Variation in Juvenile Salmon Growth Opportunities Across a Shifting Habitat Mosaic

Historically, Chinook Salmon in the California Central Valley reared in the vast wetlands of the Sacramento–San Joaquin Delta. However, more than 95% of floodplain, riparian, and wetland habitats in the Delta have become degraded because of anthropogenic factors such as pollution, introduced species, water diversions, and levees. Despite pronounced habitat loss, previous work using otolith reconstructions has revealed that some juvenile salmon continue to successfully rear for extended periods in the Delta. However, the extent to which the Delta functions to promote salmon growth relative to other habitats remains unknown. In this study, we integrated otolith microstructure (daily increment count and width) and strontium isotope (87Sr/86Sr) records to fill this critical knowledge gap by comparing the growth of natural-origin fall-run Chinook Salmon from the American River that reared in the Delta with those that remained in their natal stream. Using generalized additive models, we compared daily otolith growth rates among rearing habitats (Delta vs. American River) and years (2014 to 2018), encompassing a range of hydrologic conditions. We found that juvenile Chinook Salmon grew faster in the Delta in some years (2016), but slower in the Delta during drought conditions (2014 to 2015). The habitat that featured faster growth rates varied within and among years, suggesting the importance of maintaining a habitat mosaic for juvenile salmonids, particularly in a dynamic environment such as the California Central Valley. Linking otolith chemistry with daily growth increments provides a valuable approach to explore the mechanisms governing interannual variability in growth across habitat types, and a useful tool to quantify the effects of large-scale restoration efforts on native fishes

Moving forward in circles: challenges and opportunities in modelling population cycles

Population cycling is a widespread phenomenon, observed across a multitude of taxa in both laboratory and natural conditions. Historically, the theory associated with population cycles was tightly linked to pairwise consumer–resource interactions and studied via deterministic models, but current empirical and theoretical research reveals a much richer basis for ecological cycles. Stochasticity and seasonality can modulate or create cyclic behaviour in non-intuitive ways, the high-dimensionality in ecological systems can profoundly influence cycling, and so can demographic structure and eco-evolutionary dynamics. An inclusive theory for population cycles, ranging from ecosystem-level to demographic modelling, grounded in observational or experimental data, is therefore necessary to better understand observed cyclical patterns. In turn, by gaining better insight into the drivers of population cycles, we can begin to understand the causes of cycle gain and loss, how biodiversity interacts with population cycling, and how to effectively manage wildly fluctuating populations, all of which are growing domains of ecological research

Why Plankton Modelers Should Reconsider Using Rectangular Hyperbolic (Michaelis-Menten, Monod) Descriptions of Predator-Prey Interactions

Rectangular hyperbolic type 2 (RHt2; Michaelis-Menten or Monod -like) functions are commonly used to describe predation kinetics in plankton models, either alone or together with a prey selectivity algorithm deploying the same half-saturation constant for all prey types referenced to external prey biomass abundance. We present an analysis that indicates that such descriptions are liable to give outputs that are not plausible according to encounter theory. This is especially so for multi-prey type applications or where changes are made to the maximum feeding rate during a simulation. The RHt2 approach also gives no or limited potential for descriptions of events such as true de-selection of prey, effects of turbulence on encounters, or changes in grazer motility with satiation. We present an alternative, which carries minimal parameterisation effort and computational cost, linking allometric algorithms relating prey abundance and encounter rates to a prey-selection function controlled by satiation. The resultant Satiation-Controlled-Encounter-Based (SCEB) function provides a flexible construct describing numeric predator-prey interactions with biomass-feedback control of grazing. The SCEB function includes an attack component similar to that in the Holling disk equation but SCEB differs in having only a single (satiation-based) handling constant and an explicit maximum grazing rate. We argue that there is no justification for continuing to deploy RHt2 functions to describe plankton predator-prey interactions

Représentation de la réponse fonctionnelle dans un modèle prédateur-proie : du chémostat à l'écosystème

