A review of ecological models for brown trout: towards a new demogenetic model

Abstract – Ecological models for stream fish range in scale from individual fish to entire populations. They have been used to assess habitat quality and to predict the demographic and genetic responses to management or disturbance. In this paper, we conduct the first comprehensive review and synthesis of the vast body of modelling literature on the brown trout, Salmo trutta L., with the aim of developing the framework for a demogenetic model, i.e., a model integrating both population dynamics and genetics. We use a bibliometric literature review to identify two main categories of models: population ecology (including population dynamics and population genetics) and population distribution (including habitat–hydraulic and spatial distribution). We assess how these models have previously been applied to stream fish, particularly brown trout, and how recent models have begun to integrate them to address two key management and conservation questions: (i) How can we predict fish population responses to management intervention? and (ii) How is the genetic structure of fish populations influenced by landscape characteristics? Because salmonid populations tend to show watershed scale variation in both demographic and genetic traits, we propose that models combining demographic, genetic and spatial data are promising tools for improving their management and conservation. We conclude with a framework for an individual‐based, spatially explicit demogenetic model that we will apply to stream‐dwelling brown trout populations in the near future.     

Modelling the oceanic habitats of two pelagic species using recreational fisheries data

Defining the oceanic habitats of migratory marine species is important for both single species and ecosystem‐based fisheries management, particularly when the distribution of these habitats vary temporally. This can be achieved using species distribution models that include physical environmental predictors. In the present study, species distribution models that describe the seasonal habitats of two pelagic fish (dolphinfish, Coryphaena hippurus and yellowtail kingfish, Seriola lalandi), are developed using 19 yr of presence‐only data from a recreational angler‐based catch‐and‐release fishing programme. A Poisson point process model within a generalized additive modelling framework was used to determine the species distributions off the east coast of Australia as a function of several oceanographic covariates. This modelling framework uses presence‐only data to determine the intensity of fish (fish km^?2), rather than a probability of fish presence. Sea surface temperature (SST), sea level anomaly, SST frontal index and eddy kinetic energy were significant environmental predictors for both dolphinfish and kingfish distributions. Models for both species indicate a greater fish intensity off the east Australian coast during summer and autumn in response to the regional oceanography, namely shelf incursions by the East Australian Current. This study provides a framework for using presence‐only recreational fisheries data to create species distribution models that can contribute to the future dynamic spatial management of pelagic fisheries.     

Where do you think you’re going? Accounting for ontogenetic and climate‐induced movement in spatially stratified integrated population assessment models

Understanding spatial population structure and biocomplexity is critical for determining a species’ resilience to environmental and anthropogenic perturbations. However, integrated population models (IPMs) used to develop management advice for harvested populations have been slow to incorporate spatial dynamics. Therefore, limited research has been devoted to understanding the reliability of movement parameter estimation in spatial population models, especially for spatially dynamic marine fish populations. We implemented a spatial simulation–estimation framework that emulated a generic marine fish metapopulation to explore the impact of ontogenetic movement and climate‐induced distributional shifts between two populations. The robustness of spatially stratified IPMs was explored across a range of movement parametrizations, including ignoring connectivity or estimating movement with various levels of complexity. Ignoring connectivity was detrimental to accurate estimation of population‐specific biomass, while implementing spatial IPMs with intermediate levels of complexity (e.g. estimating movement in two‐year and two‐age blocks) performed best when no a priori information about underlying movement was available. One‐way distributional shifts mimicking climate‐induced poleward migrations presented the greatest estimation difficulties, but the incorporation of auxiliary information on connectivity (e.g. tag‐recapture data) reduced bias. The continued development of spatially stratified modelling approaches should allow harvested resources to be better utilized without increased risk. Additionally, expanded collection and incorporation of unique spatially explicit data will enhance the robustness of IPMs in the future.     

