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Background Numerical responses of ticks to changes in densities of their hosts can be complex and apparently unpredictable. Manipulations even of deterministic models can produce counterintuitive results, including tick populations that either rise or fall under increasing host densities, depending on initial conditions. Methods In this paper I use an established simulation model to demonstrate a wide range of numerical responses to different scenarios of host changes, and to examine the basic mechanisms that drive them. Results The rate and direction of change of host densities affects the extent to which questing tick numbers reflect those of their hosts. Numerical responses differ profoundly between dynamic tick-host systems and those allowed to reach equilibrium. Conclusions The key to understanding tick-host dynamics is to understand the difference between 'real' and 'visible' tick populations. An appreciation of the implications of this difference - and of the conditions that influence it - will benefit the effective interpretation of field data. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the dynamics of host-parasite systems globally. One key element in developing predictive models for these impacts is the life cycle of the parasite. It is, for example, commonly assumed that parasites with an indirect life cycle would be more sensitive to changing environmental conditions than parasites with a direct life cycle due to the greater chance that at least one of their obligate host species will go extinct. Here, we challenge this notion by contrasting parasitic nematodes with a direct life cycle against those with an indirect life cycle. Specifically, we suggest that behavioral thermoregulation by the intermediate host may buffer the larvae of indirectly transmitted parasites against temperature extremes, and hence climate warming. We term this the 'shelter effect'. Formalizing each life cycle in a comprehensive model reveals a fitness advantage for the direct life cycle over the indirect life cycle at low temperatures, but the shelter effect reverses this advantage at high temperatures. When examined for seasonal environments, the models suggest that climate warming may in some regions create a temporal niche in mid-summer that excludes parasites with a direct life cycle, but allows parasites with an indirect life cycle to persist. These patterns are amplified if parasite larvae are able to manipulate their intermediate host to increase ingestion probability by definite hosts. Furthermore, our results suggest that exploiting the benefits of host sheltering may have aided the evolution of indirect life cycles. Our modeling framework utilizes the Metabolic Theory of Ecology to synthesize the complexities of host behavioral thermoregulation and its impacts on various temperature-dependent parasite life history components in a single measure of fitness, R0. It allows quantitative predictions of climate change impacts, and is easily generalized to many host-parasite systems. [ABSTRACT FROM AUTHOR]

Background The risk posed by ticks as vectors of disease is typically assessed by blanket-drag sampling of host-seeking individuals. Comparisons of peak abundance between plots -- either in order to establish their relative risk or to identify environmental correlates -- are often carried out by sampling on one or two occasions during the period of assumed peak tick activity. Methods This paper simulates this practice by 're-sampling' from model datasets derived from an empirical field study. Re-sample dates for each plot are guided by either the previous year's peak at the plot, or the previous year's peak at a similar, nearby plot. Results from single, double and three-weekly sampling regimes are compared. Results Sampling on single dates within a two-month window of assumed peak activity has the potential to introduce profound errors; sampling on two dates (double sampling) offers greater precision, but three-weekly sampling is the least biased. Conclusions The common practice of sampling for the abundance of host-seeking ticks on single dates in each plot-year should be strenuously avoided; it is recommended that field acarologists employ regular sampling throughout the year at intervals no greater than three weeks, for a variety of epidemiological studies. [ABSTRACT FROM AUTHOR]

Seasonal variations in temperature, rainfall and resource availability are ubiquitous and can exert strong pressures on population dynamics. Infectious diseases provide some of the best-studied examples of the role of seasonality in shaping population fluctuations. In this paper, we review examples from human and wildlife disease systems to illustrate the challenges inherent in understanding the mechanisms and impacts of seasonal environmental drivers. Empirical evidence points to several biologically distinct mechanisms by which seasonality can impact host–pathogen interactions, including seasonal changes in host social behaviour and contact rates, variation in encounters with infective stages in the environment, annual pulses of host births and deaths and changes in host immune defences. Mathematical models and field observations show that the strength and mechanisms of seasonality can alter the spread and persistence of infectious diseases, and that population-level responses can range from simple annual cycles to more complex multiyear fluctuations. From an applied perspective, understanding the timing and causes of seasonality offers important insights into how parasite–host systems operate, how and when parasite control measures should be applied, and how disease risks will respond to anthropogenic climate change and altered patterns of seasonality. Finally, by focusing on well-studied examples of infectious diseases, we hope to highlight general insights that are relevant to other ecological interactions. [ABSTRACT FROM AUTHOR]

