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

Designing probiotic therapies with broad-spectrum activity against a wildlife pathogen

Host-associated microbes form an important component of immunity that protect against infection by pathogens. Treating wild individuals with these protective microbes, known as probiotics, can reduce rates of infection and disease in both wild and captive settings. However, the utility of probiotics for tackling wildlife disease requires that they offer consistent protection across the broad genomic variation of the pathogen that hosts can encounter in natural settings. Here we develop multi-isolate probiotic consortia with the aim of effecting broad-spectrum inhibition of growth of the lethal amphibian pathogen Batrachochytrium dendrobatidis (Bd) when tested against nine Bd isolates from two distinct lineages. Though we achieved strong growth inhibition between 70 and 100% for seven Bd isolates, two isolates appeared consistently resistant to inhibition, irrespective of probiotic strategy employed. We found no evidence that genomic relatedness of the chytrid predicted similarity of inhibition scores, nor that increasing the genetic diversity of the bacterial consortia could offer stronger inhibition of pathogen growth, even for the two resistant isolates. Our findings have important consequences for the application of probiotics to mitigate wildlife diseases in the face of extensive pathogen genomic variation

Population genetic structure and direct observations reveal sex-reversed patterns of dispersal in a cooperative bird

Sex-biased dispersal is pervasive and has diverse evolutionary implications, but the fundamental drivers of dispersal sex biases remain unresolved. This is due in part to limited diversity within taxonomic groups in the direction of dispersal sex biases, which leaves hypothesis testing critically dependent upon identifying rare reversals of taxonomic norms. Here, we use a combination of observational and genetic data to demonstrate a rare reversal of the avian sex bias in dispersal in the cooperatively breeding white-browed sparrow weaver (Plocepasser mahali). Direct observations revealed that (i) natal philopatry was rare, with both sexes typically dispersing locally to breed, and (ii), unusually for birds, males bred at significantly greater distances from their natal group than females. Population genetic analyses confirmed these patterns, as (i) corrected Assignment index (AIc), FST tests and isolation-by-distance metrics were all indicative of longer dispersal distances among males than females, and (ii) spatial autocorrelation analysis indicated stronger within-group genetic structure among females than males. Examining the spatial scale of extra-group mating highlighted that the resulting ‘sperm dispersal’ could have acted in concert with individual dispersal to generate these genetic patterns, but gamete dispersal alone cannot account entirely for the sex differences in genetic structure observed. That leading hypotheses for the evolution of dispersal sex biases cannot readily account for these sex-reversed patterns of dispersal in white-browed sparrow weavers highlights the continued need for attention to alternative explanations for this enigmatic phenomenon. We highlight the potential importance of sex differences in the distances over which dispersal opportunities can be detected

Perils and pitfalls of mixed-effects regression models in biology

This is the final version. Available on open access from PeerJ via the DOI in this recordData Availability: The following information was supplied regarding data availability: The R code used to conduct all simulations in the paper is available in the Supplemental Files.Biological systems, at all scales of organisation from nucleic acids to ecosystems, are inherently complex and variable. Biologists therefore use statistical analyses to detect signal among this systemic noise. Statistical models infer trends, find functional relationships and detect differences that exist among groups or are caused by experimental manipulations. They also use statistical relationships to help predict uncertain futures. All branches of the biological sciences now embrace the possibilities of mixed-effects modelling and its flexible toolkit for partitioning noise and signal. The mixed-effects model is not, however, a panacea for poor experimental design, and should be used with caution when inferring or deducing the importance of both fixed and random effects. Here we describe a selection of the perils and pitfalls that are widespread in the biological literature, but can be avoided by careful reflection, modelling and model-checking. We focus on situations where incautious modelling risks exposure to these pitfalls and the drawing of incorrect conclusions. Our stance is that statements of significance, information content or credibility all have their place in biological research, as long as these statements are cautious and well-informed by checks on the validity of assumptions. Our intention is to reveal potential perils and pitfalls in mixed model estimation so that researchers can use these powerful approaches with greater awareness and confidence. Our examples are ecological, but translate easily to all branches of biology.University of Exete

Precautionary principle or evidence-based conservation? Assessing the information content of threat data for the Yangtze finless porpoise

