Search

The blacklegged tick, Ixodes scapularis, is a vector of Borrelia burgdorferi sensu stricto (s.s.), the causative agent of Lyme disease, part of a slow-moving epidemic of Lyme borreliosis spreading across the northern hemisphere. There are well-known geographic differences in the vectorial capacity of these ticks associated with genetic variation. Despite the need for detailed genetic information in this disease system, previous phylogeographic studies of these ticks have been restricted to relatively few populations or genetic loci. Here we present the most comprehensive phylogeographic study of I. scapularis conducted by using 3RAD and surveying 353 ticks from 33 counties throughout the range of I. scapularis. We found limited genetic variation among populations from the Northeast and Upper Midwest, where Lyme disease is most common, and higher genetic variation among populations from the South. We identify four genetic clusters of I. scapularis that are consistent with four major geographic regions, plus a distinct Central Florida group. In regions where Lyme disease is increasing in frequency, the I. scapularis populations genetically group with ticks from historically highly Lyme-endemic regions. Finally, we identify ten variable DNA sites that contribute the most to population differentiation. These variable sites cluster on one of the chromosome-scale scaffolds for I. scapularis and are within identified genes. Our findings illuminate the need for additional research to identify loci causing variation in the vectorial capacity of I. scapularis and where additional tick sampling would be most valuable to further understand disease trends caused by pathogens transmitted by I. scapularis.

Parasite drug resistance presents a major obstacle to controlling and eliminating vector-borne diseases affecting humans and animals. While vector-borne disease dynamics are affected by factors related to parasite, vertebrate host and vector, research on drug resistance in filarial parasites has primarily focused on the parasite and vertebrate host, rather than the mosquito. However, we expect that the physiological costs associated with drug resistance would reduce the fitness of drug-resistant vs. drug-susceptible parasites in the mosquito wherein parasites are not exposed to drugs. Here we test this hypothesis using four isolates of the dog heartworm (Dirofilaria immitis)&mdash, two drug susceptible and two drug resistant&mdash, and two vectors&mdash, the yellow fever mosquito (Aedes aegypti) and the Asian tiger mosquito (Ae. albopictus)&mdash, as our model system. Our data indicated that while vector species had a significant effect on vectorial capacity, there was no significant difference in the vectorial capacity of mosquitoes infected with drug-resistant vs. drug-susceptible parasites. Consequently, contrary to expectations, our data indicate that drug resistance in D. immitis does not appear to reduce the transmission efficiency of these parasites, and thus the spread of drug-resistant parasites in the vertebrate population is unlikely to be mitigated by reduced fitness in the mosquito vector.

Aim: Macroecological analyses provide valuable insights into factors that influence how parasites are distributed across space and among hosts. Amid large uncertainties that arise when generalizing from local and regional findings, hierarchical approaches applied to global datasets are required to determine whether drivers of parasite infection patterns vary across scales. We assessed global patterns of haemosporidian infections across a broad diversity of avian host clades and zoogeographical realms to depict hotspots of prevalence and to identify possible underlying drivers. Location: Global. Time period: 1994–2019. Major taxa studied: Avian haemosporidian parasites (genera Plasmodium, Haemoproteus, Leucocytozoon and Parahaemoproteus). Methods: We amalgamated infection data from 53,669 individual birds representing 2,445 species world-wide. Spatio-phylogenetic hierarchical Bayesian models were built to disentangle potential landscape, climatic and biotic drivers of infection probability while accounting for spatial context and avian host phylogenetic relationships. Results: Idiosyncratic responses of the three most common haemosporidian genera to climate, habitat, host relatedness and host ecological traits indicated marked variation in host infection rates from local to global scales. Notably, host ecological drivers, such as migration distance for Plasmodium and Parahaemoproteus, exhibited predominantly varying or even opposite effects on infection rates across regions, whereas climatic effects on infection rates were more consistent across realms. Moreover, infections in some low-prevalence realms were disproportionately concentrated in a few local hotspots, suggesting that regional-scale variation in habitat and microclimate might influence transmission, in addition to global drivers. Main conclusions: Our hierarchical global analysis supports regional-scale findings showing the synergistic effects of landscape, climate and host ecological traits on parasite transmission for a cosmopolitan and diverse group of avian parasites. Our results underscore the need to account for such interactions, in addition to possible variation in drivers across regions, to produce the robust inference required to predict changes in infection risk under future scenarios.

