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Sanchez-Tojar, A.

Publications and source records attributed to Sanchez-Tojar, A..

6 recordsLinked to original sources

Effects of antibiotics on the abundance of antibiotic resistance determinants during and after antibiotic administration to beef cattle: A systematic review and meta-analysis of longitudinal studies

BackgroundBeef feedlots are increasing concerns that antibiotic use in beef cattle selects for antibiotic resistance, but limitations of primary studies and previous syntheses make it difficult to confirm a consistent effect. We conducted a rigorous systematic review and meta-analysis to summarise: 1) the effect during and after antibiotic administration; 2) its moderation by time since administration started/ended. MethodsEligible studies longitudinally compared beef cattle administered antibiotics to those that were not, measuring resistance determinants in faeces and/or environments. Information sources included Web of Science, CAB Abstracts, and Medline (last searches: 05/03/25). Risk of bias was assessed using RoB 2 and ROBINS-I. Meta-analysis was conducted where feasible, using individual participant data where necessary. ResultsThe 33 included studies were mostly small trials of North American feedlot cattle, all with high risks of bias. Meta-analysis of 11 studies of tylosin, ceftiofur, and chlortetracycline indicated positive effects on absolute abundance of resistance both during (SMDH = 0.4; 95% CI = 0.11 to 0.69, p = <0.01) and after (SMDH = 0.52; 95% CI = 0.33 to 0.71, p = <0.01) antibiotic administration. Log-transformed time was positively associated with effect size during (Slope = 0.63; 95% CI = 0.1 to 1.16, p = 0.02), and negatively associated after (Slope = -0.65; 95% CI = -1.24 to -0.06, p = 0.03) DiscussionAvailable evidence indicates time-dependent selection for antibiotic resistance in beef cattle, warranting further regulation to limit human health risks. Simultaneously, uncertainty about precise effect sizes warrants further research. FundingBBSRC Registrationhttps://doi.org/10.17605/OSF.IO/RXQHT

microbiology↗

Do egg hormones have fitness consequences in wild birds? A systematic review and meta-analysis

Egg-laying species are key models for understanding the adaptive significance of maternal effects, with egg hormones proposed as an important underlying mechanism. However, even thirty years after their discovery, the evolutionary consequences of hormone-mediated maternal effects remain unclear. Using evidence synthesis, we tested the extent to which increased prenatal maternal hormone deposition in eggs relates to fitness in wild birds (19 species, 438 effect sizes, 57 studies). Egg androgens, glucocorticoids, and thyroid hormones showed an overall near-zero mean effect for both maternal and offspring fitness proxies. However, heterogeneity was high, suggesting that egg hormone effects on fitness are context-dependent. Hormone type and age did not explain much of the observed variance, nor did methodological factors such as type of study or experimental design. Heterogeneity decomposition showed that differences in effect sizes were mostly driven by within-study variability and phylogenetic relationships. Our study provides the most comprehensive investigation to date of the relationship between egg hormones and fitness in vertebrates. By synthesizing current knowledge, we aim to overcome theoretical shortcomings in the field of maternal effects via egg hormone deposition and inspire new research into its many intriguing aspects.

evolutionary biology↗

Indirect genetic effects increase the heritable variation available to selection and are largest for behaviours: a meta-analysis

The evolutionary potential of traits is governed by the amount of heritable variation available to selection. While this is typically quantified based on genetic variation in a focal individual for its own traits (direct genetic effects, DGEs), when social interactions occur, genetic variation in interacting partners can influence a focal individuals traits (indirect genetic effects, IGEs). Theory and studies on domesticated species have suggested IGEs can greatly impact evolutionary trajectories, but whether this is true more broadly remains unclear. Here we perform a systematic review and meta-analysis to quantify the amount of trait variance explained by IGEs and the contribution of IGEs to predictions of adaptive potential. We identified 180 effect sizes from 47 studies across 21 species and found that, on average, IGEs of a single social partner account for a small but statistically significant amount of phenotypic variation (0.03). As IGEs affect the trait values of each interacting group member and due to a typically positive - although statistically nonsignificant - correlation with DGEs (rDGE-IGE = 0.26), IGEs ultimately increase trait heritability substantially from 0.27 (narrow-sense heritability) to 0.45 (total heritable variance). This 66% average increase in heritability suggests IGEs can increase the amount of genetic variation available to selection. Furthermore, whilst showing considerable variation across studies, IGEs were most prominent for behaviours, and to a lesser extent for reproduction and survival, in contrast to morphological, metabolic, physiological, and development traits. Our meta-analysis therefore shows that IGEs tend to enhance the evolutionary potential of traits, especially for those tightly related to interactions with other individuals such as behaviour and reproduction. Lay SummaryPredicting evolutionary change is important for breeding better livestock and crops, for understanding how biodiversity arises and how populations respond to environmental change. Normally, these predictions are based on how the genetic variants in an organism influence its own traits (characteristics). However, when organisms socially interact, for instance by fighting or cooperating, then the genes in one individual can influence the traits of others, therefore affecting the potential for evolutionary change. We compared 47 studies across 21 animal species and found that the effect of the genes of a single social partner is small but statistically significant, while the total contribution of social genetic effects to evolutionary potential is large. These effects are particularly important for the evolution of animals behaviours and reproductive traits, but less so for other traits such as body size and physiology. We also found that, because an individual can interact with many others and influence them all, social interactions can substantially increase the potential for a population to evolve from generation to generation. Our results show how social interactions can potentially alter the evolution of those traits known to respond to social interactions in comparison to standard expectations.