Conservation management requires evidence, but robust data on key parameters such as threats are often unavailable. Conservation-relevant insights might be available within datasets collected for other reasons, making it important to determine the information content of available data for threatened species and identify remaining data-gaps before investing time and resources in novel data collection. The Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis) has declined severely across the middle-lower Yangtze, but multiple threats exist in this system and the relative impact of different anthropogenic activities is unclear, preventing identification of appropriate mitigation strategies. Several datasets containing information on porpoises or potential threats are available from past boat-based and fishing community surveys, which might provide novel insights into causes of porpoise mortality and decline. We employed multiple analytical approaches to investigate spatial relationships between live and dead porpoises and different threats, reproductive trends over time, and sustainable offtake levels, to assess whether evidence-based conservation is feasible under current data availability. Our combined analyses provide new evidence that mortality is spatially associated with increased cargo traffic; observed mortality levels (probably a substantial underestimate of true levels) are unsustainable; and population recruitment is decreasing, although multiple factors could be responsible (pollutants, declining fish stocks, anthropogenic noise, reduced genetic diversity). Available data show little correlation between patterns of mortality and fishing activity even when analyzed across multiple spatial scales; however, interview data can be affected by multiple biases that potentially complicate attempts to reconstruct levels of bycatch, and new data are required to understand dynamics and sustainability of porpoise-fisheries interactions. This critical assessment of existing data thus suggests that in situ porpoise conservation management must target multiple co-occurring threats. Even limited available datasets can provide new insights for understanding declines, and we demonstrate the importance of an integrative approach for investigating complex conservation problems and maximizing evidence in conservation planning for poorly known taxa

Toll-like receptor variation in the bottlenecked population of the Seychelles warbler: computer simulations see the ‘ghost of selection past’ and quantify the ‘drift debt’

Balancing selection can maintain immunogenetic variation within host populations, but detecting its signal in a post-bottlenecked population is challenging due to the potentially overriding effects of drift. Toll-like receptor genes (TLRs) play a fundamental role in vertebrate immune defence and are predicted to be under balancing selection. We previously characterised variation at TLR loci in the Seychelles warbler (Acrocephalus sechellensis), an endemic passerine that has undergone a historical bottleneck. Five out of seven TLR loci were polymorphic, which is in sharp contrast to the low genome-wide variation observed. However standard population genetic statistical methods failed to detect a contemporary signature of selection at any TLR loci. We examined whether the observed TLR polymorphism could be explained by neutral evolution, simulating the population's demography in the software DIYABC. This showed that the posterior distributions of mutation rates had to be unrealistically high to explain the observed genetic variation. We then conducted simulations with an agent-based model using typical values for the mutation rate, which indicated that weak balancing selection has acted on the three TLR genes. The model was able to detect evidence of past selection elevating TLR polymorphism in the pre-bottleneck populations, but was unable to discern any effects of balancing selection in the contemporary population. Our results show drift is the overriding evolutionary force that has shaped TLR variation in the contemporary Seychelles warbler population, and the observed TLR polymorphisms might be merely the ‘ghost of selection past’. Forecast models predict immunogenetic variation in this species will continue to be eroded in the absence of contemporary balancing selection. Such ‘drift debt’ occurs when a genepool has not yet reached its new equilibrium level of polymorphism, and this loss could be an important threat to many recently bottlenecked populations

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

This is the final version of the article. Available from the publisher via the DOI in this record.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. XAH was funded by NERC grant (NE⁄F008058⁄1) with a Wildfowl & Wetlands Trust CASE partnership and RI by NERC grant (NE⁄F021690⁄1), both awarded to SB. SB is funded by an ERC Consolidator's Grant: STATEMIG 310820. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Pesticide pollution associations with riverine invertebrate communities in England

