Immunogenetic response of the bananaquit in the face of malarial parasites.

BACKGROUND: In the arms race between hosts and parasites, genes involved in the immune response are targets for natural selection. Toll-Like Receptor (TLR) genes play a role in parasite detection as part of the innate immune system whereas Major Histocompatibility Complex (MHC) genes encode proteins that display antigens as part of the vertebrate adaptive immune system. Thus, both gene families are under selection pressure from pathogens. The bananaquit (Coereba flaveola) is a passerine bird that is a common host of avian malarial parasites (Plasmodium sp. and Haemoproteus sp.). We assessed molecular variation of TLR and MHC genes in a wild population of bananaquits and identified allelic associations with resistance/susceptibility to parasitic infection to address hypotheses of avian immune response to haemosporidian parasites. RESULTS: We found that allele frequencies are associated with infection status at the immune loci studied. A consistent general trend showed the infected groups possessed more alleles at lower frequencies, and exhibited unique alleles, compared to the uninfected group. CONCLUSIONS: Our results support the theory of natural selection favoring particular alleles for resistance while maintaining overall genetic diversity in the population, a mechanism which has been demonstrated in some systems in MHC previously but understudied in TLRs.

Accumulation over evolutionary time as a major cause of biodiversity hotspots in conifers.

Biodiversity hotspots are important for understanding how areas of high species richness form, but disentangling the processes that produce them is difficult. We combine geographical ranges, phylogenetic relationships and trait data for 606 conifer species in order to explore the mechanisms underlying richness hotspot formation. We identify eight richness hotspots that overlap known centres of plant endemism and diversity, and find that conifer richness hotspots occur in mountainous areas within broader regions of long-term climate stability. Conifer hotspots are not unique in their species composition, traits or phylogenetic structure; however, a large percentage of their species are not restricted to hotspots and they rarely show either a preponderance of new radiating lineages or old relictual lineages. We suggest that conifer hotspots have primarily formed as a result of lineages accumulating over evolutionary time scales in stable mountainous areas rather than through high origination, preferential retention of relictual lineages or radiation of species with unique traits, although such processes may contribute to nuanced differences among hotspots. Conifers suggest that a simple accumulation of regional diversity can generate high species richness without additional processes and that geography rather than biology may play a primary role in hotspot formation.

Preliminary Investigation of Schmalhausen's Law in a Directly Transmitted Pathogen Outbreak System.

The past few decades have been marked by drastic modifications to the landscape by anthropogenic processes, leading to increased variability in the environment. For populations that thrive at their distributional boundaries, these changes can affect them drastically, as Schmalhausen's law predicts that their dynamics are more likely to be susceptible to environmental variation. Recently, this evolutionary theory has been put to the test in vector-borne disease emergences systems, and has been demonstrated effective in predicting emergence patterns. However, it has yet to be tested in a directly transmitted pathogen. Here, we provide a preliminary test of Schmalhausen's law using data on Marburg virus outbreaks originating from spillover events. By combining the two important aspects of Schmalhausen's law, namely climatic anomalies and distance to species distributional edges, we show that Marburgvirus outbreaks may support an aspect of this evolutionary theory, with distance to species distributional edge having a weak influence on outbreak size. However, we failed to demonstrate any effect of climatic anomalies on Marburgvirus outbreaks, arguably related to the lack of importance of these variables in directly transmitted pathogen outbreaks. With increasing zoonotic spillover events occurring from wild species, we highlight the importance of considering ecological variability to better predict emergence patterns.

Remotely sensed environmental measurements detect decoupled processes driving population dynamics at contrasting scales.