Researchers worldwide are repeatedly warning us against future zoonotic diseases resulting from humankind’s insurgence into natural ecosystems. The same zoonotic pathogens that cause severe infections in a human host frequently fail to produce any disease outcome in their natural hosts. What precise features of the immune system enable natural reservoirs to carry these pathogens so efficiently? To understand these effects, we highlight the importance of tracing the evolutionary basis of pathogen tolerance in reservoir hosts, while drawing implications from their diverse physiological and life-history traits, and ecological contexts of host-pathogen interactions. Long-term co-evolution might allow reservoir hosts to modulate immunity and evolve tolerance to zoonotic pathogens, increasing their circulation and infectious period. Such processes can also create a genetically diverse pathogen pool by allowing more mutations and genetic exchanges between circulating strains, thereby harboring rare alive-on-arrival variants with extended infectivity to new hosts (i.e., spillover). Finally, we end by underscoring the indispensability of a large multidisciplinary empirical framework to explore the proposed link between evolved tolerance, pathogen prevalence, and spillover in the wild.

Niche theory predicts specialists which will be more sensitive to environmental perturbation compared to generalists, a hypothesis receiving broad support in free-living species. Based on their niche breadth, parasites can also be classified as specialists and generalists, with specialists infecting only a few and generalists a diverse array of host species. Here, using avian haemosporidian parasites infecting wild bird populations inhabiting the Western Ghats, India as a model system, we elucidate how climate, habitat and human disturbance affects parasite prevalence both directly and indirectly via their effects on host diversity. Our data demonstrate that anthropogenic disturbance acts to reduce the prevalence of specialist parasite lineages, while increasing that of generalist lineages. Thus, as in free-living species, disturbance favours parasite communities dominated by generalist versus specialist species. Because generalist parasites are more likely to cause emerging infectious diseases, such biotic homogenisation of parasite communities could increase disease emergence risk in the Anthropocene.

Niche theory predicts specialists will be more sensitive to environmental perturbation compared to generalists, a hypothesis receiving broad support in free-living species. Based on their niche breadth, parasites can also be classified as specialists and generalists, with specialists infecting only a few and generalists a diverse array of host species. Here, using avian haemosporidian parasites infecting wild bird populations inhabiting the Western Ghats, India as a model system, we elucidate how climate, habitat and human disturbance affects parasite prevalence both directly and indirectly via their effects on host diversity. Our data demonstrates that anthropogenic disturbance acts to reduce the prevalence of specialist parasite lineages, while increasing that of generalist lineages. Thus, as in free-living species, disturbance favors parasite communities dominated by generalist vs. specialist species. Because generalist parasites are more likely to cause emerging infectious diseases, such biotic homogenization of parasite communities could increase disease emergence risk in the Anthropocene

Sample size sufficiency is a critical consideration for conducting Resource-Selection Analyses (RSAs) from GPS-based animal telemetry. Cited thresholds for sufficiency include a number of captured animals M ≥ 30 and as many relocations per animal N as possible. These thresholds render many RSA-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations.We provide the first comprehensive solution for RSA sample size by deriving closed-form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 2 biologically meaningful quantities: habitat selection strength and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores, and herbivores living in boreal, temperate, and tropical forests, montane woodlands, swamps, and arctic tundra).Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results contradict conventional wisdom by demonstrating that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with far fewer data than is commonly assumed.We identify several critical steps in implementing these equations, including (i) a priori selection of expected model coefficients, and (ii) sampling intensity for background (absence/pseudo-absence) data within a given definition of availability. We show that random sampling of background data violates the underlying mathematics of RSA, leading to incorrect values for necessary M and N and potentially incorrect RSA model outputs. We argue that these equations should be a mandatory component for all future RSA studies.

Made available in DSpace on 2022-04-28T19:43:56Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS-based animal telemetry. Cited thresholds for sufficiency include a number of captured animals (Formula presented.) and as many relocations per animal N as possible. These thresholds render many RSF-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. We provide the first comprehensive solution for RSF sample size by deriving closed-form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 3 biologically meaningful quantities: habitat selection strength, variation in individual selection and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores and herbivores living in boreal, temperate and tropical forests, montane woodlands, swamps and Arctic tundra). Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results demonstrate that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with much fewer than (Formula presented.) animals. We identify several critical steps in implementing these equations, including (a) a priori selection of expected model coefficients and (b) regular sampling of background (pseudoabsence) data within a given definition of availability. We discuss possible methods to identify a priori expectations for habitat selection coefficients, effects of scale on RSF estimation and caveats for rare species applications. We argue that these equations should be a mandatory component for all future RSF studies. Department of Wildlife Fisheries and Aquaculture Mississippi State University Quantitative Ecology and Spatial Technologies Laboratory Mississippi State University School of Mathematics and Statistics Uiversity of Sheffield Department of Biosciences Swansea University Centre for Biomathematics Swansea University Savannah River Ecology Laboratory University of Georgia Department of Integrative Biology University of Guelph Department of Biology University of Saskatchewan Haub School of Environment and Natural Resources University of Wyoming Department of Biology Memorial University of Newfoundland Instituto de Biosciências Universidad Estadual Paulista Centre for Northern Forest Ecosystem Research Ontario Ministry of Natural Resources and Forestry Department of Bioscience Aarhus University Wyoming Cooperative Fish and Wildlife Research Unit University of Wyoming IUCN/SSC Peccary Specialist Group Instituto de Biosciências Universidad Estadual Paulista

