Modelling the complete life-cycle of Atlantic salmon (Salmo salar L.) using a spatially explicit individual-based approach

How much habitat does a river need? A spatially-explicit population dynamics model to assess ratios of ontogenetical habitat needs

Restoration of spawning and juvenile habitats is often used to restore fish abundances in rivers, although often with unclear results. To study the effects of habitat limitations on the common barbel (Barbus barbus), a riverine litophilic cyprinid fish, an age-structured population model was developed. Using a Bayesian modeling approach, spawning and fry (0+ juvenile) habitat availability was integrated in the model in a spatially explicit way. Using Beverton-Holt and Ricker recruitment models, density dependence was incorporated in the spawning process and the recruitment of 0+ juveniles. Model parameters and their uncertainty ranges were obtained from reviewing the existing literature. The uncertainty of the processes was intrinsically accounted for by the inherently probabilistic nature of the Bayesian model. By testing various scenarios of habitat availabilities for the barbel, we hypothesize that improvement of the fish stock will be reached only at a well specified ratio of spawning to fry habitat. Model simulations revealed substantial abundance improvements at rather equal amounts of about 10% cover of both habitats, while even substantial improvements of either spawning or fry habitats only will result in little or no increase of abundance. Higher ratios of spawning to fry habitat were found to lower population recovery times. This work provides a tool that serves the assessment and comparison of river restoration scenarios as well as benchmarking rehabilitation targets in the planning phase. When targeting restoration of fish stocks, focusing only on one key life stage or process (such as spawning), without considering potential bottlenecks in other stages, can result in little to no improvement.

Integrating an individual-based model with approximate Bayesian computation to predict the invasion of a freshwater fish provides insights into dispersal and range expansion dynamics

Short-distance dispersal enables introduced alien species to colonise and invade local habitats following their initial introduction, but is often poorly understood for many freshwater taxa. Knowledge gaps in range expansion of alien species can be overcome using predictive approaches such as individual based models (IBMs), especially if predictions can be improved through fitting to empirical data, but this can be challenging for models having multiple parameters. We therefore estimated the parameters of a model implemented in the RangeShifter IBM platform by approximate Bayesian computation (ABC) in order to predict the further invasion of a lowland river (Great Ouse, England) by a small-bodied invasive fish (bitterling Rhodeus sericeus). Prior estimates for parameters were obtained from the literature and expert opinion. Model fitting was conducted using a time-series (1983 to 2018) of sampling data at fixed locations and revealed that for 5 of 11 model parameters, the posterior distributions differed markedly from prior assumptions. In particular, sub-adult maximum emigration probability was substantially higher in the posteriors than priors. Simulations of bitterling range expansion predicted that following detection in 1984, their early expansion involved a relatively high population growth rate that stabilised after 5 years. The pattern of bitterling patch occupancy was sigmoidal, with 20% of the catchment occupied after 20 years, increasing to 80% after 30 years. Predictions were then for 95% occupancy after 69 years. The development of this IBM thus successfully simulated the range expansion dynamics of this small-bodied invasive fish, with ABC improving the simulation precision. This combined methodology also highlighted that sub-adult dispersal was more likely to contribute to the rapid colonisation rate than expert opinion suggested. These results emphasise the importance of time-series data for refining IBM parameters generally and increasing our understanding of dispersal behaviour and range expansion dynamics specifically.