The increasing availability of satellite imagery has supported a rapid expansion in forward-looking studies seeking to track and predict how climate change will influence wild population dynamics. However, these data can also be used in retrospect to provide additional context for historical data in the absence of contemporaneous environmental measurements. We used 167 Landsat-5 Thematic Mapper (TM) images spanning 13 years to identify environmental drivers of fitness and population size in a well-characterized population of banner-tailed kangaroo rats (Dipodomys spectabilis) in the southwestern United States. We found evidence of two decoupled processes that may be driving population dynamics in opposing directions over distinct time frames. Specifically, increasing mean surface temperature corresponded to increased individual fitness, where fitness is defined as the number of offspring produced by a single individual. This result contrasts with our findings for population size, where increasing surface temperature led to decreased numbers of active mounds. These relationships between surface temperature and (i) individual fitness and (ii) population size would not have been identified in the absence of remotely sensed data, indicating that such information can be used to test existing hypotheses and generate new ecological predictions regarding fitness at multiple spatial scales and degrees of sampling effort. To our knowledge, this study is the first to directly link remotely sensed environmental data to individual fitness in a nearly exhaustively sampled population, opening a new avenue for incorporating remote sensing data into eco-evolutionary studies.

Footprint of war: integrating armed conflicts in disease ecology.

War is an understudied and yet significant contributor to disease outbreaks, necessitating approaches incorporating conflicts into disease studies. We discuss mechanisms by which war affects disease dynamics, and supply an illustrative example. Lastly, we provide relevant data sources and pathways for incorporating metrics of armed conflict into disease ecology.

Traits, phylogeny and host cell receptors predict Ebolavirus host status among African mammals.

We explore how animal host traits, phylogenetic identity and cell receptor sequences relate to infection status and mortality from ebolaviruses. We gathered exhaustive databases of mortality from Ebolavirus after exposure and infection status based on PCR and antibody tests. We performed ridge regressions predicting mortality and infection as a function of traits, phylogenetic eigenvectors and separately host receptor sequences. We found that mortality from Ebolavirus had a strong association to life history characteristics and phylogeny. In contrast, infection status related not just to life history and phylogeny, but also to fruit consumption which suggests that geographic overlap of frugivorous mammals can lead to spread of virus in the wild. Niemann Pick C1 (NPC1) receptor sequences predicted infection statuses of bats included in our study with very high accuracy, suggesting that characterizing NPC1 in additional species is a promising avenue for future work. We combine the predictions from our mortality and infection status models to differentiate between species that are infected and also die from Ebolavirus versus species that are infected but tolerate the virus (possible reservoirs of Ebolavirus). We therefore present the first comprehensive estimates of Ebolavirus reservoir statuses for all known terrestrial mammals in Africa.

Drivers of African Filovirus (Ebola and Marburg) Outbreaks.

Outbreaks of African filoviruses often have high mortality, including more than 11,000 deaths among 28,562 cases during the West Africa Ebola outbreak of 2014-2016. Numerous studies have investigated the factors that contributed to individual filovirus outbreaks, but there has been little quantitative synthesis of this work. In addition, the ways in which the typical causes of filovirus outbreaks differ from other zoonoses remain poorly described. In this study, we quantify factors associated with 45 outbreaks of African filoviruses (ebolaviruses and Marburg virus) using a rubric of 48 candidate causal drivers. For filovirus outbreaks, we reviewed >700 peer-reviewed and gray literature sources and developed a list of the factors reported to contribute to each outbreak (i.e., a "driver profile" for each outbreak). We compare and contrast the profiles of filovirus outbreaks to 200 background outbreaks, randomly selected from a global database of 4463 outbreaks of bacterial and viral zoonotic diseases. We also test whether the quantitative patterns that we observed were robust to the influences of six covariates, country-level factors such as gross domestic product, population density, and latitude that have been shown to bias global outbreak data. We find that, regardless of whether covariates are included or excluded from models, the driver profile of filovirus outbreaks differs from that of background outbreaks. Socioeconomic factors such as trade and travel, wild game consumption, failures of medical procedures, and deficiencies in human health infrastructure were more frequently reported in filovirus outbreaks than in the comparison group. Based on our results, we also present a review of drivers reported in at least 10% of filovirus outbreaks, with examples of each provided.

Comparison of Minimally Invasive Monitoring Methods and Live Trapping in Mammals.

The conservation and management of wildlife requires the accurate assessment of wildlife population sizes. However, there is a lack of synthesis of research that compares methods used to estimate population size in the wild. Using a meta-analysis approach, we compared the number of detected individuals in a study made using live trapping and less invasive approaches, such as camera trapping and genetic identification. We scanned 668 papers related to these methods and identified data for 44 populations (all focused on mammals) wherein at least two methods (live trapping, camera trapping, genetic identification) were used. We used these data to quantify the difference in number of individuals detected using trapping and less invasive methods using a regression and used the residuals from each regression to evaluate potential drivers of these trends. We found that both trapping and less invasive methods (camera traps and genetic analyses) produced similar estimates overall, but less invasive methods tended to detect more individuals compared to trapping efforts (mean = 3.17 more individuals). We also found that the method by which camera data are analyzed can significantly alter estimates of population size, such that the inclusion of spatial information was related to larger population size estimates. Finally, we compared counts of individuals made using camera traps and genetic data and found that estimates were similar but that genetic approaches identified more individuals on average (mean = 9.07 individuals). Overall, our data suggest that all of the methods used in the studies we reviewed detected similar numbers of individuals. As live trapping can be more costly than less invasive methods and can pose more risk to animal well-fare, we suggest minimally invasive methods are preferable for population monitoring when less-invasive methods can be deployed efficiently.

Mechanisms underlying detection of seed dormancy by a scatter-hoarding rodent.

The mechanism underlying detection of seed dormancy by scatter-hoarding rodents is unclear, although previous work suggests that the pericarp plays an important role in signaling dormancy status. Eastern gray squirrels (Sciurus carolinensis) consume early germinating seeds as they are more likely to perish immediately, whereas dormant seeds tend to be cached. To examine the mechanisms underlying dormancy detection, we characterized physical and chemical differences between germinating and dormant pericarps of northern red oak (Quercus rubra), American chestnut (Castanea dentata) and the BC3 hybrid of Chinese chestnut and American chestnut (Castanea mollissima × C. dentata) using scanning electron microscopy and gas chromatography- mass spectrometry. We found that, as seeds break dormancy, the wax layer on the pericarp degrades and is accompanied by the escape of lower molecular weight kernel compounds or lipid metabolism byproducts. Our field experiments showed that squirrels were 4-8 times more likely to consume seeds that were altered to remove pericarp wax coating or that were sprayed with seed chemicals. We argue that dormancy detection by scatter-hoarding rodents is a complex process involving physical cues such as loss of pericarp wax and chemical cues such as emission of olfactory cues.

Eastern gray squirrels are consistent shoppers of seed traits: insights from discrete choice experiments.

Seeds of many hardwood trees are dispersed by scatter-hoarding rodents, and this process is often mediated by the traits of seeds. Although numerous studies have linked seed traits to seed preference by rodents, little is known about how rodents forage for seeds when multiple desirable and undesirable seed traits are available simultaneously. Here, we adopt a novel method of designing choice experiments to study how eastern gray squirrels (Sciurus carolinensis) select for 6 traits (caloric value, protein content, tannin concentration, kernel mass, dormancy period and toughness of shell) among seeds. From n = 426 seed-pair presentations, we found that squirrels preferentially consumed seeds with short dormancy or tougher shells, and preferentially cached seeds with larger kernel mass, tougher shells and higher tannin concentrations. By incorporating random effects, we found that squirrels exhibited consistent preferences for seed traits, which is likely due to the fitness consequences associated with maintaining cached resources. Furthermore, we found that squirrels were willing to trade between multiple traits when caching seeds, which likely results in more seed species being cached in the fall. Ultimately, our approach allowed us to compute the relative values of different seed traits to squirrels, despite covariance among studied traits across seed species. In addition, by investigating how squirrels trade among different seed traits, important insights can be gleaned into behavioral mechanisms underlying seed caching (and, thus, seed survival) dynamics as well as evolutionary strategies adopted by plants to attract seed dispersers. We describe how discrete choice experiments can be used to study resource selection in other ecological systems.

Performance Benchmarks for Scholarly Metrics Associated with Fisheries and Wildlife Faculty.

