The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues relating to the use of information theory and multi-model inference in ecology, and demonstrate the tendency for data dredging to lead to greatly inflated Type I error rate (false positives) and impaired inference. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

Infectious diseases can alter the demography of their host populations, reducing their viability even in the absence of mass mortality. Amphibians are the most threatened group of vertebrates globally, and emerging infectious diseases play a large role in their continued population declines. Viruses belonging to the genus Ranavirus are responsible for one of the deadliest and most widespread of these diseases. To date, no work has used individual level data to investigate how ranaviruses affect population demographic structure. We used skeletochronology and morphology to evaluate the impact of ranaviruses on the age structure of populations of the European common frog (Rana temporaria) in the United Kingdom. We compared ecologically similar populations that differed only in their historical presence or absence of ranavirosis (the acute syndrome caused by ranavirus infection). Our results suggest that ranavirosis may truncate the age structure of R. temporaria populations. One potential explanation for such a shift might be increased adult mortality and subsequent shifts in the life history of younger age classes that increase reproductive output earlier in life. Additionally we constructed population projection models which indicated that such increased adult mortality could heighten the vulnerability of frog populations to stochastic environmental challenges.

Amphibians are the most threatened species-rich vertebrate group, with species extinctions and population declines occurring globally, even in protected and seemingly pristine habitats. These ‘enigmatic declines’ are generated by climate change and infectious diseases. However, the consequences of these declines are undocumented as no baseline ecological data exists for most affected areas. Like other neotropical countries, Costa Rica, including Área de Conservación Guanacaste (ACG) in north-western Costa Rica, experienced rapid amphibian population declines and apparent extinctions during the past three decades. To delineate amphibian diversity patterns within ACG, a large-scale comparison of multiple sites and habitats was conducted. Distance and time constrained visual encounter surveys characterised species richness at five sites—Murciélago (dry forest), Santa Rosa (dry forest), Maritza (mid-elevation dry-rain forest intersect), San Gerardo (rainforest) and Cacao (cloud forest). Furthermore, species-richness patterns for Cacao were compared with historic data from 1987–8, before amphibians declined in the area. Rainforests had the highest species richness, with triple the species of their dry forest counterparts. A decline of 45% (20 to 11 species) in amphibian species richness was encountered when comparing historic and contemporary data for Cacao. Conservation efforts sometimes focus on increasing the resilience of protected areas, by increasing their range of ecosystems. In this sense ACG is unique containing many tropical ecosystems compressed in a small geographic space, all protected and recognised as a UNESCO world heritage site. It thus provides an extraordinary platform to understand changes, past and present, and the resilience of tropical ecosystems and assemblages, or lack thereof, to climate change.

The putatively positive association between host genetic diversity and the ability to defend against pathogens has long attracted the attention of evolutionary biologists. Chytridiomycosis, a disease caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), has emerged in recent decades as a cause of dramatic declines and extinctions across the amphibian clade. Bd susceptibility can vary widely across populations of the same species, but the relationship between standing genetic diversity and susceptibility has remained notably underexplored so far. Here, we focus on a putatively Bd-naive system of two mainland and two island populations of the common toad (Bufo bufo) at the edge of the species' range and use controlled infection experiments and dd-RAD sequencing of >10 000 SNPs across 95 individuals to characterize the role of host population identity, genetic variation and individual body mass in mediating host response to the pathogen. We found strong genetic differentiation between populations and marked variation in their susceptibility to Bd. This variation was not, however, governed by isolation-mediated genetic erosion, and individual heterozygosity was even found to be negatively correlated with survival. Individual survival during infection experiments was strongly positively related to body mass, which itself was unrelated to population of origin or heterozygosity. Our findings underscore the general importance of context-dependency when assessing the role of host genetic variation for the ability of defence against pathogens.

Background
With conventional coral reef conservation methods proving ineffective against intensifying climate change, efforts have focussed on augmenting coral tolerance to warmer water—the primary driver of coral declines. We document coral cover and composition in relation to sea surface temperature (SST) over 25-years, of six marginal reefs in an upwelling area of Costa Rica’s Eastern Tropical Pacific.