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has been characterized by unprecedented rates of spatio-temporal spread. Here, we summarize the main events in the pandemic's timeline and evaluate what has been learnt by the public health community. We also discuss the implications for future public health policy and, specifically, the practice of epidemic control. We critically analyze this ongoing pandemic's timeline and contrast it with the 2002–2003 SARS outbreak. We identify specific areas (e.g., pathogen identification and initial reporting) wherein the international community learnt valuable lessons from the SARS outbreak. However, we also identify the key areas where international public health policy failed leading to the exponential spread of the pandemic. We outline a clear agenda for improved pandemic control in the future.

International audience; In the Fall of 2016 a workshop was held which brought together over 50 scientists from the ecological and radio- logical fields to discuss feasibility and challenges of reintegrating ecosystem science into radioecology. There is a growing desire to incorporate attributes of ecosystem science into radiological risk assessment and radioecological research more generally, fueled by recent advances in quantification of emergent ecosystem at- tributes and the desire to accurately reflect impacts of radiological stressors upon ecosystem function. This paper is a synthesis of the discussions and consensus of the workshop participant's responses to three primary questions, which were: 1) How can ecosystem science support radiological risk assessment? 2) What ecosystem level endpoints potentially could be used for radiological risk assessment? and 3) What inference strategies and associated methods would be most appropriate to assess the effects of radionuclides on ecosystem structure and function? The consensus of the participants was that ecosystem science can and should support radiological risk assessment through the incorporation of quantitative metrics that reflect ecosystem functions which are sensi- tive to radiological contaminants. The participants also agreed that many such endpoints exit or are thought to exit and while many are used in ecological risk assessment currently, additional data need to be collected that link the causal mechanisms of radiological exposure to these endpoints. Finally, the participants agreed that ra- diological risk assessments must be designed and informed by rigorous statistical frameworks capable of reveal- ing the causal inference tying radiological exposure to the endpoints selected for measurement.

Parasites, and the diseases they cause, are important from an ecological and evolutionary perspective because they can negatively affect host fitness and can regulate host populations. Consequently, conservation biology has long recognized the vital role that parasites can play in the process of species endangerment and recovery. However, we are only beginning to understand how deeply parasites are embedded in ecological systems, and there is a growing recognition of the important ways in which parasites affect ecosystem structure and function. Thus, there is an urgent need to revisit how parasites are viewed from a conservation perspective and broaden the role that disease ecology plays in conservation-related research and outcomes. This review broadly focusses on the role that disease ecology can play in biological conservation. Our review specifically emphasizes on how the integration of tools and analytical approaches associated with both disease and molecular ecology can be leveraged to aid conservation biology. Our review first concentrates on disease-mediated extinctions and wildlife epidemics. We then focus on elucidating how host–parasite interactions has improved our understanding of the eco-evolutionary dynamics affecting hosts at the individual, population, community and ecosystem scales. We believe that the role of parasites as drivers and indicators of ecosystem health is especially an exciting area of research that has the potential to fundamentally alter our view of parasites and their role in biological conservation. The review concludes with a broad overview of the current and potential applications of modern genomic tools in disease ecology to aid biological conservation.

Background The ability of blood-feeding arthropods to successfully acquire and transmit pathogens of medical and veterinary importance has been shown to be interfered with, or enhanced by, the arthropod’s native microbiome. Mosquitoes transmit viruses, protozoan and filarial nematodes, the majority of which contribute to the 17% of infectious disease cases worldwide. Dirofilaria immitis, a mosquito-transmitted filarial nematodes of dogs and cats, is vectored by several mosquito species including Aedes aegypti. Methods In this study, we investigated the impact of D. immitis colonization on the microbiome of laboratory reared female Ae. aegypti. Metagenomic analysis of the V3–V4 variable region of the microbial 16S RNA gene was used for identification of the microbial differences down to species level. Results We generated a total of 1068 OTUs representing 16 phyla, 181 genera and 271 bacterial species. Overall, in order of abundance, Proteobacteria, Bacteroidetes, Actinobacteria and Firmicutes were the most represented phylum with D. immitis-infected mosquitoes having more of Proteobacteria (71%) than uninfected mosquitoes (56.9%). An interesting finding in this study is the detection of Klebsiella oxytoca in relatively similar abundance in infected and uninfected mosquitoes, suggesting a possible endosymbiotic relationship, and has been previously shown to indirectly compete for nutrients with fungi on domestic housefly eggs and larvae. While D. immitis colonization has no effect on the overall species richness, we identified significant differences in the composition of selected bacterial genera and phyla between the two groups. We also reported distinct compositional and phylogenetic differences in the individual bacterial species when commonly identified bacteria were compared. Conclusions To the best of our knowledge, this is the first study to understand the impact of a filarial infection on the microbiome of its mosquito vector. Further studies are required to identify bacteria species that could play an important role in the mosquito biology. While the microbiome composition of Ae. aegypti mosquito have been previously reported, our study shows that in an effort to establish itself, a filarial nematode modifies and alters the overall microbial diversity within its mosquito host.

