Short-term temperature fluctuations increase disease in a Daphnia-parasite infectious disease system.

Climate change has profound effects on infectious disease dynamics, yet the impacts of increased short-term temperature fluctuations on disease spread remain poorly understood. We empirically tested the theoretical prediction that short-term thermal fluctuations suppress endemic infection prevalence at the pathogen's thermal optimum. This prediction follows from a mechanistic disease transmission model analyzed using stochastic simulations of the model parameterized with thermal performance curves (TPCs) from metabolic scaling theory and using nonlinear averaging, which predicts ecological outcomes consistent with Jensen's inequality (i.e., reduced performance around concave-down portions of a thermal response curve). Experimental observations of replicated epidemics of the microparasite Ordospora colligata in Daphnia magna populations indicate that temperature variability had the opposite effect of our theoretical predictions and instead increase endemic infection prevalence. This positive effect of temperature variability is qualitatively consistent with a published hypothesis that parasites may acclimate more rapidly to fluctuating temperatures than their hosts; however, incorporating hypothetical effects of delayed host acclimation into the mechanistic transmission model did not fully account for the observed pattern. The experimental data indicate that shifts in the distribution of infection burden underlie the positive effect of temperature fluctuations on endemic prevalence. The increase in disease risk associated with climate fluctuations may therefore result from disease processes interacting across scales, particularly within-host dynamics, that are not captured by combining standard transmission models with metabolic scaling theory.

Experimental evidence of size-selective harvest and environmental stochasticity effects on population demography, fluctuations and non-linearity.

Theory and analyses of fisheries data sets indicate that harvesting can alter population structure and destabilise non-linear processes, which increases population fluctuations. We conducted a factorial experiment on the population dynamics of Daphnia magna in relation to size-selective harvesting and stochasticity of food supply. Harvesting and stochasticity treatments both increased population fluctuations. Timeseries analysis indicated that fluctuations in control populations were non-linear, and non-linearity increased substantially in response to harvesting. Both harvesting and stochasticity induced population juvenescence, but harvesting did so via the depletion of adults, whereas stochasticity increased the abundance of juveniles. A fitted fisheries model indicated that harvesting shifted populations towards higher reproductive rates and larger-magnitude damped oscillations that amplify demographic noise. These findings provide experimental evidence that harvesting increases the non-linearity of population fluctuations and that both harvesting and stochasticity increase population variability and juvenescence.

Applying stochastic and Bayesian integral projection modeling to amphibian population viability analysis.

Integral projection models (IPMs) can estimate the population dynamics of species for which both discrete life stages and continuous variables influence demographic rates. Stochastic IPMs for imperiled species, in turn, can facilitate population viability analyses (PVAs) to guide conservation decision-making. Biphasic amphibians are globally distributed, often highly imperiled, and ecologically well suited to the IPM approach. Herein, we present a stochastic size- and stage-structured IPM for a biphasic amphibian, the U.S. federally threatened California tiger salamander (CTS) (Ambystoma californiense). This Bayesian model reveals that CTS population dynamics show greatest elasticity to changes in juvenile and metamorph growth and that populations are likely to experience rapid growth at low density. We integrated this IPM with climatic drivers of CTS demography to develop a PVA and examined CTS extinction risk under the primary threats of habitat loss and climate change. The PVA indicated that long-term viability is possible with surprisingly high (20%-50%) terrestrial mortality but simultaneously identified likely minimum terrestrial buffer requirements of 600-1000 m while accounting for numerous parameter uncertainties through the Bayesian framework. These analyses underscore the value of stochastic and Bayesian IPMs for understanding both climate-dependent taxa and those with cryptic life histories (e.g., biphasic amphibians) in service of ecological discovery and biodiversity conservation. In addition to providing guidance for CTS recovery, the contributed IPM and PVA supply a framework for applying these tools to investigations of ecologically similar species.

Bias in self-reported parasite data from the salmon farming industry.

Many industries are required to monitor themselves in meeting regulatory policies intended to protect the environment. Self-reporting of environmental performance can place the cost of monitoring on companies rather than taxpayers, but there are obvious risks of bias, often addressed through external audits or inspections. Surprisingly, there have been relatively few empirical analyses of bias in industry self-reported data. Here, we test for bias in reporting of environmental compliance data using a unique data set from Canadian salmon farms, where companies monitor the number of parasitic sea lice on fish in open sea pens, in order to minimize impacts on wild fish in surrounding waters. We fit a hierarchical population-dynamics model to these sea-louse count data using a Bayesian approach. We found that the industry's monthly counts of two sea-louse species, Caligus clemensi and Lepeophtheirus salmonis, increased by a factor of 1.95 (95% credible interval: 1.57, 2.42) and 1.18 (1.06, 1.31), respectively, in months when counts were audited by the federal fisheries department. Consequently, industry sea-louse counts are less likely to trigger costly but mandated delousing treatments intended to avoid sea-louse epidemics in wild juvenile salmon. These results highlight the potential for combining external audits of industry self-reported data with analyses of their reporting to maintain compliance with regulations, achieve intended conservation goals, and build public confidence in the process.

