Biological control in a disturbed environment

Most ecological and epidemiological models describe systems with continuous uninterrupted interactions between populations. Many systems, though, have ecological disturbances, such as those associated with planting and harvesting of a seasonal crop. In this paper, we introduce host–parasite–hyperparasite systems as models of biological control in a disturbed environment, where the host–parasite interactions are discontinuous. One model is a parasite–hyperparasite system designed to capture the essence of biological control and the other is a host–parasite–hyperparasite system that incorporates many more features of the population dynamics. Two types of discontinuity are included in the models. One corresponds to a pulse of new parasites at harvest and the other reflects the discontinuous presence of the host due to planting and harvesting. Such discontinuities are characteristic of many ecosystems involving parasitism or other interactions with an annual host. The models are tested against data from an experiment investigating the persistent biological control of the fungal plant parasite of lettuce Sclerotinia minor by the fungal hyperparasite Sporidesmium sclerotivorum, over successive crops. Using a combination of mathematical analysis, model fitting and parameter estimation, the factors that contribute the observed persistence of the parasite are examined. Analytical results show that repeated planting and harvesting of the host allows the parasite to persist by maintaining a quantity of host tissue in the system on which the parasite can reproduce. When the host dynamics are not included explicitly in the model, we demonstrate that homogeneous mixing fails to predict the persistence of the parasite population, while incorporating spatial heterogeneity by allowing for heterogeneous mixing prevents fade-out. Including the host''s dynamics lessens the effect of heterogeneous mixing on persistence, though the predicted values for the parasite population are closer to the observed values. An alternative hypothesis for persistence involving a stepped change in rates of infection is also tested and model fitting is used to show that changes in some environmental conditions may contribute to parasite persistence. The importance of disturbances and periodic forcing in models for interacting populations is discussed.     

Population mixing promotes arms race host–parasite coevolution

The consequences of host–parasite coevolution are highly contingent on the qualitative coevolutionary dynamics: whether selection fluctuates (fluctuating selection dynamic; FSD), or is directional towards increasing infectivity/resistance (arms race dynamic; ARD). Both genetics and ecology can play an important role in determining whether coevolution follows FSD or ARD, but the ecological conditions under which FSD shifts to ARD, and vice versa, are not well understood. The degree of population mixing is thought to increase host exposure to parasites, hence selecting for greater resistance and infectivity ranges, and we hypothesize this promotes ARD. We tested this by coevolving bacteria and viruses in soil microcosms and found that population mixing shifted bacteria–virus coevolution from FSD to ARD. A simple theoretical model produced qualitatively similar results, showing that mechanisms that increase host exposure to parasites tend to push dynamics towards ARD. The shift from FSD to ARD with increased population mixing may help to explain variation in coevolutionary dynamics between different host–parasite systems, and more specifically the observed discrepancies between laboratory and field bacteria–virus coevolutionary studies.     

Stochastic environmental fluctuations drive epidemiology in experimental host–parasite metapopulations

Environmental fluctuations are important for parasite spread and persistence. However, the effects of the spatial and temporal structure of environmental fluctuations on host–parasite dynamics are not well understood. Temporal fluctuations can be random but positively autocorrelated, such that the environment is similar to the recent past (red noise), or random and uncorrelated with the past (white noise). We imposed red or white temporal temperature fluctuations on experimental metapopulations of Paramecium caudatum, experiencing an epidemic of the bacterial parasite Holospora undulata. Metapopulations (two subpopulations linked by migration) experienced fluctuations between stressful (5°C) and permissive (23°C) conditions following red or white temporal sequences. Spatial variation in temperature fluctuations was implemented by exposing subpopulations to the same (synchronous temperatures) or different (asynchronous temperatures) temporal sequences. Red noise, compared with white noise, enhanced parasite persistence. Despite this, red noise coupled with asynchronous temperatures allowed infected host populations to maintain sizes equivalent to uninfected populations. It is likely that this occurs because subpopulations in permissive conditions rescue declining subpopulations in stressful conditions. We show how patterns of temporal and spatial environmental fluctuations can impact parasite spread and host population abundance. We conclude that accurate prediction of parasite epidemics may require realistic models of environmental noise.     

