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Salmon lice Lepeophtheirus salmonis infestation of sea trout Salmo trutta results in both additional marine mortality and behavioral changes which may contribute to sea trout population decline. For effective management of activities that increase exposure to salmon lice, such as salmon aquaculture, it is necessary to have a full understanding of how salmon lice may affect sea trout populations. An individual-based model (IBTRUTTA) was therefore developed to investigate the potential effects of salmon lice infestation on sea trout population abundance and dynamics based on data from the River Halselva and Altafjord system in northern Norway. This model allowed investigation of the effect of lice-induced mortality and also the compensatory salmonid behavioral mechanisms of premature return to freshwater, either persistent for overwintering or transitory after which sea trout could go back to sea. It was found that, in the absence of compensatory mechanisms, even low rates of lice infestation could lead to marked declines in sea trout abundance. Compensatory behavioral mechanisms had the potential to reduce these de - clines, but persistent premature return resulted in reduced body mass of returning adults. The shape of the stock-recruitment relationship was also shown to strongly affect how lice-induced mortality impacted the population. Individual-based model · Sea trout · Salmon lice · Lice-induced mortality · Premature return

For successful evaluation of the overall effects of salmon louse infestation on brown trout population dynamics, it is crucial to have a realistic understanding of how lice infestation distributions are generated and how they should be interpreted. Here, we simulated the potential effects of spatio-temporal variance in lice larvae densities, temporal variance in sea trout marine migration timing and spatial variance in marine habitat use on lice infestation distributions. We show that, when sampling populations with individual variation in marine behaviour, e.g. from post-smolts to veteran migrants, we must expect multi-modal mixture lice infestation distributions. Applying standard statistical distributions, such as the Poisson, negative binomial or zeroinflated distributions, can be too simplistic and give biased results. Temporary increases in salmon lice load in a given area may have inconsistent effects among individuals of a population and may be critical for vulnerable groups such as post-smolts, dependent on timing. For many analyses, it will be necessary to resolve the contributions from groups of fish with different lice infestation expectations due to spatio-temporal differences in habitat use within the overall mixture distribution. Another consequence is that different data sources, obtained by different methods or sampled at different locations and periods, must be expected to give different lice infestation distributions, even when sampling the same population. We also discuss additional factors that may complicate the interpretation of salmon lice infestation distributions on sea trout, such as lice-induced mortality, and behavioural changes, such as premature return to less saline water for delousing. Salmo trutta · Lepeophtheirus salmonis · Anadromy · Marine migration · Aquaculture · Negative binomial distribution · Zero-inflated models © The authors 2020. Open Access under Creative Commons by Attribution Licence. Use, distribution and reproduction are un - restricted. Authors and original publication must be credited.

The monogenean parasite Gyrodactylus salaris poses serious threats to many Atlantic salmon populations and presents many conservation and management questions/foci and challenges. It is therefore critical to identify potential vectors for infection. To test whether hybrids of native Atlantic salmon (Salmo salar) × brown trout (Salmo trutta) are suitable as reservoir hosts for G. salaris during winter, infected hybrid parr were released into a natural subarctic brook in the autumn. Six months later, 23.9% of the pit-tagged fish were recaptured. During the experimental period, the hybrids had a sixfold increase in mean intensity of G. salaris, while the prevalence decreased from 81% to 35%. There was high interindividual hybrid variability in susceptibility to infections. The maximum infrapopulation growth rate (0.018 day−1) of G. salaris throughout the winter was comparable to earlier laboratory experiments at similar temperatures. The results confirm that infrapopulations of G. salaris may reproduce on a hybrid population for several generations at low water temperatures (~1 °C). Wild salmon–trout hybrids are undoubtedly susceptible to G. salaris and represent an important reservoir host for the parasite independent of other co-occurring susceptible hosts. Consequently, these hybrids may pose a serious risk for G. salaris transmission to nearby, uninfected rivers by migratory individuals.