Modelling climate change effects on Atlantic salmon: Implications for mitigation in regulated rivers

Climate change is expected to alter future temperature and discharge regimes of rivers. These regimes have a strong influence on the life history of most aquatic river species, and are key variables controlling the growth and survival of Atlantic salmon. This study explores how the future abundance of Atlantic salmon may be influenced by climate-induced changes in water temperature and discharge in a regulated river, and investigates how negative impacts in the future can be mitigated by applying different regulated discharge regimes during critical periods for salmon survival. A spatially explicit individual-based model was used to predict juvenile Atlantic salmon population abundance in a regulated river under a range of future water temperature and discharge scenarios (derived from climate data predicted by the Hadley Centre's Global Climate Model (GCM) HadAm3H and the Max Plank Institute's GCM ECHAM4), which were then compared with populations predicted under control scenarios representing past conditions. Parr abundance decreased in all future scenarios compared to the control scenarios due to reduced wetted areas (with the effect depending on climate scenario, GCM, and GCM spatial domain). To examine the potential for mitigation of climate change-induced reductions in wetted area, simulations were run with specific minimum discharge regimes. An increase in abundance of both parr and smolt occurred with an increase in the limit of minimum permitted discharge for three of the four GCM/GCM spatial domains examined. This study shows that, in regulated rivers with upstream storage capacity, negative effects of climate change on Atlantic salmon populations can potentially be mitigated by release of water from reservoirs during critical periods for juvenile salmon.

Predicting the Potential for Natural Recovery of Atlantic Salmon (Salmo salar L.) Populations following the Introduction of Gyrodactylus salaris Malmberg, 1957 (Monogenea)

Gyrodactylus salaris (Monogenea, Platyhelminthes) is a notifiable freshwater pathogen responsible for causing catastrophic damage to wild Atlantic salmon stocks, most notably in Norway. In some strains of Baltic salmon (e.g., from the river Neva) however, the impact is greatly reduced due to some form of innate resistance that regulates parasite numbers, resulting in fewer host mortalities. Gyrodactylus salaris is known from 17 European states; its status in a further 35 states remains unknown; the UK, the Republic of Ireland and certain watersheds in Finland are free of the parasite. Thus, the parasite poses a serious threat if it emerges in Atlantic salmon rearing regions throughout Europe. At present, infections are generally controlled via extreme measures such as the treatment of entire river catchments with the biocide rotenone, in order to remove all hosts, before restocking with the original genetic stock. The use of rotenone in this way in EU countries is unlikely as it would be in contravention of the Water Framework Directive. Not only are such treatments economically and environmentally costly, they also eradicate the potential for any host/parasite evolutionary process to occur. Based on previous studies, UK salmon stocks have been shown to be highly susceptible to infection, analogous to Norwegian stocks. The present study investigates the impact of a G. salaris outbreak within a naïve salmon population in order to determine long-term consequences of infection and the likelihood of coexistence. Simulation of the salmon/ G. salaris system was carried out via a deterministic mathematical modelling approach to examine the dynamics of host-pathogen interactions. Results indicated that in order for highly susceptible Atlantic strains to evolve a resistance, both a moderate-strong deceleratingly costly trade-off on birth rate and a lower overall cost of the immune response are required. The present study provides insights into the potential long term impact of G. salaris if introduced into G. salaris-free territories and suggests that in the absence of external controls salmon populations are likely to recover to high densities nearing 90% of that observed pre-infection.

Modelling the effects of stranding on the Atlantic salmon population in the Dale River, Norway

Rapid dewatering in rivers as a consequence of hydropower operations may cause stranding of juvenile fish and have a negative impact on fish populations. We implemented stranding into an Atlantic salmon population model in order to evaluate long-term effects on the population in the Dale River, Western Norway. Furthermore, we assessed the sensitivity of the stranding model to dewatered area in comparison to biological parameters, and compared different methods for calculating wetted area, the main abiotic input parameter to the population model. Five scenarios were simulated dependent on fish life-stage, season and light level. Our simulation results showed largest negative effect on the population abundance for hydropeaking during winter daylight. Salmon smolt production had highest sensitivity to the stranding mortality of older juvenile fish, suggesting that stranding of fish at these life-stages is likely to have greater population impacts than that of earlier life-stages. Downstream retention effects on the ramping velocity were found to be negligible in the stranding model, but are suggested to be important in the context of mitigation measure design.

IBSEM: An Individual-Based Atlantic Salmon Population Model

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a ‘wild’ genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors.