Managing host-parasite interactions in humans and wildlife in times of global change.

Global change in the Anthropocene has modified the environment of almost any species on earth, be it through climate change, habitat modifications, pollution, human intervention in the form of mass drug administration (MDA), or vaccination. This can have far-reaching consequences on all organisational levels of life, including eco-physiological stress at the cell and organism level, individual fitness and behaviour, population viability, species interactions and biodiversity. Host-parasite interactions often require highly adapted strategies by the parasite to survive and reproduce within the host environment and ensure efficient transmission among hosts. Yet, our understanding of the system-level outcomes of the intricate interplay of within host survival and among host parasite spread is in its infancy. We shed light on how global change affects host-parasite interactions at different organisational levels and address challenges and opportunities to work towards better-informed management of parasite control. We argue that global change affects host-parasite interactions in wildlife inhabiting natural environments rather differently than in humans and invasive species that benefit from anthropogenic environments as habitat and more deliberate rather than erratic exposure to therapeutic drugs and other control efforts.

Distinct spread of DNA and RNA viruses among mammals amid prominent role of domestic species.

AIM: Emerging infectious diseases arising from pathogen spillover from mammals to humans constitute a substantial health threat. Tracing virus origin and predicting the most likely host species for future spillover events are major objectives in One Health disciplines.We assessed patterns of virus sharing among a large diversity of mammals, including humans and domestic species. LOCATION: Global. TIME PERIOD: Current. MAJOR TAXA STUDIED: Mammals and associated viruses. METHODS: We used network centrality analysis and trait-based Bayesian hierarchical models to explore patterns of virus sharing among mammals. We analysed a global database that compiled the associations between 1,785 virus species and 725 mammalian host species as sourced from automatic screening of meta-data accompanying published nucleotide sequences between 1950 and 2019. RESULTS: We show that based on current evidence, domesticated mammals hold the most central positions in networks of known mammal-virus associations. Among entire host-virus networks, Carnivora and Chiroptera hold central positions for mainly sharing RNA viruses, whereas ungulates hold central positions for sharing both RNA and DNA viruses with other host species. We revealed strong evidence that DNA viruses were phylogenetically more host specific than RNA viruses. RNA viruses exhibited low functional host specificity despite an overall tendency to infect phylogenetically related species, signifying high potential to shift across hosts with different ecological niches. The frequencies of sharing viruses among hosts and the proportion of zoonotic viruses in hosts were larger for RNA than for DNA viruses. MAIN CONCLUSIONS: Acknowledging the role of domestic species in addition to host and virus traits in patterns of virus sharing is necessary to improve our understanding of virus spread and spillover in times of global change. Understanding multi-host virus-sharing pathways adds focus to curtail disease spread.

Models of spatiotemporal variation in rabbit abundance reveal management hot spots for an invasive species.

The European rabbit (Oryctolagus cuniculus) is a notorious economic and environmental pest species in its invasive range. To better understand the population and range dynamics of this species, 41 yr of abundance data have been collected from 116 unique sites across a broad range of climatic and environmental conditions in Australia. We analyzed this time series of abundance data to determine whether interannual variation in climatic conditions can be used to map historic, contemporary, and potential future fluctuations in rabbit abundance from regional to continental scales. We constructed a hierarchical Bayesian regression model of relative abundance that corrected for observation error and seasonal biases. The corrected abundances were regressed against environmental and disease variables in order to project high spatiotemporal resolution, continent-wide rabbit abundances. We show that rabbit abundance in Australia is highly variable in space and time, being driven primarily by internnual variation in temperature and precipitation in concert with the prevalence of a non-pathogenic virus. Moreover, we show that internnual variation in local spatial abundances can be mapped effectively at a continental scale using highly resolved spatiotemporal predictors, allowing "hot spots" of persistently high rabbit abundance to be identified. Importantly, cross-validated model performance was fair to excellent within and across distinct climate zones. Long-term monitoring data for invasive species can be used to map fine-scale spatiotemporal fluctuations in abundance patterns when accurately accounting for inherent sampling biases. Our analysis provides ecologists and pest managers with a clearer understanding of the determinants of rabbit abundance in Australia, offering an important new approach for predicting spatial abundance patterns of invasive species at the near-term temporal scales that are directly relevant to resource management.

