Ordinal Probit Functional Regression Models with Application to Computer-Use Behavior in Rhesus Monkeys

Research in functional regression has made great strides in expanding to non-Gaussian functional outcomes, however the exploration of ordinal functional outcomes remains limited. Motivated by a study of computer-use behavior in rhesus macaques (\emph{Macaca mulatta}), we introduce the Ordinal Probit Functional Regression Model or OPFRM to perform ordinal function-on-scalar regression. The OPFRM is flexibly formulated to allow for the choice of different basis functions including penalized B-splines, wavelets, and O'Sullivan splines. We demonstrate the operating characteristics of the model in simulation using a variety of underlying covariance patterns showing the model performs reasonably well in estimation under multiple basis functions. We also present and compare two approaches for conducting posterior inference showing that joint credible intervals tend to out perform point-wise credible. Finally, in application, we determine demographic factors associated with the monkeys' computer use over the course of a year and provide a brief analysis of the findings

So near and yet so far: Harmonic radar reveals reduced homing ability of nosema infected honeybees

Pathogens may gain a fitness advantage through manipulation of the behaviour of their hosts. Likewise, host behavioural changes can be a defence mechanism, counteracting the impact of pathogens on host fitness. We apply harmonic radar technology to characterize the impact of an emerging pathogen - Nosema ceranae (Microsporidia) - on honeybee (Apis mellifera) flight and orientation performance in the field. Honeybees are the most important commercial pollinators. Emerging diseases have been proposed to play a prominent role in colony decline, partly through sub-lethal behavioural manipulation of their hosts. We found that homing success was significantly reduced in diseased (65.8%) versus healthy foragers (92.5%). Although lost bees had significantly reduced continuous flight times and prolonged resting times, other flight characteristics and navigational abilities showed no significant difference between infected and non-infected bees. Our results suggest that infected bees express normal flight characteristics but are constrained in their homing ability, potentially compromising the colony by reducing its resource inputs, but also counteracting the intra-colony spread of infection. We provide the first high-resolution analysis of sub-lethal effects of an emerging disease on insect flight behaviour. The potential causes and the implications for both host and parasite are discussed

So near and yet so far: Harmonic radar reveals reduced homing ability of nosema infected honeybees

Pathogens may gain a fitness advantage through manipulation of the behaviour of their hosts. Likewise, host behavioural changes can be a defence mechanism, counteracting the impact of pathogens on host fitness. We apply harmonic radar technology to characterize the impact of an emerging pathogen - Nosema ceranae (Microsporidia) - on honeybee (Apis mellifera) flight and orientation performance in the field. Honeybees are the most important commercial pollinators. Emerging diseases have been proposed to play a prominent role in colony decline, partly through sub-lethal behavioural manipulation of their hosts. We found that homing success was significantly reduced in diseased (65.8%) versus healthy foragers (92.5%). Although lost bees had significantly reduced continuous flight times and prolonged resting times, other flight characteristics and navigational abilities showed no significant difference between infected and non-infected bees. Our results suggest that infected bees express normal flight characteristics but are constrained in their homing ability, potentially compromising the colony by reducing its resource inputs, but also counteracting the intra-colony spread of infection. We provide the first high-resolution analysis of sub-lethal effects of an emerging disease on insect flight behaviour. The potential causes and the implications for both host and parasite are discussed

widespread cross-infection of multiple RNA viruses across wild and managed bees

Declining populations of bee pollinators are a cause of concern, with major repercussions for biodiversity loss and food security. RNA viruses associated with honeybees represent a potential threat to other insect pollinators, but the extent of this threat is poorly understood. This study aims to attain a detailed understanding of the current and ongoing risk of emerging infectious disease (EID) transmission between managed and wild pollinator species across a wide range of RNA viruses. Within a structured large-scale national survey across 26 independent sites, we quantify the prevalence and pathogen loads of multiple RNA viruses in co-occurring managed honeybee (Apis mellifera) and wild bumblebee (Bombus spp.) populations. We then construct models that compare virus prevalence between wild and managed pollinators. Multiple RNA viruses associated with honeybees are widespread in sympatric wild bumblebee populations. Virus prevalence in honeybees is a significant predictor of virus prevalence in bumblebees, but we remain cautious in speculating over the principle direction of pathogen transmission. We demonstrate species-specific differences in prevalence, indicating significant variation in disease susceptibility or tolerance. Pathogen loads within individual bumblebees may be high and in the case of at least one RNA virus, prevalence is higher in wild bumblebees than in managed honeybee populations. Our findings indicate widespread transmission of RNA viruses between managed and wild bee pollinators, pointing to an interconnected network of potential disease pressures within and among pollinator species. In the context of the biodiversity crisis, our study emphasizes the importance of targeting a wide range of pathogens and defining host associations when considering potential drivers of population decline

1200 High Quality Metagenome-Assembled Genomes from the Rumen of African Cattle and their relevance in the context of sub-optimal feeding

BACKGROUND: The Boran (Bos indicus), indigenous Zebu cattle breed from sub-Saharan Africa, is remarkably well adapted to harsh tropical environments. Due to financial constraints and low-quality forage, African livestock are rarely fed at 100% maintenance energy requirements (MER) and the effect of sub-optimal restricted feeding on the rumen microbiome of African Zebu cattle remains largely unexplored. We collected 24 rumen fluid samples from six Boran cattle fed at sub-optimal and optimal MER levels and characterised their rumen microbial composition by performing shotgun metagenomics and de novo assembly of metagenome-assembled genomes (MAGs). These MAGs were used as reference database to investigate the effect of diet restriction on the composition and functional potential of the rumen microbiome of African cattle. RESULTS: We report 1200 newly discovered MAGs from the rumen of Boran cattle. A total of 850 were dereplicated, and their uniqueness confirmed with pairwise comparisons (based on Mash distances) between African MAGs and other publicly available genomes from the rumen. A genome-centric investigation into sub-optimal diets highlighted a statistically significant effect on rumen microbial abundance profiles and a previously unobserved relationship between whole microbiome shifts in functional potential and taxon-level associations in metabolic pathways. CONCLUSIONS: This study is the first to identify 1200 high-quality African rumen-specific MAGs and provides further insight into the rumen function in harsh environments with food scarcity. The genomic information from the rumen microbiome of an indigenous African cattle breed sheds light on the microbiome contribution to rumen functionality and constitutes a vital resource in addressing food security in developing countries

Predation thresholds for reintroduction of native avifauna following suppression of invasive Brown Treesnakes on Guam

The brown treesnake (BTS) (Boiga irregularis) invasion on Guåhan (in English, Guam) led to the extirpation of nearly all native forest birds. In recent years, methods have been developed to reduce BTS abundance on a landscape scale. To help assess the prospects for the successful reintroduction of native birds to Guåhan following BTS suppression, we modeled bird population persistence based on their life history characteristics and relative sensitivity to BTS predation. We constructed individual-based models and simulated BTS predation in hypothetical founding populations for each of seven candidate bird species. We represented BTS predation risk in two steps: risk of being encountered and risk of mortality if encountered. We link encounter risk from the bird’s perspective to snake contact rates at camera traps with live animal lures, the most direct practical means of estimating BTS predation risk. Our simulations support the well-documented fact that Guåhan’s birds cannot persist with an uncontrolled population of BTS but do indicate that bird persistence in Guåhan’s forests is possible with suppression short of total eradication. We estimate threshold BTS contact rates would need to be below 0.0002–0.0006 snake contacts per bird per night for these birds to persist on the landscape, which translates to an annual encounter probability of 0.07–0.20. We simulated the effects of snake-proof nest boxes for Sihek (Todiramphus cinnamominus) and Såli (Aplonis opaca), but the benefits were small relative to the overall variation in contact rate thresholds among species. This variation among focal bird species in sustainable predation levels can be used to prioritize species for reintroduction in a BTS-suppressed landscape, but variation among these species is narrow relative to the required reduction from current BTS levels, which may be four orders of magnitude higher (\u3e0.18). Our modeling indicates that the required predation thresholds may need to be lower than have yet been demonstrated with current BTS management. Our predation threshold metric provides an important management tool to help estimate target BTS suppression levels that can be used to determine when bird reintroduction campaigns might begin and serves as a model for other systems to match predator control with reintroduction efforts

An integrated approach to use genetic resources for resurrection plants to enhance drought tolerance in breeding-extension programs [abstract]

Only abstract of poster available.Track V: BiomassThe ultimate goals of this project are to gain a basic understanding of the unique gene and gene regulatory networks that are necessary and sufficient for vegetative tissues to withstand dehydration and then rapidly recover upon rehydration and to use the knowledge gained to develop crops, maize and forage grasses that maintain biomass production under drought condition. Our approach is to combine comparative genomics and phylogenetics to identify genes and gene networks that are adaptive and central to the tolerance of cellular dehydration. This involves the use of resurrection species as models for dehydration tolerance coupled with a suite of comparative bioinformatic tools that allows for the phylogenetic assessment of gene expression patterns in response to dehydration and rehydration. Once the key genetic elements have been identified and assessed we will use a transgenic functional assessment of their involvement in the phenotype, both at a molecular and physiological level, of drought tolerance. One of our key resurrection species is the South African grass Sporobolus stapfianus, which is capable of surviving -240 MPa of water deficit (a hundred times lower than most crop plants). This plant not only serves as a model for monocot crops such as maize and switchgrass, our major targets for crop improvement, but also serves as a direct possibility for an alternate forage grass and biomass source. The improvement of biomass production under drought conditions is not only important for sustainable biofuel production but also for food and energy security. Funded by a CSREES-NRI Grant of $450,000 over three years to PI Mel Oliver USDA-ARS-PGRU Columbia, CoPIs Robert Sharp, University of Missouri; John Cushman, University of Nevada, Reno; Paxton Payton, USDA-ARS-PSRU Lubbock