Migratory hosts can maintain the high-dose/refuge effect in a structured host-parasite system: The case of sea lice and salmon.

Migration can reduce parasite burdens in migratory hosts, but it connects populations and can drive disease dynamics in domestic species. Farmed salmon are infested by sea louse parasites, often carried by migratory wild salmonids, resulting in a costly problem for industry and risk to wild populations when farms amplify louse numbers. Chemical treatment can control lice, but resistance has evolved in many salmon-farming regions. Resistance has, however, been slow to evolve in the north-east Pacific Ocean, where large wild-salmon populations harbour large sea louse populations. Using a mathematical model of host-macroparasite dynamics, we explored the roles of domestic, wild oceanic and connective migratory host populations in maintaining treatment susceptibility in associated sea lice. Our results show that a large wild salmon population, unexposed to direct infestation by lice from farms; high levels of on-farm treatment; and a healthy migratory host population are all critical to slowing or stopping the evolution of treatment resistance. Our results reproduce the "high-dose/refuge effect," from the agricultural literature, with the added requirement of a migratory host population to maintain treatment susceptibility. This work highlights the role that migratory hosts may play in shared wildlife/livestock disease, where evolution can occur in ecological time.

Environmental DNA from multiple pathogens is elevated near active Atlantic salmon farms.

The spread of infection from reservoir host populations is a key mechanism for disease emergence and extinction risk and is a management concern for salmon aquaculture and fisheries. Using a quantitative environmental DNA methodology, we assessed pathogen environmental DNA in relation to salmon farms in coastal British Columbia, Canada, by testing for 39 species of salmon pathogens (viral, bacterial, and eukaryotic) in 134 marine environmental samples at 58 salmon farm sites (both active and inactive) over 3 years. Environmental DNA from 22 pathogen species was detected 496 times and species varied in their occurrence among years and sites, likely reflecting variation in environmental factors, other native host species, and strength of association with domesticated Atlantic salmon. Overall, we found that the probability of detecting pathogen environmental DNA (eDNA) was 2.72 (95% CI: 1.48, 5.02) times higher at active versus inactive salmon farm sites and 1.76 (95% CI: 1.28, 2.42) times higher per standard deviation increase in domesticated Atlantic salmon eDNA concentration at a site. If the distribution of pathogen eDNA accurately reflects the distribution of viable pathogens, our findings suggest that salmon farms serve as a potential reservoir for a number of infectious agents; thereby elevating the risk of exposure for wild salmon and other fish species that share the marine environment.

Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model.

Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the metabolic theory of ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host-parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time and final infection prevalence in an experimentally warmed system of Daphnia and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE subfunctions can predict warming-induced disease emergence in data-rich systems-a critical step towards generalizing the approach to other systems.

Predators can influence the host-parasite dynamics of their prey via nonconsumptive effects.

Ecological communities are partly structured by indirect interactions, where one species can indirectly affect another by altering its interactions with a third species. In the absence of direct predation, nonconsumptive effects of predators on prey have important implications for subsequent community interactions. To better understand these interactions, we used a Daphnia-parasite-predator cue system to evaluate if predation risk affects Daphnia responses to a parasite. We investigated the effects of predator cues on two aspects of host-parasite interactions (susceptibility to infection and infection intensity), and whether or not these effects differed between sexes. Our results show that changes in response to predator cues caused an increase in the prevalence and intensity of parasite infections in female predator-exposed Daphnia. Importantly, the magnitude of infection risk depended on how long Daphnia were exposed to the cues. Additionally, heavily infected Daphnia that were constantly exposed to cues produced relatively more offspring. While males were ~5× less likely to become infected compared to females, we were unable to detect effects of predator cues on male Daphnia-parasite interactions. In sum, predators, prey, and their parasites can form complex subnetworks in food webs, necessitating a nuanced understanding of how nonconsumptive effects may mediate these interactions.

A unifying framework for the transient parasite dynamics of migratory hosts.

