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Predators can modulate disease transmission within prey populations by influencing prey demography and behavior. Predator-prey dynamics can involve multiple species in heterogeneous landscapes; however, studies of predation on disease transmission rarely consider the role of landscapes or the transmission among diverse prey species (i.e., spillover). We used high-resolution habitat and movement data to model spillover risk of the brainworm parasite ( Parelaphostrongylus tenuis ) between two prey species [white-tailed deer ( Odocoileus virginianus ) and moose ( Alces alces )], accounting for predator [gray wolf ( Canis lupus )] presence and landscape configuration. Results revealed that spring migratory movements of cervid hosts increased parasite spillover risk from deer to moose, an effect tempered by changes in elevation, land cover, and wolf presence. Wolves induced host-species segregation, a nonlethal mechanism that modulated disease emergence by reducing spatiotemporal overlap between infected and susceptible prey, showing that wildlife disease dynamics may change with landscape disturbance and the loss of large carnivores.

Wildlife can be exposed to antimicrobial-resistant bacteria (ARB) via multiple pathways. Spatial overlap with domestic animals is a prominent exposure pathway. However, most studies of wildlife-domestic animal interfaces have focused on livestock and little is known about the wildlife-companion animal interface. Here, we investigated the prevalence and phylogenetic relatedness of extended-spectrum cephalosporin-resistant (ESC-R) Escherichia coli from raccoons (Procyon lotor) and domestic dogs (Canis lupus familiaris) in the metropolitan area of Chicago, IL, USA. To assess the potential importance of spatial overlap with dogs, we explored whether raccoons sampled at public parks (i.e., parks where people and dogs could enter) differed in prevalence and phylogenetic relatedness of ESC-R E. coli to raccoons sampled at private parks (i.e., parks where people and dogs could not enter). Raccoons had a significantly higher prevalence of ESC-R E. coli (56.9%) than dogs (16.5%). However, the richness of ESC-R E. coli did not vary by host species. Further, core single-nucleotide polymorphism (SNP)-based phylogenetic analyses revealed that isolates did not cluster by host species, and in some cases displayed a high degree of similarity (i.e., differed by less than 20 core SNPs). Spatial overlap analyses revealed that ESC-R E. coli were more likely to be isolated from raccoons at public parks than raccoons at private parks, but only for parks located in suburban areas of Chicago, not urban areas. That said, ESC-R E. coli isolated from raccoons did not genetically cluster by park of origin. Our findings suggest that domestic dogs and urban/suburban raccoons can have a diverse range of ARB, some of which display a high degree of genetic relatedness (i.e., differ by less than 20 core SNPs). Given the differences in prevalence, domestic dogs are unlikely to be an important source of exposure for mesocarnivores in urbanized areas. IMPORTANCE Antimicrobial-resistant bacteria (ARB) have been detected in numerous wildlife species across the globe, which may have important implications for human and animal health. Wildlife can be exposed to ARB via numerous pathways, including via spatial overlap with domestic animals. However, the interface with domestic animals has mostly been explored for livestock and little is known about the interface between wild animals and companion animals. Our work suggests that urban and suburban wildlife can have similar ARB to local domestic dogs, but local dogs are unlikely to be a direct source of exposure for urban-adapted wildlife. This finding is important because it underscores the need to incorporate wildlife into antimicrobial resistance surveillance efforts, and to investigate whether certain urban wildlife species could act as additional epidemiological pathways of exposure for companion animals, and indirectly for humans.

[This corrects the article DOI: 10.1093/cz/zox047.]

Populations inhabiting the bioclimatic edges of a species' geographic range face an increasing amount of stress from alterations to their environment associated with climate change. Moose Alces alces are large-bodied ungulates that are sensitive to heat stress and have exhibited population declines and range contractions along their southern geographic extent. Using a hidden Markov model to analyze movement and accelerometer data, we assigned behaviors (rest, forage, or travel) to all locations of global positioning system-collared moose ( n =  13, moose-years = 19) living near the southern edge of the species' range in and around Voyageurs National Park, MN, USA. We assessed how moose behavior changed relative to weather, landscape, and the presence of predators. Moose significantly reduced travel and increased resting behaviors at ambient temperatures as low as 15 °C and 24 °C during the spring and summer, respectively. In general, moose behavior changed seasonally in association with distance to lakes and ponds. Moose used wetlands for travel throughout the year, rested in conifer forests, and foraged in shrublands. The influence of wolves Canis lupus varied among individual moose and season, but the largest influence was a reduction in travel during spring when near a wolf home range core, primarily by pregnant females. Our analysis goes beyond habitat selection to capture how moose alter their activities based on their environment. Our findings, along with climate change forecasts, suggest that moose in this area will be required to further alter their activity patterns and space use in order to find sufficient forage and avoid heat stress.