Methods
Using reef survey data and sea surface temperature (SST) dating back over 25-years, we document coral cover and composition of six marginal reefs in an upwelling area of Costa Rica’s Eastern Tropical Pacific in relation to thermal highs and lows.


Results.
A ubiquitous and catastrophic coral die-off event occurred in 2009, driven by SST minima and likely by the presence of extreme harmful algal blooms. Coral cover was dramatically reduced and coral composition shifted from dominant branching Pocillopora to massive Pavona, Porites, and Gardineroseris. The lack of coral recovery in the decade since indicates a breach in ecosystem tipping-point and highlights a need for resilience-based management (RBM) and restoration. We propose a locally tailored and globally scalable approach to coral reef declines that is founded in RBM and informed by coral health dynamics.

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.

Abstract


Invasive non‐native species can alter animal‐mediated seed dispersal interactions and ultimately affect the stability of recipient communities. The degree of such disturbances, however, is highly variable and depends on several factors, two of which have received little attention: the relative timing of native and non‐native fruiting phenologies, and the associated variation in relative resource availability across the fruiting period. Both are likely to alter plant–seed disperser interactions threatened by biological invasions.

Here we investigated the impact of plant invasions on the seasonal dynamics of frugivory and seed dispersal networks across a large‐scale experimental setup and a plant invasion gradient on a tropical island. We recorded fruit and frugivore abundances, and plant–frugivore interactions across eight inselbergs (i.e. rocky outcrops) with different levels of plant invasion during 10 months on the island of Mahé, Seychelles. By combining four sampling methods of plant–frugivore interactions we constructed quantitative seed dispersal networks at all sites across two 5‐month seasons: the on‐peak and off‐peak fruiting season.

Our findings showed that, by fruiting mostly synchronously with natives, non‐native plants compete with natives for dispersal services, predominantly carried out by native frugivores. Variation in native seed dispersal was driven by plant invasion and seasonality. Specifically, native seed dispersal declined with the degree of invasion; dispersal frequency increased with fruit abundance more strongly during the off‐peak fruiting season; and networks became increasingly specialised during off‐peak. These results indicated that during the main fruiting peak seed dispersal services were saturated, which likely intensified the competition between native and non‐native fruits. When resources were scarce during off‐peak fruiting season, native and non‐native frugivores were more selective in their fruit choice at sites dominated by non‐native plants.

We showed that native plant and frugivore populations and native seed dispersal interactions were more vulnerable in invaded plant communities, where non‐native plants compete with natives for dispersal services potentially reducing native recruitment. As invasive non‐native plants dominate many ecosystems world‐wide, particularly on islands, our findings showed that controlling plant invasions in vulnerable native communities can be critical to maintain native ecosystem functions and biodiversity.

Read the free Plain Language Summary for this article on the Journal blog.

Striking effects of cooperation on the reproductive variance of relatives help to explain the global biogeography of altruism.

Abstract


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.

Interactions between hosts and their resident microbial communities are a fundamental component of fitness for both agents. Though recent research has highlighted the importance of interactions between animals and their bacterial communities, comparative evidence for fungi is lacking, especially in natural populations. Using data from 49 species, we present novel evidence of strong covariation between fungal and bacterial communities across the host phylogeny, indicative of recruitment by hosts for specific suites of microbes. Using co-occurrence networks, we demonstrate marked variation across host taxonomy in patterns of covariation between bacterial and fungal abundances. Host phylogeny drives differences in the overall richness of bacterial and fungal communities, but the effect of diet on richness was only evident in the mammalian gut microbiome. Sample type, tissue storage and DNA extraction method also affected bacterial and fungal community composition, and future studies would benefit from standardized approaches to sample processing. Collectively these data indicate fungal microbiomes may play a key role in host fitness and suggest an urgent need to study multiple agents of the animal microbiome to accurately determine the strength and ecological significance of host-microbe interactions.