Migrations allow animals to track seasonal changes in resources, find mates, and avoid harsh climates, but these regular, long-distance movements also have implications for parasite dynamics and animal health. Migratory animals have been dubbed "superspreaders" of infection, but migration can also reduce parasite burdens within host populations via migratory escape from contaminated habitats and transmission hotspots, migratory recovery due to parasite mortality, and migratory culling of infected individuals. Here, we show that a single migratory host-macroparasite model can give rise to these different phenomena under different parametrizations, providing a unifying framework for a mechanistic understanding of the parasite dynamics of migratory animals. Importantly, our model includes the impact of parasite burden on host movement capability during migration, which can lead to "parasite-induced migratory stalling" due to a positive feedback between increasing parasite burdens and reduced movement. Our results provide general insight into the conditions leading to different health outcomes in migratory wildlife. Our approach lays the foundation for tactical models that can help understand, predict, and mitigate future changes of disease risk in migratory wildlife that may arise from shifting migratory patterns, loss of migratory behavior, or climate effects on parasite development, mortality, and transmission.

Predicting the Thermal and Allometric Dependencies of Disease Transmission via the Metabolic Theory of Ecology.

The metabolic theory of ecology (MTE) provides a general framework of allometric and thermal dependence that may be useful for predicting how climate change will affect disease spread. Using Daphnia magna and a microsporidian gut parasite, we conducted two experiments across a wide thermal range and fitted transmission models that utilize MTE submodels for transmission parameters. We decomposed transmission into contact rate and probability of infection and further decomposed probability of infection into a product of gut residence time (GRT) and per-parasite infection rate of gut cells. Contact rate generally increased with temperature and scaled positively with body size, whereas infection rate had a narrow hump-shaped thermal response and scaled negatively with body size. GRT increased with host size and was longest at extreme temperatures. GRT and infection rate inside the gut combined to create a 3.5 times higher probability of infection for the smallest relative to the largest individuals. Small temperature changes caused large differences in transmission. We also fit several alternative transmission models to data at individual temperatures. The more complex models-parasite antagonism or synergism and host heterogeneity-did not substantially improve the fit to the data. Our results show that transmission rate is the product of several distinct thermal and allometric functions that can be predicted continuously across temperature and host size using the MTE.

Matrix Models of Hierarchical Demography: Linking Group- and Population-Level Dynamics in Cooperative Breeders.

For highly social species, population dynamics depend on hierarchical demography that links local processes, group dynamics, and population growth. Here, we describe a stage-structured matrix model of hierarchical demography, which provides a framework for understanding social influences on population change. Our approach accounts for dispersal and affords insight into population dynamics at multiple scales. The method has close parallels to integral projection models but focuses on a discrete characteristic (group size). Using detailed long-term records for meerkats (Suricata suricatta), we apply our model to explore patterns of local density dependence and implications of group size for group and population growth. Taking into account dispersers, the model predicts a per capita growth rate for social groups that declines with group size. It predicts that larger social groups should produce a greater number of new breeding groups; thus, dominant breeding females (responsible for most reproduction) are likely to be more productive in larger groups. Considering the potential for future population growth, larger groups have the highest reproductive value, but per capita reproductive value is maximized for individuals in smaller groups. Across a plausible range of dispersal conditions, meerkats' long-run population growth rate is maximized when individuals form groups of intermediate size.

Oust the louse: leaping behaviour removes sea lice from wild juvenile sockeye salmon Oncorhynchus nerka.

We conducted a manipulative field experiment to determine whether the leaping behaviour of wild juvenile sockeye salmon Oncorhynchus nerka dislodges ectoparasitic sea lice Caligus clemensi and Lepeophtheirus salmonis by comparing sea-lice abundances between O. nerka juveniles prevented from leaping and juveniles allowed to leap at a natural frequency. Juvenile O. nerka allowed to leap had consistently fewer sea lice after the experiment than fish that were prevented from leaping. Combined with past research, these results imply potential costs due to parasitism and indicate that the leaping behaviour of juvenile O. nerka does, in fact, dislodge sea lice.

Collapse, Tipping Points, and Spatial Demographic Structure Arising from the Adopted Migrant Life History.

The roles of dispersal and recruitment have long been a focal point in ecology and conservation. The adopted migrant hypothesis proposes a life history in which social learning transmits migratory knowledge between generations of iteroparous fish. Specifically, juveniles disperse from the parental spawning site, encounter and recruit to a local adult population, and learn migration routes between spawning and foraging habitats by following older, experienced fish. Although the adopted migrant life history may apply to many species of pelagic marine fishes, there is scant theoretical or empirical work on the consequent population dynamics. We developed and analyzed a mathematical model of this life history in which the recruitment of juveniles depends on the relative abundance of the local populations and recruitment overlap, which measures the ease with which juveniles are recruited by a nonparental population. We demonstrate that the adopted migrant life history can maintain spatial demographic structure among local populations, that it can also predispose local populations to collapse when a tipping point is crossed, and that recovery after collapse is impaired by reduced recruitment at small local population sizes.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics.

The complexity of host-parasite interactions makes it difficult to predict how host-parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level.

Experimental evidence of a pathogen invasion threshold.