Disease models have provided conflicting evidence as to whether spatial heterogeneity promotes or impedes pathogen persistence. Moreover, there has been limited theoretical investigation into how animal movement behavior interacts with the spatial organization of resources (e.g., clustered, random, uniform) across a landscape to affect infectious disease dynamics. Importantly, spatial heterogeneity of resources can sometimes lead to nonlinear or counterintuitive outcomes depending on the host and pathogen system. There is a clear need to develop a general theoretical framework that could be used to create testable predictions for specific host-pathogen systems. Here, we develop an individual-based model integrated with movement ecology approaches to investigate how host movement behaviors interact with landscape heterogeneity (in the form of various levels of resource abundance and clustering) to affect pathogen dynamics. For most of the parameter space, our results support the counterintuitive idea that fragmentation promotes pathogen persistence, but this finding was largely dependent on perceptual range of the host, conspecific density, and recovery rate. For simulations with high conspecific density, slower recovery rates, and larger perceptual ranges, more complex disease dynamics emerged, and the most fragmented landscapes were not necessarily the most conducive to outbreaks or pathogen persistence. These results point to the importance of interactions between landscape structure, individual movement behavior, and pathogen transmission for predicting and understanding disease dynamics., Competing Interests: The authors declare no conflict of interest.

Invasion potential should be part of the evaluation of candidate species for any species introduction. However, estimating invasion risks remains a challenging problem, particularly in complex landscapes. Certain plant traits are generally considered to increase invasive potential and there is an understanding that landscapes influence invasions dynamics, but little research has been done to explore how those drivers of invasions interact. We evaluate the relative roles of, and potential interactions between, plant invasiveness traits and landscape characteristics on invasions with a case study using a model parameterized for the potentially invasive biomass crop, Miscanthus × giganteus. Using that model we simulate invasions on 1000 real landscapes to evaluate how landscape characteristics, including both composition and spatial structure, affect invasion outcomes. We conducted replicate simulations with differing strengths of plant invasiveness traits (dispersal ability, establishment ability, population growth rate, and the ability to utilize dispersal corridors) to evaluate how the importance of landscape characteristics for predicting invasion patterns changes depending on the invader details. Analysis of simulations showed that the presence of highly suitable habitat (e.g., grasslands) is generally the strongest determinant of invasion dynamics but that there are also more subtle interactions between landscapes and invader traits. These effects can also vary between different aspects of invasion dynamics (short vs. long time scales and population size vs. spatial extent). These results illustrate that invasions are complex emergent processes with multiple drivers and effective management needs to reflect the ecology of the species of interest and the particular goals or risks for which efforts need to be optimized., Competing Interests: The authors have declared that no competing interests exist.

Individual differences in contact rate can arise from host, group and landscape heterogeneity and can result in different patterns of spatial spread for diseases in wildlife populations with concomitant implications for disease control in wildlife of conservation concern, livestock and humans. While dynamic disease models can provide a better understanding of the drivers of spatial spread, the effects of landscape heterogeneity have only been modelled in a few well-studied wildlife systems such as rabies and bovine tuberculosis. Such spatial models tend to be either purely theoretical with intrinsic limiting assumptions or individual-based models that are often highly species- and system-specific, limiting the breadth of their utility. Our goal was to review studies that have utilized dynamic, spatial models to answer questions about pathogen transmission in wildlife and identify key gaps in the literature. We begin by providing an overview of the main types of dynamic, spatial models (e.g., metapopulation, network, lattice, cellular automata, individual-based and continuous-space) and their relation to each other. We investigate different types of ecological questions that these models have been used to explore: pathogen invasion dynamics and range expansion, spatial heterogeneity and pathogen persistence, the implications of management and intervention strategies and the role of evolution in host-pathogen dynamics. We reviewed 168 studies that consider pathogen transmission in free-ranging wildlife and classify them by the model type employed, the focal host-pathogen system, and their overall research themes and motivation. We observed a significant focus on mammalian hosts, a few well-studied or purely theoretical pathogen systems, and a lack of studies occurring at the wildlife-public health or wildlife-livestock interfaces. Finally, we discuss challenges and future directions in the context of unprecedented human-mediated environmental change. Spatial models may provide new insights into understanding, for example, how global warming and habitat disturbance contribute to disease maintenance and emergence. Moving forward, better integration of dynamic, spatial disease models with approaches from movement ecology, landscape genetics/genomics and ecoimmunology may provide new avenues for investigation and aid in the control of zoonotic and emerging infectious diseases., (© 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