evolutionary biology↗

A global meta-analysis reveals more variable life histories in urban birds compared to their non-urban neighbours

Cities pose a major ecological challenge for wildlife worldwide. Phenotypic variation, which can result from underlying genetic variation or plasticity, is an important metric to understand eco-evolutionary responses to environmental change. Recent work suggests that urban populations might have higher levels of phenotypic variation than non-urban counterparts. This prediction, however, has never been tested across species nor over a broad geographical range. Here, we conduct a meta-analysis of the avian literature to compare urban versus non-urban means and variation in phenology (i.e., lay date) and reproductive effort (i.e., clutch size, number of fledglings). First, we show that urban populations reproduce earlier and have smaller broods than non-urban conspecifics. Second, we show that urban populations have higher phenotypic variation in laying date than non-urban populations. This result arises from differences between populations within breeding seasons, conceivably due to higher landscape heterogeneity in urban habitats. These findings reveal a novel effect of urbanisation on animal life-histories with potential implications for species adaptation to urban environments (which will require further investigation). Higher variation in phenology in birds subjected to urban disturbance could result from plastic responses to a heterogeneous environment, or from higher genetic variation in phenology, possibly linked to higher evolutionary potential.

evolutionary biology↗

Meta-analysis challenges a textbook example of status signalling: evidence for publication bias

The status signalling hypothesis aims to explain conspecific variation in ornamentation by suggesting that some ornaments signal dominance status. Here, we use multilevel meta-analytic models to challenge the textbook example of this hypothesis, the black bib of house sparrows (Passer domesticus). We conducted a systematic review, and obtained raw data from published and unpublished studies to test whether dominance rank is positively associated with bib size across studies. Contrary to previous studies, our meta-analysis did not support this prediction. Furthermore, we found several biases in the literature that further question the support available for the status signalling hypothesis. First, the overall effect size of unpublished studies was zero, compared to the medium effect size detected in published studies. Second, the effect sizes of published studies decreased over time, and recently published effects were, on average, no longer distinguishable from zero. We discuss several explanations including pleiotropic, population- and context-dependent effects. Our findings call for reconsidering this established textbook example in evolutionary and behavioural ecology, raise important concerns about the validity of the current scientific publishing culture, and should stimulate renewed interest in understanding within-species variation in ornamental traits.

evolutionary biology↗

A practical guide for inferring reliable dominance hierarchies and estimating their uncertainty

Many animal social structures are organized hierarchically, with dominant individuals monopolizing resources. Dominance hierarchies have received great attention from behavioural and evolutionary ecologists. As a result, there are many methods for inferring hierarchies from social interactions. Yet, there are no clear guidelines about how many observed dominance interactions (i.e. sampling effort) are necessary for inferring reliable dominance hierarchies, nor are there any established tools for quantifying their uncertainty. In this study, we simulated interactions (winners and losers) in scenarios of varying steepness (the probability that a dominant defeats a subordinate based on their difference in rank). Using these data, we (1) quantify how the number of interactions recorded and hierarchy steepness affect the performance of three methods, (2) propose an amendment that improves the performance of a popular method, and (3) suggest two easy procedures to measure uncertainty in the inferred hierarchy. First, we found that the ratio of interactions to individuals required to infer reliable hierarchies is surprisingly low, but depends on the hierarchy steepness and method used. We then show that Davids score and our novel randomized Elo-rating are the two best methods, whereas the original Elo-rating and the recently described ADAGIO perform less well. Finally, we propose two simple methods to estimate uncertainty at the individual and group level. These uncertainty measures further allow to differentiate non-existent, very flat and highly uncertain hierarchies from intermediate, steep and certain hierarchies. Overall, we find that the methods for inferring dominance hierarchies are relatively robust, even when the ratio of observed interactions to individuals is as low as 10 to 20. However, we suggest that implementing simple procedures for estimating uncertainty will benefit researchers, and quantifying the shape of the dominance hierarchies will provide new insights into the study organisms.\n\nHighlightsO_LIDavids score and the randomized Elo-rating perform best.\nC_LIO_LIMethod performance depends on hierarchy steepness and sampling effort.\nC_LIO_LIGenerally, inferring dominance hierarchies requires relatively few observations.\nC_LIO_LIThe R package \"aniDom\" allows easy estimation of hierarchy uncertainty.\nC_LIO_LIHierarchy uncertainty provides insights into the shape of the dominance hierarchy.\nC_LI

animal behavior and cognition↗