Une des grandes problématiques en écologie est d’identifier les liens qui existent entre ce qui se passe au niveau de la physiologie et du comportement des individus et les propriétés émergentes qui apparaissent au niveau de la population et des écosystèmes dans leur globalité.Dans cette thèse, nous avons abordé cette problématique à travers la modélisation du phénomène de prédation, en nous intéressant plus particulièrement à la représentation mathématique de la réponse fonctionnelle. Cette fonction représente la quantité de proies consommées par prédateur et par unité de temps. Elle synthétiseau niveau de la population un ensemble de processus survenant à différentes échelles d’organisation. La modélisation du phénomène de prédation rencontre diverses limitations liées à la complexité de ce processus biologique, et il existe donc une forte incertitude sur la nature de la réponse fonctionnelle à utiliser.A travers l’étude d’un modèle prédateur-proie en chemostat d’une part, et l’utilisation de méthodes de changement d’échelle sur un modèle prédateur-proie en patchs d’autre part, nous avons cherché à déterminer les sources de variations dans la représentation de cette réponse.Tout d’abord, nous avons mis en évidence l’influence de la variabilité des données sur la paramétrisation de la réponse fonctionnelle ainsi que sur la robustesse des sorties du modèle. Une étude de sensibilité a également permis de montrer la forte sensibilité structurelle du modèle face à cette formulation, qui peut-être plus importante que face à des changements de paramètres.De plus, il apparait que la représentation mathématique de la réponse fonctionnelle dépend fortement de l’échelle d’observation considérée. En effet, la nature de la réponse peut être modifiée lorsque l’on passe de l’échelle d’une population à celle de la communauté.One of the major issues in ecology is to identify the links between what happens in terms of physiology and behavior of individuals and the emergent properties that appear at the population and ecosystems level. In this thesis, we addressed this problem through modeling of the phenomenon of predation, especially by focusing on the mathematical functional response representation. This function represents the amount of prey consumed by predator per unit time. It synthesizes at the population level a set processes occurring at different scales of organization. Modeling of the phenomenon of predation encounters various limitations related to the complexity of this biological process, and there is, therefore, considerable uncertainty aboutthe nature of the functional response to use.Through the study of a predator-prey model in chemostat on the one hand, and use of scaling methods in a patches predator-prey model on the other hand, we seek to determine sources of variations in therepresentation of that response.First, we demonstrated the influence of data variability on the parameterization of the functional response as well as the robustness of the model outputs. A sensitivity study has also demonstrated the high structural sensitivity of the model to the formulation of this response, which may be more important than to parameterchanges.In addition, it appears that the mathematical representation of the functional response depends strongly on the scale of observation considered. The nature of the response can, indeed, be modified when changing the scale from the population to the community level

Représentation de la réponse fonctionnelle dans un modèle prédateur-proie (du chémostat à l'écosystème)

Une des grandes problématiques en écologie est d identifier les liens qui existent entre ce qui se passe au niveau de la physiologie et du comportement des individus et les propriétés émergentes qui apparaissent au niveau de la population et des écosystèmes dans leur globalité.Dans cette thèse, nous avons abordé cette problématique à travers la modélisation du phénomène de prédation, en nous intéressant plus particulièrement à la représentation mathématique de la réponse fonctionnelle. Cette fonction représente la quantité de proies consommées par prédateur et par unité de temps. Elle synthétiseau niveau de la population un ensemble de processus survenant à différentes échelles d organisation. La modélisation du phénomène de prédation rencontre diverses limitations liées à la complexité de ce processus biologique, et il existe donc une forte incertitude sur la nature de la réponse fonctionnelle à utiliser.A travers l étude d un modèle prédateur-proie en chemostat d une part, et l utilisation de méthodes de changement d échelle sur un modèle prédateur-proie en patchs d autre part, nous avons cherché à déterminer les sources de variations dans la représentation de cette réponse.Tout d abord, nous avons mis en évidence l influence de la variabilité des données sur la paramétrisation de la réponse fonctionnelle ainsi que sur la robustesse des sorties du modèle. Une étude de sensibilité a également permis de montrer la forte sensibilité structurelle du modèle face à cette formulation, qui peut-être plus importante que face à des changements de paramètres.De plus, il apparait que la représentation mathématique de la réponse fonctionnelle dépend fortement de l échelle d observation considérée. En effet, la nature de la réponse peut être modifiée lorsque l on passe de l échelle d une population à celle de la communauté.One of the major issues in ecology is to identify the links between what happens in terms of physiology and behavior of individuals and the emergent properties that appear at the population and ecosystems level. In this thesis, we addressed this problem through modeling of the phenomenon of predation, especially by focusing on the mathematical functional response representation. This function represents the amount of prey consumed by predator per unit time. It synthesizes at the population level a set processes occurring at different scales of organization. Modeling of the phenomenon of predation encounters various limitations related to the complexity of this biological process, and there is, therefore, considerable uncertainty aboutthe nature of the functional response to use.Through the study of a predator-prey model in chemostat on the one hand, and use of scaling methods in a patches predator-prey model on the other hand, we seek to determine sources of variations in therepresentation of that response.First, we demonstrated the influence of data variability on the parameterization of the functional response as well as the robustness of the model outputs. A sensitivity study has also demonstrated the high structural sensitivity of the model to the formulation of this response, which may be more important than to parameterchanges.In addition, it appears that the mathematical representation of the functional response depends strongly on the scale of observation considered. The nature of the response can, indeed, be modified when changing the scale from the population to the community level.AIX-MARSEILLE2-Bib.electronique (130559901) / SudocSudocFranceF