Molecular-based approaches might be misleading for assessing the ‘potential importance’ of possible reservoirs for parasites unless used in conjunction with population dynamics and ecological studies that provide an understanding of the linkages between the enzootic transmission cycle (in wild animals) and that in domestic animals. Better understanding of ecological constraints on Leishmania transmission is needed to assess fully the passage of the parasite between its sandfly vector and different mammalian host species. We use a straightforward mathematical framework to illustrate that misuse of association patterns, as guidance for implementation of control measures, can in fact increase the endemism of leishmaniasis. [Copyright &y& Elsevier]

Damage caused by introduced species results from the high population densities and large body sizes that they attain in their new location. Escape from the effects of natural enemies is a frequent explanation given for the success of introduced species. Because some parasites can reduce host density and decrease body size, an invader that leaves parasites behind and encounters few new parasites can experience a demographic release and become a pest. To test whether introduced species are less parasitized, we have compared the parasites of exotic species in their native and introduced ranges, using 26 host species of molluscs, crustaceans, fishes, birds, mammals, amphibians and reptiles. Here we report that the number of parasite species found in native populations is twice that found in exotic populations. In addition, introduced populations are less heavily parasitized (in terms of percentage infected) than are native populations. Reduced parasitization of introduced species has several causes, including reduced probability of the introduction of parasites with exotic species (or early extinction after host establishment), absence of other required hosts in the new location, and the host-specific limitations of native parasites adapting to new hosts. [ABSTRACT FROM AUTHOR]

Pathogen spillover from wildlife to domestic animals and humans, and the reverse, has caused significant epidemics and pandemics worldwide. Although pathogen emergence has been linked to anthropogenic land conversion, a general framework to disentangle underlying processes is lacking. We develop a multi-host model for pathogen transmission between species inhabiting intact and converted habitat. Interspecies contacts and host populations vary with the proportion of land converted; enabling us to quantify infection risk across a changing landscape. In a range of scenarios, the highest spillover risk occurs at intermediate levels of habitat loss, whereas the largest, but rarest, epidemics occur at extremes of land conversion. This framework provides insights into the mechanisms driving disease emergence and spillover during land conversion. The finding that the risk of spillover is highest at intermediate levels of habitat loss provides important guidance for conservation and public health policy. [ABSTRACT FROM AUTHOR]

To forecast marine disease outbreaks as oceans warm requires new environmental surveillance tools. We describe an iterative process for developing these tools that combines research, development and deployment for suitable systems. The first step is to identify candidate host–pathogen systems. The 24 candidate systems we identified include sponges, corals, oysters, crustaceans, sea stars, fishes and sea grasses (among others). To illustrate the other steps, we present a case study of epizootic shell disease (ESD) in the American lobster. Increasing prevalence of ESD is a contributing factor to lobster fishery collapse in southern New England (SNE), raising concerns that disease prevalence will increase in the northern Gulf of Maine under climate change. The lowest maximum bottom temperature associated with ESD prevalence in SNE is 12°C. Our seasonal outlook for 2015 and long-term projections show bottom temperatures greater than or equal to 12°C may occur in this and coming years in the coastal bays of Maine. The tools presented will allow managers to target efforts to monitor the effects of ESD on fishery sustainability and will be iteratively refined. The approach and case example highlight that temperature-based surveillance tools can inform research, monitoring and management of emerging and continuing marine disease threats. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the dynamics of infectious diseases around the globe. Predictive models remain elusive due to the complexity of host-parasite systems and insufficient data describing how environmental conditions affect various system components. Here, we link host-macroparasite models with the Metabolic Theory of Ecology, providing a mechanistic framework that allows integrating multiple nonlinear environmental effects to estimate parasite fitness under novel conditions. The models allow determining the fundamental thermal niche of a parasite, and thus, whether climate change leads to range contraction or may permit a range expansion. Applying the models to seasonal environments, and using an arctic nematode with an endotherm host for illustration, we show that climate warming can split a continuous spring-to-fall transmission season into two separate transmission seasons with altered timings. Although the models are strategic and most suitable to evaluate broad-scale patterns of climate change impacts, close correspondence between model predictions and empirical data indicates model applicability also at the species level. As the application of Metabolic Theory considerably aids the a priori estimation of model parameters, even in data-sparse systems, we suggest that the presented approach could provide a framework for understanding and predicting climatic impacts for many host-parasite systems worldwide. [ABSTRACT FROM AUTHOR]