Spatially-explicit Models of Fish Growth Rate

Brandt, Stephen B.; Mason, Doran M.; Patrick, E. Vincent

doi:10.1577/1548-8446(1992)017<0023:smofgr>2.0.co;2

Cited by 136 publications

(112 citation statements)

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“…Identifying the factors affecting fish growth rates is important ecologically due to the importance of growth as a key life history trait and its role in, for example, production and juvenile recruitment (Brandt et al, 1992;Berkeley et al, 2004). In the freshwater phase of stream-dwelling salmonid fishes, biotic factors are important determinants of individual growth rates due to, for example, competition for territory and food (Keeley, 2001;Richard et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Influences of environmental and chemical parameters on the spatial growth patterns of four riverine cyprinid fishes

Liu

Chen

Britton

2015

Knowl. Manag. Aquat. Ecosyst.

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Key-words:roach, chub, disturbance, somatic growth, environmental change Understanding intraspecific variability in fish somatic growth rates is important as growth is a key life history trait that plays a fundamental role in many biological and ecological processes. Here, the influence of environmental and chemical parameters was tested on intraspecific variability in growth rates of the cyprinid fishes roach Rutilus rutilus, chub Squalius cephalus and dace Leuciscus leuciscus across 13 rivers in England, and also compared with those for barbel Barbus barbus from the same rivers. Outputs indicated that growth rate responses to the parameters were species-specific, with more significant effects generally detected on juvenile growth than lifetime growth. For R. rutilus and S. cephalus, latitude (as a surrogate of temperature) was the most significant predictor of their growth rates, with growth rates decreasing as latitude increased. Contrary to prediction, aspects of degraded water quality accelerated the growth rates of these fishes, except in B. barbus, although concentrations of nitrogenous compounds were below toxicity thresholds. This emphasizes the ability of populations of these cyprinid fishes to tolerate some environmental disturbances and, in entirety, suggests that the intraspecific variability in the growth rates of these fishes is significantly influenced by abiotic parameters and their association with levels of anthropogenic disturbance. RÉSUMÉ

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Section: Introductionmentioning

confidence: 99%

Influences of environmental and chemical parameters on the spatial growth patterns of four riverine cyprinid fishes

Liu

Chen

Britton

2015

Knowl. Manag. Aquat. Ecosyst.

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“…Bioenergetics models relate environmental conditions to size and species-specific growth rates taking into consideration the inherent non-linear aspects of these relationships (Brandt et al, 1992;Brandt and Kirsch, 1993). Growth rate potential (hereafter GRP) describes the amount of growth achievable by a size and species-specific predator when placed in a predetermined volume of water characterised by a particular suite of environmental conditions.…”

Section: Bioenergetics Sub-modelmentioning

confidence: 99%

“…(4)) reaches 1. When PA ≥ C max , P is set to 1, as further increases in prey availability cannot be used or eaten by the predator due to physiological constraints such as gut fullness, and digestion rate (see Brandt et al, 1992;Brandt, 1993;Tyler, 1998). When PA < C max , consumption (C) becomes a proportion (P) of maximum consumption (C max ).…”

Section: Consumptionmentioning

confidence: 99%

“…Associations between environmental conditions and predator-prey interactions have been quantified using a spatially explicit approach (Brandt et al, 1992). These models reveal that spatial complexity within aquatic systems can constrain predator and prey distributions, effectively limiting the amount of prey available to predators in the spatial dimension (e.g., Brandt and Kirsch, 1993;Goyke and Brandt, 1993;Hondorp and Brandt, 1996).…”

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confidence: 99%

“…Spatial models have demonstrated that predators tracking both prey abundances and optimal temperatures have highest production potentials in areas where these environmental characteristics overlap (Brandt et al, 1992;Brandt, 1993;Luo and Brandt, 1993;Goyke and Brandt, 1993;Hondorp and Brandt, 1996). Spatial modelling, however, is largely limited to 'snapshots' taken over short time periods, and does little to resolve how often these overlapping conditions develop and how long they persist.…”

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confidence: 99%

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Estimating fish production potentials using a temporally explicit model

Roy

Haffner

Brandt

2004

Ecological Modelling

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A temporally explicit model is developed to predict the growth rate potential of fish in response to temporal fluctuations in both prey availability and temperature structure of the water column at both long (seasonal) and short (daily) time scales. The model was tested in a 20 m water column in Lake Ontario using chinook salmon (Oncorhynchus tshawytcsha) and alewife (Alosa pseudoharengus) as predator and prey species, respectively. Prey availability was assessed using acoustic techniques, while temperature was measured with a temperature-depth profiler. Chinook growth rate potential was significantly greater during June than during other sampled months. The latter months supported little to no chinook growth potential as a result of low overlap in conditions supporting growth. On a diel scale, chinook growth rate potential was typically greater during crepuscular and night periods than during the day. Results reveal that both short and long term variability of prey density and thermal structure impose stringent limits to fish growth potential and production, and that fish grow well only over finite periods. The temporally explicit model provides quantitative predictions of fish production potential as influenced by temporal changes in habitat quality and/or climatic conditions. In light of recent modifications to both local and regional climate conditions, and the localised nature of fish harvesting practices, this model can assist in setting realistic production estimates and future potential harvesting quotas.

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