The main objective of this study was to characterize spatial patterns of white-tailed deer (Odocoileus virginianus) movement related to bovine tuberculosis (bTB) transmission risk to cattle in north-western Minnesota. Twenty-one adult deer (16 females and 5 males) were captured during winter (January-March) 2011 in areas adjacent to where an outbreak (2005-2009) of bTB occurred in deer and cattle. Deer were fitted with GPS collars programmed to collect deer location information every 90 min over a 15-month period. The exact locations of cattle, cattle feeding areas, and stored forage that were available to collared deer were assessed seasonally. In total, 47% (n = 9) of collared deer survived to the end of the study. Causes of mortality included wolves (n = 6), hunters (n = 1) and unknown (n = 2); additionally, 2 deer were censored due to collar malfunctions. Our results indicated that 5 deer (25%) had home ranges that included 6 cattle farms (20%). Most (77%) of the deer visits occurred in areas where cattle were present, with most visits (60%) from 00:00 to 06:00. March to May revealed the most farm visitations by deer (37%). This study provided baseline information regarding cattle-deer interactions critical to transmission of bTB in this region and suggested that risk mitigation practices should be implemented to separate wildlife and domestic livestock when feasible., (© 2016 Blackwell Verlag GmbH.)

Managing intentional species introductions requires evaluating potential ecological risks. However, it is difficult to weigh costs and benefits when data about interactions between novel species and the communities they are introduced to are scarce. In anticipation of expanded cultivation of perennial biomass crops, we experimentally introduced Miscanthus sinensis and Miscanthus × giganteus (two non-native candidate biomass crops) into two different non-crop habitats (old field and flood-plain forest) to evaluate their establishment success and impact on ambient local communities. We followed these controlled introductions and the composition dynamics of the receiving communities over a 5-year period. Habitats differed widely in adult Miscanthus survival and reproduction potential between species, although seed persistence and seedling emergence were similar in the two biomass crops in both habitats. Few introductions survived in the floodplain forest habitat, and this mortality precluded analyses of their potential impacts there. In old field habitats, proportional survival ranged from 0.3 to 0.4, and plant survival and growth increased with age. However, there was no evidence of biomass crop species effects on community richness or evenness or strong impacts on the resident old field constituents across 5 years. These results suggest that Miscanthus species could establish outside of cultivated fields, but there will likely be a lag in any impacts on the receiving communities. Local North American invasions by M. sinensis and M. sacchariflorus display the potential for Miscanthus species to develop aggressively expanding populations. However, the weak short-term community-level impacts demonstrated in the current study indicate a clear management window in which eradicating species footholds is easily achieved, if they can be detected early enough. Diligent long-term monitoring, detection, and eradication plans are needed to successfully minimize harmful invasions from these biomass crops.

A hallmark assumption of traditional approaches to disease modelling is that individuals within a given population mix uniformly and at random. However, this assumption does not always hold true; contact heterogeneity or preferential associations can have a substantial impact on the duration, size, and dynamics of epidemics. Contact heterogeneity has been readily adopted in epidemiological studies of humans, but has been less studied in wildlife. While contact network studies are becoming more common for wildlife, their methodologies, fundamental assumptions, host species, and parasites vary widely. The goal of this article is to review how contact networks have been used to study macro- and microparasite transmission in wildlife. The review will: (i) explain why contact heterogeneity is relevant for wildlife populations; (ii) explore theoretical and applied questions that contact networks have been used to answer; (iii) give an overview of unresolved methodological issues; and (iv) suggest improvements and future directions for contact network studies in wildlife., (© 2015 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.)