Sharing detection heterogeneity information among species in community models of occupancy and abundance can strengthen inference

1. The estimation of abundance and distribution and factors governing patterns in these parameters is central to the field of ecology. The continued development of hierarchical models that best utilize available information to inform these processes is a key goal of quantitative ecologists. However, much remains to be learned about simultaneously modeling true abundance, presence, and trajectories of ecological communities.
2. Simultaneous modeling of the population dynamics of multiple species provides an interesting mechanism to examine patterns in community processes and, as we emphasize herein, to improve species‐specific estimates by leveraging detection information among species. Here, we demonstrate a simple but effective approach to share information about observation parameters among species in hierarchical community abundance and occupancy models, where we use shared random effects among species to account for spatiotemporal heterogeneity in detection probability.
3. We demonstrate the efficacy of our modeling approach using simulated abundance data, where we recover well our simulated parameters using N‐mixture models. Our approach substantially increases precision in estimates of abundance compared with models that do not share detection information among species. We then expand this model and apply it to repeated detection/non‐detection data collected on six species of tits (Paridae) breeding at 119 1 km² sampling sites across a P. montanus hybrid zone in northern Switzerland (2004–2020). We find strong impacts of forest cover and elevation on population persistence and colonization in all species. We also demonstrate evidence for interspecific competition on population persistence and colonization probabilities, where the presence of marsh tits reduces population persistence and colonization probability of sympatric willow tits, potentially decreasing gene flow among willow tit subspecies.
4. While conceptually simple, our results have important implications for the future modeling of population abundance, colonization, persistence, and trajectories in community frameworks. We suggest potential extensions of our modeling in this paper and discuss how leveraging data from multiple species can improve model performance and sharpen ecological inference.

     

Carry-over effects,sequential density dependence and the dynamics of populations in a seasonal environment

Most animal populations have distinct breeding and non-breeding periods, yet the implications of seasonality on population dynamics are not well understood. Here, we introduce an experimental model system to study the population dynamics of two important consequences of seasonality: sequential density dependence and carry-over effects (COEs). Using a replicated seasonal population of Drosophila, we placed individuals at four densities in the non-breeding season and then, among those that survived, placed them to breed at three different densities. We show that COEs arising from variation in non-breeding density negatively impacts individual performance by reducing per capita breeding output by 29–77%, implying that non-lethal COEs can have a strong influence on population abundance. We then parametrized a bi-seasonal population model from the experimental results, and show that both sequential density dependence and COEs can stabilize long-term population dynamics and that COEs can reduce population size at low intrinsic rates of growth. Our results have important implications for predicting the successful colonization of new habitats, and for understanding the long-term persistence of seasonal populations in a wide range of taxa, including migratory organisms.     

Sea lice and salmon population dynamics: effects of exposure time for migratory fish

The ecological impact of parasite transmission from fish farms is probably mediated by the migration of wild fishes, which determines the period of exposure to parasites. For Pacific salmon and the parasitic sea louse, Lepeophtheirus salmonis, analysis of the exposure period may resolve conflicting observations of epizootic mortality in field studies and parasite rejection in experiments. This is because exposure periods can differ by 2–3 orders of magnitude, ranging from months in the field to hours in experiments. We developed a mathematical model of salmon–louse population dynamics, parametrized by a study that monitored naturally infected juvenile salmon held in ocean enclosures. Analysis of replicated trials indicates that lice suffer high mortality, particularly during pre-adult stages. The model suggests louse populations rapidly decline following brief exposure of juvenile salmon, similar to laboratory study designs and data. However, when the exposure period lasts for several weeks, as occurs when juvenile salmon migrate past salmon farms, the model predicts that lice accumulate to abundances that can elevate salmon mortality and depress salmon populations. The duration of parasite exposure is probably critical to salmon–louse population dynamics, and should therefore be accommodated in coastal planning and management where fish farms are situated on wild fish migration routes.     