Research productivity and impact are often considered in professional evaluations of academics, and performance metrics based on publications and citations increasingly are used in such evaluations. To promote evidence-based and informed use of these metrics, we collected publication and citation data for 437 tenure-track faculty members at 33 research-extensive universities in the United States belonging to the National Association of University Fisheries and Wildlife Programs. For each faculty member, we computed 8 commonly used performance metrics based on numbers of publications and citations, and recorded covariates including academic age (time since Ph.D.), sex, percentage of appointment devoted to research, and the sub-disciplinary research focus. Standardized deviance residuals from regression models were used to compare faculty after accounting for variation in performance due to these covariates. We also aggregated residuals to enable comparison across universities. Finally, we tested for temporal trends in citation practices to assess whether the "law of constant ratios", used to enable comparison of performance metrics between disciplines that differ in citation and publication practices, applied to fisheries and wildlife sub-disciplines when mapped to Web of Science Journal Citation Report categories. Our regression models reduced deviance by » to ½. Standardized residuals for each faculty member, when combined across metrics as a simple average or weighted via factor analysis, produced similar results in terms of performance based on percentile rankings. Significant variation was observed in scholarly performance across universities, after accounting for the influence of covariates. In contrast to findings for other disciplines, normalized citation ratios for fisheries and wildlife sub-disciplines increased across years. Increases were comparable for all sub-disciplines except ecology. We discuss the advantages and limitations of our methods, illustrate their use when applied to new data, and suggest future improvements. Our benchmarking approach may provide a useful tool to augment detailed, qualitative assessment of performance.

The importance of including imperfect detection models in eDNA experimental design.

Environmental DNA (eDNA) is DNA that has been isolated from field samples, and it is increasingly used to infer the presence or absence of particular species in an ecosystem. However, the combination of sampling procedures and subsequent molecular amplification of eDNA can lead to spurious results. As such, it is imperative that eDNA studies include a statistical framework for interpreting eDNA presence/absence data. We reviewed published literature for studies that utilized eDNA where the species density was known and compared the probability of detecting the focal species to the sampling and analysis protocols. Although biomass of the target species and the volume per sample did not impact detectability, the number of field replicates and number of samples from each replicate were positively related to detection. Additionally, increased number of PCR replicates and increased primer specificity significantly increased detectability. Accordingly, we advocate for increased use of occupancy modelling as a method to incorporate effects of sampling effort and PCR sensitivity in eDNA study design. Based on simulation results and the hierarchical nature of occupancy models, we suggest that field replicates, as opposed to molecular replicates, result in better detection probabilities of target species.

Segregating the Effects of Seed Traits and Common Ancestry of Hardwood Trees on Eastern Gray Squirrel Foraging Decisions.

The evolution of specific seed traits in scatter-hoarded tree species often has been attributed to granivore foraging behavior. However, the degree to which foraging investments and seed traits correlate with phylogenetic relationships among trees remains unexplored. We presented seeds of 23 different hardwood tree species (families Betulaceae, Fagaceae, Juglandaceae) to eastern gray squirrels (Sciurus carolinensis), and measured the time and distance travelled by squirrels that consumed or cached each seed. We estimated 11 physical and chemical seed traits for each species, and the phylogenetic relationships between the 23 hardwood trees. Variance partitioning revealed that considerable variation in foraging investment was attributable to seed traits alone (27-73%), and combined effects of seed traits and phylogeny of hardwood trees (5-55%). A phylogenetic PCA (pPCA) on seed traits and tree phylogeny resulted in 2 "global" axes of traits that were phylogenetically autocorrelated at the family and genus level and a third "local" axis in which traits were not phylogenetically autocorrelated. Collectively, these axes explained 30-76% of the variation in squirrel foraging investments. The first global pPCA axis, which produced large scores for seed species with thin shells, low lipid and high carbohydrate content, was negatively related to time to consume and cache seeds and travel distance to cache. The second global pPCA axis, which produced large scores for seeds with high protein, low tannin and low dormancy levels, was an important predictor of consumption time only. The local pPCA axis primarily reflected kernel mass. Although it explained only 12% of the variation in trait space and was not autocorrelated among phylogenetic clades, the local axis was related to all four squirrel foraging investments. Squirrel foraging behaviors are influenced by a combination of phylogenetically conserved and more evolutionarily labile seed traits that is consistent with a weak or more diffuse coevolutionary relationship between rodents and hardwood trees rather than a direct coevolutionary relationship.