. As telomere length (TL) often predicts survival and lifespan, there is considerable interest in the origins of inter-individual variation in TL. Cross-generational effects of parental age on offspring TL are thought to be a key source of variation, but the rarity of longitudinal studies that examine the telomeres of successive offspring born throughout the lives of parents leaves such effects poorly understood. Here, we exploit TL measures of successive offspring produced throughout the long breeding tenures of parents in wild white-browed sparrow weaver (
. Plocepasser mahali
. ) societies, to isolate the effects of within-parent changes in age on offspring TLs. Our analyses reveal the first evidence to date of a positive within-parent effect of advancing age on offspring TL: as individual parents age, they produce offspring with longer telomeres (a modest effect that persists into offspring adulthood). We consider the potential for pre- and post-natal mechanisms to explain our findings. As telomere attrition predicts offspring survival to adulthood in this species, this positive parental age effect could impact parent and offspring fitness if it arose via differential telomere attrition during offspring development. Our findings support the view that cross-generational effects of parental age can be a source of inter-individual variation in TL.
.

AbstractSocial environments influence multiple traits of individuals including immunity, stress and ageing, often in sex‐specific ways. The composition of the microbiome (the assemblage of symbiotic microorganisms within a host) is determined by environmental factors and the host's immune, endocrine and neural systems. The social environment could alter host microbiomes extrinsically by affecting transmission between individuals, probably promoting homogeneity in the microbiome of social partners. Alternatively, intrinsic effects arising from interactions between the microbiome and host physiology (the microbiota‐gut‐brain axis) could translate social stress into dysbiotic microbiomes, with consequences for host health. We investigated how manipulating social environments during larval and adult life‐stages altered the microbiome composition of Drosophila melanogaster fruit flies. We used social contexts that particularly alter the development and lifespan of males, predicting that any intrinsic social effects on the microbiome would therefore be sex‐specific. The presence of adult males during the larval stage significantly altered the microbiome of pupae of both sexes. In adults, same‐sex grouping increased bacterial diversity in both sexes. Importantly, the microbiome community structure of males was more sensitive to social contact at older ages, an effect partially mitigated by housing focal males with young rather than coaged groups. Functional analyses suggest that these microbiome changes impact ageing and immune responses. This is consistent with the hypothesis that the substantial effects of the social environment on individual health are mediated through intrinsic effects on the microbiome, and provides a model for understanding the mechanistic basis of the microbiota‐gut‐brain axis.

Preventing extinctions requires understanding macroecological patterns of vulnerability or persistence. However, correlates of risk can be nonlinear, within-species risk varies geographically, and current-day threats cannot reveal drivers of past losses. We investigated factors that regulated survival or extinction in Caribbean mammals, which have experienced the globally highest level of human-caused postglacial mammalian extinctions, and included all extinct and extant Holocene island populations of non-volant species (219 survivals or extinctions across 118 islands). Extinction selectivity shows a statistically detectable and complex body mass effect, with survival probability decreasing for both mass extremes, indicating that intermediate-sized species have been more resilient. A strong interaction between mass and age of first human arrival provides quantitative evidence of larger mammals going extinct on the earliest islands colonized, revealing an extinction filter caused by past human activities. Survival probability increases on islands with lower mean elevation (mostly small cays acting as offshore refugia) and decreases with more frequent hurricanes, highlighting the risk of extreme weather events and rising sea levels to surviving species on low-lying cays. These findings demonstrate the interplay between intrinsic biology, regional ecology and specific local threats, providing insights for understanding drivers of biodiversity loss across island systems and fragmented habitats worldwide.

ABSTRACTInteractions between hosts and their resident microbial communities are a fundamental component of fitness for both agents. Though recent research has highlighted the importance of interactions between animals and their bacterial communities, comparative evidence for fungi is lacking, especially in natural populations. Using data from 49 species, we present novel evidence of strong covariation between fungal and bacterial communities across the host phylogeny, indicative of recruitment by hosts for specific suites of microbes. Using co-occurrence networks, we demonstrate that fungi form critical components of putative microbial interaction networks, where the strength and frequency of interactions varies with host taxonomy. Host phylogeny drives differences in overall richness of bacterial and fungal communities, but the effect of diet on richness was only evident in mammals and for the bacterial microbiome. Collectively these data indicate fungal microbiomes may play a key role in host fitness and suggest an urgent need to study multiple agents of the animal microbiome to accurately determine the strength and ecological significance of host-microbe interactions.SIGNIFICANCE STATEMENTMicrobes perform vital metabolic functions that shape the physiology of their hosts. However, almost all research to date in wild animals has focused exclusively on the bacterial microbiota, to the exclusion of other microbial groups. Although likely to be critical components of the host microbiome, we have limited knowledge of the drivers of fungal composition across host species. Here we show that fungal community composition is determined by host species identity and phylogeny, and that fungi form extensive interaction networks with bacteria in the microbiome of a diverse range of animal species. This highlights the importance of microbial interactions as mediators of microbiome-health relationships in the wild.