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: I have shared a link to my code and data sources in manuscript.Globally freshwater biodiversity has experienced major decline and chemical pollutants are believed to have played a significant role in this decline, but this has not been well quantified for most riverine invertebrate populations. Here we applied a biogeographically independent trait-based bioindicator, SPEARpesticides across sites across five regions (Northern, Midlands and Western, Anglian, Southeast, and Southwest) in England to investigate for associations specifically between pesticide use/pollution and riverine invertebrate communities over a 55-year period (1965-2019). Both spatially and temporally post-1990, the Anglian and Thames regions consistently showed the lowest SPEARpesticides scores, illustrating the presence of fewer pesticide sensitive species. The Anglian region had the highest pesticide use compared to all other regions from 1990 to 2018 and there were negative relationships between the level of pesticide/insecticide use and the regional SPEARpesticides score. Biochemical Oxygen Demand and ammonia, as measures of general water quality, were also negatively correlated with the SPEARpesticides scores across the regions, but these factors were not the driver for the lower SPEARpesticides scores seen in the Anglian region. Based on SPEARpesticides scores, riverine invertebrate communities in England have been most impacted in the Anglian region and we evidence chronic insecticide exposure is likely a significant factor in shaping the status of those invertebrate communities.Natural Environment Research Council (NERC)Department for Environment, Food & Rural AffairsJoint Nature Conservation Committe

Assessment of the impacts of GABA and AChE targeting pesticides on freshwater invertebrate family richness in English Rivers.

This is the final version. Available from Elsevier via the DOI in this record. Data availability: Data will be made available on request.Globally, riverine system biodiversity is threatened by a range of stressors, spanning pollution, sedimentation, alterations to water flow, and climate change. Pesticides have been associated with population level impacts on freshwater invertebrates for acute high-level exposures, but far less is known about the chronic impact of episodic exposure to specific classes of pesticides or their mixtures. Here we employed the use of the UK Environment Agency's monitoring datasets over 40 years (covering years 1980 to 2019) to assess the impacts of AChE (acetylcholinesterase) and GABA (gamma-aminobutyric acid) receptor targeting pesticides on invertebrate family richness at English river sites. Concentrations of AChE and GABA pesticides toxic to freshwater invertebrates occurred (measured) across 18 of the 66 river sites assessed. For one of the three river sites (all found in the Midlands region of England) where data recorded over the past 40 years were sufficient for robust modelling studies, both AChE and GABA pesticides associated with invertebrate family richness. Here, where AChE total pesticide concentrations were classified as high, 46 of 64 invertebrate families were absent, and where GABA total pesticide concentration were classified as high, 16 of 64 invertebrate families were absent. Using a combination of field evidence and laboratory toxicity thresholds for population relevant endpoints we identify families of invertebrates most at risk in the selected English rivers to AChE and GABA pesticides. We, furthermore, provide strong evidence that the absence of the invertebrate family Polycentropodidae (caddisfly) from one field site is due to exposure effects to AChE pesticides.Natural Environment Research Council (NERC)Department for Environment, Food and Rural Affairs (UK)Joint Nature Conservation Committe

Analysing detection gaps in acoustic telemetry data to infer differential movement patterns in fish

A wide array of technologies are available for gaining insight into the movement of wild aquatic animals. Although acoustic telemetry can lack the fine‐scale spatial resolution of some satellite tracking technologies, the substantially longer battery life can yield important long‐term data on individual behavior and movement for low per‐unit cost. Typically, however, receiver arrays are designed to maximize spatial coverage at the cost of positional accuracy leading to potentially longer detection gaps as individuals move out of range between monitored locations. This is particularly true when these technologies are deployed to monitor species in hard‐to‐access locations. Here, we develop a novel approach to analyzing acoustic telemetry data, using the timing and duration of gaps between animal detections to infer different behaviors. Using the durations between detections at the same and different receiver locations (i.e., detection gaps), we classify behaviors into “restricted” or potential wider “out‐of‐range” movements synonymous with longer distance dispersal. We apply this method to investigate spatial and temporal segregation of inferred movement patterns in two sympatric species of reef shark within a large, remote, marine protected area (MPA). Response variables were generated using network analysis, and drivers of these movements were identified using generalized linear mixed models and multimodel inference. Species, diel period, and season were significant predictors of “out‐of‐range” movements. Silvertip sharks were overall more likely to undertake “out‐of‐range” movements, compared with gray reef sharks, indicating spatial segregation, and corroborating previous stable isotope work between these two species. High individual variability in “out‐of‐range” movements in both species was also identified. We present a novel gap analysis of telemetry data to help infer differential movement and space use patterns where acoustic coverage is imperfect and other tracking methods are impractical at scale. In remote locations, inference may be the best available tool and this approach shows that acoustic telemetry gap analysis can be used for comparative studies in fish ecology, or combined with other research techniques to better understand functional mechanisms driving behavior