Memory is among the most important and neglected forces that shapes animal movement patterns. Research on the movement-memory interface is crucial to understand how animals use spatial learning to navigate across space because memory-based navigation is directly linked to animals' space use and home range behaviour; however, because memory cannot be measured directly, it is difficult to account for. Here, we incorporated spatial memory into step selection functions (SSF) to understand how resource selection and spatial memory affect space use of feral hogs (Sus scrofa). We used Biased Random Bridge kernel estimates linked to residence time as a surrogate for memory and tested four conceptually different dynamic maps of spatial memory. We applied this memory-based SSF to a data set of hog relocations to evaluate the importance of land cover type, time of day and spatial memory on the animals' space use. Our approach has shown how the incorporation of spatial memory into animal movement models can improve estimates of habitat selection. Memory-based SSF provided a feasible way to gain insight into how animals use spatial learning to guide their movement decisions. We found that while hogs selected forested areas and water bodies and avoided grasslands during the day (primarily at noon), they had a strong tendency to select previously visited areas, mainly those held in recent memory. Beyond actively updating their memory with recent experiences, hogs were able to discriminate among spatial memories encoded at different circadian phases of their activity. Even though hogs are thought to have long memory retention, they likely relied on recent experiences because the local food resources are quickly depleted and slowly renewed, yielding an uncertain spatial distribution of resources., (© 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.)

The presence and movements of organisms both reflect and influence the distribution of ecological resources in space and time. The monitoring of animal movement by telemetry devices is being increasingly used to inform management of marine, freshwater and terrestrial ecosystems. Here, we brought together academics, and environmental managers to determine the extent of animal movement research in the Australasian region, and assess the opportunities and challenges in the sharing and reuse of these data. This working group was formed under the Australian Centre for Ecological Analysis and Synthesis (ACEAS), whose overall aim was to facilitate trans-organisational and transdisciplinary synthesis. We discovered that between 2000 and 2012 at least 501 peer-reviewed scientific papers were published that report animal location data collected by telemetry devices from within the Australasian region. Collectively, this involved the capture and electronic tagging of 12 656 animals. The majority of studies were undertaken to address specific management questions; rarely were these data used beyond their original intent. We estimate that approximately half (~500) of all animal telemetry projects undertaken remained unpublished, a similar proportion were not discoverable via online resources, and less than 8.8% of all animals tagged and tracked had their data stored in a discoverable and accessible manner. Animal telemetry data contain a wealth of information about how animals and species interact with each other and the landscapes they inhabit. These data are expensive and difficult to collect and can reduce survivorship of the tagged individuals, which implies an ethical obligation to make the data available to the scientific community. This is the first study to quantify the gap between telemetry devices placed on animals and findings/data published, and presents methods for improvement. Instigation of these strategies will enhance the cost-effectiveness of the research and maximise its impact on the management of natural resources., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Population fluctuations are generally attributed to the deterministic consequences of strong non-linear interactions among organisms, or the effects of random stochastic environmental variation superimposed upon the deterministic skeleton describing population change. Analysis of the population dynamics of the mussel Mytilus californianus taken in 16 plots over 18-years found no evidence that these processes explained observed strong fluctuations. Instead, population fluctuations arose because environmental stochasticity varied with abundance, which we term density-linked stochasticity. This phenomenon arises from biologically relevant mechanisms: recruitment variation and transmission of disturbance among neighboring individuals. Density-linked stochasticity is probably present frequently in populations, as it arises naturally from several general ecological processes, including stage structure variation with density, ontogenetic niche shifts, and local transmission of stochastic perturbations. More thoroughly characterizing and interpreting deviations from the mean behavior of a system will lead to better ecological prediction and improved insight into the important processes affecting populations and ecosystems.