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.

AbstractSocial environments influence multiple traits of individuals including immunity, stress and ageing, often in sex-specific ways. The composition of the microbiome (the assemblage of symbiotic microorganisms within a host) is determined by environmental factors and the host’s immune, endocrine and neural systems. The social environment could alter host microbiomes extrinsically by affecting transmission between individuals, likely promoting homogeneity in the microbiome of social partners. Alternatively, intrinsic effects arising from interactions between the microbiome and host physiology (the microbiota-gut-brain axis) could translate social stress into dysbiotic microbiomes, with consequences for host health. We investigated how manipulating social environments during larval and adult life-stages altered the microbiome composition of Drosophila melanogaster fruit flies. We used social contexts that particularly alter the development and lifespan of males, predicting that any intrinsic social effects on the microbiome would therefore be sex-specific. The presence of adult males during the larval stage significantly altered the microbiome of pupae of both sexes. In adults, same-sex grouping increased bacterial diversity in both sexes. Importantly, the microbiome community structure of males was more sensitive to social contact at older ages, an effect partially mitigated by housing focal males with young rather than co-aged groups. Functional analyses suggest that these microbiome changes impact ageing and immune responses. This is consistent with the hypothesis that the substantial effects of the social environment on individual health are mediated through intrinsic effects on the microbiome, and provides a model for understanding the mechanistic basis of the microbiota-gut-brain axis.Significance statementThe social environment has pervasive, multifaceted effects on individual health and fitness. If a host’s microbiome is sensitive to the social environment then it could be an important mediator of social effects, as the reciprocal relationships between hosts and their microbiomes have substantial implications for host health. Using a Drosophila melanogaster fruit fly model we show that the fly microbiome is sensitive to the social environment in a sex, age and life-stage dependent manner. In particular, older adult male microbiome communities are altered by same-sex social contact, but this depends on the age of the social partners. These changes have functional effects on fly immunity and lifespan, evidence that indeed this is an influential mediator of social effects on health.

Variation among animals in their host-associated microbial communities is increasingly recognized as a key determinant of important life history traits including growth, metabolism, and resistance to disease. Quantitative estimates of the factors shaping the stability of host microbiomes over time at the individual level in non-model organisms are scarce. Addressing this gap in our knowledge is important, as variation among individuals in microbiome stability may represent temporal gain or loss of key microbial species and functions linked to host health and/or fitness. Here we use controlled experiments to investigate how both heterogeneity in microbial species richness of the environment and exposure to the emerging pathogen Ranavirus influence the structure and temporal dynamics of the skin microbiome in a vertebrate host, the European common frog (Rana temporaria). Our evidence suggests that altering the bacterial species richness of the environment drives divergent temporal microbiome dynamics of the amphibian skin. Exposure to ranavirus effects changes in skin microbiome structure irrespective of total microbial diversity, but individuals with higher pre-exposure skin microbiome diversity appeared to exhibit higher survival. Higher diversity skin microbiomes also appear less stable over time compared to lower diversity microbiomes, but stability of the 100 most abundant (“core”) community members was similar irrespective of microbiome richness. Our study highlights the importance of extrinsic factors in determining the stability of host microbiomes over time, which may in turn have important consequences for the stability of host-microbe interactions and microbiome-fitness correlations.

