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.

For some salmon populations, the individual and population effects of sea lice (Lepeophtheirus salmonis) transmission from sea cage salmon farms is probably mediated by predation, which is a primary natural source of mortality of juvenile salmon. We examined how sea lice infestation affects predation risk and mortality of juvenile pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon, and developed a mathematical model to assess the implications for population dynamics and conservation. A risk-taking experiment indicated that infected juvenile pink salmon accept a higher predation risk in order to obtain foraging opportunities. In a schooling experiment with juvenile chum salmon, infected individuals had increased nearest-neighbor distances and occupied peripheral positions in the school. Prey selection experiments with cutthroat trout (O. clarkii) predators indicated that infection reduces the ability of juvenile pink salmon to evade a predatory strike. Group predation experiments with coho salmon (O. kisutch) feeding on juvenile pink or chum salmon indicated that predators selectively consume infected prey. The experimental results indicate that lice may increase the rate of prey capture but not the handling time of a predator. Based on this result, we developed a mathematical model of sea lice and salmon population dynamics in which parasitism affects the attack rate in a type II functional response. Analysis of the model indicates that: (1) the estimated mortality of wild juvenile salmon due to sea lice infestation is probably higher than previously thought; (2) predation can cause a simultaneous decline in sea louse abundance on wild fish and salmon productivity that could mislead managers and regulators; and (3) compensatory mortality occurs in the saturation region of the type II functional response where prey are abundant because predators increase mortality of parasites but not overall predation rates. These findings indicate that predation is an important component of salmon-louse dynamics and has implications for estimating mortality, reducing infection, and developing conservation policy.

Effective disease management can benefit from mathematical models that identify drivers of epidemiological change and guide decision-making. This is well illustrated in the host-parasite system of sea lice and salmon, which has been modelled extensively due to the economic costs associated with sea louse infections on salmon farms and the conservation concerns associated with sea louse infections on wild salmon. Consequently, a rich modelling literature devoted to sea louse and salmon epidemiology has been developed. We provide a synthesis of the mathematical and statistical models that have been used to study the epidemiology of sea lice and salmon. These studies span both conceptual and tactical models to quantify the effects of infections on host populations and communities, describe and predict patterns of transmission and dispersal, and guide evidence-based management of wild and farmed salmon. As aquaculture production continues to increase, advances made in modelling sea louse and salmon epidemiology should inform the sustainable management of marine resources.

The resilience of coastal social-ecological systems may depend on adaptive responses to aquaculture disease outbreaks that can threaten wild and farm fish. A nine-year study of parasitic sea lice (Lepeophtheirus salmonis) and pink salmon (Oncorhynchus gorbuscha) from Pacific Canada indicates that adaptive changes in parasite management on salmon farms have yielded positive conservation outcomes. After four years of sea lice epizootics and wild salmon population decline, parasiticide application on salmon farms was adapted to the timing of wild salmon migrations. Winter treatment of farm fish with parasiticides, prior to the out-migration of wild juvenile salmon, has reduced epizootics of wild salmon without significantly increasing the annual number of treatments. Levels of parasites on wild juvenile salmon significantly influence the growth rate of affected salmon populations, suggesting that these changes in management have had positive outcomes for wild salmon populations. These adaptive changes have not occurred through formal adaptive management, but rather, through multi-stakeholder processes arising from a contentious scientific and public debate. Despite the apparent success of parasite control on salmon farms in the study region, there remain concerns about the long-term sustainability of this approach because of the unknown ecological effects of parasticides and the potential for parasite resistance to chemical treatments.

Muskoxen are increasingly exposed to multiple stressors that may impact their health and fitness. We measured stress hormones in their qiviut (wooly undercoat), and found differences across seasons, years and between sexes. Qiviut cortisol is a promising tool for guiding muskox conservation in a rapidly changing Arctic.

Effective wildlife management requires accurate and timely information on conservation status and trends, and knowledge of the factors driving population change. Reliable monitoring of wildlife population health, including disease, body condition, and population trends and demographics, is central to achieving this, but conventional scientific monitoring alone is often not sufficient. Combining different approaches and knowledge types can provide a more holistic understanding than conventional science alone and can bridge gaps in scientific monitoring in remote and sparsely populated areas. Inclusion of traditional ecological knowledge (TEK) is core to the wildlife co-management mandate of the Canadian territories and is usually included through consultation and engagement processes. We propose a status assessment framework that provides a systematic and transparent approach to including TEK, as well as local ecological knowledge (LEK), in the design, implementation, and interpretation of wildlife conservation status assessments. Drawing on a community-based monitoring program for muskoxen and caribou in northern Canada, we describe how scientific knowledge and TEK/LEK, documented through conventional monitoring, hunter-based sampling, or qualitative methods, can be brought together to inform indicators of wildlife health within our proposed assessment framework.

Fire is a major disturbance driving the dynamics of the world's savannas. Almost all fires are set by humans who are increasingly altering fire timing and frequency on every continent. The world's largest protected areas of savannas are found in monsoonal northern Australia. These include relatively intact, tall, open forests where traditional indigenous fire regimes have been largely replaced in the past half century by contemporary patterns with trees experiencing fire as often as three out of five years. Eucalypt canopy trees form the basic structure of these savannas and changes to the canopy due to fire regimes cascade to affect other plants and animals. In this study, we used data from nearly three decades of field studies on the effects of fire on individual trees to define eight life‐history stages and to calculate transition rates among stages. We developed a stage‐based matrix population model that explicitly considers how fire season and understory influence growth, survival, and recruitment for each life‐history stage. Long‐term population growth rates and transient population dynamics were calculated under five different fire regimes, each in two understory types, using both deterministic and stochastic simulations of seasonal timing of fires. We found that fire was necessary for long‐term persistence of eucalypt canopy tree populations but, under annual fires, most populations did not survive. Population persistence was highly dependent on fire regime (fire season and frequency) and understory type. A stochastic model tended to yield higher population growth rates than the deterministic model with regular, periodic fires, even under the same long‐term frequency of fires. Transient population dynamics over 100 yr also depended on fire regime and understory, with implications for savanna physiognomy and management. Model predictions were tested in an independent data set from a 21‐yr longitudinal field study in Kakadu National Park. This study is a novel and integrative contribution to our understanding of fire in savanna biomes regarding the potential for long‐term persistence and transient dynamics of savanna canopy tree populations. The model is relatively simple, generalizable, and adaptable for further investigations of the population dynamics of savanna trees under fire.

Conservation management of wild fish may include fish health management in sympatric populations of domesticated fish in aquaculture. We developed a mathematical model for the population dynamics of parasitic sea lice (Lepeophtheirus salmonis) on domesticated populations of Atlantic salmon (Salmo salar) in the Broughton Archipelago region of British Columbia. The model was fit to a seven-year dataset of monthly sea louse counts on farms in the area to estimate population growth rates in relation to abiotic factors (temperature and salinity), local host density (measured as cohort surface area), and the use of a parasiticide, emamectin benzoate, on farms. We then used the model to evaluate management scenarios in relation to policy guidelines that seek to keep motile louse abundance below an average three per farmed salmon during the March–June juvenile wild Pacific salmon (Oncorhynchus spp.) migration. Abiotic factors mediated the duration of effectiveness of parasiticide treatments, and results suggest treatment of farmed salmon conducted in January or early February minimized average louse abundance per farmed salmon during the juvenile wild salmon migration. Adapting the management of parasites on farmed salmon according to migrations of wild salmon may therefore provide a precautionary approach to conserving wild salmon populations in salmon farming regions.