Process-based modelling of invertebrate drift transport, net energy intake and reach carrying capacity for drift-feeding salmonids

We present an overview of a process-based modelling approach for predicting how change in flow affects drift density, net rate of energy intake (NREI) and numbers of drift-feeding salmonids. It involves linking an existing two-dimensional flow model (River2D) with models of invertebrate drift transp...

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Bibliographic Details
Published in:Ecological modelling 2007-10, Vol.207 (2), p.171-188
Main Authors: Hayes, John W., Hughes, Nicholas F., Kelly, Lon H.
Format: Article
Language:English
Subjects:
Animal and plant ecology
Animal, plant and microbial ecology
Biological and medical sciences
Brown trout
Carrying capacity
Drift transport
Drift-feeding
Foraging model
Fresh water ecosystems
Freshwater
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Habitat
Habitat suitability
Hydraulic modelling
IFIM
Invertebrata
Invertebrate drift
Methods and techniques (sampling, tagging, trapping, modelling...)
Modelling
NREI
Process-based modelling
Process-modelling
River2D
Salmo trutta
Salmonidae
Salmonids
Synecology
WUA
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Summary:We present an overview of a process-based modelling approach for predicting how change in flow affects drift density, net rate of energy intake (NREI) and numbers of drift-feeding salmonids. It involves linking an existing two-dimensional flow model (River2D) with models of invertebrate drift transport and drift-foraging which we have developed. We describe, demonstrate and partially test our models in an application on a 80 m × 20 m pool on a New Zealand river. We show how these models realistically capture hydraulic, drift dispersion and bioenergetics drift-foraging processes to predict the relationship between stream flow, habitat quality and quantity (in terms of NREI), and carrying capacity for drift-feeding salmonids. Overall, the 2D hydraulic model made good predictions of water levels, depths and water velocity at the calibration flow and a lower (validation) flow. The drift transport model made good predictions of the spatial distribution of invertebrate drift density throughout the pool at low flow after it was calibrated against observed drift density at the higher flow. The model correctly predicted that drift density would decline downstream and into the margins due to the process of settling dominating over entry from the stream bed, and that drift would be carried further downstream and laterally as flow increased. The foraging model made a reasonable prediction (6–7) of the numbers of 0.5 m adult brown trout observed (5) in the pool. It accurately predicted that trout should be distributed down the thalweg where net rate of energy intake (NREI) was highest, but when NREI was adjusted for depletion by feeding fish the predicted drift-feeding locations were more closely spaced (bunched) than observed fish locations. Our process-based modelling approach has important implications for improving biological realism in predictions of the response of drift-feeding fishes to flow change within the context of the IFIM.
ISSN:0304-3800
1872-7026
DOI:10.1016/j.ecolmodel.2007.04.032