A nonlinear,low data requirement model for producing spatially explicit fishery forecasts

Spatial variability can confound accurate estimates of catch per unit effort (CPUE), especially in highly migratory species. The incorporation of spatial structure into fishery stock assessment models should ultimately improve forecasts of stock biomass. Here, we describe a nonlinear time series model for producing spatially explicit forecasts of CPUE that does not require ancillary environmental or demographic data, or specification of a model functional form. We demonstrate this method using spatially resolved (1° × 1° cells) CPUE time series of North Pacific albacore in the California Current System. The spatial model is highly significant (P < 0.00001) and outperforms two spatial null models. We then create a spatial forecast map for years beyond the range of data. Such approaches can guide spatial management of resources and provide a complement to more data‐intensive, highly parameterized population dynamics and ecosystem models currently in use.     

Spatio‐temporal analyses of marine predator diets from data‐rich and data‐limited systems

Accounting for variation in prey mortality and predator metabolic potential arising from spatial variation in consumption is an important task in ecology and resource management. However, there is no statistical method for processing stomach content data that accounts for fine‐scale spatio‐temporal structure while expanding individual stomach samples to population‐level estimates of predation. Therefore, we developed an approach that fits a spatio‐temporal model to both prey‐biomass‐per‐predator‐biomass data (i.e. the ratio of prey biomass in stomachs to predator weight) and predator biomass survey data, to predict “predator‐expanded‐stomach‐contents” (PESCs). PESC estimates can be used to visualize either the annual landscape of PESCs (spatio‐temporal variation), or can be aggregated across space to calculate annual variation in diet proportions (variation among prey items and among years). We demonstrated our approach in two contrasting scenarios: a data‐rich situation involving eastern Bering Sea (EBS) large‐size walleye pollock (Gadus chalcogrammus, Gadidae) for 1992–2015; and a data‐limited situation involving West Florida Shelf red grouper (Epinephelus morio, Epinephelidae) for 2011–2015. Large walleye pollock PESC was predicted to be higher in very warm years on the Middle Shelf of the EBS, where food is abundant. Red grouper PESC was variable in north‐western Florida waters, presumably due to spatio‐temporal variation in harmful algal bloom severity. Our approach can be employed to parameterize or validate diverse ecosystem models, and can serve to address many fundamental ecological questions, such as providing an improved understanding of how climate‐driven changes in spatial overlap between predator and prey distributions might influence predation pressure.     

Indirect connectivity estimates of amphibian breeding wetlands from spatially explicit occupancy models

相似文献   

Using angling and electric fishing to estimate smallmouth bass abundance in a river

Estimating abundance is fundamental to effective fishery management but can be challenging in a river where spatial and temporal heterogeneity may preclude the consistent use of a single sampling gear and different gears have differing size selectivity and capture probabilities of fish. In this study, the number of smallmouth bass, Micropterus dolomieu Lacepède, was estimated based on mark–recapture data from angling and boat electric fishing in a 4.2‐km regulated section (mean width = 115 m) of the Broad River, South Carolina, USA. Closed‐population capture–mark–recapture models were fit in the Bayesian hierarchical modelling framework with an estimated number of 2,380 fish (95% credible interval: 1,578–3,693) over 200 mm TL, although simulations indicated that abundance would be slightly overestimated (<20%) when two gears selected for different individuals. Integrating two gear types into a mark–recapture study can provide a method for assessing abundance in spatially or temporally heterogeneous habitats.     

Population status and distribution of whitespotted conger (Conger myriaster) in Yellow Sea: An important migratory species along coastal China with limited data

