A global synthesis of survival estimates for microbats

Accurate survival estimates are needed to construct robust population models, which are a powerful tool for understanding and predicting the fates of species under scenarios of environmental change. Microbats make up 17% of the global mammalian fauna, yet the processes that drive differences in demographics between species are poorly understood. We collected survival estimates for 44 microbat species from the literature and constructed a model to determine the effects of reproductive, feeding and demographic traits on survival. Our trait-based model indicated that bat species which produce more young per year exhibit lower apparent annual survival, as do males and juveniles compared with females and adults, respectively. Using 8 years of monitoring data for two Australian species, we demonstrate how knowledge about the effect of traits on survival can be incorporated into Bayesian survival analyses. This approach can be applied to any group and is not restricted to bats or even mammals. The incorporation of informative priors based on traits can allow for more timely construction of population models to support management decisions and actions.     

Statistical ecology comes of age

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.     

Proteomics search of influenza A viruses for adaptive mutations to human hosts

Evaluation of: Miotto O, Heiny AT, Albrecht R et al. Complete-proteome mapping of human influenza A adaptive mutations: implications for human transmissibility of zoonotic strains. PLoS ONE 5(2), e9025 (2010).

The emergence of an influenza pandemic is of great concern globally. It is, therefore, necessary to have a better understanding of the adaptation of influenza A viruses to humans. The mutation patterns affecting host tropism may provide information on the mechanisms and determinants of the host barrier. The work by Miotto et al. describes a catalog of mutations observed specifically in human influenza A viruses by analyzing almost 100,000 influenza A virus protein sequences. These sites may be important for host tropism and characteristic mutations of human influenza viruses may be required for efficient human-to-human transmission. The catalog can be used for genetic surveillance of zoonotic strains of the influenza A virus to determine their pandemic potential, as well as for basic research on the influenza A virus.     

Inferring macro‐ecological patterns from local presence/absence data

Biodiversity provides support for life, vital provisions, regulating services and has positive cultural impacts. It is therefore important to have accurate methods to measure biodiversity, in order to safeguard it when we discover it to be threatened. For practical reasons, biodiversity is usually measured at fine scales whereas diversity issues (e.g. conservation) interest regional or global scales. Moreover, biodiversity may change across spatial scales. It is therefore a key challenge to be able to translate local information on biodiversity into global patterns. Many databases give no information about the abundances of a species within an area, but only its occurrence in each of the surveyed plots. In this paper, we introduce an analytical framework (implemented in a ready‐to‐use R code) to infer species richness and abundances at large spatial scales in biodiversity‐rich ecosystems when species presence/absence information is available on various scattered samples (i.e. upscaling). This framework is based on the scale‐invariance property of the negative binomial. Our approach allows to infer and link within a unique framework important and well‐known biodiversity patterns of ecological theory, such as the species accumulation curve (SAC) and the relative species abundance (RSA) as well as a new emergent pattern, which is the relative species occupancy (RSO). Our estimates are robust and accurate, as confirmed by tests performed on both in silico‐generated and real forests. We demonstrate the accuracy of our predictions using data from two well‐studied forest stands. Moreover, we compared our results with other popular methods proposed in the literature to infer species richness from presence to absence data and we showed that our framework gives better estimates. It has thus important applications to biodiversity research and conservation practice.     

Long-term variation in influenza A virus prevalence and subtype diversity in migratory mallards in northern Europe

Data on long-term circulation of pathogens in wildlife populations are seldom collected, and hence understanding of spatial–temporal variation in prevalence and genotypes is limited. Here, we analysed a long-term surveillance series on influenza A virus (IAV) in mallards collected at an important migratory stopover site from 2002 to 2010, and characterized seasonal dynamics in virus prevalence and subtype diversity. Prevalence dynamics were influenced by year, but retained a common pattern for all years whereby prevalence was low in spring and summer, but increased in early autumn with a first peak in August, and a second more pronounced peak during October–November. A total of 74 haemagglutinin (HA)/neuraminidase (NA) combinations were isolated, including all NA and most HA (H1–H12) subtypes. The most common subtype combinations were H4N6, H1N1, H2N3, H5N2, H6N2 and H11N9, and showed a clear linkage between specific HA and NA subtypes. Furthermore, there was a temporal structuring of subtypes within seasons based on HA phylogenetic relatedness. Dissimilar HA subtypes tended to have different temporal occurrence within seasons, where the subtypes that dominated in early autumn were rare in late autumn, and vice versa. This suggests that build-up of herd immunity affected IAV dynamics in this system.     

Identifying biotic drivers of population dynamics in a benthic–pelagic community

Benthic species and communities are linked to pelagic zooplankton through life‐stages encompassing both benthic and pelagic habitats and through a mutual dependency on primary producers as a food source. Many zooplankton taxa contribute to the sedimentary system as benthic eggs. Our main aim was to investigate the nature of the population level biotic interactions between and within these two seemingly independent communities, both dependent on the pelagic primary production, while simultaneously accounting for environmental drivers (salinity, temperature, and oxygen conditions). To this end, we applied multivariate autoregressive state‐space models to long (1966–2007) time series of annual abundance data, comparing models with and without interspecific interactions, and models with and without environmental variables included. We were not able to detect any direct coupling between sediment‐dwelling benthic taxa and pelagic copepods and cladocerans on the annual scale, but the most parsimonious model indicated that interactions within the benthic community are important. There were also positive residual correlations between the copepods and cladocerans potentially reflecting the availability of a shared resource or similar seasonal dependence, whereas both groups tended to correlate negatively with the zoobenthic taxa. The most notable single interaction within the benthic community was a tendency for a negative effect of Limecola balthica on the amphipods Monoporeia affinis and Pontoporeia femorata which can help explain the observed decrease in amphipods due to increased competitive interference.     

Demography,education, and research trends in the interdisciplinary field of disease ecology

Micro‐ and macroparasites are a leading cause of mortality for humans, animals, and plants, and there is great need to understand their origins, transmission dynamics, and impacts. Disease ecology formed as an interdisciplinary field in the 1970s to fill this need and has recently rapidly grown in size and influence. Because interdisciplinary fields integrate diverse scientific expertise and training experiences, understanding their composition and research priorities is often difficult. Here, for the first time, we quantify the composition and educational experiences of a subset of disease ecology practitioners and identify topical trends in published research. We combined a large survey of self‐declared disease ecologists with a literature synthesis involving machine‐learning topic detection of over 18,500 disease ecology research articles. The number of graduate degrees earned by disease ecology practitioners has grown dramatically since the early 2000s. Similar to other science fields, we show that practitioners in disease ecology have diversified in the last decade in terms of gender identity and institution, with weaker diversification in race and ethnicity. Topic detection analysis revealed how the frequency of publications on certain topics has declined (e.g., HIV, serology), increased (e.g., the dilution effect, infectious disease in bats), remained relatively common (e.g., malaria ecology, influenza, vaccine research and development), or have consistently remained relatively infrequent (e.g., theoretical models, field experiments). Other topics, such as climate change, superspreading, emerging infectious diseases, and network analyses, have recently come to prominence. This study helps identify the major themes of disease ecology and demonstrates how publication frequency corresponds to emergent health and environmental threats. More broadly, our approach provides a framework to examine the composition and publication trends of other major research fields that cross traditional disciplinary boundaries.     

A hierarchical model for analyzing multisite individual-level disease surveillance data from multiple systems

Passive surveillance systems are widely used to monitor diseases occurrence over wide spatial areas due to their cost-effectiveness and integration into broadly distributed healthcare systems. However, such systems are generally associated with imperfect ascertainment of disease cases and with heterogeneous capture probabilities arising from factors such as differential access to care. Augmenting passive surveillance systems with other surveillance efforts provides a way to estimate the true number of incident cases. We develop a hierarchical modeling framework for analyzing data from multiple surveillance systems that allows for individual-level covariate-dependent heterogeneous capture probabilities, and borrows information across surveillance sites to improve estimation of the true number of incident cases. Inference is carried out via a two-stage Bayesian procedure. Simulation studies illustrated superior performance of the proposed approach with respect to bias, root mean square error, and coverage compared to a model that does not borrow information across sites. We applied the proposed model to data from three surveillance systems reporting pulmonary tuberculosis (PTB) cases in a major center of ongoing transmission in China. The analysis yielded bias-corrected estimates of PTB cases from the passive system and led to the identification of risk factors associated with PTB rates, as well as factors influencing the operating characteristics of the implemented surveillance systems.     