Climate variation influences host specificity in avian malaria parasites.

Parasites with low host specificity (e.g. infecting a large diversity of host species) are of special interest in disease ecology, as they are likely more capable of circumventing ecological or evolutionary barriers to infect new hosts than are specialist parasites. Yet for many parasites, host specificity is not fixed and can vary in response to environmental conditions. Using data on host associations for avian malaria parasites (Apicomplexa: Haemosporida), we develop a hierarchical model that quantifies this environmental dependency by partitioning host specificity variation into region- and parasite-level effects. Parasites were generally phylogenetic host specialists, infecting phylogenetically clustered subsets of available avian hosts. However, the magnitude of this specialisation varied biogeographically, with parasites exhibiting higher host specificity in regions with more pronounced rainfall seasonality and wetter dry seasons. Recognising the environmental dependency of parasite specialisation can provide useful leverage for improving predictions of infection risk in response to global climate change.

Individual and temporal variation in pathogen load predicts long-term impacts of an emerging infectious disease.

Emerging infectious diseases increasingly threaten wildlife populations. Most studies focus on managing short-term epidemic properties, such as controlling early outbreaks. Predicting long-term endemic characteristics with limited retrospective data is more challenging. We used individual-based modeling informed by individual variation in pathogen load and transmissibility to predict long-term impacts of a lethal, transmissible cancer on Tasmanian devil (Sarcophilus harrisii) populations. For this, we employed approximate Bayesian computation to identify model scenarios that best matched known epidemiological and demographic system properties derived from 10 yr of data after disease emergence, enabling us to forecast future system dynamics. We show that the dramatic devil population declines observed thus far are likely attributable to transient dynamics (initial dynamics after disease emergence). Only 21% of matching scenarios led to devil extinction within 100 yr following devil facial tumor disease (DFTD) introduction, whereas DFTD faded out in 57% of simulations. In the remaining 22% of simulations, disease and host coexisted for at least 100 yr, usually with long-period oscillations. Our findings show that pathogen extirpation or host-pathogen coexistence are much more likely than the DFTD-induced devil extinction, with crucial management ramifications. Accounting for individual-level disease progression and the long-term outcome of devil-DFTD interactions at the population-level, our findings suggest that immediate management interventions are unlikely to be necessary to ensure the persistence of Tasmanian devil populations. This is because strong population declines of devils after disease emergence do not necessarily translate into long-term population declines at equilibria. Our modeling approach is widely applicable to other host-pathogen systems to predict disease impact beyond transient dynamics.

Unravelling changing interspecific interactions across environmental gradients using Markov random fields.

Inferring interactions between co-occurring species is key to identify processes governing community assembly. Incorporating interspecific interactions in predictive models is common in ecology, yet most methods do not adequately account for indirect interactions (where an interaction between two species is masked by their shared interactions with a third) and assume interactions do not vary along environmental gradients. Markov random fields (MRF) overcome these limitations by estimating interspecific interactions, while controlling for indirect interactions, from multispecies occurrence data. We illustrate the utility of MRFs for ecologists interested in interspecific interactions, and demonstrate how covariates can be included (a set of models known as Conditional Random Fields, CRF) to infer how interactions vary along environmental gradients. We apply CRFs to two data sets of presence-absence data. The first illustrates how blood parasite (Haemoproteus, Plasmodium, and nematode microfilaria spp.) co-infection probabilities covary with relative abundance of their avian hosts. The second shows that co-occurrences between mosquito larvae and predatory insects vary along water temperature gradients. Other applications are discussed, including the potential to identify replacement or shifting impacts of highly connected species along climate or land-use gradients. We provide tools for building CRFs and plotting/interpreting results as an R package.

Global spread of helminth parasites at the human-domestic animal-wildlife interface.

Changes in species distributions open novel parasite transmission routes at the human-wildlife interface, yet the strength of biotic and biogeographical factors that prevent or facilitate parasite host shifting are not well understood. We investigated global patterns of helminth parasite (Nematoda, Cestoda, Trematoda) sharing between mammalian wildlife species and domestic mammal hosts (including humans) using >24,000 unique country-level records of host-parasite associations. We used hierarchical modelling and species trait data to determine possible drivers of the level of parasite sharing between wildlife species and either humans or domestic animal hosts. We found the diet of wildlife species to be a strong predictor of levels of helminth parasite sharing with humans and domestic animals, followed by a moderate effect of zoogeographical region and minor effects of species' habitat and climatic niches. Combining model predictions with the distribution and ecological profile data of wildlife species, we projected global risk maps that uncovered strikingly similar patterns of wildlife parasite sharing across geographical areas for the different domestic host species (including humans). These similarities are largely explained by the fact that widespread parasites are commonly recorded infecting several domestic species. If the dietary profile and position in the trophic chain of a wildlife species largely drives its level of helminth parasite sharing with humans/domestic animals, future range shifts of host species that result in novel trophic interactions may likely increase parasite host shifting and have important ramifications for human and animal health.

Disentangling synergistic disease dynamics: Implications for the viral biocontrol of rabbits.

European rabbits (Oryctolagus cuniculus) have been exposed to rabbit haemorrhagic disease virus (RHDV) and myxoma virus (MYXV) in their native and invasive ranges for decades. Yet, the long-term effects of these viruses on rabbit population dynamics remain poorly understood. In this context, we analysed 17 years of detailed capture-mark-recapture data (2000-2016) from Turretfield, South Australia, using a probabilistic state-space hierarchical modelling framework to estimate rabbit survival and epidemiological dynamics. While RHDV infection and disease-induced death were most prominent during annual epidemics in winter and spring, we found evidence for continuous infection of susceptible individuals with RHDV throughout the year. RHDV-susceptible rabbits had, on average, 25% lower monthly survival rates compared to immune individuals, while the average monthly force of infection in winter and spring was ~38%. These combined to result in an average infection-induced mortality rate of 69% in winter and spring. Individuals susceptible to MYXV and immune to RHDV had similar survival probabilities to those having survived infections from both viruses, whereas individuals susceptible to both RHDV and MYXV had higher survival probabilities than those susceptible to RHDV and immune to MYXV. This suggests that MYXV may reduce the future survival rates of individuals that endure initial MYXV infection. There was no evidence for long-term changes in disease-induced mortality and infection rates for either RHDV or MYXV. We conclude that continuous, year-round virus perpetuation (and perhaps heterogeneity in modes of transmission and infectious doses during and after epidemics) acts to reduce the efficiency of RHDV and MYXV as biocontrol agents of rabbits in their invasive range. However, if virulence can be maintained as relatively constant through time, RHDV and MYXV will likely continue realizing strong benefits as biocontrol agents.

Infection of the fittest: devil facial tumour disease has greatest effect on individuals with highest reproductive output.

Emerging infectious diseases rarely affect all members of a population equally and determining how individuals' susceptibility to infection is related to other components of their fitness is critical to understanding disease impacts at a population level and for predicting evolutionary trajectories. We introduce a novel state-space model framework to investigate survival and fecundity of Tasmanian devils (Sarcophilus harrisii) affected by a transmissible cancer, devil facial tumour disease. We show that those devils that become host to tumours have otherwise greater fitness, with higher survival and fecundity rates prior to disease-induced death than non-host individuals that do not become infected, although high tumour loads lead to high mortality. Our finding that individuals with the greatest reproductive value are those most affected by the cancer demonstrates the need to quantify both survival and fecundity in context of disease progression for understanding the impact of disease on wildlife populations.

Euarchontan Opsin Variation Brings New Focus to Primate Origins.

Debate on the adaptive origins of primates has long focused on the functional ecology of the primate visual system. For example, it is hypothesized that variable expression of short- (SWS1) and middle-to-long-wavelength sensitive (M/LWS) opsins, which confer color vision, can be used to infer ancestral activity patterns and therefore selective ecological pressures. A problem with this approach is that opsin gene variation is incompletely known in the grandorder Euarchonta, that is, the orders Scandentia (treeshrews), Dermoptera (colugos), and Primates. The ancestral state of primate color vision is therefore uncertain. Here, we report on the genes (OPN1SW and OPN1LW) that encode SWS1 and M/LWS opsins in seven species of treeshrew, including the sole nocturnal scandentian Ptilocercus lowii. In addition, we examined the opsin genes of the Central American woolly opossum (Caluromys derbianus), an enduring ecological analogue in the debate on primate origins. Our results indicate: 1) retention of ultraviolet (UV) visual sensitivity in C. derbianus and a shift from UV to blue spectral sensitivities at the base of Euarchonta; 2) ancient pseudogenization of OPN1SW in the ancestors of P. lowii, but a signature of purifying selection in those of C. derbianus; and, 3) the absence of OPN1LW polymorphism among diurnal treeshrews. These findings suggest functional variation in the color vision of nocturnal mammals and a distinctive visual ecology of early primates, perhaps one that demanded greater spatial resolution under light levels that could support cone-mediated color discrimination.

Co-infections and environmental conditions drive the distributions of blood parasites in wild birds.

Experimental work increasingly suggests that non-random pathogen associations can affect the spread or severity of disease. Yet due to difficulties distinguishing and interpreting co-infections, evidence for the presence and directionality of pathogen co-occurrences in wildlife is rudimentary. We provide empirical evidence for pathogen co-occurrences by analysing infection matrices for avian malaria (Haemoproteus and Plasmodium spp.) and parasitic filarial nematodes (microfilariae) in wild birds (New Caledonian Zosterops spp.). Using visual and genus-specific molecular parasite screening, we identified high levels of co-infections that would have been missed using PCR alone. Avian malaria lineages were assigned to species level using morphological descriptions. We estimated parasite co-occurrence probabilities, while accounting for environmental predictors, in a hierarchical multivariate logistic regression. Co-infections occurred in 36% of infected birds. We identified both positively and negatively correlated parasite co-occurrence probabilities when accounting for host, habitat and island effects. Two of three pairwise avian malaria co-occurrences were strongly negative, despite each malaria parasite occurring across all islands and habitats. Birds with microfilariae had elevated heterophil to lymphocyte ratios and were all co-infected with avian malaria, consistent with evidence that host immune modulation by parasitic nematodes facilitates malaria co-infections. Importantly, co-occurrence patterns with microfilariae varied in direction among avian malaria species; two malaria parasites correlated positively but a third correlated negatively with microfilariae. We show that wildlife co-infections are frequent, possibly affecting infection rates through competition or facilitation. We argue that combining multiple diagnostic screening methods with multivariate logistic regression offers a platform to disentangle impacts of environmental factors and parasite co-occurrences on wildlife disease.

Tick exposure and extreme climate events impact survival and threaten the persistence of a long-lived lizard.

Assessing the impacts of multiple, often synergistic, stressors on the population dynamics of long-lived species is becoming increasingly important due to recent and future global change. Tiliqua rugosa (sleepy lizard) is a long-lived skink (>30 years) that is adapted to survive in semi-arid environments with varying levels of parasite exposure and highly seasonal food availability. We used an exhaustive database of 30 years of capture-mark-recapture records to quantify the impacts of both parasite exposure and environmental conditions on the lizard's survival rates and long-term population dynamics. Lizard abundance was relatively stable throughout the study period; however, there were changing patterns in adult and juvenile apparent survival rates, driven by spatial and temporal variation in levels of tick exposure and temporal variation in environmental conditions. Extreme weather events during the winter and spring seasons were identified as important environmental drivers of survival. Climate models predict a dramatic increase in the frequency of extreme hot and dry winter and spring seasons in our South Australian study region; from a contemporary probability of 0.17 up to 0.47-0.83 in 2080 depending on the emissions scenario. Our stochastic population model projections showed that these future climatic conditions will induce a decline in the abundance of this long-lived reptile of up to 67% within 30 years from 2080, under worst case scenario modelling. The results have broad implications for future work investigating the drivers of population dynamics and persistence. We highlight the importance of long-term data sets and accounting for synergistic impacts between multiple stressors. We show that predicted increases in the frequency of extreme climate events have the potential to considerably and negatively influence a long-lived species, which might previously have been assumed to be resilient to environmental perturbations.

Environmental effects and individual body condition drive seasonal fecundity of rabbits: identifying acute and lagged processes.