The performance of field sampling for parasite detection in a wild passerine

Parasites can impact the behavior of animals and alter the interplay with ecological factors in their environment. Studying the effects that parasites have on animals thus requires accurate estimates of infections in individuals. However, quantifying parasites can be challenging due to several factors. Laboratory techniques, physiological fluctuations, methodological constraints, and environmental influences can introduce measurement errors, in particular when screening individuals in the wild. These issues are pervasive in ecological studies where it is common to sample study subjects only once. Such factors should be carefully considered when choosing a sampling strategy, yet presently there is little guidance covering the major sources of error. In this study, we estimate the reliability and sensitivity of different sampling practices at detecting two internal parasites—Serratospiculoides amaculata and Isospora sp.—in a model organism, the great tit Parus major. We combine field and captive sampling to assess whether individual parasite infection status and load can be estimated from single field samples, using different laboratory techniques—McMaster and mini‐FLOTAC. We test whether they vary in their performance, and quantify how sample processing affects parasite detection rates. We found that single field samples had elevated rates of false negatives. By contrast, samples collected from captivity over 24 h were highly reliable (few false negatives) and accurate (repeatable in the intensity of infection). In terms of methods, we found that the McMaster technique provided more repeatable estimates than the mini‐FLOTAC for S. amaculata eggs, and both techniques were largely equally suitable for Isospora oocysts. Our study shows that field samples are likely to be unreliable in accurately detecting the presence of parasites and, in particular, for estimating parasite loads in songbirds. We highlight important considerations for those designing host–parasite studies in captive or wild systems giving guidance that can help select suitable methods, minimize biases, and acknowledge possible limitations.     

The epidemiological consequences of immune priming

Exposure to low doses of pathogens that do not result in the host becoming infectious may ‘prime’ the immune response and increase protection to subsequent challenge. There is increasing evidence that such immune priming is a widespread and important feature of invertebrate host–pathogen interactions. Immune priming clearly has implications for individual hosts but will also have population-level implications. We present a susceptible–primed–infectious model—in contrast to the classic susceptible–infectious–recovered framework—to investigate the impacts of immune priming on pathogen persistence and population stability. We describe impacts of immune priming on the epidemiology of the disease in both constant and seasonal environments. A key result is that immune priming may act to destabilize population dynamics. In particular, when the proportion of individuals becoming primed rather than infected is high, but this priming does not confer full immunity, the population may be strongly destabilized through the generation of limit cycles. We discuss the implications of our model both in the context of invertebrate immunity and more widely.     

Multi-Strain Infections and ‘Relapse’ of Leucocytozoon sabrazesi Gametocytes in Domestic Chickens in Southern China

Leucocytozoon parasites infect many species of avian hosts, including domestic chicken, and can inflict heavy economic loss to the poultry industry. Although the prevalence and distribution of two Leucocytozoon species (L. sabrazesi and L. caulleryi) have been reported in China previously, there are many questions related to the parasite infection that remain unanswered, including population diversity and transmission dynamics in domestic chickens. Here we surveyed chicken blood samples from seven sites in four provinces of China to identify Leucocytozoon infection, characterized parasite diversity within individual infected hosts and between sampling sites, and investigated the dynamics of gametocytemia in chickens over time. We found high infection rates in three of the seven sites. Clustering parasite sequences of the mitochondrial cytochrome oxidase III (coxIII) and cytochrome b (cytb) genes showed lack of grouping according to geographic origins and individual hosts carrying large numbers of L. sabrazesi strains. Monitoring gametocytemia in blood samples from infected chickens over time showed ‘relapse’ or persistence of low-level gametocytemia for 4–5 months, which could be explored as an in vivo model for testing drugs against liver stages of Apicomplexan parasites. This study provides important information on population diversity and transmission dynamics of L. sabrazesi and for disease control.     

Plasmodium vivax Diversity and Population Structure across Four Continents

Plasmodium vivax is the geographically most widespread human malaria parasite. To analyze patterns of microsatellite diversity and population structure across countries of different transmission intensity, genotyping data from 11 microsatellite markers was either generated or compiled from 841 isolates from four continents collected in 1999–2008. Diversity was highest in South-East Asia (mean allelic richness 10.0–12.8), intermediate in the South Pacific (8.1–9.9) Madagascar and Sudan (7.9–8.4), and lowest in South America and Central Asia (5.5–7.2). A reduced panel of only 3 markers was sufficient to identify approx. 90% of all haplotypes in South Pacific, African and SE-Asian populations, but only 60–80% in Latin American populations, suggesting that typing of 2–6 markers, depending on the level of endemicity, is sufficient for epidemiological studies. Clustering analysis showed distinct clusters in Peru and Brazil, but little sub-structuring was observed within Africa, SE-Asia or the South Pacific. Isolates from Uzbekistan were exceptional, as a near-clonal parasite population was observed that was clearly separated from all other populations (F _ST>0.2). Outside Central Asia F _ST values were highest (0.11–0.16) between South American and all other populations, and lowest (0.04–0.07) between populations from South-East Asia and the South Pacific. These comparisons between P. vivax populations from four continents indicated that not only transmission intensity, but also geographical isolation affect diversity and population structure. However, the high effective population size results in slow changes of these parameters. This persistency must be taken into account when assessing the impact of control programs on the genetic structure of parasite populations.     

