abundances were observed in the northern bays than in the southern bays. The trawl survey exhibited the lowest catch-per-site in Sinepuxent Bay and the highest in Assawoman Bay. The seine survey had the lowest catch-per-site in Chincoteague Bay while the other three embayments were of similar magnitude. There was clear seasonality in assemblage structure with peak abundance and diversity in the summer compared to other seasons. Blue crabs in particular showed a c. 2-fold decline in relative abundance from early summer to fall, which is likely attributable to harvest removals (i.e., an exploitation rate of c. 50%). Seagrass coverage, although increasing over the course of the 10 year survey, did not have obvious effects on species diversity and abundance across or within the embayments, although it did have positive associations with two important species: bay anchovy and summer flounder Pavalich thys dentatus. Atlantic menhaden were most dominant in Assawoman Bay, which could be related to higher primary production typically observed in this Bay in comparison to the other three. (PDF contains 99 pages)

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A study of planktonic foraminiferal assemblages from 19 stations in the neritic and oceanic regions off the Coromandel Coast, Bay of Bengal has been made using a multivariate statistical method termed as factor analysis. On the basis of abundance, 17 foraminiferal species, species were clustered into 5 groups with row normalisation and varimax rotation for Q-mode factor analysis. The 19 stations were also grouped into 5 groups with only 2 groups statistically significant using column normalisation and varimax rotation for R-mode analysis. This assemblage grouping method is suitable because groups of species/stations can explain the maximum amount of variation in them in relation to prevailing environmental conditions in the area of study.