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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Generational Spreading Speed and the Dynamics of Population Range Expansion.

Some of the most fundamental quantities in population ecology describe the growth and spread of populations. Population dynamics are often characterized by the annual rate of increase, λ, or the generational rate of increase, R0. Analyses involving R0 have deepened our understanding of disease dynamics and life-history complexities beyond that afforded by analysis of annual growth alone. While range expansion is quantified by the annual spreading speed, a spatial analog of λ, an R0-like expression for the rate of spread is missing. Using integrodifference models, we derive the appropriate generational spreading speed for populations with complex (stage-structured) life histories. The resulting measure, relevant to locations near the expanding edge of a (re)colonizing population, incorporates both local population growth and explicit spatial dispersal rather than solely growth across a population, as is the case for R0. The calculations for generational spreading speed are often simpler than those for annual spreading speed, and analytic or partial analytic solutions can yield insight into the processes that facilitate or slow a population's spatial spread. We analyze the spatial dynamics of green crabs, sea otters, and teasel as examples to demonstrate the flexibility of our methods and the intuitive insights that they afford.

On signals of phase transitions in salmon population dynamics.

Critical slowing down (CSD) reflects the decline in resilience of equilibria near a bifurcation and may reveal early warning signals (EWS) of ecological phase transitions. We studied CSD in the recruitment dynamics of 120 stocks of three Pacific salmon (Oncorhynchus spp.) species in relation to critical transitions in fishery models. Pink salmon (Oncorhynchus gorbuscha) exhibited increased variability and autocorrelation in populations that had a growth parameter, r, close to zero, consistent with EWS of extinction. However, models and data for sockeye salmon (Oncorhynchus nerka) indicate that portfolio effects from heterogeneity in age-at-maturity may obscure EWS. Chum salmon (Oncorhynchus keta) show intermediate results. The data do not reveal EWS of Ricker-type bifurcations that cause oscillations and chaos at high r. These results not only provide empirical support for CSD in some ecological systems, but also indicate that portfolio effects of age structure may conceal EWS of some critical transitions.

Can reduced predation offset negative effects of sea louse parasites on chum salmon?

The impact of parasites on hosts is invariably negative when considered in isolation, but may be complex and unexpected in nature. For example, if parasites make hosts less desirable to predators then gains from reduced predation may offset direct costs of being parasitized. We explore these ideas in the context of sea louse infestations on salmon. In Pacific Canada, sea lice can spread from farmed salmon to migrating juvenile wild salmon. Low numbers of sea lice can cause mortality of juvenile pink and chum salmon. For pink salmon, this has resulted in reduced productivity of river populations exposed to salmon farming. However, for chum salmon, we did not find an effect of sea louse infestations on productivity, despite high statistical power. Motivated by this unexpected result, we used a mathematical model to show how a parasite-induced shift in predation pressure from chum salmon to pink salmon could offset negative direct impacts of sea lice on chum salmon. This shift in predation is proposed to occur because predators show an innate preference for pink salmon prey. This preference may be more easily expressed when sea lice compromise juvenile salmon hosts, making them easier to catch. Our results indicate how the ecological context of host-parasite interactions may dampen, or even reverse, the expected impact of parasites on host populations.

Does social status within a dominance hierarchy mediate individual growth, residency and relocation?

The availability of food, and hence energy, is known to influence the abundance, habitat choice and growth of individuals. In contrast, there is a paucity of knowledge on how the interaction of energy supply and social status determines patterns of residency and movement. This study tests whether the presence of conspecifics and an individual's social status in relation to food supply influence the fitness and movement of a drift-feeding fish (Galaxias fasciatus). Using an information-theoretic approach (AIC), our analysis indicated that the most parsimonious model of fish movement among pools was one that included food supply, social rank and fish relative growth rate. Our results indicated that subordinate fish relocated more frequently compared to dominant fish, most likely as a consequence of intra-specific competition that limited the access of these smaller fish to resources and constrained their growth. Our results suggest that energy constraints may force individuals to explore new habitats in an effort to find more energetically profitable patches. We conclude that intra-specific competition mediated through the social hierarchy amongst closely interacting individuals plays a key role in determining individual growth, residency and relocation.

Effects of parasites from salmon farms on productivity of wild salmon.

The ecological risks of salmon aquaculture have motivated changes to management and policy designed to protect wild salmon populations and habitats in several countries. In Canada, much attention has focused on outbreaks of parasitic copepods, sea lice (Lepeophtheirus salmonis), on farmed and wild salmon in the Broughton Archipelago, British Columbia. Several recent studies have reached contradictory conclusions on whether the spread of lice from salmon farms affects the productivity of sympatric wild salmon populations. We analyzed recently available sea lice data on farms and spawner-recruit data for pink (Oncorhynchus gorbuscha) and coho (Oncorhynchus kisutch) salmon populations in the Broughton Archipelago and nearby regions where farms are not present. Our results show that sea lice abundance on farms is negatively associated with productivity of both pink and coho salmon in the Broughton Archipelago. These results reconcile the contradictory findings of previous studies and suggest that management and policy measures designed to protect wild salmon from sea lice should yield conservation and fishery benefits.