Distributions of Hardy-Weinberg equilibrium test statistics

It is well established that test statistics and P-values derived from discrete data, such as genetic markers, are also discrete. In most genetic applications, the null distribution for a discrete test statistic is approximated with a continuous distribution, but this approximation may not be reasonable. In some cases using the continuous approximation for the expected null distribution may cause truly null test statistics to appear nonnull. We explore the implications of using continuous distributions to approximate the discrete distributions of Hardy–Weinberg equilibrium test statistics and P-values. We derive exact P-value distributions under the null and alternative hypotheses, enabling a more accurate analysis than is possible with continuous approximations. We apply these methods to biological data and find that using continuous distribution theory with exact tests may underestimate the extent of Hardy–Weinberg disequilibrium in a sample. The implications may be most important for the widespread use of whole-genome case–control association studies and Hardy–Weinberg equilibrium (HWE) testing for data quality control.     

Cross‐continental comparison of parasite communities in a wide‐ranging carnivore suggests associations with prey diversity and host density

1. Parasites are integral to ecosystem functioning yet often overlooked. Improved understanding of host–parasite associations is important, particularly for wide‐ranging species for which host range shifts and climate change could alter host–parasite interactions and their effects on ecosystem function.
2. Among the most widely distributed mammals with diverse diets, gray wolves (Canis lupus) host parasites that are transmitted among canids and via prey species. Wolf–parasite associations may therefore influence the population dynamics and ecological functions of both wolves and their prey. Our goal was to identify large‐scale processes that shape host–parasite interactions across populations, with the wolf as a model organism.
3. By compiling data from various studies, we examined the fecal prevalence of gastrointestinal parasites in six wolf populations from two continents in relation to wolf density, diet diversity, and other ecological conditions.
4. As expected, we found that the fecal prevalence of parasites transmitted directly to wolves via contact with other canids or their excreta was positively associated with wolf density. Contrary to our expectations, the fecal prevalence of parasites transmitted via prey was negatively associated with prey diversity. We also found that parasite communities reflected landscape characteristics and specific prey items available to wolves.
5. Several parasite taxa identified in this study, including hookworms and coccidian protozoans, can cause morbidity and mortality in canids, especially in pups, or in combination with other stressors. The density–prevalence relationship for parasites with simple life cycles may reflect a regulatory role of gastrointestinal parasites on wolf populations. Our result that fecal prevalence of parasites was lower in wolves with more diverse diets could provide insight into the mechanisms by which biodiversity may regulate disease. A diverse suite of predator–prey interactions could regulate the effects of parasitism on prey populations and mitigate the transmission of infectious agents, including zoonoses, spread via trophic interactions.

     

Heterogeneous Persister Cells Formation in Acinetobacter baumannii

Bacterial persistence is a feature that allows susceptible bacteria to survive extreme concentrations of antibiotics and it has been verified in a number of species, such as Escherichia coli, Pseudomonas aeruginosa, Staphylococcus spp., Mycobacterium spp. However, even though Acinetobacter baumannii is an important nosocomial pathogen, data regarding its persistence phenotype are still lacking. Therefore, the aim of this study was to evaluate the persistence phenotype in A. baumannii strains, as well as its variation among strains after treatment with polymyxin B and tobramycin. Stationary cultures of 37 polymyxin B-susceptible clinical strains of A. baumannii were analyzed for surviving cells after exposure to 15 µg/mL of polymyxin B for 6 h, by serial dilutions and colony counting. Among these, the 30 tobramycin-susceptible isolates also underwent tobramycin treatment at a concentration of 160 µg/mL and persister cells occurrence was evaluated equally. A high heterogeneity of persister cells formation patterns among isolates was observed. Polymyxin B-treated cultures presented persister cells corresponding from 0.0007% to 10.1% of the initial population and two isolates failed to produce detectable persister cells under this condition. A high variability could also be observed when cells were treated with tobramycin: the persister fraction corresponded to 0.0003%–11.84% of the pre-treatment population. Moreover, no correlation was found between persister subpopulations comparing both antibiotics among isolates, indicating that different mechanisms underlie the internal control of this phenotype. This is the first report of persister cells occurrence in A. baumannii. Our data suggest that distinct factors regulate the tolerance for unrelated antibiotics in this species, contrasting the multi-drug tolerance observed in other species (eg. dormancy-mediated tolerance). Supporting this observation, polymyxin B – an antibiotic that is believed to act on non-dividing cells as well – failed to eradicate persister cells in the majority of the isolates, possibly reflecting a disconnection between persistence and dormancy.     