Additional file 1: Figure S1. Agarose gel electrophoresis of PCR amplified D. immitis 656-bp cox1 mtDNA gene confirming the infection status of Ae. aegypti. Figure S2. Quality plots of forward and reverse reads. Figure S3. Summary of sequence reads following demultiplexing. Figure S4. Relative abundance of bacteria phyla across individual mosquito samples analyzed. Figure S5. Relative abundance of bacteria families across individual mosquito samples analyzed. Figure S6. Relative abundance of bacteria genera across individual mosquito samples analyzed. Figure S7. Relative abundance of bacteria species across individual mosquito samples analyzed. Figure S8. Heat map analysis of the differential composition showing most abundant bacteria genera identified in this study. Figure S9. Phylogenetic reconstruction of the relative abundances of bacteria genera identified from both D. immitis-infected and uninfected mosquitoes.

Development of specific IgE antibodies to the oligosaccharide galactose-α-1, 3-galactose (α-gal) following tick bites has been shown to be the source of red meat allergy. In this study, we investigated the presence of α-gal in four tick species: the lone-star tick (Amblyomma americanum), the Gulf-Coast tick (Amblyomma maculatum), the American dog tick (Dermacentor variabilis), and the black-legged tick (Ixodes scapularis) by using a combination of immunoproteomic approach and, carbohydrate analysis. Anti-α-gal antibodies identified α-gal in the salivary glands of both Am. americanum and Ix. scapularis, while Am. maculatum and De. variabilis appeared to lack the carbohydrate. PNGase F treatment confirmed the deglycosylation of N-linked α-gal-containing proteins in tick salivary glands. Immunolocalization of α-gal moieties to the salivary secretory vesicles of the salivary acini also confirmed the secretory nature of α-gal-containing antigens in ticks. Am. americanum ticks were fed on human blood (lacks α-gal) using a silicone membrane system to determine the source of the α-gal. N-linked glycan analysis revealed that Am. americanum and Ix. scapularis have α-gal in their saliva and salivary glands, but Am. maculatum contains no detectable quantity. Consistent with the glycan analysis, salivary samples from Am. americanum and Ix. scapularis stimulated activation of basophils primed with plasma from α-gal allergic subjects. Together, these data support the idea that bites from certain tick species may specifically create a risk for the development of α-gal-specific IgE and hypersensitivity reactions in humans. Alpha-Gal syndrome challenges the current food allergy paradigm and broadens opportunities for future research.

Geographic sampling location information, Parasite prevalence per host species with the number of unique parasite lineages, parasite lineage names and GenBank accession numbers, host ecological trait data, other tables and figures supporting the conclusions of this study.

Detailed information on field sampling; PCR, DNA sequencing; parasite/host phylogenetic analyses; host specificity and co-phylogenetic analyses.

Development of specific IgE antibodies to the oligosaccharide galactose-α-1, 3-galactose (α-gal) following tick bites has been shown to be the source of red meat allergy. In this study, we investigated the presence of α-gal in four tick species: the lone-star tick (Amblyomma americanum), the Gulf-Coast tick (Amblyomma maculatum), the American dog tick (Dermacentor variabilis), and the black-legged tick (Ixodes scapularis) by using a combination of immunoproteome, carbohydrate analysis, and basophil activation approaches. Using anti-α-gal antibodies, α-gal was identified in the salivary glands of bothAm. americanumandIx. scapularis, whileAm. maculatumandDe. variabilisappeared to lack the sugar. PNGase F treatment confirmed the deglycosylation of N-linked α-gal-containing proteins in tick salivary glands. Immunolocalization of α-gal moieties to the salivary secretory vesicles of the salivary acini also confirmed the secretory nature of α-gal-containing antigens in ticks.Am. americanumticks were fed human blood (lacks α-gal) using an artificial membrane feeding system to determine the source of α-gal. N-linked glycan analysis revealed thatAm. americanumandIx. scapularishave α-gal in their saliva and salivary glands, butAm. maculatumcontains no detectable quantity. Salivary samples fromAm. americanumandIx. scapularisstimulated activation of basophils primed with plasma from α-gal allergic subjects. Together, our data support the idea that bites from certain tick species may specifically create a risk for the development of α-gal-specific IgE and hypersensitivity reactions in humans. Alpha-Gal syndrome challenges the current food allergy paradigm and broadens opportunities for future research.

