Xavier A. Harrison

Carry‐over effects as drivers of fitness differences in animals

1. Carry-over effects occur when processes in one season influence the success of an individual in the following season. This phenomenon has the potential to explain a large amount of variation in individual fitness, but so far has only been described in a limited number of species. This is largely due to difficulties associated with tracking individuals between periods of the annual cycle, but also because of a lack of research specifically designed to examine hypotheses related to carry-over effects. 2. We review the known mechanisms that drive carry-over effects, most notably macronutrient supply, and highlight the types of life histories and ecological situations where we would expect them to most often occur. We also identify a number of other potential mechanisms that require investigation, including micronutrients such as antioxidants. 3. We propose a series of experiments designed to estimate the relative contributions of extrinsic and intrinsic quality effects in the pre-breeding season, which in turn will allow an accurate estimation of the magnitude of carry-over effects. To date this has proven immensely difficult, and we hope that the experimental frameworks described here will stimulate new avenues of research vital to advancing our understanding of how carry-over effects can shape animal life histories. 4. We also explore the potential of state-dependent modelling as a tool for investigating carry-over effects, most notably for its ability to calculate optimal rates of acquisition of a multitude of resources over the course of the annual cycle, and also because it allows us to vary the strength of density-dependent relationships which can alter the magnitude of carry-over effects in either a synergistic or agonistic fashion. 5. In conclusion carry-over effects are likely to be far more widespread than currently indicated, and they are likely to be driven by a multitude of factors including both macro- and micronutrients. For this reason they could feasibly be responsible for a large amount of the observed variation in performance among individuals, and consequently warrant a wealth of new research designed specifically to decompose components of variation in fitness attributes related to processes across and within seasons.

Using observation-level random effects to model overdispersion in count data in ecology and evolution

Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated) data, or an excess frequency of zeroes (zero-inflation). Accounting for overdispersion in such models is vital, as failing to do so can lead to biased parameter estimates, and false conclusions regarding hypotheses of interest. Observation-level random effects (OLRE), where each data point receives a unique level of a random effect that models the extra-Poisson variation present in the data, are commonly employed to cope with overdispersion in count data. However studies investigating the efficacy of observation-level random effects as a means to deal with overdispersion are scarce. Here I use simulations to show that in cases where overdispersion is caused by random extra-Poisson noise, or aggregation in the count data, observation-level random effects yield more accurate parameter estimates compared to when overdispersion is simply ignored. Conversely, OLRE fail to reduce bias in zero-inflated data, and in some cases increase bias at high levels of overdispersion. There was a positive relationship between the magnitude of overdispersion and the degree of bias in parameter estimates. Critically, the simulations reveal that failing to account for overdispersion in mixed models can erroneously inflate measures of explained variance (r2), which may lead to researchers overestimating the predictive power of variables of interest. This work suggests use of observation-level random effects provides a simple and robust means to account for overdispersion in count data, but also that their ability to minimise bias is not uniform across all types of overdispersion and must be applied judiciously.

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.

Performance of Proximity Loggers in Recording Intra and Inter-Species Interactions: A Laboratory and Field- Based Validation Study

Knowledge of the way in which animals interact through social networks can help to address questions surrounding the ecological and evolutionary consequences of social organisation, and to understand and manage the spread of infectious diseases. Automated proximity loggers are increasingly being used to record interactions between animals, but the accuracy and reliability of the collected data remain largely un-assessed. Here we use laboratory and observational field data to assess the performance of these devices fitted to a herd of 32 beef cattle (Bos taurus) and nine groups of badgers (Meles meles, n  = 77) living in the surrounding woods. The distances at which loggers detected each other were found to decrease over time, potentially related to diminishing battery power that may be a function of temperature. Loggers were highly accurate in recording the identification of contacted conspecifics, but less reliable at determining contact duration. There was a tendency for extended interactions to be recorded as a series of shorter contacts. We show how data can be manipulated to correct this discrepancy and accurately reflect observed interaction patterns by combining records between any two loggers that occur within a 1 to 2 minute amalgamation window, and then removing any remaining 1 second records. We make universally applicable recommendations for the effective use of proximity loggers, to improve the validity of data arising from future studies.

Using "Omics" and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases

Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called “omics,” are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov–Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.

Heterozygosity–fitness correlations in a migratory bird: an analysis of inbreeding and single‐locus effects

Studies in a multitude of taxa have described a correlation between heterozygosity and fitness and usually conclude that this is evidence for inbreeding depression. Here, we have used multilocus heterozygosity (MLH) estimates from 15 microsatellite markers to show evidence of heterozygosity–fitness correlations (HFCs) in a long‐distance migratory bird, the light‐bellied Brent goose. We found significant, positive heterozygosity–heterozygosity correlations between random subsets of the markers we employed, and no evidence that a model containing all loci as individual predictors in a multiple regression explained significantly more variation than a model with MLH as a single predictor. Collectively, these results lend support to the hypothesis that the HFCs we have observed are a function of inbreeding depression. However, we do find that fitness correlations are only detectable in years where population‐level productivity is high enough for the reproductive asymmetry between high and low heterozygosity individuals to become apparent. We suggest that lack of evidence of heterozygosity–fitness correlations in animal systems may be because heterozygosity is a poor proxy measure of inbreeding, especially when employing low numbers of markers, but alternatively because the asymmetries between individuals of different heterozygosities may only be apparent when environmental effects on fitness are less pronounced.

