Spatial variation and effects of habitat on temperate reef fish assemblages in northeastern New Zealand

By Marti J. Anderson, R. Millar. 2004

312 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/f412975d7567fb0c71c97d7136ba357e32986438

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Citations in the corpus

Significance of woodland key habitats for polypore diversity and red-listed species in boreal forests (2008, background): “Binomial index is known to manage well also with data sets where sample sizes vary greatly in terms of the number of species per site (Anderson and Millar 2004; Oksanen et al. 2005).”
Distance‐Based Tests for Homogeneity of Multivariate Dispersions (2006, methodology): “…and power, is then demonstrated for two sets of ecological community data: the percentage cover of Indonesian coral species responding to an El Niño event (Warwick, Clarke, and Suharsono, 1990) and spatial variation in abundances of New Zealand temperate reef fishes (Anderson and Millar, 2004).”
Spatial prediction of demersal fish distributions: enhancing our understanding of species–environment relationships (2009, background): “…environmental or ecological limitations, such as the availability of refuges, territory and food, or the presence of competition or predation (Ebeling et al. 1980, Choat & Ayling 1987, McCormick 1994, Friedlander & Parrish 1998, García-Charton & PérezRuzafa 2001, Anderson & Millar 2004).”
A little bait goes a long way: The influence of bait quantity on a temperate fish assemblage sampled using stereo-BRUVs (2013, methodology): “Assemblage composition data was analysed using a Bray–Curtis resemblance matrix, while a Euclidean distance resemblance matrix was used for all univariate analyses (Anderson and Millar, 2004).”
Allochthonous brown algae are the primary food source for consumers in a temperate, coastal environment (2009, methodology): “As with univariate analyses, we were most interested in the amount of variation attributable to the different sources, and focussed on estimates of the pseudo-variance components, calculated as for the univariate case from the means squares yielded by PERMANOVA (Anderson & Millar 2004).”
Loss of fucoid algae along a gradient of urbanisation, and structure of benthic assemblages (2008, methodology): “…analysis was assessed using estimates of the magnitude of effect sizes of fixed factors, based on mean squares of the full model (Underwood 1997, Anderson & Millar 2004), expressed as the ratio among the effect size of each fixed factor (θ2i) and the sum of the effect sizes of all fixed factors…”
Bait attraction affects the performance of remote underwater video stations in assessment of demersal fish community structure (2007, methodology): “A 2-way non-parametric multivariate analysis of variance (PERMANOVA) showed that statistically significant higher mean numbers of individuals (MaxNi; Fig.”
The application of predicted habitat models to investigate the spatial ecology of demersal fish assemblages (2010, background): “Research into patterns of Wsh assemblages has demonstrated the associations between benthic type and topographic complexity, both in temperate (Choat and Ayling 1987; Jenkins and Sutherland 1997; Jenkins and Wheatley 1998; Hyndes et al. 1999; O’Hara 2001; Curley et al. 2002; Giannoulaki et al. 2003;”
Community structure of temperate reef fishes in kelp-dominated subtidal habitats of northern Chile (2007, background): “These examples support the notion that the distributional patterns of reef fishes may be reflective of trophic requirements (Ferreira et al. 2001; Anderson and Millar 2004), and variation in fish assemblages is correlated with variations in available food resources (Gárcia-Charton and PérezRuzafa 20”
Remedies for pseudoreplication (2004, background): “Anderson and Millar (2004)used a multilevel experimental design to survey fish abundance on inshore reefs off the north-eastern coast of New Zealand.”
Evaluating the biological effectiveness of fully and partially protected marine areas (2013, background): “[5,55]) or due to site-specific features in reserves that differ from those in control areas [5,13,54,100].”