Animals can modulate their own exposure to environmental contaminants through behavioral plasticity such as diet and habitat choice. However, it remains unclear if behavior also has cascading effects on contaminant exposure across multiple generations. In insects, oviposition site selection is an important behavior females can use to modify offspring contaminant exposure risk. In this study, we use the yellow fever mosquito, Aedes aegypti, to test how methylmercury (MeHg) affects oviposition site selection. We found that mosquito larval development rate and survival were negatively affected at MeHg concentrations ≥100 ppb. Adult females not exposed to MeHg as larvae avoided oviposition sites with high MeHg concentrations (>50 ppb), but MeHg exposure at the larval stage significantly affected this oviposition site selection. Specifically, females raised from larvae exposed to non-toxic MeHg levels (i.e., five-50 ppb) showed a significant increase in preference for oviposition sites contaminated with toxic MeHg concentrations (≥500 ppb), compared to unexposed controls. This maladaptive behavioral response could be because, when conditioned with non-toxic MeHg concentrations, MeHg-associated olfactory cues act as a “supernormal” stimulus during oviposition site selection. Importantly, however, this maladaptive behavioral response is eliminated in female mosquitoes raised from larvae exposed to toxic MeHg concentrations (i.e. 100 ppb), and these mosquitoes showed a significant increase in preference for MeHg uncontaminated oviposition sites, compared to unexposed controls. Thus, in mosquitoes, the magnitude of MeHg exposure in one generation can impact MeHg exposure in subsequent generations by altering oviposition site selection behavior. Our results have broad implications for our understanding of how contaminant-mediated behavioral modifications can feedback on contaminant exposure risk across multiple generations, and consequently how behavior can affect the evolutionary trajectory of organisms inhabiting a heterogeneously contaminated environment.

Metal pollution is a growing concern that affects the health of humans and animals globally. Copper is an essential insect micronutrient required for respiration, pigmentation and oxidative stress protection but can also act as a potentially toxic trace element. While several studies have focused on the negative fitness effects of copper on the aquatic larvae of mosquitoes, the effects of larval copper exposure on adult mosquito fitness (i.e., survival and fecundity) and their ability to transmit parasites (i.e., vector competence) remains unclear. Here, using a well-studied model vector-parasite system, the mosquito Aedes aegypti and parasite Dirofilaria immitis, we show that sublethal copper exposure in larval mosquitoes alters adult female fecundity and vector competence. Specifically, mosquitoes exposed to copper had a hormetic fecundity response and mosquitoes exposed to 600 μg/L of copper had significantly fewer infective parasite larvae than control mosquitoes not exposed to copper. Thus, exposure of mosquito larvae to copper levels far below EPA-mandated safe drinking water limits (1300 μg/L) can impact vector-borne disease dynamics not only by reducing mosquito abundance (through increased larval mortality), but also by reducing parasite transmission risk. Our results also demonstrated that larval copper is retained through metamorphosis to adulthood in mosquitoes, indicating that these insects could transfer copper from aquatic to terrestrial foodwebs, especially in urban areas where they are abundant. To our knowledge this is the first study to directly link metal exposure with vector competence (i.e., ability to transmit parasites) in any vector-parasite system. Additionally, it also demonstrates unequivocally that mosquitoes can transfer contaminants from aquatic to terrestrial ecosystems. These results have broad implications for public health because they directly linking contaminants and vector-borne disease dynamics, as well as linking mosquitoes and contaminant dynamics.

Prevention of infection with canine heartworm (Dirofilaria immitis) is based on the compliant administration of macrocyclic lactone (ML) drugs. Resistance to ML drugs is well documented in D. immitis; however, there remains a paucity of information on the spatial distribution and prevalence of resistant isolates. This project aims to improve understanding of ML-resistance by using a population genetic approach. We developed a large panel of microsatellite loci and identified 12 novel highly polymorphic markers. These 12, and five previously published markers were used to screen pools of microfilariae from 16 confirmed drug-susceptible, 25 confirmed drug-resistant, and from 10 suspected drug-resistant field isolates. In isolates where microfilarial suppression testing indicated resistance, Spatial Principal Component Analysis (sPCoA), Neighbor Joining Trees and Bayesian clustering all revealed high genetic similarity between pre- and post-treatment samples. Somewhat surprisingly, the Neighbor Joining tree and sPCoA generated using pairwise Nei's distances did not reveal clustering for resistant isolates, nor did it reveal state-level geographic clustering from samples collected in Georgia, Louisiana or Mississippi. In contrast, Discriminant Analysis of Principle Components was able to discriminate between susceptible, suspected-resistant and resistant samples. However, no resistance-associated markers were detected, and this clustering was driven by the combined effects of multiple alleles across multiple loci. Additionally, we measured unexpectedly large genetic distances between different passages of laboratory strains that originated from the same source infection. This finding strongly suggests that the genetic makeup of laboratory isolates can change substantially with each passage, likely due to genetic bottlenecking. Taken together, these data suggest greater than expected genetic variability in the resistant isolates, and in D. immitis overall. Our results also suggest that microsatellite genotyping lacks the sensitivity to detect a specific genetic signature for resistance. Future investigations using genomic analyses will be required to elucidate the genetic relationships of ML-resistant isolates.