Whitespotted conger (Conger myriaster) is a marine migratory species with important economic and ecological values in Northwestern Pacific. The population status and distribution of whitespotted conger may have changed in the eastern coastal water of China owing to the intensive fishing pressure and human activities in the past few decades. There have been miscellaneous concerns about its population trend and potential environment‐driven variations in spatiotemporal distribution. Delta‐generalized linear models, generalized linear mixed models, and a set of correlation analyses were performed to answer the above concerns, and a stratified random sampling‐designed bottom trawl survey from 2011 to 2017 in Haizhou Bay of the central Yellow Sea was conducted to collect samples. Our study suggested that whitespotted conger remained a relatively stable population status with slight fluctuations likely caused by climate variability during 2011–2017. The hierarchical generalized linear mixed models with spatial random effect performed better than the generalized linear model and the common generalized linear mixed models. Spatiotemporal differences of whitespotted conger were significantly associated with bottom water salinity, depth, sampling time, and space, which were probably mainly influenced by a combination of the Cold Water Mass, the Yellow Sea Warm Current, and the Yellow Sea Coastal Current. The predicted spatiotemporal distribution of whitespotted conger has a monthly variation matching its seasonable migration and an overall higher abundance in the deeper water than that in the neritic areas in Haizhou Bay.     

Spatial variation in body size and reproductive condition of subtidal mussels: Considerations for sustainable management

Population characteristics such as body size and reproductive condition are widely used by industry and resource managers as criteria for harvesting commercial species. Given the broad-scale approaches commonly adopted by managers to evaluate stocks, any spatial heterogeneity in the structure and functioning of those stocks may result in inaccurate assessments, interpretation and inappropriate management. Spatial heterogeneity in body size and reproductive condition has been shown in intertidal populations of Mytilus spp., but no assessment of subtidal structure has been made despite the importance of these populations as a mariculture resource. A spatially stratified sampling programme was used to test hypotheses of differences in bed structure depending on position within the bed. Commercial gears were used to harvest seed mussels and two condition indices were tested to identify a rapid accurate approach to evaluate reproductive condition for resource managers. Differences in the size and condition of mussels were dependent on spatial position within the population, with mussels exhibiting strong seasonal growth patterns. Edge-zone mussels showed both greater reproductive condition and body size than bed centre mussels. Reproductive condition also covaried with body size. Differences in spatial structure and function have the potential to confound stock assessments if appropriate sampling programmes are not utilised. Appropriate survey and reproductive condition assessment methods should be used to support subtidal stock persistence and optimal exploitation practices.     

Multiple metrics provide context for the distribution of a highly mobile fish predator,the blue catfish

Data sets with increased spatial and temporal resolution can help researchers and resource managers quantify representative distributional patterns of mobile sportfish. In this research, first, we illustrate patterns of sportfish distribution using individual (percent of population, residence time, number of movements) and combined distributional metrics. Second, we apply these metrics to one highly mobile fish species, the blue catfish (Ictalurus furcatus), across a range of spatial (whole reservoir, region, site) and temporal (year, month, diel period) scales. Specifically, we tracked 123 acoustically tagged blue catfish with a 20‐receiver array in Milford Reservoir, KS, USA. When we integrated metrics, four site‐specific distributional patterns emerged: (a) a large, active multi‐site fish aggregation, (b) localised site fidelity, (c) transitional sites and (d) rarely used locations. These patterns would not have been detected using a single metric as each measurement revealed a different piece of the distribution story. For example, if we had only quantified percent of population, we could identify fish location, but not whether individual fish spent time at a location or were just passing through. Our examination of multiple scales also provided a novel context for interpreting site‐specific patterns. As an illustration of this insight, using conventional approaches, we would have observed heterogeneity, but we would not have detected fish aggregations, in which individual fish either remained or repeatedly returned to a site. In summary, our results show the advantage of setting the entire ecosystem as the study boundary to integrate multiple responses using a spatially and temporally extensive data set.     