Malaria parasite clones with the highest transmission rates to mosquitoes also tend to induce the most severe fitness consequences (or virulence) in mammals. This is in accord with expectations from the virulence-transmission trade-off hypothesis. However, the mechanisms underlying how different clones cause virulence are not well understood. Here, using data from eight murine malaria clones, we apply recently developed statistical methods to infer differences in clone characteristics, including induction of differing host-mediated changes in red blood cell (RBC) supply. Our results indicate that the within-host mechanisms underlying similar levels of virulence are variable and that killing of uninfected RBCs by immune effectors and/or retention of RBCs in the spleen may ultimately reduce virulence. Furthermore, the correlation between clone virulence and the degree of host-induced mortality of uninfected RBCs indicates that hosts increasingly restrict their RBC supply with increasing intrinsic virulence of the clone with which they are infected. Our results demonstrate a role for self-harm in self-defence for hosts and highlight the diversity and modes of virulence of malaria.

An important aspect of hearing and acoustic communication is the ability to discriminate differences in sound level. Little is known about level discrimination in anuran amphibians (frogs and toads), for which vocal communication in noisy social environments is often critical for reproduction. This study used two-choice phonotaxis tests to investigate the ability of females of Cope's gray treefrog (Hyla chrysoscelis) to discriminate between two advertisement calls differing only in sound pressure level by 2, 4, or 6 dB. Tests were conducted in the presence and absence of chorus-shaped noise (73 dB) and using two different ranges of signal levels (73-79 dB and 79-85 dB). Females discriminated between two signals differing by as little as 2-4 dB. In contrast to expectations based on the "near miss to Weber's law" in birds and mammals, level discrimination was slightly better at the lower range of signal amplitudes, a finding consistent with earlier studies of frogs and insects. Realistic levels of background noise simulating a breeding chorus had no discernable effect on discrimination at the sound level differences tested in this study. These results have important implications for studies of auditory masking and signaling behavior in the contexts of anuran hearing and sound communication.

Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal 'settling down', accomplished by including one or more focal points that attract the animal's movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Lévy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.

Patterns of resource selection by animal populations emerge as a result of the behavior of many individuals. Statistical models that describe these population-level patterns of habitat use can miss important interactions between individual animals and characteristics of their local environment; however, identifying these interactions is difficult. One approach to this problem is to incorporate models of individual movement into resource selection models. To do this, we propose a model for step selection functions (SSF) that is composed of a resource-independent movement kernel and a resource selection function (RSF). We show that standard case-control logistic regression may be used to fit the SSF; however, the sampling scheme used to generate control points (i.e., the definition of availability) must be accommodated. We used three sampling schemes to analyze simulated movement data and found that ignoring sampling and the resource-independent movement kernel yielded biased estimates of selection. The level of bias depended on the method used to generate control locations, the strength of selection, and the spatial scale of the resource map. Using empirical or parametric methods to sample control locations produced biased estimates under stronger selection; however, we show that the addition of a distance function to the analysis substantially reduced that bias. Assuming a uniform availability within a fixed buffer yielded strongly biased selection estimates that could be corrected by including the distance function but remained inefficient relative to the empirical and parametric sampling methods. As a case study, we used location data collected from elk in Yellowstone National Park, USA, to show that selection and bias may be temporally variable. Because under constant selection the amount of bias depends on the scale at which a resource is distributed in the landscape, we suggest that distance always be included as a covariate in SSF analyses. This approach to modeling resource selection is easily implemented using common statistical tools and promises to provide deeper insight into the movement ecology of animals.

Increasing global concentrations of atmospheric CO(2) are predicted to decrease ocean pH, with potentially severe impacts on marine food webs, but empirical data documenting ocean pH over time are limited. In a high-resolution dataset spanning 8 years, pH at a north-temperate coastal site declined with increasing atmospheric CO(2) levels and varied substantially in response to biological processes and physical conditions that fluctuate over multiple time scales. Applying a method to link environmental change to species dynamics via multispecies Markov chain models reveals strong links between in situ benthic species dynamics and variation in ocean pH, with calcareous species generally performing more poorly than noncalcareous species in years with low pH. The models project the long-term consequences of these dynamic changes, which predict substantial shifts in the species dominating the habitat as a consequence of both direct effects of reduced calcification and indirect effects arising from the web of species interactions. Our results indicate that pH decline is proceeding at a more rapid rate than previously predicted in some areas, and that this decline has ecological consequences for near shore benthic ecosystems.