The vectorial capacity of mosquitoes depends upon the magnitude of reduction of parasite load upon infection through resistance mechanisms (e.g., immune-mediated killing) and the ability of mosquitoes to offset infection-mediated costs through tolerance mechanisms (e.g., tissue repair). Here we use a common-garden experimental framework to measure variation in resistance and tolerance to dog heartworm (Dirofilaria immitis) between natural Aedes albopictus mosquito populations representing areas of low and high transmission intensity. Our data revealed that survival to the extrinsic incubation period, the earliest time point at which infective L3 larvae develop, significantly differed between populations (ranging from 10-60%) when mosquitoes infected with D. immitis at both the low (15 microfilaria/μl blood) and high (30 microfilaria/μl blood) infection dose (Dose: χ2 = 191.473; P < 0.001; Population: χ2 = 24.485; P = 0.001; Dose × Population: χ2 = 35.566; P = 0.001). Contrary to expectations, we found that mosquito populations with highest resistance (i.e., greatest reduction in parasite load) also exhibited highest mortality upon infection (F1,12 = 6.781, P = 0.023; Dose: F1,12 = 6.747; P = 0.023; Mortality × Dose: F1,12 = 0.111, P = 0.744). Expressing the effect of the number of killed (NKILLED) and live (NLIVE) parasite on survival of mosquitoes from the different population, we document a significant inter-population variation in the survival cost of additional parasite (i.e., tolerance to infection (NLIVE × Population: χ2 = 22.845; P = 0.002; NKILLED × Population: χ2 = 31.959; P = < 0.001; NLIVE × NKILLED × Population: χ2 = 22.266; P = 0.002), in conjunction with negative relationship between tolerance and resistance (Resistance: F1,12 = 11.870, P = 0.005; Dose: F1,12 = 16.0170, P = 0.002; Resistance × Dose: F1,12 = 9.699, P =0.009). Importantly, populations from areas with high transmission intensity (as measured by parasite prevalence in dogs) showed elevated tolerance (Prevalence: F1,12 = 9.5, P = 0.012; Prevalence2: F1,12 = 4.353, P = 0.064; Dose: F1,12 = 38.855, P = F1,12 = 8.175, P = 0.014; Dose: F1,12 = 0.005, P = 0.946; Tolerance × Dose: F1,12 = 0.920, P = 0.356). Consequently, our data indicate that spatial variation in disease transmission intensity is linked to the evolution of tolerance in natural mosquito populations, which in turn can feedback to impact disease risk.

Globally, diseases transmitted by arthropod vectors, such as mosquitoes, remain a major cause of morbidity and mortality [1]. The defense responses of mosquito and other arthropod vectors against parasites are important for understanding disease transmission dynamics and for the development of novel disease-control strategies. Consequently, the mechanisms by which mosquitoes resist parasitic infection (e.g., immune-mediated killing) have long been studied [2, 3]. However, the ability of mosquitoes to ameliorate the negative fitness consequences of infection through tolerance mechanisms (e.g., tissue repair) has been virtually ignored (but see [4, 5]). Ignoring parasite tolerance is especially taxing in vector biology because unlike resistance, which typically reduces vectorial capacity, tolerance is expected to increase vectorial capacity by reducing parasite-mediated mortality without killing parasites [6], contributing to the recurrent emergence of vector-borne diseases and its stabilization and exacerbation. Despite its importance, there is currently no evidence for the evolution of tolerance in natural mosquito populations. Here, we use a common-garden experimental framework to measure variation in resistance and tolerance to dog heartworm (Dirofilaria immitis) between eight natural Aedes albopictus mosquito populations representing areas of low and high transmission intensity. We find significant inter-population variation in tolerance and elevated tolerance where transmission intensity is high. Additionally, as expected, we find that increased tolerance is associated with higher vectorial capacity. Consequently, our results indicate that high transmission intensity can lead to the evolution of more competent disease vectors, which can feed back to impact disease risk.

The source‐sink model undoubtedly is one of the most established paradigms for associating variance in population dynamics with heterogeneity in habitat quality. However, despite extensive theoretical support by the scientific community, the majority of studies seeking empirical validation for this model have lacked sufficient data to distinguish source and sink habitats, particularly for large or secretive mammals. Using relatively long‐term mark‐recapture and genetic data for a generalist mesopredator within a fragmented agricultural ecosystem, we show that use of a two‐stage approach incorporating both genetic and demographic data can be a powerful tool for evaluating the population structure of organisms occupying complex ecological systems. We further demonstrate that a strong concordance exists between demographic attributes and underlying genetic expectations, suggesting evaluation of fine‐scale genetic patterns alone may provide valuable insights into the population dynamics of species. These data have important implications for advancing our ability to quantify heterogeneity in population stability, particularly for large or imperiled species where sufficient demographic data cannot be obtained to parameterize traditional source‐sink models.