Association of swine influenza H1N1 pandemic virus(SIV-H1N1p) with porcine respiratory disease complex in sows from commercial pig farms in Colombia

Porcine respiratory disease complex(PRDC) is a serious health problem that mainly affects growing and finishing pigs. PRDC is caused by a combination of viral and bacterial agents, such as porcine reproductive and respiratory syndrome virus(PRRSV), swine influenza virus(SIV), Mycoplasma hyopneumoniae(Myh), Actinobacillus pleuropneumoniae(APP), Pasteurella multocida and Porcine circovirus 2(PCV2). To characterize the specific role of swine influenza virus in PRDC presentation in Colombia, 11 farms from three major production regions in Colombia were examined in this study. Nasal swabs, bronchial lavage and lung tissue samples were obtained from animals displaying symptoms compatible with SIV. Isolation of SIV was performed in 9-day embryonated chicken eggs or Madin-Darby Canine Kidney(MDCK) cells. Positive isolates, identified via the hemagglutination inhibition test, were further analyzed using PCR. Overall, 7 of the 11 farms were positive for SIV. Notably, sequencing of the gene encoding the hemagglutinin(HA) protein led to grouping of strains into circulating viruses identified during the human outbreak of 2009, classified as pandemic H1N1-2009. Serum samples from 198 gilts and multiparous sows between 2008 and 2009 were obtained to determine antibody presence of APP, Myh, PCV2 and PRRSV in both SIV-H1N1p-negative and-positive farms, but higher levels were recorded for SIV-H1N1p-positive farms. Odds ratio(OR) and P values revealed statistically significant differences(p0.05) in PRDC presentation in gilts and multiparous sows of farms positive for SIV-H1N1 p. Our findings indicate that positive farms have increased risk of PRDC presentation, in particular, PCV2, APP and Myh.     

Beyond lifetime reproductive success: the posthumous reproductive dynamics of male Trinidadian guppies

In semelparous populations, dormant germ banks (e.g. seeds) have been proposed as important in maintaining genotypes that are adaptive at different times in fluctuating environments. Such hidden storage of genetic diversity need not be exclusive to dormant banks. Genotype diversity may be preserved in many iteroparous animals through sperm-storage mechanisms in females. This allows males to reproduce posthumously and increase the effective sizes of seemingly female-biased populations. Although long-term sperm storage has been demonstrated in many organisms, the understanding of its importance in the wild is very poor. We here show the prevalence of male posthumous reproduction in wild Trinidadian guppies, through the combination of mark–recapture and pedigree analyses of a multigenerational individual-based dataset. A significant proportion of the reproductive population consisted of dead males, who could conceive up to 10 months after death (the maximum allowed by the length of the dataset), which is more than twice the estimated generation time. Demographic analysis shows that the fecundity of dead males can play an important role in population growth and selection.     

Association of swine influenza HIN1 pandemic virus （SIV- HINlp） with porcine respiratory disease complex in sows from commercial pig farms in Colombia

Porcine respiratory disease complex （PRDC） is a serious health problem that mainly affects growing and finishing pigs. PRDC is caused by a combination of viral and bacterial agents, such as porcine reproductive and respiratory syndrome virus （PRRSV）, swine influenza virus （SIV）, Mycoplasma hyopneumoniae （Myh）, Actinobacillus pleuropneumoniae （APP）, Pasteurella multocida and Porcine circovirus 2 （PCV2）. To characterize the specific role of swine influenza virus in PRDC presentation in Colombia, 11 farms from three major production regions in Colombia were examined in this study. Nasal swabs, bronchial lavage and lung tissue samples were obtained from animals displaying symptoms compatible with SIV. Isolation of SIV was performed in 9-day embryonated chicken eggs or Madin-Darby Canine Kidney （MDCK） cells. Positive isolates, identified via the hemagglutination inhibition test, were further analyzed using PCR. Overall, 7 of the 11 farms were positive for SIV. Notably, sequencing of the gene encoding the hemagglutinin （HA） protein led to grouping of strains into circulating viruses identified during the human outbreak of 2009, classified as pandemic H1N1-2009. Serum samples from 198 gilts and multiparous sows between 2008 and 2009 were obtained to determine antibody presence of APP, Myh, PCV2 and PRRSV in both SIV-H1Nlp-negative and -positive farms, but higher levels were recorded for SIV- HI Nlp-positive farms. Odds ratio （OR） and P values revealed statistically significant differences （p〈0.05） in PRDC presentation in gilts and multiparous sows of farms positive for SIV-HINlp. Our findings indicate that positive farms have increased risk of PRDC presentation, in particular, PCV2, APP and Myh.     

Reassortant swine influenza viruses isolated in Japan contain genes from pandemic A(H1N1) 2009

In 2013, three reassortant swine influenza viruses (SIVs)—two H1N2 and one H3N2—were isolated from symptomatic pigs in Japan; each contained genes from the pandemic A(H1N1) 2009 virus and endemic SIVs. Phylogenetic analysis revealed that the two H1N2 viruses, A/swine/Gunma/1/2013 and A/swine/Ibaraki/1/2013, were reassortants that contain genes from the following three distinct lineages: (i) H1 and nucleoprotein (NP) genes derived from a classical swine H1 HA lineage uniquely circulating among Japanese SIVs; (ii) neuraminidase (NA) genes from human‐like H1N2 swine viruses; and (iii) other genes from pandemic A(H1N1) 2009 viruses. The H3N2 virus, A/swine/Miyazaki/2/2013, comprised genes from two sources: (i) hemagglutinin (HA) and NA genes derived from human and human‐like H3N2 swine viruses and (ii) other genes from pandemic A(H1N1) 2009 viruses. Phylogenetic analysis also indicated that each of the reassortants may have arisen independently in Japanese pigs. A/swine/Miyazaki/2/2013 were found to have strong antigenic reactivities with antisera generated for some seasonal human‐lineage viruses isolated during or before 2003, whereas A/swine/Miyazaki/2/2013 reactivities with antisera against viruses isolated after 2004 were clearly weaker. In addition, antisera against some strains of seasonal human‐lineage H1 viruses did not react with either A/swine/Gunma/1/2013 or A/swine/Ibaraki/1/2013. These findings indicate that emergence and spread of these reassortant SIVs is a potential public health risk.     

Spatial and seasonal patterns of fish assemblages in mountain streams of the Ren River,southwest China

The spatial–temporal patterns of fish assemblages in lotic systems can provide useful information in developing effective conservation measures. This study aimed to explore the spatial and seasonal changes in fish assemblages and their association with environmental factors in mountain streams of the Ren River, southwest China. Field investigations were conducted at 18 sites during the rainy and dry seasons in 2017. A total of 1,330 individuals, belonging to three orders, eight families, 19 genera, and 21 species, were collected. Analysis of similarities (ANOSIM) showed that the structure of fish assemblages varied significantly at the spatial scale, but not at the seasonal scale. In low‐order sites, fish assemblages were mainly dominated by cold‐water and rheophilic species (e.g., Rhynchocypris oxycephalus, Scaphesthes macrolepis, Metahomaloptera omeiensis, and Gnathopogon herzensteini), while those in high‐order sites were predominated by warm‐water and eurytopic or stagnophilic species (e.g., Squalidus argentatus, Hemiculter leucisculus, and Zacco platypus). Canonical correspondence analysis (CCA) showed that the fish assemblages were structured by a combination of large‐scale landscape factors (e.g., altitude and C‐link) and small‐scale habitat features (e.g., channel width, water temperature, and depth). Among these factors, landscape had the greatest influence on fish assemblages, while local habitat variables were less important or were only significant in certain seasons.     

Genetic characterization of swine influenza viruses isolated in Japan between 2009 and 2012

Eleven swine influenza viruses (SIVs) isolated from pigs in Japanese institutions between 2009 and 2012 were genetically characterized. Seven H1N1 were shown to have originated from A(H1N1)pdm09 viruses. Two H1N2 viruses contained H1 and N2 genes of Japanese H1N2 SIV origin together with internal genes of A(H1N1)pdm09 viruses. Two H3N2 viruses isolated during animal quarantine were identified as triple reassortant H3N2 viruses maintained among pigs in North America. This study shows that A(H1N1)pdm09 viruses and their reassortant strains are already present in domestic pigs in Japan and that novel SIVs are possibly being imported from abroad.     

