Predictive models of small fish presence and abundance in northern New Zealand harbours

Francis, Malcolm P.; Morrison, Mark A.; Leathwick, John R.; Walsh, Cameron; Middleton, Crispin

doi:10.1016/j.ecss.2005.03.007

Cited by 56 publications

(46 citation statements)

References 37 publications

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“…Logistic models have been successfully used in habitat suitability studies (e.g. Stoner et al 2001) and may even perform better than abundance models (Francis et al 2005). Along each environmental variable, the smoother spline function (s in Eq.…”

Section: Methodsmentioning

confidence: 99%

Habitat selectivity of substrate-spawning fish: modelling requirements for the Eurasian perch Perca fluviatilis

Snickars¹,

Sundblad²,

Sandström³

et al. 2010

Mar. Ecol. Prog. Ser.

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Substrate spawning fish are believed to be selective in their choice of spawning habitat, yet few studies have shown the relative importance of different characteristics in terms of habitat quality. We used an extensive and detailed dataset to identify the factors that govern both large-scale (10 3 to 10 5 m) and local-scale (10 1 to 10 2 m) selection by a substrate-spawning fish, the Eurasian perch Perca fluviatilis L. Distribution of spawning habitat was strongly dependent on habitat characteristics defined by substrate, wave exposure, temperature and depth. The most important predictor was the type of spawning substrate, which generally consisted of different types of vegetation. Substrates providing rigidity and structural complexity were preferred, despite abundant presence of other substrate types. Shallow depth and sheltered areas were also selected habitat characteristics. The response to temperature was scale-dependent, with a stronger selection expressed at the local scale. The specific selectivity suggests that spawning patterns can be successfully modelled with sufficient detail using only a few fundamental environmental variables. Wave exposure and depth are readily available for large-scale spatial predictions, while temperature and substrate require further development in most coastal areas. The high specificity of the characteristics determining habitat quality suggests that it should be possible to apply this modelling approach for identification and conservation of spawning habitats of Eurasian perch and other substrate-spawning fishes in coastal waters.

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Section: Methodsmentioning

confidence: 99%

Habitat selectivity of substrate-spawning fish: modelling requirements for the Eurasian perch Perca fluviatilis

Snickars¹,

Sundblad²,

Sandström³

et al. 2010

Mar. Ecol. Prog. Ser.

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show abstract

“…Giannoulaki et al (2006) used GAMs to identify the relationship between anchovy presence and environmental variables. Francis et al (2005) predicted small fish presence and abundance in northern New Zealand harbours. Many authors suggested several approaches to improve model fitting and prediction capacity in GAM.…”

Section: Generalized Linear Additive and Mixed Modelsmentioning

confidence: 97%

“…They can also potentially capture genuine geographic effects, such as proximity to favourable habitat features (e.g. spawning sites), or where juvenile dispersal is aided by particular habitat combinations (Francis et al, 2005). Similarly, inclusion of time of day, month/season and year in models may capture temporal patterns without explaining them.…”

Section: Data Acquisition and Preparationmentioning

confidence: 97%

Modelling of essential fish habitat based on remote sensing, spatial analysis and GIS

et al. 2008

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We review the variety of existing modelling approaches applied to species habitat mapping and we discuss issues arising from the availability and nature of sampled biological data and corresponding ecological and environmental habitat descriptors, as well as the different spatial analysis approaches that are selected according to specific hypotheses. We focus on marine species habitat mapping, presenting an overview of work on modelling fish habitat carried out through a European Communities Policy-Support Action, EnviEFH 'Environmental Approach to Essential Fish Habitat (EFH) Designation' (2005)(2006)(2007)(2008). The selection of the appropriate habitat model is dataset-specific and the resulting EFH maps are often similar in spite of using different models. Derived EFH maps are based on either environmental ranges (used as minimum and maximum environmental habitat descriptors) or probability of occurrence values. We apply model outputs to regions larger than sampled areas making use of the capacity of satellite data to cover wide areas.

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“…The smaller members of the flatfish complex are best described as opportunist strategists (King & McFarlane 2003), being characterised by small size, rapid growth, short-lived and relatively high fecundity. Flatfish are distributed widely throughout New Zealand, being frequently encountered in coastal inlets, embayments and estuaries (Jones & Hadfield 1985;Francis et al 2005). There are significant flatfish fisheries in the Hauraki Gulf, Kaipara and Manukau Harbours (Paul 2000), and Tasman Bay and the Canterbury Bight (Ministry of Fisheries 2009).…”

Section: Introductionmentioning

confidence: 99%

What causes the high interannual variability of flatfish (Rhombosoleaspp.) in Lake Ellesmere?

Jellyman

2011

New Zealand Journal of Marine and Freshwater Research

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Lake Ellesmere, Canterbury, a large coastal lake is mechanically opened to the sea at predetermined water levels. The lake maintains important customary and commercial eel (Anguilla spp.) and flatfish (Rhombosolea spp.) fisheries, although the harvest of flatfish varies considerably between years. The three main flatfish species (black flounders Rhombosolea retiaria, sand flounders R. plebia and yellowbelly flounders R. leporina) recruit in spring, grow rapidly within the lake, and reach the minimum commercial size within two or three years. Maturing fish endeavour to leave the lake to spawn at sea during summer and autumn. There is a weak association between commercial catches and lake openings lagged by two years, but strong associations between catches in the lake and in the Canterbury Bight. The high interannual variability in abundance partly reflects timing and duration of lake openings, the opportunity of maturing fish to emigrate to sea, and the strength of regional recruitment.

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Predictive models of small fish presence and abundance in northern New Zealand harbours

Cited by 56 publications

References 37 publications

Habitat selectivity of substrate-spawning fish: modelling requirements for the Eurasian perch Perca fluviatilis

Habitat selectivity of substrate-spawning fish: modelling requirements for the Eurasian perch Perca fluviatilis

Modelling of essential fish habitat based on remote sensing, spatial analysis and GIS

What causes the high interannual variability of flatfish (Rhombosoleaspp.) in Lake Ellesmere?

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