Host density thresholds to pathogen invasion separate regions of parameter space corresponding to endemic and disease-free states. The host density threshold is a central concept in theoretical epidemiology and a common target of human and wildlife disease control programmes, but there is mixed evidence supporting the existence of thresholds, especially in wildlife populations or for pathogens with complex transmission modes (e.g. environmental transmission). Here, we demonstrate the existence of a host density threshold for an environmentally transmitted pathogen by combining an epidemiological model with a microcosm experiment. Experimental epidemics consisted of replicate populations of naive crustacean zooplankton (Daphnia dentifera) hosts across a range of host densities (20-640 hosts l-1) that were exposed to an environmentally transmitted fungal pathogen (Metschnikowia bicuspidata). Epidemiological model simulations, parametrized independently of the experiment, qualitatively predicted experimental pathogen invasion thresholds. Variability in parameter estimates did not strongly influence outcomes, though systematic changes to key parameters have the potential to shift pathogen invasion thresholds. In summary, we provide one of the first clear experimental demonstrations of pathogen invasion thresholds in a replicated experimental system, and provide evidence that such thresholds may be predictable using independently constructed epidemiological models.

An asymmetric producer-scrounger game: body size and the social foraging behavior of coho salmon.

A tension between cooperation and conflict characterizes the behavioral dynamics of many social species. The foraging benefits of group living include increased efficiency and reduced need for vigilance, but social foraging can also encourage theft of captured prey from conspecifics. The payoffs of stealing prey from others (scrounging) versus capturing prey (producing) may depend not only on the frequency of each foraging strategy in the group but also on an individual's ability to steal. By observing the foraging behavior of juvenile coho salmon (Oncorhynchus kisutch), we found that, within a group, relatively smaller coho acted primarily as producers and took longer to handle prey, and were therefore more likely to be targeted by scroungers than relatively larger coho. Further, our observations suggest that the frequency of scrounging may be higher when groups contained individuals of different sizes. Based on these observations, we developed a model of phenotype-limited producer-scrounger dynamics, in which rates of stealing were structured by the relative size of producers and scroungers within the foraging group. Model simulations show that when the success of stealing is positively related to body size, relatively large predators should tend to be scroungers while smaller predators should be producers. Contrary to previous models, we also found that, under certain conditions, producer and scrounger strategies could coexist for both large and small phenotypes. Large scroungers tended to receive the highest payoff, suggesting that producer-scrounger dynamics may result in an uneven distribution of benefits among group members that-under the right conditions-could entrench social positions of dominance.

Marine mammal population decline linked to obscured by-catch.

Declines of marine megafauna due to fisheries by-catch are thought to be mitigated by exclusion devices that release nontarget species. However, exclusion devices may instead conceal negative effects associated with by-catch caused by fisheries (i.e., unobserved or discarded by-catch with low postrelease survival or reproduction). We show that the decline of the endangered New Zealand (NZ) sea lion (Phocarctos hookeri) is linked to latent levels of by-catch occurring in sub-Antarctic trawl fisheries. Exclusion devices have been used since 2001 but have not slowed or reversed population decline. However, 35% of the variability in NZ sea lion pup production is explained by latent by-catch, and the population would increase without this factor. Our results indicate that exclusion devices can obscure rather than alleviate fishery impacts on marine megafauna.

Study design and parameter estimability for spatial and temporal ecological models.

The statistical tools available to ecologists are becoming increasingly sophisticated, allowing more complex, mechanistic models to be fit to ecological data. Such models have the potential to provide new insights into the processes underlying ecological patterns, but the inferences made are limited by the information in the data. Statistical nonestimability of model parameters due to insufficient information in the data is a problem too-often ignored by ecologists employing complex models. Here, we show how a new statistical computing method called data cloning can be used to inform study design by assessing the estimability of parameters under different spatial and temporal scales of sampling. A case study of parasite transmission from farmed to wild salmon highlights that assessing the estimability of ecologically relevant parameters should be a key step when designing studies in which fitting complex mechanistic models is the end goal.

Sea-louse parasites on juvenile wild salmon in the Broughton Archipelago, British Columbia, Canada.

The global expansion of aquaculture has changed the structure of fish populations in coastal environments, with implications for disease dynamics. In Pacific Canada, farmed salmon act as reservoir hosts for parasites and pathogens, including sea lice (Lepeophtheirus salmonis and Caligus clemensi) that can transmit to migrating wild salmon. Assessing the impact of salmon farms on wild salmon requires regular monitoring of sea-louse infections on both farmed and wild fish. Since 2001, we have collected juvenile pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon annually at three sites in the Broughton Archipelago in British Columbia, Canada, during the annual juvenile salmon migration from fresh water to the open ocean. From sampled fish, we recorded counts of parasitic copepodid-, chalimus-, and motile-stage sea lice. We report louse abundances as well as supplementary observations of fish size, development, and health.