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues relating to the use of information theory and multi-model inference in ecology, and demonstrate the tendency for data dredging to lead to greatly inflated Type I error rate (false positives) and impaired inference. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

AbstractHost-associated microbes are vital for combatting infections and maintaining health. In amphibians, certain skin-associated bacteria inhibit the fungal pathogen Batrachochytrium dendrobatidis (Bd), yet our understanding of host microbial ecology and its role in disease outbreaks is limited. We sampled skin-associated bacteria and Bd from Pyrenean midwife toad populations exhibiting enzootic or epizootic disease dynamics. We demonstrate that bacterial communities differ between life stages with few shared taxa, indicative of restructuring at metamorphosis. We detected a significant effect of infection history on metamorph skin microbiota, with reduced bacterial diversity in epizootic populations and differences in community structure and predicted function. Genome sequencing of Bd isolates supports a single introduction to the Pyrenees and reveals no association between pathogen genetics and epidemiological trends. Our findings provide an ecologically relevant insight into the microbial ecology of amphibian skin and highlight the relative importance of host microbiota and pathogen genetics in predicting disease outcome.

Infectious diseases can alter the demography of their host populations, reducing their viability even in the absence of mass mortality. Amphibians are the most threatened group of vertebrates globally, and emerging infectious diseases play a large role in their continued population declines. Viruses belonging to the genus Ranavirus are responsible for one of the deadliest and most widespread of these diseases. To date, no work has used individual level data to investigate how ranaviruses affect population demographic structure. We used skeletochronology and morphology to evaluate the impact of ranaviruses on the age structure of populations of the European common frog (Rana temporaria) in the United Kingdom. We compared ecologically similar populations that differed only in their historical presence or absence of ranavirosis (the acute syndrome caused by ranavirus infection). Our results suggest that ranavirosis may truncate the age structure of R. temporaria populations. One potential explanation for such a shift might be increased adult mortality and subsequent shifts in the life history of younger age classes that increase reproductive output earlier in life. Additionally we constructed population projection models which indicated that such increased adult mortality could heighten the vulnerability of frog populations to stochastic environmental challenges.

The purpose of this study was to determine whether limited occurrence data for highly threatened species can provide useful spatial information to inform conservation. The study was conducted across central and southern China. We developed a habitat suitability model for the Critically Endangered Chinese giant salamander (Andrias davidianus) based on one biotic and three abiotic parameters from single-site locality records, which represent the only relevant environmental data available for this species. We then validated model quality by testing whether increased percentage of predicted suitable habitat at the county level correlated with independent data on giant salamander presence. We randomly selected 48 counties containing historical records which were distinct from, and independent of, the single-site records used to develop the model, and 47 additional counties containing >50% predicted suitable habitat. We interviewed 2,812 respondents near potential giant salamander habitat across these counties and tested for differences in respondent giant salamander reports between counties selected using each method. Our model predicts that suitable giant salamander habitat is found widely across central and southern China, with counties containing ≥50% predicted suitable habitat distributed in 13 provinces. Counties with historical records contain significantly more predicted suitable habitat than counties without historical records. There are no statistical differences in any patterns of respondent giant salamander reports in surveyed counties selected from our model compared with the areas of known historical giant salamander distribution. A Chinese giant salamander habitat suitability model with strong predictive power can be derived from the restricted range of environmental variables associated with limited available presence-only occurrence records, constituting a cost-effective strategy to guide spatial allocation of conservation planning. Few reported sightings were recent, however, with most being over 20 years old, so that identification of areas of suitable habitat does not necessarily indicate continued survival of the species at these locations.

Amphibian populations worldwide are at risk of extinction from infectious diseases, including chytridiomycosis caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd). Amphibian cutaneous microbiomes interact with Bd and can confer protective benefits to the host. The composition of the microbiome itself is influenced by many environment- and host-related factors. However, little is known about the interacting effects of host population structure, genetic variation and developmental stage on microbiome composition and Bd prevalence across multiple sites. Here we explore these questions in Amietia hymenopus, a disease-affected frog in southern Africa. We use microsatellite genotyping and 16S amplicon sequencing to show that the microbiome associated with tadpole mouthparts is structured spatially, and is influenced by host genotype and developmental stage. We observed strong genetic structure in host populations based on rivers and geographic distances, but this did not correspond to spatial patterns in microbiome composition. These results indicate that demographic and host genetic factors affect microbiome composition within sites, but different factors are responsible for host population structure and microbiome structure at the between-site level. Our results help to elucidate complex within- and among- population drivers of microbiome structure in amphibian populations. That there is a genetic basis to microbiome composition in amphibians could help to inform amphibian conservation efforts against infectious diseases.