The reproduction of many species is determined by seasonally-driven resource supply. But it is difficult to quantify whether the fecundity is sensitive to short- or long-term exposure to environmental conditions such as rainfall that drive resource supply. Using 25 years of data on individual fecundity of European female rabbits, Oryctolagus cuniculus, from semiarid Australia, we investigate the role of individual body condition, rainfall and temperature as drivers of seasonal and long-term and population-level changes in fecundity (breeding probability, ovulation rate, embryo survival). We built distributed lag models in a hierarchical Bayesian framework to account for both immediate and time-lagged effects of climate and other environmental drivers, and possible shifts in reproduction over consecutive seasons. We show that rainfall during summer, when rabbits typically breed only rarely, increased breeding probability immediately and with time lags of up to 10 weeks. However, an earlier onset of the yearly breeding period did not result in more overall reproductive output. Better body condition was associated with an earlier onset of breeding and higher embryo survival. Breeding probability in the main breeding season declined with increased breeding activity in the preceding season and only individuals in good body condition were able to breed late in the season. Higher temperatures reduce breeding success across seasons. We conclude that a better understanding of seasonal dynamics and plasticity (and their interplay) in reproduction will provide crucial insights into how lagomorphs are likely to respond and potentially adapt to the influence of future climate and other environmental change.

A cyst-forming coccidian with large geographical range infecting forest and commensal rodents: Sarcocystis muricoelognathis sp. nov.

BACKGROUND: The geographic distribution and host-parasite interaction networks of Sarcocystis spp. in small mammals in eastern Asia remain incompletely known. METHODS: Experimental infections, morphological and molecular characterizations were used for discrimination of a new Sarcocystis species isolated from colubrid snakes and small mammals collected in Thailand, Borneo and China. RESULTS: We identified a new species, Sarcocystis muricoelognathis sp. nov., that features a relatively wide geographic distribution and infects both commensal and forest-inhabiting intermediate hosts. Sarcocystis sporocysts collected from rat snakes (Coelognathus radiatus, C. flavolineatus) in Thailand induced development of sarcocysts in experimental SD rats showing a type 10a cyst wall ultrastructure that was identical with those found in Rattus norvegicus from China and the forest rat Maxomys whiteheadi in Borneo. Its cystozoites had equal sizes in all intermediate hosts and locations, while sporocysts and cystozoites were distinct from other Sarcocystis species. Partial 28S rRNA sequences of S. muricoelognathis from M. whiteheadi were largely identical to those from R. norvegicus in China but distinct from newly sequenced Sarcocystis zuoi. The phylogeny of the nuclear 18S rRNA gene placed S. muricoelognathis within the so-called S. zuoi complex, including Sarcocystis attenuati, S. kani, S. scandentiborneensis and S. zuoi, while the latter clustered with the new species. However, the phylogeny of the ITS1-region confirmed the distinction between S. muricoelognathis and S. zuoi. Moreover, all three gene trees suggested that an isolate previously addressed as S. zuoi from Thailand (KU341120) is conspecific with S. muricoelognathis. Partial mitochondrial cox1 sequences of S. muricoelognathis were almost identical with those from other members of the group suggesting a shared, recent ancestry. Additionally, we isolated two partial 28S rRNA Sarcocystis sequences from Low's squirrel Sundasciurus lowii that clustered with those of S. scandentiborneensis from treeshews. CONCLUSIONS: Our results provide strong evidence of broad geographic distributions of rodent-associated Sarcocystis and host shifts between commensal and forest small mammal species, even if the known host associations remain likely only snapshots of the true associations.

Inferring host specificity and network formation through agent-based models: tick-mammal interactions in Borneo.