This work is partially supported by Research Councils UK We consider spatial point pattern data that have been observed repeatedly over a period of time in an inhomogeneous environment. Each spatial point pattern can be regarded as a “snapshot” of the underlying point process at a series of times. Thus, the number of points and corresponding locations of points differ for each snapshot. Each snapshot can be analyzed independently, but in many cases there may be little information in the data relating to model parameters, particularly parameters relating to the interaction between points. Thus, we develop an integrated approach, simultaneously analyzing all snapshots within a single robust and consistent analysis. We assume that sufficient time has passed between observation dates so that the spatial point patterns can be regarded as independent replicates, given spatial covariates. We develop a joint mixed effects Gibbs point process model for the replicates of spatial point patterns by considering environmental covariates in the analysis as fixed effects, to model the heterogeneous environment, with a random effects (or hierarchical) component to account for the different observation days for the intensity function. We demonstrate how the model can be fitted within a Bayesian framework using an auxiliary variable approach to deal with the issue of the random effects component. We apply the methods to a data set of musk oxen herds and demonstrate the increased precision of the parameter estimates when considering all available data within a single integrated analysis. Postprint

We consider spatial point patterns that have been observed repeatedly in the same area at several points in time. We take a maximum pseudolikelihood approach (besag :1976) to parameter estimation in the context of Gibbs processes (Stoyan et al., 1995, Illian et al., 2008). More specifically, we discuss pair-wise interaction processes where the conditional intensity has a log-linear form and extend existing models by expressing the intensity and the interaction terms in the pseudolikelihood as a sum of fixed and random effects, where the latter accounts for variation over time. We initially derive a Strauss process model with mixed effects. As this model is too simplistic in the given context, we further consider a more general model that allows for inter-group differences in intensity and interaction strength and has a more flexible interaction function. We apply the approximate Berman–Turner device (Baddeley and Turner, 2000) to a generalised linear mixed model with log link and Poisson outcome rather than a simple generalised linear model. Estimates are obtained using existing software for generalised linear mixed models based on penalised quasi-likelihood methods (Bresow and Clayton, 1993). The approach is applied to a data set detailing the spatial locations of different types of muskoxen herds in a fixed area in Greenland at different points in time within several years (Meltofte and Berg, 2004). Copyright © 2009 John Wiley & Sons, Ltd.

Climatic factors influence the interactions among trophic levels in an ecosystem in multiple ways. However, whereas most studies focus on single factors in isolation, mainly due to interrelation and correlation among drivers complicating interpretation and analyses, there are still only few studies on how multiple ecosystems respond to climate related factors at the same time. Here, we use a hierarchical Bayesian model with a bioenergetic predator-prey framework to study how different climatic factors affect trophic interactions and production in small Arctic lakes. Natural variation in temperature and catchment land-cover was used as a natural experiment to exemplify how interactions between and production of primary producers (phytoplankton) and grazers (zooplankton) are driven by direct (temperature) and indirect (catchment vegetation) factors, as well as the presence or absence of apex predators (fish). The results show that increased vegetation cover increased phytoplankton growth rate by mediating lake nutrient concentration. At the same time, increased temperature also increased grazing rates by zooplankton. Presence of fish increased zooplankton mortality rates, thus reducing grazing. The Arctic is currently experiencing an increase in both temperature and shrub vegetation cover due to climate change, a trend, which is likely to continue. Our results point towards a possible future general weakening of zooplankton grazing on phytoplankton and greening of arctic lakes with increasing temperatures. At the same time, the impact of the presence of an apex predator indicate considerable local variation in the response. This makes direction and strength of global change impacts difficult to forecast. © 2017 Finstad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Capturing components of the weather that drive environment-animal interactions is a perennial problem in ecology. Identifying biologically significant elements of weather conditions in sensible statistics suitable for analysis of life history variation and population dynamics is central. Meteorological variables such as temperature, precipitation, and wind modulate rates of heat loss in animals, but analysis of their effects on endothermic species is complicated by the fact that their influence on energy balance is not invariably linear, even across the thermoneutral range. Rather, the thermal load imposed by a given set of weather conditions is a function of organisms' metabolic requirement, which, crucially, may vary spontaneously both seasonally and across different life phases. We propose that the endogenous component of variation in metabolic demand introduces a temporal dimension and that, as a consequence, the specific effect of meteorological variables on energy balance and attendant life history parameters is a function of the timing of weather events with respect to the organism's metabolic rhythm(s). To test this, we examined how a spontaneous increase in metabolic demand influenced the effect of weather on early development in a large mammal. Specifically, we examined interaction between the exponential rise in the energy requirements of pregnancy and depth of snow, which restricts dams' access to forage, on the body mass of reindeer calves (Rangifer tarandus) at weaning. As expected, we detected a significant temporal component: the specific negative effect of snow on weaning mass was not constant, but increased across pregnancy. The life history response was therefore better predicted by interaction between the magnitude and the timing of weather events than by their magnitude alone. To our knowledge, this is the first demonstration of the influence of an endogenous metabolic dynamic on the impact of weather on a life history trait in a free-living mammal. Evaluating weather variables with respect to endogenous variation in metabolic demand adds biological realism and is likely to improve understanding of the influence of environmental variation on life history traits in many ecological contexts.