Understanding why some parasites emerge in novel host communities while others do not has broad implications for human and wildlife health. In the case of haemosporidian blood parasites, epidemic wild bird mortalities on oceanic islands have been linked to Plasmodium spp., but not genera like Haemoproteus . Indeed, Haemoproteus is absent from many oceanic islands. By contrast, birds on continental islands share long coevolutionary histories with both Plasmodium and Haemoproteus , and are thus ideal model systems to elucidate eco-evolutionary endpoints associated with these parasites in oceanic islands. Here, we examine eco-evolutionary dynamics of avian haemosporidian in the Shola sky-island archipelago of the Western Ghats, India. Our analyses reveal that compared to Plasmodium , Haemoproteus lineages were highly host-specific and diversified via co-speciation with their hosts. We show that community structure of host-generalist Plasmodium was primarily driven by geographical factors (e.g. biogeographic barriers), while that of host-specialist Haemoproteus was driven by host species barriers (e.g. phylogenetic distance). Consequently, a few host species can harbour a high diversity of Plasmodium lineages which, in turn, are capable of infecting multiple host species. These two mechanisms can act in concert to increase the risk of introduction, establishment, and emergence of novel Plasmodium lineages in island systems.

Kin structure, the spatial aggregation of related individuals, impacts many processes important to conservation (e.g. inbreeding), and patterns of kin structure could be impacted by human-mediated habitat fragmentation and loss. While kin structure is expected to increase with habitat fragmentation (reduced connectivity), the effects of habitat loss (reduced resource availability) remain unclear. Disentangling the effects of habitat fragmentation and loss is challenging because they usually are spatially correlated, and because most species are negatively affected by both processes. Raccoons Procyon lotor is a model species to test how habitat loss affects kin structure because, although relatively unaffected by habitat fragmentation (because of high dispersal ability), they are negatively affected by habitat loss (forest-related resources being important for female reproductive success). To elucidate the causes and consequences of kin structure in raccoons, we utilized genetic and demographic data collected from 998 individuals trapped from 27 spatially distinct habitat patches (local populations) situated in an agricultural ecosystem. Our results highlight an important, but often ignored fact: structural connectivity does not necessarily predict functional dispersal patterns in natural populations. Thus, in raccoons, local populations with low kin structure were associated with high landscape disturbance (i.e. high levels of habitat loss and low connectivity), and were characterized by demographic instability (i.e. high immigration, emigration and/or mortality). Alternatively, local populations exhibiting high kin structure were associated with low landscape disturbance and high demographic stability (i.e. high natality and philopatry). We propose that such increased philopatry in resource-rich patches could lead to a functional isolation (‘isolation by resource’) exacerbating the negative effects of landscape modification because of isolation by distance and/or resistance, especially in species with low dispersal capability. Our results also indicate that high levels of genetic diversity may be associated with low (rather than high) patch quality because populations in such patches could be composed predominantly of (unrelated) immigrants.

Population genetic tools can facilitate successful conservation and management of wildlife populations. However, the ability of such approaches to inform wildlife management and conservation programs depends upon assumptions linking genetic patterns to ecological processes, one implicit assumption usually being that genetic parameters (e.g., population genetic differentiation) estimated using a set of loci accurately reflect underlying demographic and microevolutionary forces affecting the population(s) under study. This is an important assumption because it also implies that we have acknowledged that genetic parameters estimated by a set of target loci inherently are associated with a sampling variance. Specifically, a perception exists that heterozygote deficits caused by biological mechanisms (e.g., a Wahlund effect) and null alleles can be differentiated by the expectation that the former leads to a concordant pattern across all loci, whereas the latter leads to locus-specific effects. We use Monte-Carlo simulation to demonstrate that these expectations do not always hold under biologically realistic conditions. Our analyses indicate that the conservative approach of discarding loci deviating from Hardy-Weinberg equilibrium expectations could rob us of our most informative markers, weakening our ability to interpret biological phenomena. © 2012 The Wildlife Society.