Patterns of host-parasite association are poorly understood in tropical forests. While we typically observe only snapshots of the diverse assemblages and interactions under variable conditions, there is a desire to make inferences about prevalence and host-specificity patterns. We studied the interaction of ticks with non-volant small mammals in forests of Borneo. We inferred the probability of species interactions from individual-level data in a multi-level Bayesian model that incorporated environmental covariates and advanced estimates for rarely observed species through model averaging. We estimated the likelihood of observing particular interaction frequencies under field conditions and a scenario of exhaustive sampling and examined the consequences for inferring host specificity. We recorded a total of 13 different tick species belonging to the five genera Amblyomma, Dermacentor, Haemaphysalis, Ixodes, and Rhipicephalus from a total of 37 different host species (Rodentia, Scandentia, Carnivora, Soricidae) on 237 out of 1,444 host individuals. Infestation probabilities revealed most variation across host species but less variation across tick species with three common rat and two tree shrew species being most heavily infested. Host species identity explained ca. 75 % of the variation in infestation probability and another 8-10 % was explained by local host abundance. Host traits and site-specific attributes had little explanatory power. Host specificity was estimated to be similarly low for all tick species, which were all likely to infest 34-37 host species if exhaustively sampled. By taking into consideration the hierarchical organization of individual interactions that may take place under variable conditions and that shape host-parasite networks, we can discern uncertainty and sampling bias from true interaction frequencies, whereas network attributes derived from observed values may lead to highly misleading results. Multi-level approaches may help to move this field towards inferential approaches for understanding mechanisms that shape the strength and dynamics in ecological networks.

Diet and the evolution of ADH7 across seven orders of mammals.

Dietary variation within and across species drives the eco-evolutionary responsiveness of genes necessary to metabolize nutrients and other components. Recent evidence from humans and other mammals suggests that sugar-rich diets of floral nectar and ripe fruit have favoured mutations in, and functional preservation of, the ADH7 gene, which encodes the ADH class 4 enzyme responsible for metabolizing ethanol. Here we interrogate a large, comparative dataset of ADH7 gene sequence variation, including that underlying the amino acid residue located at the key site (294) that regulates the affinity of ADH7 for ethanol. Our analyses span 171 mammal species, including 59 newly sequenced. We report extensive variation, especially among frugivorous and nectarivorous bats, with potential for functional impact. We also report widespread variation in the retention and probable pseudogenization of ADH7. However, we find little statistical evidence of an overarching impact of dietary behaviour on putative ADH7 function or presence of derived alleles at site 294 across mammals, which suggests that the evolution of ADH7 is shaped by complex factors. Our study reports extensive new diversity in a gene of longstanding ecological interest, offers new sources of variation to be explored in functional assays in future study, and advances our understanding of the processes of molecular evolution.

The supply of multiple ecosystem services requires biodiversity across spatial scales.

The impact of local biodiversity loss on ecosystem functioning is well established, but the role of larger-scale biodiversity dynamics in the delivery of ecosystem services remains poorly understood. Here we address this gap using a comprehensive dataset describing the supply of 16 cultural, regulating and provisioning ecosystem services in 150 European agricultural grassland plots, and detailed multi-scale data on land use and plant diversity. After controlling for land-use and abiotic factors, we show that both plot-level and surrounding plant diversity play an important role in the supply of cultural and aboveground regulating ecosystem services. In contrast, provisioning and belowground regulating ecosystem services are more strongly driven by field-level management and abiotic factors. Structural equation models revealed that surrounding plant diversity promotes ecosystem services both directly, probably by fostering the spill-over of ecosystem service providers from surrounding areas, and indirectly, by maintaining plot-level diversity. By influencing the ecosystem services that local stakeholders prioritized, biodiversity at different scales was also shown to positively influence a wide range of stakeholder groups. These results provide a comprehensive picture of which ecosystem services rely most strongly on biodiversity, and the respective scales of biodiversity that drive these services. This key information is required for the upscaling of biodiversity-ecosystem service relationships, and the informed management of biodiversity within agricultural landscapes.

Environmental factors affect Acidobacterial communities below the subgroup level in grassland and forest soils.