This is the pre-peer reviewed version of the following article: Hendrichsen, D.K., Kristoffersen, R., Gjelland, K.O., Knudsen, R., Kusterle, S., Rikardsen, A., ... Olstad, K. (2014). Transmission dynamics of the monogenean Gyrodactylus salaris under seminatural conditions. Journal of Fish Diseases. 38(6), 541-550, which has been published in final form at https://doi.org/10.1111/jfd.12263 . This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Tracking individual variation in the dynamics of parasite infections in wild populations is often complicated by lack of knowledge of the epidemiological history of hosts. Whereas the dynamics and development of Gyrodactylus salaris Malmberg, 1957, on Atlantic salmon, Salmo salar L., are known from laboratory studies, knowledge about infection development on individual wild fishes is currently sparse. In this study, the dynamics of an infection of G. salaris on individually marked Atlantic salmon parr was followed in a section of a natural stream. During the 6‐week experiment, the prevalence increased from 3.3 to 60.0%, with an average increase in intensity of 4.1% day−1. Survival analyses showed an initially high probability (93.6%) of staying uninfected by G. salaris, decreasing significantly to 37% after 6 weeks. The results showed that even at subarctic water temperatures and with an initially low risk of infection, the parasite spread rapidly in the Atlantic salmon population, with the capacity to reach 100% prevalence within a short summer season. The study thus track individual infection trajectories of Atlantic salmon living under near‐natural conditions, providing an integration of key population parameters from controlled experiments with the dynamics of the epizootic observed in free‐living living populations.

The nutritional state of animals is tightly linked to the ambient environment, and for northern ungulates the state strongly influences vital population demographics, such as pregnancy rates. Continuously growing tissues, such as hair, can be viewed as dietary records of animals over longer temporal scales. Using sequential data on nitrogen stable isotopes (δ15N) in muskox guard hairs from ten individuals in high arctic Northeast Greenland, we were able to reconstruct the dietary history of muskoxen over approximately 2.5 years with a high temporal resolution of app. 9 days. The dietary chronology included almost three full summer and winter periods. The diet showed strong intra- and inter-annual seasonality, and was significantly linked to changes in local environmental conditions (temperature and snow depth). The summer diets were highly similar across years, reflecting a graminoid-dominated diet. In contrast, winter diets were markedly different between years, a pattern apparently linked to snow conditions. Snow-rich winters had markedly higher δ15N values than snow-poor winters, indicating that muskoxen had limited access to forage, and relied more heavily on their body stores. Due to the close link between body stores and calf production in northern ungulates, the dietary winter signals could eventually serve as an indicator of calf production the following spring. Our study opens the field for further studies and longer chronologies to test such links. The method of sequential stable isotope analysis of guard hairs thus constitutes a promising candidate for population-level monitoring of animals in remote, arctic areas.

Background Statistical autoregressive analyses of direct and delayed density dependence are widespread in ecological research. The models suggest that changes in ecological factors affecting density dependence, like predation and landscape heterogeneity are directly portrayed in the first and second order autoregressive parameters, and the models are therefore used to decipher complex biological patterns. However, independent tests of model predictions are complicated by the inherent variability of natural populations, where differences in landscape structure, climate or species composition prevent controlled repeated analyses. To circumvent this problem, we applied second-order autoregressive time series analyses to data generated by a realistic agent-based computer model. The model simulated life history decisions of individual field voles under controlled variations in predator pressure and landscape fragmentation. Analyses were made on three levels: comparisons between predated and non-predated populations, between populations exposed to different types of predators and between populations experiencing different degrees of habitat fragmentation. Results The results are unambiguous: Changes in landscape fragmentation and the numerical response of predators are clearly portrayed in the statistical time series structure as predicted by the autoregressive model. Populations without predators displayed significantly stronger negative direct density dependence than did those exposed to predators, where direct density dependence was only moderately negative. The effects of predation versus no predation had an even stronger effect on the delayed density dependence of the simulated prey populations. In non-predated prey populations, the coefficients of delayed density dependence were distinctly positive, whereas they were negative in predated populations. Similarly, increasing the degree of fragmentation of optimal habitat available to the prey was accompanied with a shift in the delayed density dependence, from strongly negative to gradually becoming less negative. Conclusion We conclude that statistical second-order autoregressive time series analyses are capable of deciphering interactions within and across trophic levels and their effect on direct and delayed density dependence.