Cultural inheritance drives site fidelity and migratory connectivity in a long-distance migrant.

Cultural transmission is thought to be a mechanism by which migratory animals settle into habitats, but little evidence exists in wild populations because of the difficulty of following individuals over successive generations and wide geographical distances. Cultural inheritance of migration routes represents a mechanism whereby geographical isolation can arise between separate groups and could constrain individuals to potentially suboptimal sites within their range. Conversely, adopting the parental migratory route in adult life, rather than dispersing randomly, may increase an individual’s reproductive success because that strategy has already been proven to allow successful breeding. We combined a pedigree of related light‐bellied Brent geese (Branta bernicla hrota) with 6 years of observations of marked birds to calculate the dispersal distances of adult offspring from their parents in both Ireland and Iceland. In both countries, the majority of offspring were found to recruit into or near their parental sites, indicating migratory connectivity in the flyway. Despite this kin structure, we found no evidence of genetic differentiation using genotype data from 1127 individuals across 15 microsatellite loci. We suggest that the existence of migratory connectivity of subpopulations is far more common than previous research indicates and that cultural information may play an important role in structuring reproductive isolation among them.

Multiple post‐mating barriers to hybridization in field crickets

Mechanisms that prevent different species from interbreeding are fundamental to the maintenance of biodiversity. Barriers to interspecific matings, such as failure to recognize a potential mate, are often relatively easy to identify. Those occurring after mating, such as differences in the how successful sperm are in competition for fertilisations, are cryptic and have the potential to create selection on females to mate multiply as a defence against maladaptive hybridization. Cryptic advantages to conspecific sperm may be very widespread and have been identified based on the observations of higher paternity of conspecifics in several species. However, a relationship between the fate of sperm from two species within the female and paternity has never been demonstrated. We use competitive microsatellite PCR to show that in two hybridising cricket species, Gryllus bimaculatus and G. campestris, sequential cryptic reproductive barriers are present. In competition with heterospecifics, more sperm from conspecific males is stored by females. Additionally, sperm from conspecific males has a higher fertilisation probability. This reveals that conspecific sperm precedence can occur through processes fundamentally under the control of females, providing avenues for females to evolve multiple mating as a defence against hybridization, with the counterintuitive outcome that promiscuity reinforces isolation and may promote speciation.

Amphibian Symbiotic Bacteria Do Not Show a Universal Ability To Inhibit Growth of the Global Panzootic Lineage of Batrachochytrium dendrobatidis

ABSTRACT Microbiomes associated with multicellular organisms influence the disease susceptibility of hosts. The potential exists for such bacteria to protect wildlife from infectious diseases, particularly in the case of the globally distributed and highly virulent fungal pathogen Batrachochytrium dendrobatidis of the global panzootic lineage (B. dendrobatidis GPL), responsible for mass extinctions and population declines of amphibians. B. dendrobatidis GPL exhibits wide genotypic and virulence variation, and the ability of candidate probiotics to restrict growth across B. dendrobatidis isolates has not previously been considered. Here we show that only a small proportion of candidate probiotics exhibited broad-spectrum inhibition across B. dendrobatidis GPL isolates. Moreover, some bacterial genera showed significantly greater inhibition than others, but overall, genus and species were not particularly reliable predictors of inhibitory capabilities. These findings indicate that bacterial consortia are likely to offer a more stable and effective approach to probiotics, particularly if related bacteria are selected from genera with greater antimicrobial capabilities. Together these results highlight a complex interaction between pathogens and host-associated symbiotic bacteria that will require consideration in the development of bacterial probiotics for wildlife conservation. Future efforts to construct protective microbiomes should incorporate bacteria that exhibit broad-spectrum inhibition of B. dendrobatidis GPL isolates.

Environmental conditions during breeding modify the strength of mass-dependent carry-over effects in a migratory bird.

In many animals, processes occurring in one season carry over to influence reproductive success and survival in future seasons. The strength of such carry-over effects is unlikely to be uniform across years, yet our understanding of the processes that are capable of modifying their strength remains limited. Here we show that female light-bellied Brent geese with higher body mass prior to spring migration successfully reared more offspring during breeding, but only in years where environmental conditions during breeding were favourable. In years of bad weather during breeding, all birds suffered reduced reproductive output irrespective of pre-migration mass. Our results suggest that the magnitude of reproductive benefits gained by maximising body stores to fuel breeding fluctuates markedly among years in concert with conditions during the breeding season, as does the degree to which carry-over effects are capable of driving variance in reproductive success among individuals. Therefore while carry-over effects have considerable power to drive fitness asymmetries among individuals, our ability to interpret these effects in terms of their implications for population dynamics is dependent on knowledge of fitness determinants occurring in subsequent seasons.