Symbiotic bacterial communities can protect their hosts from infection by pathogens. Treatment of wild individuals with protective bacteria (probiotics) isolated from hosts can combat the spread of emerging infectious diseases. However, it is unclear whether candidate probiotic bacteria can offer consistent protection across multiple isolates of globally distributed pathogens. Here, we use the lethal amphibian fungal pathogen Batrachochytrium dendrobatidis to investigate whether probiotic richness (number of bacteria) or genetic distance among consortia members influences broad-scale in vitro inhibitory capabilities of probiotics across multiple isolates of the pathogen. We show that inhibition of multiple pathogen isolates by individual bacteria is rare, with no systematic pattern among bacterial genera in ability to inhibit multiple B. dendrobatidis isolates. Bacterial consortia can offer stronger protection against B. dendrobatidis compared to single strains, and this tended to be more pronounced for consortia containing multiple genera compared with those consisting of bacteria from a single genus (i.e. with lower genetic distance), but critically, this effect was not uniform across all B. dendrobatidis isolates. These novel insights have important implications for the effective design of bacterial probiotics to mitigate emerging infectious diseases.

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues relating to the use of information theory and multi-model inference in ecology, and demonstrate the tendency for data dredging to lead to greatly inflated Type I error rate (false positives) and impaired inference. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

AbstractInfectious diseases can influence the life history strategy of their hosts and such influences subsequently impact the demography of infected populations, reducing viability independently of increased mortality or morbidity. Amphibians are the most threatened group of vertebrates and emerging infectious diseases play a large role in their population declines. Viruses of genus Ranavirus are responsible for one of the deadliest of these diseases. To date no work has evaluated the impact of ranaviruses on host life-history post metamorphosis or population demographic structure at the individual level. In this study, we used skeletochronology and morphology to evaluate the impact of ranaviruses on the demography of populations of European common frog (Rana temporaria) in the United Kingdom. We compared ecologically similar populations that differed only in their historical presence or absence of ranaviral disease. Our results suggest that ranaviruses are associated with shifts in the age structure of infected populations, potentially caused by increased adult mortality and associated shifts in the life history of younger age classes. Population projection models indicate that such age truncation could heighten the vulnerability of frog populations to stochastic environmental challenges. Our individual level data provide further compelling evidence that the emergence of infectious diseases can alter host demography, subsequently increasing population vulnerability to additional stressors.

Microbial ecology provides insights into the ecological and evolutionary dynamics of microbial communities underpinning every ecosystem on Earth. Microbial communities can now be investigated in unprecedented detail, although there is still a wealth of open questions to be tackled. Here we identify 50 research questions of fundamental importance to the science or application of microbial ecology, with the intention of summarising the field and bringing focus to new research avenues. Questions are categorised into seven themes: host-microbiome interactions; health and infectious diseases; human health and food security; microbial ecology in a changing world; environmental processes; functional diversity; and evolutionary processes. Many questions recognise that microbes provide an extraordinary array of functional diversity that can be harnessed to solve real-world problems. Our limited knowledge of spatial and temporal variation in microbial diversity and function is also reflected, as is the need to integrate micro- and macro-ecological concepts, and knowledge derived from studies with humans and other diverse organisms. Although not exhaustive, the questions presented are intended to stimulate discussion and provide focus for researchers, funders and policy makers, informing the future research agenda in microbial ecology.

AbstractEnvironmental heterogeneity is known to modulate the interactions between pathogens and hosts. However, the impact of environmental heterogeneity on the structure of host-associated microbial communities, and how these communities respond to pathogenic exposure remain poorly understood. Here we use an experimental framework to probe the links between environmental heterogeneity, skin microbiome structure and infection by the emerging pathogenRanavirusin a vertebrate host, the European common frog (Rana temporaria). We provide evidence that environmental complexity directly influences the diversity and structure of the host skin microbiome, and that more diverse microbiomes are more resistant to perturbation associated with exposure toRanavirus. Our data also indicate that host microbiome diversity covaries with survival following exposure toRanavirus. Our study highlights the importance of extrinsic factors in driving host-pathogen dynamics in vertebrate hosts, and suggests that environment-mediated variation in the structure of the host microbiome may covary with observed differences in host susceptibility to disease in the wild.

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.