Demonstrating frequency-dependent transmission of sarcoptic mange in red foxes

Understanding the relationship between disease transmission and host density is essential for predicting disease spread and control. Using long-term data on sarcoptic mange in a red fox Vulpes vulpes population, we tested long-held assumptions of density- and frequency-dependent direct disease transmission. We also assessed the role of indirect transmission. Contrary to assumptions typical of epidemiological models, mange dynamics are better explained by frequency-dependent disease transmission than by density-dependent transmission in this canid. We found no support for indirect transmission. We present the first estimates of R₀ and age-specific transmission coefficients for mange in foxes. These parameters are important for managing this poorly understood but highly contagious and economically damaging disease.     

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.     

Competition for resources can explain patterns of social and individual learning in nature

In nature, animals often ignore socially available information despite the multiple theoretical benefits of social learning over individual trial-and-error learning. Using information filtered by others is quicker, more efficient and less risky than randomly sampling the environment. To explain the mix of social and individual learning used by animals in nature, most models penalize the quality of socially derived information as either out of date, of poor fidelity or costly to acquire. Competition for limited resources, a fundamental evolutionary force, provides a compelling, yet hitherto overlooked, explanation for the evolution of mixed-learning strategies. We present a novel model of social learning that incorporates competition and demonstrates that (i) social learning is favoured when competition is weak, but (ii) if competition is strong social learning is favoured only when resource quality is highly variable and there is low environmental turnover. The frequency of social learning in our model always evolves until it reduces the mean foraging success of the population. The results of our model are consistent with empirical studies showing that individuals rely less on social information where resources vary little in quality and where there is high within-patch competition. Our model provides a framework for understanding the evolution of social learning, a prerequisite for human cumulative culture.     

Interannual patterns of avian diseases in wild New Zealand avifauna near conservation areas

The past few years have seen a noticeable increase in the emergence of infectious diseases in wildlife, especially vector-borne diseases, presenting a challenge for the conservation of endangered species. One such vector-borne disease, avian malaria (Plasmodium spp.) is on the rise in New Zealand avifauna, threatening bird populations that are among the most extinction-prone in the world. Furthermore, recent reports have outlined an increase in deaths of native iconic bird species specifically due to this disease. In order to help manage breakouts of this pathogen at a local scale, we need a better understanding of potential drivers of the emergence of avian malaria in wild New Zealand avifauna. Here, we set to test the role of climatic drivers in synchronizing contacts between avian hosts and vectors, assess the temporal stability of transmission dynamics between years, and determine the role of introduced species in causing spill-over of this pathogen towards native species. Our study focused on three sites that were sampled regularly during two consecutive years in the austral summer, each site being adjacent to a breeding colony of Yellow-eyed penguins (Megadyptes antipodes). Our results reveal an overall temporal stability of avian malaria incidence patterns, with a decrease in infection throughout the austral summer for both sampled years. Moreover, we highlight a phylogenetic signal among sampled bird species, with introduced species being more heavily infected by avian malaria than their native counterparts. In contrast, we found no effect of the two climatic drivers investigated, temperature and rainfall, on mosquito abundance. Our results suggest a strong effect of alien species acting as reservoirs for diseases spilling-over towards immunologically naïve species, and provide conservation managers with a critical timeframe to control avian malaria breakouts.     

Integrating high‐speed videos in capture‐mark‐recapture studies of insects

Capture–mark–recapture (CMR) studies have been used extensively in ecology and evolution. While it is feasible to apply CMR in some animals, it is considerably more challenging in small fast‐moving species such as insects. In these groups, low recapture rates can bias estimates of demographic parameters, thereby handicapping effective analysis and management of wild populations. Here, we use high‐speed videos (HSV) to capture two large dragonfly species, Anax junius and Rhionaeschna multicolor, that rarely land and, thus, are particularly challenging for CMR studies. We test whether HSV, compared to conventional “eye” observations, increases the “resighting” rates and, consequently, improves estimates of both survival rates and the effects of demographic covariates on survival. We show that the use of HSV increases the number of resights by 64% in A. junius and 48% in R. multicolor. HSV improved our estimates of resighting and survival probability which were either under‐ or overestimated with the conventional observations. Including HSV improved credible intervals for resighting rate and survival probability by 190% and 130% in A. junius and R. multicolor, respectively. Hence, it has the potential to open the door to a wide range of research possibilities on species that are traditionally difficult to monitor with distance sampling, including within insects and birds.