In soil, Acidobacteria constitute on average 20% of all bacteria, are highly diverse, and are physiologically active in situ. However, their individual functions and interactions with higher taxa in soil are still unknown. Here, potential effects of land use, soil properties, plant diversity, and soil nanofauna on acidobacterial community composition were studied by cultivation-independent methods in grassland and forest soils from three different regions in Germany. The analysis of 16S rRNA gene clone libraries representing all studied soils revealed that grassland soils were dominated by subgroup Gp6 and forest soils by subgroup Gp1 Acidobacteria. The analysis of a large number of sites (n = 57) by 16S rRNA gene fingerprinting methods (terminal restriction fragment length polymorphism [T-RFLP] and denaturing gradient gel electrophoresis [DGGE]) showed that Acidobacteria diversities differed between grassland and forest soils but also among the three different regions. Edaphic properties, such as pH, organic carbon, total nitrogen, C/N ratio, phosphorus, nitrate, ammonium, soil moisture, soil temperature, and soil respiration, had an impact on community composition as assessed by fingerprinting. However, interrelations with environmental parameters among subgroup terminal restriction fragments (T-RFs) differed significantly, e.g., different Gp1 T-RFs correlated positively or negatively with nitrogen content. Novel significant correlations of Acidobacteria subpopulations (i.e., individual populations within subgroups) with soil nanofauna and vascular plant diversity were revealed only by analysis of clone sequences. Thus, for detecting novel interrelations of environmental parameters with Acidobacteria, individual populations within subgroups have to be considered.

Ectoparasite infestation patterns of domestic dogs in suburban and rural areas in Borneo.

Domestic dogs, Canis lupus, have been one of the longest companions of humans and have introduced their own menagerie of parasites and pathogens into this relationship. Here, we investigate the parasitic load of 212 domestic dogs with fleas (Siphonaptera) chewing lice (Phthiraptera), and ticks (Acarina) along a gradient from rural areas with near-natural forest cover to suburban areas in Northern Borneo (Sabah, Malaysia). We used a spatially-explicit hierarchical Bayesian model that allowed us to impute missing data and to consider spatial structure in modelling dog infestation probability and parasite density. We collected a total of 1,968 fleas of two species, Ctenocephalides orientis and Ctenocephalides felis felis, from 195 dogs (prevalence, 92 %). Flea density was higher on dogs residing in houses made of bamboo or corrugated metal (increase of 40 % from the average) compared to timber or stone/compound houses. Host-dependent and landscape-level environmental variables and spatial structure only had a weak explanatory power. We found adults of the invasive chewing louse Heterodoxus spiniger on 42 dogs (20 %). The effect of housing conditions was opposite to those for fleas; lice were only found on dogs residing in stone or timber houses. We found ticks of the species Rhipicephalus sanguineus as well as Haemaphysalis bispinosa gp., Haemaphysalis cornigera, Haemaphysalis koenigsbergi, and Haemaphysalis semermis on 36 dogs (17 %). The most common tick species was R. sanguineus, recorded from 23 dogs. Tick infestations were highest on dogs using both plantation and forest areas (282 % increase in overall tick density of dogs using all habitat types). The infestation probability of dogs with lice and ticks decreased with elevation, most infestations occurred below 800 m above sea level. However, the density of lice and ticks revealed no spatial structure; infestation probability of dogs with these two groups revealed considerable autocorrelation. Our study shows that environmental conditions on the house level appeared to be more influential on flea and lice density whereas tick density was also influenced by habitat use. Infestation of dogs with Haemaphysalis ticks identified an important link between dogs and forest wildlife for potential pathogen transmission.

Disruption of Metapopulation Structure Reduces Tasmanian Devil Facial Tumour Disease Spread at the Expense of Abundance and Genetic Diversity.

Metapopulation structure plays a fundamental role in the persistence of wildlife populations. It can also drive the spread of infectious diseases and transmissible cancers such as the Tasmanian devil facial tumour disease (DFTD). While disrupting this structure can reduce disease spread, it can also impair host resilience by disrupting gene flow and colonisation dynamics. Using an individual-based metapopulation model we investigated the synergistic effects of host dispersal, disease transmission rate and inter-individual contact distance for transmission, on the spread and persistence of DFTD from local to regional scales. Disease spread, and the ensuing population declines, are synergistically determined by individuals' dispersal, disease transmission rate and within-population mixing. Transmission rates can be magnified by high dispersal and inter-individual transmission distance. The isolation of local populations effectively reduced metapopulation-level disease prevalence but caused severe declines in metapopulation size and genetic diversity. The relative position of managed (i.e., isolated) local populations had a significant effect on disease prevalence, highlighting the importance of considering metapopulation structure when implementing metapopulation-scale disease control measures. Our findings suggest that population isolation is not an ideal management method for preventing disease spread in species inhabiting already fragmented landscapes, where genetic diversity and extinction risk are already a concern.