Inbreeding within human Schistosoma mansoni: do host-specific factors shape the genetic composition of parasite populations?

The size, structure and distribution of host populations are key determinants of the genetic composition of parasite populations. Despite the evolutionary and epidemiological merits, there has been little consideration of how host heterogeneities affect the evolutionary trajectories of parasite populations. We assessed the genetic composition of natural populations of the parasite Schistosoma mansoni in northern Senegal. A total of 1346 parasites were collected from 14 snail and 57 human hosts within three villages and individually genotyped using nine microsatellite markers. Human host demographic parameters (age, gender and village of residence) and co-infection with Schistosoma haematobium were documented, and S. mansoni infection intensities were quantified. F-statistics and clustering analyses revealed a random distribution (panmixia) of parasite genetic variation among villages and hosts, confirming the concept of human hosts as ‘genetic mixing bowls'' for schistosomes. Host gender and village of residence did not show any association with parasite genetics. Host age, however, was significantly correlated with parasite inbreeding and heterozygosity, with children being more infected by related parasites than adults. The patterns may be explained by (1) genotype-dependent ‘concomitant immunity'' that leads to selective recruitment of genetically unrelated worms with host age, and/or (2) the ‘genetic mixing bowl'' hypothesis, where older hosts have been exposed to a wider variety of parasite strains than children. The present study suggests that host-specific factors may shape the genetic composition of schistosome populations, revealing important insights into host–parasite interactions within a natural system.     

Variation in parasite resistance of Arctic charr,Salvelinus alpinus,between and within sympatric morphs

Genetic variation in resistance against parasite infections is a predominant feature in host–parasite systems. However, mechanisms maintaining genetic polymorphism in resistance in natural host populations are generally poorly known. We explored whether differences in natural infection pressure between resource‐based morphs of Arctic charr (Salvelinus alpinus) have resulted in differentiation in resistance profiles. We experimentally exposed offspring of two morphs from Lake Þingvallavatn (Iceland), the pelagic planktivorous charr (“murta”) and the large benthivorous charr (“kuðungableikja”), to their common parasite, eye fluke Diplostomum baeri, infecting the eye humor. We found that there were no differences in resistance between the morphs, but clear differences among families within each morph. Moreover, we found suggestive evidence of resistance of offspring within families being positively correlated with the parasite load of the father, but not with that of the mother. Our results suggest that the inherited basis of parasite resistance in this system is likely to be related to variation among host individuals within each morph rather than ecological factors driving divergent resistance profiles at morph level. Overall, this may have implications for evolution of resistance through processes such as sexual selection.     

TLR4 and NKT Cell Synergy in Immunotherapy against Visceral Leishmaniasis

NKT cells play an important role in autoimmune diseases, tumor surveillance, and infectious diseases, providing in most cases protection against infection. NKT cells are reactive to CD1d presented glycolipid antigens. They can modulate immune responses by promoting the secretion of type 1, type 2, or immune regulatory cytokines. Pathogen-derived signals to dendritic cells mediated via Toll like Receptors (TLR) can be modulated by activated invariant Natural Killer T (iNKT) cells. The terminal β-(1–4)-galactose residues of glycans can modulate host responsiveness in a T helper type-1 direction via IFN-γ and TLRs. We have attempted to develop a defined immunotherapeutic, based on the cooperative action of a TLR ligand and iNKT cell using a mouse model of visceral leishmaniasis. We evaluated the anti-Leishmania immune responses and the protective efficacy of the β-(1–4)-galactose terminal NKT cell ligand glycosphingophospholipid (GSPL) antigen of L. donovani parasites. Our results suggest that TLR4 can function as an upstream sensor for GSPL and provoke intracellular inflammatory signaling necessary for parasite killing. Treatment with GSPL was able to induce a strong effective T cell response that contributed to effective control of acute parasite burden and led to undetectable parasite persistence in the infected animals. These studies for the first time demonstrate the interactions between a TLR ligand and iNKT cell activation in visceral leishmaniasis immunotherapeutic.     

