A large-scale approach can help detect general processes driving the dynamics of brown trout populations in extensive areas (original) (raw)
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Spatial scale and degree of synchrony in brown trout (salmo trutta) population dynamics
Spatio-temporal variability of the physical conditions in streams is known to influence freshwater population dynamics. However, the complex relationship between these physical factors (mainly available habitat, water temperature, discharge, sediment transport) and the biological response is not yet clearly understood in either natural or regulated streams. In order to investigate this relationship, it is essential to understand how the influences of these physical factors differ in time and space. In the present study, we analyzed the spatio- emporal patterns of fluctuation in 31 brown trout populations spread across France, in both natural and regulated (i.e. by-passed sections downstream of hydroelectric water intakes) sites. This data is a result of annual fish monitoring surveys carried out continuously over a minimum of 5 years. Using statistical methods, we estimated the degree of synchrony among brown trout cohort densities (young-of-the-year, juveniles and adults) and evalu...
Canadian Journal of Fisheries and Aquatic Sciences, 2012
This study looks at the relative influence of water temperature and density dependence on the spatial variation in body size of 126 brown trout (Salmo trutta) cohorts from 12 Iberian rivers over a 12-year period. Mean cohort mass and length of age groups 0+ to 2+ varied significantly among sampling sites because of the concurrent effect of water temperature and density dependence. Density in suitable habitat had a limiting role that influenced potential maximum growth of cohorts, and water temperature differentiated these cohorts in two groups of sites with high and low potential maximum growth. Water temperature had a positive cumulative effect on body size of all age classes. However, body size of age-0 trout was nonlinearly influenced by short-term exposure to extreme water temperature. Thus, extremely high temperatures became a limiting factor and had deleterious effects on growth. There were intracohort and intercohort effects of density dependence throughout the life span, which were mainly due to the density in the available suitable habitat of trout of the same age or older. The present study supports the hypothesis that both density-dependent and density-independent processes are crucial for the understanding of population dynamics and that their relative importance varies across scales of space and time.
Oecologia, 2015
survival and growth patterns varied over space and time, and evidence of size-dependent survival was found in all but the smallest stream. At this stream, the probability of reaching larger sizes was lower compared to the other wider and deeper streams. Water temperature variables performed better in the modelling of the highest-altitude population, explaining over a 99 % of the variability in maturation transitions and survival of large fish. The relationships between body size, temperature and fitness components found in this study highlight the utility of multi-state approaches to investigate small-scale demographic processes in heterogeneous environments, and to provide reliable ecological knowledge for management purposes.
Scaling up population dynamics: integrating theory and data
Oecologia, 2005
How to scale up from local-scale interactions to regional-scale dynamics is a critical issue in field ecology. We show how to implement a systematic approach to the problem of scaling up, using scale transition theory. Scale transition theory shows that dynamics on larger spatial scales differ from predictions based on the local dynamics alone because of an interaction between localscale nonlinear dynamics and spatial variation in density or the environment. Based on this theory, a systematic approach to scaling up has four steps: (1) derive a model to translate the effects of local dynamics to the regional scale, and to identify key interactions between nonlinearity and spatial variation, (2) measure local-scale model parameters to determine nonlinearities at local scales, (3) measure spatial variation, and (4) combine nonlinearity and variation measures to obtain the scale transition. We illustrate the approach, with an example from benthic stream ecology of caddisflies living in riffles. By sampling from a simulated system, we show how collecting the appropriate data at local (riffle) scales to measure nonlinearities, combined with measures of spatial variation, leads to the correct inference for dynamics at the larger scale of the stream. The approach provides a way to investigate the mechanisms and consequences of changes in population dynamics with spatial scale using a relatively small amount of field data.
Nature Communications
Populations with homogeneous distributions have better bet-hedging capacity than more heterogeneously distributed populations. Both population dynamics and environmental factors may influence the spatial variability of a population, but clear empirical evidence of such causal linkages is sparse. Using 25-year fish survey data from the North Sea, we quantify causal effects of age structure, abundance, and environment on nine fish species. We use empirical dynamic modeling—an approach based on state-space reconstruction rather than correlation—to demonstrate causal effects of those factors on population spatial variability. The causal effects are detected in most study species, though direction and strength vary. Specifically, truncated age structure elevates population spatial variability. Warming and spatially heterogeneous temperatures may enhance population spatial variability, whereas abundance and large-scale environmental effects are inconclusive. Fishing may affect population ...