Implementation of the zooplankton functional response in plankton models: State of the art, recent challenges and future directions

The conventional way of describing grazing in plankton models is based on a zooplankton functional response framework, according to which the consumption rate is computed as the product of a certain function of food (the functional response) and the density/biomass of herbivorous zooplankton. A large amount of literature on experimental feeding reports the existence of a zooplankton functional response in microcosms and small mesocosms, which goes a long way towards explaining the popularity of this framework both in mean-field (e.g. NPZD models) and spatially resolved models. On the other hand, the complex foraging behaviour of zooplankton (feeding cycles) as well as spatial heterogeneity of food and grazer distributions (plankton patchiness) across time and space scales raise questions as to the existence of a functional response of herbivores in vivo. In the current review, we discuss limitations of the 'classical' zooplankton functional response and consider possible ways to amend this framework to cope with the complexity of real planktonic ecosystems. Our general conclusion is that although the functional response of herbivores often does not exist in real ecosystems (especially in the form observed in the laboratory), this framework can be rather useful in modelling - but it does need some amendment which can be made based on various techniques of model reduction. We also show that the shape of the functional response depends on the spatial resolution ('frame') of the model. We argue that incorporating foraging behaviour and spatial heterogeneity in plankton models would not necessarily require the use of individual based modelling - an approach which is now becoming dominant in the literature. Finally, we list concrete future directions and challenges and emphasize the importance of a closer collaboration between plankton biologists and modellers in order to make further progress towards better descriptions of zooplankton grazing

Variation in Juvenile Salmon Growth Opportunities Across a Shifting Habitat Mosaic

Historically, Chinook Salmon in the California Central Valley reared in the vast wetlands of the Sacramento–San Joaquin Delta. However, more than 95% of floodplain, riparian, and wetland habitats in the Delta have become degraded because of anthropogenic factors such as pollution, introduced species, water diversions, and levees. Despite pronounced habitat loss, previous work using otolith reconstructions has revealed that some juvenile salmon continue to successfully rear for extended periods in the Delta. However, the extent to which the Delta functions to promote salmon growth relative to other habitats remains unknown. In this study, we integrated otolith microstructure (daily increment count and width) and strontium isotope (87Sr/86Sr) records to fill this critical knowledge gap by comparing the growth of natural-origin fall-run Chinook Salmon from the American River that reared in the Delta with those that remained in their natal stream. Using generalized additive models, we compared daily otolith growth rates among rearing habitats (Delta vs. American River) and years (2014 to 2018), encompassing a range of hydrologic conditions. We found that juvenile Chinook Salmon grew faster in the Delta in some years (2016), but slower in the Delta during drought conditions (2014 to 2015). The habitat that featured faster growth rates varied within and among years, suggesting the importance of maintaining a habitat mosaic for juvenile salmonids, particularly in a dynamic environment such as the California Central Valley. Linking otolith chemistry with daily growth increments provides a valuable approach to explore the mechanisms governing interannual variability in growth across habitat types, and a useful tool to quantify the effects of large-scale restoration efforts on native fishes