Many aspects of parasite biology critically depend on their hosts, and understanding how host‐parasite populations are co‐structured can help improve our understanding of the ecology of parasites, their hosts, and host‐parasite interactions. This study utilized genetic data collected from raccoons (Procyon lotor), and a specialist parasite, the raccoon tick (Ixodes texanus), to test for genetic co‐structuring of host‐parasite populations at both landscape and host scales. At the landscape scale, our analyses revealed a significant correlation between genetic and geographic distance matrices (i.e., isolation by distance) in ticks, but not their hosts. While there are several mechanisms that could lead to a stronger pattern of isolation by distance in tick vs. raccoon datasets, our analyses suggest that at least one reason for the above pattern is the substantial increase in statistical power (due to the ≈8‐fold increase in sample size) afforded by sampling parasites. Host‐scale analyses indicated higher relatedness between ticks sampled from related vs. unrelated raccoons trapped within the same habitat patch, a pattern likely driven by increased contact rates between related hosts. By utilizing fine‐scale genetic data from both parasites and hosts, our analyses help improve our understanding of epidemiology and host ecology.

The spatial aggregation of related individuals can affect disease dynamics by altering contact rates between individuals and/or groups of individuals. However, kin-structure likely affects contact rates in a scale-dependent manner: increasing contact rates within, but decreasing contact rates amongst spatial groups. Thus, the effect of kin-structure on disease exposure risk should depend upon the spatial scale relevant for pathogen transmission. This study was undertaken to test the effects of kin-structure on disease dynamics in raccoons (Procyon lotor) inhabiting a highly fragmented agricultural ecosystem. Raccoons (n = 566) were trapped at 31 spatially discrete habitat patches (local populations). Trapped individuals were genotyped at 13 microsatellites and their serum screened for antibodies to canine distemper virus (CDV) and multiple Leptospira spp. serovars. Our analyses revealed that the effects of kin-structure on transmission dynamics are dependent on both spatial scale and the pathogen under consideration. Thus, in the directly transmitted pathogen (CDV), the probability of pathogen co-exposure (the proportion of individual pairs where both individuals were seropositive for a particular pathogen) was positively correlated with genealogical proximity within local populations. Conversely, in the environmentally transmitted leptospires co-exposure was homogeneous within local populations and was positively correlated with gene flow among these populations. Our analyses also revealed that, after controlling for confounding effects of landscape and demographic variables, the effects of kin-structure on disease exposure risk was pathogen-specific. In particular, increasing kin-structure was associated with increased disease exposure risk in the directly transmitted pathogen (CDV), and alternatively with decreased disease exposure risk in environmentally transmitted leptospires. The potential, scale-dependent, effects of kin-structure on disease exposure risk revealed by our analyses could play an important role in elucidating disease dynamics in natural populations and in planning effective disease mitigation strategies.

Fragmentation has drastically altered the quality of habitats throughout numerous ecosystems, often leading to dramatic changes in the composition of wildlife communities. The ecology and associated movement behavior of a species may also be modified as a result of forest fragmentation, resulting in changes in genetic composition of the affected species. In this research, we evaluated the genetic structure of the Virginia opossum ( Didelphis virginiana Kerr, 1792) at the landscape and local scales in a fragmented, agricultural ecosystem in northern Indiana using 13 microsatellite loci. We examined 290 samples from opossums inhabiting 28 discrete habitat patches, and evaluated partitioning of genetic variation of opossums among and within habitat patches. We observed low but significant levels of genetic structure (FST = 0.005) overall, and pairwise comparisons of FSTvalues among habitat patches also were relatively low. Relatedness within patches was highly variable (–0.077 ≤ rxy ≤ 0.060), with a few patches exhibiting significantly higher levels of relatedness than random expectations, and we detected no evidence of sex-biased natal dispersal. These results contrast with previous field studies that documented male-biased dispersal in the Virginia opossum, indicating dispersal in this species is plastic and dependent upon local environmental conditions.

Human land-use practices have dramatically altered the composition and configuration of native habitats throughout many ecosystems. Within heterogeneous landscapes generalist predators often thrive, causing cascading effects on local biological communities, yet there are few data to suggest how attributes of fragmentation influence local population dynamics of these species. We monitored 25 raccoon (Procyon lotor) populations from 2004 to 2009 in a fragmented agricultural landscape to evaluate the influence of local and landscape habitat attributes on spatial and temporal variation in demography. Our results indicate that agricultural ecosystems support increased densities of raccoons relative to many other rural landscapes, but that spatial and temporal variation in demography exists that is driven by non-agricultural habitat attributes rather than the availability of crops. At the landscape scale, both density and population stability were positively associated with the size and contiguity of forest patches, while at the local scale density was positively correlated with plant diversity and the density of tree cavities. In addition, populations occupying forest patches with greater levels of plant diversity and stable water resources exhibited less temporal variability than populations with limited plant species complexity or water availability. The proportion of populations comprised of females was most strongly influenced by the availability of tree cavities and soft mast. Despite the abundance of mesopredators in heterogeneous landscapes, our results indicate that all patches do not contribute equally to the regional abundance and persistence of these species. Thus, a clear understanding of how landscape attributes contribute to variation in demography is critical to the optimization of management strategies.