PISCATOR, an individual-based model to analyze the dynamics of lake fish communities
Ecological Modelling, 2002
Unraveling the mechanisms that drive dynamics of multi-species fish communities is notoriously difficult. Not only are the interactions between fish populations complex, but also the functional niche of individual animals changes profoundly as they grow, making variation in size within populations and even within cohorts highly important to consider. Not surprisingly, traditional aggregated populations models have proved limited in their capacity to describe the dynamics of interacting fish species, and individual-based models have become popular for modeling fish populations. Nonetheless, the majority of the individual-based models describes either a single species or focus entirely on a certain life stage. We present the individual-based model Piscator, which describes a multi-species fish community and demonstrates techniques to deal with the inherent complexity of such a model. We propose a novel procedure for calibration and analysis, in which the complexity of the model is increased step-by-step. We also illustrate the use of a special Monte-Carlo sensitivity analysis to identify clusters of parameters that have roughly the same effects on the model results. As an example, we use the model to analyze a fishery experiment in the Frisian Lakes (The Netherlands). Despite high bream catches (40-50 kg ha − 1 per year), it was observed that the seine fishery had unexpected little effect on the bream population. Our simulation results suggest that if one takes community feedbacks and climatic variability into account, this effect can be explained. The main cause was, besides a reduction of piscivory due to a simultaneous gill-net fishery, a coincidental strong year-class just before the fishery started. The strong development of this year-class could be explained by 3 subsequent warm years, whereas yearly variations in recruitment were less important. We also suggest that this relatively realistic model could play a role in ecological theory. It can be used to analyze the conditions for multi-year cycles and chaotic dynamics, phenomena that are usually predicted only from simple abstract models.
Population Dynamics and Environmental Variability
Integrative and Comparative Biology, 1969
SYNOPSIS. A model relating environmental variability and population variability is proposed and discussed. The model strongly emphasizes the importance o£ the different consequences of erratic and regular environmental variability, which are discussed from both the theoretical and empirical viewpoints. Data on population variability for six species in three communities (temperate intertidal, subtropical intertidal, and oligotrophic lake benthic) are presented and discussed in the context of the model. In general, environmental variability and population variability are strongly correlated. The impact of erratic environmental variability is apparent in one community.
Aquatic Living Resources, 1998
A model is used to explore whether local density-dependent recruitment relationships can be observed when considering a larger scale. A virtual population of spawners is tracked within an artificial environment composed of cells. Spawners can move from one cell to another on a spatial grid defined as a square lattice (lattice scale) made of 20 x 20 jointed hexagonal cells (local scale). Five spawner's behaviours are experimented successively: i) spawners stay in the same,cell to spawn; ii) they move randomly towards one of the neighbouring cells; iii) they move towards the least populated neighbouring cell; iv) they move towards the most populated neighbouring cell; and v) they move randomly towards a neighbouring cell and then move towards the most populated neighbouring cell. When the migration of spawners is achieved, spawners reproduce only once, recruitment takes place and then they disappear. The recruitment is an event which occurs at a local scale: at the scale of the cell. Using Ricker's stock-recruitment relationship, in each cell the number of recruits is a function of the spawners. Random migrations and migrations towards the less populated cell allow a homogeneous distribution of the spawners throughout the lattice. Whereas in the three other cases, this distribution is not homogenised. The homogenisation of the lattice allows synchrony between local populations and then a stock-recruitment relationship is observable at the lattice scale. Simulations show that local density-dependence is not always detectable when considering large spatial scale. This result strengthens the idea that the choice of spatial scale is essential when studying stockrecruitment relationship. O IfremerElsevier, Paris Spatial dynamics I stock-recruitment relationship I Ricker's relationship I density dependence I spawning behaviour I individual based model Résumé-Modélisation de dynamiques spatiales et de relations locales de densité-dépendance chez, des populations de pois