Using Life-Cycle Models to Identify Monitoring Gaps for Central Valley Spring-Run Chinook Salmon

Life cycle models (LCMs) provide a quantitative framework that allows evaluation of how management actions targeting specific life stages can have population-level impacts on a species. The LCM building process is also a powerful tool that can be used to identify data gaps existing in the knowledge of the target species, and that might strongly influence overall population dynamics. LCMs are particularly useful for species such as salmon that are highly migratory and use multiple aquatic ecosystems throughout their life. Furthermore, they are lacking for threatened Central Valley spring-run Chinook (Oncorhynchus tshawytscha; CVSC). Here, we developed a CVSC LCM to describe the dynamics of Mill, Deer and Butte Creek CVSC populations. We used model construction, calibration and a global sensitivity analysis to highlight important data gaps in the monitoring of those populations. In particular, we found strong model sensitivity and high uncertainty in various egg, juvenile and adult ocean life stages’ biological processes. We concluded that the current CVSC monitoring network is insufficient to support using a LCM to inform how future management actions (e.g., hydrology and habitat restoration) influence CVSC dynamics. We propose a series of monitoring recommendations, such as the development of an enhanced juvenile tracking monitoring program and the implementation of juvenile trapping efficiency methodology combined with genetic identification tools, to help fill highlighted data gaps. These additional data collection efforts will provide critical quantitative information about the status of this imperiled species at key life stages (e.g., CVSC juvenile abundance estimates), and create a more comprehensive monitoring framework fundamental for working on the recovery of the entire stock. Furthermore, additional data collection will strengthen the LCM parameterization and calibration process, and ultimately improve the model’s predictive performance

Study of a virus-bacteria interaction model in a chemostat : application of geometrical singular perturbation theory

This paper provides a mathematical analysis of a virus-marine bacteria interaction model. The model is a simplified case of the model published and used by Middelboe (Middelboe, M. 2000 Microb. Ecol. 40, 114-124). It takes account of the virus, the susceptible bacteria, the infected bacteria and the substrate in a chemostat. We show that the numerical values of the parameters given by Middelboe allow two different time scales to be considered. We then use the geometrical singular perturbation theory to study the model. We show that there are two invariant submanifolds of dimension two in the four-dimensional phase space and that these manifolds cross themselves on the boundary of the domain of biological relevance. We then perform a rescaling to understand the dynamics in the vicinity of the intersection of the manifolds. Our results are discussed in the marine ecological context

Using Life-Cycle Models to Identify Monitoring Gaps for Central Valley Spring-Run Chinook Salmon

Life cycle models (LCMs) provide a quantitative framework that allows evaluation of how management actions targeting specific life stages can have population-level impacts on a species. The LCM building process is also a powerful tool that can be used to identify data gaps existing in the knowledge of the target species, and that might strongly influence overall population dynamics. LCMs are particularly useful for species such as salmon that are highly migratory and use multiple aquatic ecosystems throughout their life. Furthermore, they are lacking for threatened Central Valley spring-run Chinook (Oncorhynchus tshawytscha; CVSC). Here, we developed a CVSC LCM to describe the dynamics of Mill, Deer and Butte Creek CVSC populations. We used model construction, calibration and a global sensitivity analysis to highlight important data gaps in the monitoring of those populations. In particular, we found strong model sensitivity and high uncertainty in various egg, juvenile and adult ocean life stages’ biological processes. We concluded that the current CVSC monitoring network is insufficient to support using a LCM to inform how future management actions (e.g., hydrology and habitat restoration) influence CVSC dynamics. We propose a series of monitoring recommendations, such as the development of an enhanced juvenile tracking monitoring program and the implementation of juvenile trapping efficiency methodology combined with genetic identification tools, to help fill highlighted data gaps. These additional data collection efforts will provide critical quantitative information about the status of this imperiled species at key life stages (e.g., CVSC juvenile abundance estimates), and create a more comprehensive monitoring framework fundamental for working on the recovery of the entire stock. Furthermore, additional data collection will strengthen the LCM parameterization and calibration process, and ultimately improve the model’s predictive performance