Ephemeral rivers act as linear oases in drylands providing key resources to people and wildlife. However, not much is known about these rivers' sensitivities to human activities. We investigated the landscape-level determinants of riparian tree dieback along the Swakop River, a dammed ephemeral river in Namibia, focusing on the native ana tree (Faidherbia albida) and the invasive mesquite (Prosopis spp.). We surveyed over 1,900 individual trees distributed across 24 sites along a 250 km stretch of the river. General linear mixed models were used to test five hypotheses relating to three anthropogenic threats: river flow disruption from damming, human settlement and invasive species. We found widespread dieback in both tree populations: 51% mortality in ana tree, with surviving trees exhibiting 18% canopy death (median); and 26% mortality in mesquite, with surviving trees exhibiting 10% canopy death. Dieback in the ana tree was most severe where trees grew on drier stretches of the river, where tributary flow was absent and where mesquite grew more abundantly. Dieback in the mesquite, a more drought-tolerant taxon, did not show any such patterns. Our findings suggest that dieback in the ana tree is primarily driven by changes in river flow resulting from upstream dam creation and that tributary flows provide a local buffer against this loss of main channel flow. The hypothesis that the invasive mesquite may contribute to ana tree dieback was also supported. Our findings suggest that large dams along the main channels of ephemeral rivers have the ability to cause widespread mortality in downstream riparian trees. To mitigate such impacts, management might focus on the maintenance of natural tributary flows to buffer local tree populations from the disruption to main channel flow.

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 (

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.

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.

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 (r (2)), 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.

The distribution of reproductive success within societies is a key determinant of the outcomes of social evolution. Attempts to explain social diversity, therefore, require that we quantify reproductive skews and identify the mechanisms that generate them. Here, we address this priority using life history and genotypic data from >600 individuals in 40 wild groups of the cooperatively breeding white-browed sparrow weaver, Plocepasser mahali. We show that groups comprise up to six males and seven females, but within-group reproduction is completely monopolised by a single dominant male and female, while extra-group males sire 12-18 % of offspring. Strong within-group kin structure could frequently explain these monopolies, as subordinates had typically delayed dispersal from their natal groups and so frequently (1) lacked within-group outbreeding partners, and/or (2) stood to gain little from contesting dominant reproduction, being almost as related to the dominant's young as they would have been to their own. Kin structure alone cannot account entirely for these monopolies, however, as they remained complete following the immigration of unrelated males and females. That subordinate females remain reproductively quiescent despite also showing comparable body condition to dominants, overlapping them substantially in age, and showing no evidence of elevated stress hormone levels raises the possibility that they exercise reproductive restraint due instead to a threat of action by dominants and/or deficits in offspring fitness that might arise if subordinates bred. Our findings highlight the complexity of the mechanisms that generate reproductive disparities in animal societies and the challenge of identifying them when skews are complete. © 2013 Springer-Verlag Berlin Heidelberg.

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. 

In many cooperatively breeding species, females mate extra-group, the adaptive value of which remains poorly understood. One hypothesis posits that females employ extra-group mating to access mates whose genotypes are more dissimilar to their own than their social mates, so as to increase offspring heterozygosity. We test this hypothesis using life history and genetic data from 36 cooperatively breeding white-browed sparrow weaver (Plocepasser mahali) groups. Contrary to prediction, a dominant female's relatedness to her social mate did not drive extra-group mating decisions and, moreover, extra-group mating females were significantly more related to their extra-group sires than their social mates. Instead, dominant females were substantially more likely to mate extra-group when paired to a dominant male of low heterozygosity, and their extra-group mates (typically dominants themselves) were significantly more heterozygous than the males they cuckolded. The combined effects of mating with extra-group males of closer relatedness, but higher heterozygosity resulted in extra-group-sired offspring that were no more heterozygous than their within-group-sired half-siblings. Our findings are consistent with a role for male-male competition in driving extra-group mating and suggest that the local kin structure typical of cooperative breeders could counter potential benefits to females of mating extra-group by exposing them to a risk of inbreeding. © 2013 John Wiley & Sons Ltd.

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. © 2013 Blackwell Publishing Ltd.

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.

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.

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. © 2011 Blackwell Publishing Ltd.