DENSITY-DEPENDENT GROWTH
; BROOK TROUT GROWTH
; JUVENILE ATLANTIC SALMON
; POPULATION VITAL-RATES
; STREAM FISH ECOLOGY
; LONG-TERM DATA
; BROWN TROUT
; WATER TEMPERATURE
; MACROINVERTEBRATE DRIFT
; TEMPORAL VARIATION
WOS学科分类:
Ecology
WOS研究方向:
Environmental Sciences & Ecology
英文摘要:
Growth is a fundamental ecological process of stream-dwelling salmonids which is strongly interrelated to critical life history events (emergence, mortality, sexual maturity, smolting, spawning). The ability to accurately model growth becomes critical when making population predictions over large temporal (multi-decadal) and spatial (meso) scales, e.g., investigating the effect of global change. Body length collection by removal sampling is a widely-used practice for monitoring fish populations over such large scales. Such data can be efficiently integrated into a Hierarchical Bayesian Model (HBM) and lead to interesting findings on fish dynamics. We illustrate this approach by presenting an integrated HBM of brown trout (Salmo trutta) growth, population dynamics, and removal sampling data collection processes using large temporal and spatial scales data (20 years; 48 sites placed along a 100 km latitudinal gradient). Growth and population dynamics are modelled by ordinary differential equations with parameters bound together in a hierarchical structure. The observation process is modelled with a combination of a Poisson error, a binomial error, and a mixture of Gaussian distributions. Absolute fit is measured using posterior predictive checks, those results indicate that our model fits the data well. Results indicate that growth rate is positively correlated to catchment area. This result corroborates those of other studies (laboratory, exploratory) that identified factors besides water temperature that are related to daily ration and have a significant effect on stream-dwelling salmonid growth at a large scale. Our study also illustrates the value of integrated HBM and electrofishing removal sampling data to study in situ fish populations over large scales.
1.Univ Toulouse, CNRS, INPT, EcoLab,UPS, Toulouse, France 2.Gest Ambiental Navarra SA, C Padre Adoain 219 Bajo, Pamplona 31013, Spain 3.Univ Toulouse, CNRS, IRD, GET,UPS, Toulouse, France 4.Gobierno Navarra, Dept Desarrollo Rural & Media Ambiente, C Gonzalez Tablas 9, Navarra 31005, Spain 5.Univ Victoria, Dept Biol, Victoria, BC V8W 3N5, Canada
Recommended Citation:
Laplanche, Christophe,Leunda, Pedro M.,Boithias, Laurie,et al. Advantages and insights from a hierarchical Bayesian growth and dynamics model based on salmonid electrofishing removal data[J]. ECOLOGICAL MODELLING,2019-01-01,392:8-21