Spatial assessment of predator–prey relationships in the North Sea: the influence of abiotic habitat properties on the spatial overlap between 0‐group cod and grey gurnard

The understanding of spatio‐temporal dynamics of marine ecosystems is crucial for ecosystem‐based fisheries management and climate change impact assessments. We quantified temporal changes in the distribution of 0‐group cod (Gadus morhua) and grey gurnard (Eutriglia gurnardus), a primary predator of 0‐group cod, with the help of regression kriging and assessed the temporal dynamics of the related spatial predator–prey overlap of these two species at different spatial scales. We analysed the robustness of relationships among abiotic habitat properties (temperature, salinity and depth) and abundance. Small cod was mainly found in low salinity areas of the Skagerrak but larger year classes were able to expand their distribution area towards the central and northern North Sea. In contrast, grey gurnard was mainly found in waters with salinities above 33 and temperatures above 14°C. This species has expanded its high density areas in the central North Sea northward over the last two decades. Recruitment success of cod was negatively correlated to a Moran's I cross‐correlation index, a proxy for the degree of spatial overlap between both species. Strong cod year classes overlapped less with grey gurnard at the large and medium spatial scale. In general, the relationships between abiotic habitat properties and abundance showed an increased inter‐annual variability, which was likely caused by underlying factors not taken into account in the distribution models. Thus assemblage modeling approaches combining the strength of different model types should be considered in the future to predict potential distribution patterns under climate change scenarios.     

Spatially explicit fisheries simulation models for policy evaluation

This paper deals with the design of modelling tools suitable for investigating the consequences of alternative policies on the dynamics of resources and fisheries, such as the evaluation of marine protected areas (MPA). We first review the numerous models that have been developed for this purpose, and compare them from several standpoints: population modelling, exploitation modelling and management measure modelling. We then present a generic fisheries simulation model, Integration of Spatial Information for FISHeries simulation (ISIS‐Fish). This spatially explicit model allows quantitative policy screening for fisheries with mixed‐species harvests. It may be used to investigate the effects of combined management scenarios including a variety of policies: total allowable catch (TAC), licenses, gear restrictions, MPA, etc. Fisher's response to management may be accounted for by means of decision rules conditioned on population and exploitation parameters. An application to a simple example illustrates the relevance of this kind of tool for policy screening, particularly in the case of mixed fisheries. Finally, the reviewed models and ISIS‐Fish are discussed and confronted in the light of the underlying assumptions and model objectives. In the light of this discussion, we identify desirable features for fisheries simulation models aimed at policy evaluation, and particularly MPA evaluation.     

Fine‐scale habitat partitioning of Chilean and Peale's dolphins and their overlap with aquaculture

相似文献   

Environmental factors and megafauna spatio‐temporal co‐occurrence with purse‐seine fisheries

Tropical tuna purse‐seine fisheries spatially co‐occur with various megafauna species, such as whale sharks, dolphins and baleen whales in all oceans of the world. Here, we analyzed a 10‐year (2002–2011) dataset from logbooks of European tropical tuna purse‐seine vessels operating in the tropical Eastern Atlantic and Western Indian Oceans, with the aim of identifying the principle environmental variables under which such co‐occurrence appear. We applied a Delta‐model approach using Generalized Additive Models (GAM) and Boosted Regression Trees (BRT) models, accounting for spatial autocorrelation using a contiguity matrix based on a residuals autocovariate (RAC) approach. The variables that contributed most in the models were chlorophyll‐a concentration in the Atlantic Ocean, as well as depth and monsoon in the Indian Ocean. High co‐occurrence between whale sharks, baleen whales and tuna purse‐seine fisheries were mostly observed in productive areas during particular seasons. In light of the lack of a full coverage scientific observer on board program, the large, long‐term dataset obtained from logbooks of tuna purse‐seine vessels is highly important for identifying seasonal and spatial co‐occurrence between the distribution of fisheries and megafauna, and the underlying environmental variables. This study can help to design conservation management measures for megafauna species within the framework of spatial fishery management strategies.     