Publisher Summary This chapter focuses on the extent to which evolutionarily distinct species at different trophic levels respond to similar changes in climate. By using a broad spectrum of statistically and ecologically founded approaches, the chapter analyzes concurrently the influence of climatic variability and trophic interactions on the temporal population dynamics of species in the terrestrial vertebrate community at Zackenberg. The chapter describes and compares the population dynamics of three predator species, two herbivore species, and five wader species with respect to intraspecific density dependence, consumer–resource interactions, and direct as well as indirect intertrophic-level-mediated effects of varying snow cover. The results discussed in the chapter show that the temporal population dynamics of all three predators, both herbivores and three out of five wader species, displayed significant direct density dependence. Only two species displayed dynamics characterized by delayed density dependence. The direct effects of winter's snow were related to over-wintering strategies of resident and migrating species, respectively. The dynamics of all four resident species were significantly affected by variations in snow cover.

Publisher Summary This chapter describes and analyzes the predator–prey dynamics representative of the terrestrial ecosystem in Zackenbergdalen. By using comprehensive, temporally replicated data on the collared lemming and its predators, the chapter focuses on the predator–lemming dynamics embracing a period of 10 years. The chapter discusses the predator–lemming model, specifically modified to reflect the observed predator–lemming system in Zackenbergdalen. In spring and summer, predation pressure is heavy, and the lemming predators are capable of reducing the density of collared lemmings in most summers. In winter, however, stoat predation alone is insufficient to regulate the collared lemming population. These marked effects of predators are also visible in the behavior of collared lemmings in summer. Collared lemmings spend most of their time belowground, and aboveground, they divide their time almost equally between foraging and being vigilant. Climate not only contributes to the shaping of the seasonal dynamics of the lemming population but also affects the pattern of fluctuations. Earlier onset of winter has no impact on the periodicity, whereas the later the onset of winter the longer the periodicity of the lemming fluctuations, moving toward less stable population fluctuations.

Publisher Summary This chapter focuses on a 10‐year data series from Zackenberg on the trophic interactions between two characteristic arctic plant species, arctic willow Salix arctica and mountain avens Dryas octopetala , and three herbivore species covering the very scale of size present at Zackenberg, namely, the moth Sympistis zetterstedtii , the collared lemming Dicrostonyx groenlandicus and the musk ox Ovibos moschatus . Beside the impact of predation, climate in terms of timing and duration of the snow‐cover is one of the most important variables affecting the plant–herbivore system. Positive winter temperatures that create thawing events with ice horizons in the snow and icing on bare ground can have catastrophic effects on both vegetation and herbivores. Data from Zackenberg show that timing of snowmelt, the length of the growing season and summer temperature are the basic variables that determine the phenology of flowering and primary production upon which the herbivores depend, and snow may be the most important climatic factor affecting the different trophic levels and the interactions between them. Hence, the spatio‐temporal distribution of snow, as well as thawing events during winter, may have considerable effects on the herbivores by influencing their access to forage in winter.

Mobbing is a widespread anti-predator strategy in birds, and predators are generally expected to avoid mobbing. For example, observational studies suggest that the cryptic roosting behaviour of nocturnal predators, such as many owls, may be a strategy to limit mobbing. In this paper, we present the results of the first experimental study investigating to what degree roost exposure influences the risk of being mobbed, and the intensity of a mobbing incidence once initiated. To determine these factors, we used an experimental setup with taxidermic mounts of tawny owls Strix aluco in Grib Skov forest, Denmark. The risk of an owl being mobbed during a 50 min morning survey period increased with the exposure of its roosting position, from 24% when hidden to 85% when openly exposed. The corresponding increase in the afternoon was from 6% to 36%. This suggests that an owl may minimize the mobbing rate by reducing the encounter rate with potential mobbers through its choice of roost. Once initiated, the duration of the mobbing (a proxy for the presumed cost of being mobbed) was independent of the roosting position of the mounted owl, but was positively correlated with the number of birds in the mob.