Host-Seeking Behavior and Dispersal of Triatoma infestans,a Vector of Chagas Disease,under Semi-field Conditions

Chagas disease affects millions of people in Latin America. The control of this vector-borne disease focuses on halting transmission by reducing or eliminating insect vector populations. Most transmission of Trypanosoma cruzi, the causative agent of Chagas disease, involves insects living within or very close to households and feeding mostly on domestic animals. As animal hosts can be intermittently present it is important to understand how host availability can modify transmission risk to humans and to characterize the host-seeking dispersal of triatomine vectors on a very fine scale. We used a semi-field system with motion-detection cameras to characterize the dispersal of Triatoma infestans, and compare the behavior of vector populations in the constant presence of hosts (guinea pigs), and after the removal of the hosts. The emigration rate – net insect population decline in original refuge – following host removal was on average 19.7% of insects per 10 days compared to 10.2% in constant host populations (p = 0.029). However, dispersal of T. infestans occurred in both directions, towards and away from the initial location of the hosts. The majority of insects that moved towards the original location of guinea pigs remained there for 4 weeks. Oviposition and mortality were observed and analyzed in the context of insect dispersal, but only mortality was higher in the group where animal hosts were removed (p-value <0.01). We discuss different survival strategies associated with the observed behavior and its implications for vector control. Removing domestic animals in infested areas increases vector dispersal from the first day of host removal. The implications of these patterns of vector dispersal in a field setting are not yet known but could result in movement towards human rooms.     

Movement can mediate temporal mismatches between resource availability and biological events in host–pathogen interactions

Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species’ populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host–pathogen systems. We adapted an established individual‐based model of host–pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host''s explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life‐history events affect host–pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts’ biological events. However, a temporal mismatch reduced host–pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat‐dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host–pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.     

Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range

1. Estimating the impacts of anthropogenic disturbances requires an understanding of the habitat‐use patterns of individuals within a population. This is especially the case when disturbances are localized within a population''s spatial range, as variation in habitat use within a population can drastically alter the distribution of impacts.
2. Here, we illustrate the potential for multilevel binomial models to generate spatial networks from capture–recapture data, a common data source used in wildlife studies to monitor population dynamics and habitat use. These spatial networks capture which regions of a population''s spatial distribution share similar/dissimilar individual usage patterns, and can be especially useful for detecting structured habitat use within the population''s spatial range.
3. Using simulations and 18 years of capture–recapture data from St. Lawrence Estuary (SLE) beluga, we show that this approach can successfully estimate the magnitude of similarities/dissimilarities in individual usage patterns across sectors, and identify sectors that share similar individual usage patterns that differ from other sectors, that is, structured habitat use. In the case of SLE beluga, this method identified multiple clusters of individuals, each preferentially using restricted areas within their summer range of the SLE.
4. Multilevel binomial models can be effective at estimating spatial structure in habitat use within wildlife populations sampled by capture–recapture of individuals, and can be especially useful when sampling effort is not evenly distributed. Our finding of a structured habitat use within the SLE beluga summer range has direct implications for estimating individual exposures to localized stressors, such as underwater noise from shipping or other activities.

     

The probability of evolutionary rescue: towards a quantitative comparison between theory and evolution experiments

Evolutionary rescue occurs when a population genetically adapts to a new stressful environment that would otherwise cause its extinction. Forecasting the probability of persistence under stress, including emergence of drug resistance as a special case of interest, requires experimentally validated quantitative predictions. Here, we propose general analytical predictions, based on diffusion approximations, for the probability of evolutionary rescue. We assume a narrow genetic basis for adaptation to stress, as is often the case for drug resistance. First, we extend the rescue model of Orr & Unckless (Am. Nat. 2008 172, 160–169) to a broader demographic and genetic context, allowing the model to apply to empirical systems with variation among mutation effects on demography, overlapping generations and bottlenecks, all common features of microbial populations. Second, we confront our predictions of rescue probability with two datasets from experiments with Saccharomyces cerevisiae (yeast) and Pseudomonas fluorescens (bacterium). The tests show the qualitative agreement between the model and observed patterns, and illustrate how biologically relevant quantities, such as the per capita rate of rescue, can be estimated from fits of empirical data. Finally, we use the results of the model to suggest further, more quantitative, tests of evolutionary rescue theory.