Seasonal variability of cephalopod populations: a spatio‐temporal approach in the Western Mediterranean Sea

Cephalopod populations show wide temporal fluctuations in abundance, which have usually been investigated at inter‐annual scales related to environmental variability. However, cephalopods are also strongly linked to seasonal environmental fluctuations owing to their short life cycles and single seasonal breeding. Therefore, population abundance critically depends on the success of breeding and recruitment from the previous year and the optimization of resources in a narrow period of favorable conditions. This adaptation of population dynamics is paramount in marked oligotrophic systems, such as the western Mediterranean Sea. We used monthly landings per unit effort (LPUE) to explore the spatio‐temporal variability in seasonal patterns of three cephalopod species (Illex coindetii, Eledone cirrhosa and Octopus vulgaris). Common trends across the study area were characterized for each species. In all cases, seasonal patterns were geographically aggregated in relation to differences in local environment (i.e., primary production and surface hydro‐climatology). Variability in the mean seasonal pattern over time was also investigated under contrasting environmental or population regimes. The mean seasonal trend was more pronounced in regimes of high‐population densities, suggesting a density‐dependent control that can modify the strength of the environmental forcing in the seasonal patterns. Our study also evidences a spatial synchrony in the seasonal fluctuations of LPUEs. Scales of synchrony ranged from 70 to 200 km, indicating a patchy‐aggregated spatial pattern as a part of complex population structures in the western Mediterranean. Improving our understanding of seasonal dynamics of cephalopods across temporal and spatial scales may lead to improved forecasts and management strategies.     

Understanding what controls the spawning distribution of North Sea whiting (Merlangius merlangus) using a multi‐model approach

The processes that control the spatial distribution of North Sea whiting (Merlangius merlangus) spawning adults are investigated using a statistical multi‐model approach. Models of external and internal controls on the population, such as environmental conditions, spatial constraints, present or past spatial distribution, and demographic state of the population, are evaluated, compared and ranked to select those that are the best able to predict the observed distribution of spawning adults. Model selection is greatly influenced by the selection method, either based on data fitting or prediction, as well as by the threshold value used to stop the selection. Model selection based on prediction tends to select simpler models than selection based on data fitting. The hypotheses underlying the selected models are inferred to play a significant role in controlling North Sea whiting spatial distribution. The multi‐model inference approach developed in this study enables comparison of several theoretical concepts and hypotheses and the results provide important clues on the processes involved in the control of the spatial distribution of whiting. We conclude that whiting has a high spatial fidelity to spawning site which can be linked to either geographical attachment or year‐to‐year persistence of the spatial distribution of the population. Environmental factors – temperature and salinity – appear to influence the geographical extent of spawning whiting distribution, whereas local abundance levels are primarily controlled by internal factors, i.e., population size and spatial segregation between ages.     

Reproductive resilience: a paradigm shift in understanding spawner‐recruit systems in exploited marine fish

A close relationship between adult abundance and stock productivity may not exist for many marine fish stocks, resulting in concern that the management goal of maximum sustainable yield is either inefficient or risky. Although reproductive success is tightly coupled with adult abundance and fecundity in many terrestrial animals, in exploited marine fish where and when fish spawn and consequent dispersal dynamics may have a greater impact. Here, we propose an eco‐evolutionary perspective, reproductive resilience, to understand connectivity and productivity in marine fish. Reproductive resilience is the capacity of a population to maintain the reproductive success needed to result in long‐term population stability despite disturbances. A stock's reproductive resilience is driven by the underlying traits in its spawner‐recruit system, selected for over evolutionary timescales, and the ecological context within which it is operating. Spawner‐recruit systems are species specific, have both density‐dependent and fitness feedback loops and are made up of fixed, behavioural and ecologically variable traits. They operate over multiple temporal, spatial and biological scales, with trait diversity affecting reproductive resilience at both the population and individual (i.e. portfolio) scales. Models of spawner‐recruit systems fall within three categories: (i) two‐dimensional models (i.e. spawner and recruit); (ii) process‐based biophysical dispersal models which integrate physical and environmental processes into understanding recruitment; and (iii) complex spatially explicit integrated life cycle models. We review these models and their underlying assumptions about reproductive success vs. our emerging mechanistic understanding. We conclude with practical guidelines for integrating reproductive resilience into assessments of population connectivity and stock productivity.