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Given the multitude of challenges Earth is facing, sustainability science is of key importance to our continued existence. Evolution is the fundamental biological process underlying the origin of all biodiversity. This phylogenetic diversity fosters the resilience of ecosystems to environmental change, and provides numerous resources to society, and options for the future. Genetic diversity within species is also key to the ability of populations to evolve and adapt to environmental change. Yet, the value of evolutionary processes and the consequences of their impairment have not generally been considered in sustainability research. We argue that biological evolution is important for sustainability and that the concepts, theory, data, and methodological approaches used in evolutionary biology can, in crucial ways, contribute to achieving the UN Sustainable Development Goals (SDGs). We discuss how evolutionary principles are relevant to understanding, maintaining, and improving Nature Contributions to People (NCP) and how they contribute to the SDGs. We highlight specific applications of evolution, evolutionary theory, and evolutionary biologys diverse toolbox, grouped into four major routes through which evolution and evolutionary insights can impact sustainability. We argue that information on both within-species evolutionary potential and among-species phylogenetic diversity is necessary to predict population, community, and ecosystem responses to global change and to make informed decisions on sustainable production, health, and well-being. We provide examples of how evolutionary insights and the tools developed by evolutionary biology can not only inspire and enhance progress on the trajectory to sustainability, but also highlight some obstacles that hitherto seem to have impeded an efficient uptake of evolutionary insights in sustainability research and actions to sustain SDGs. We call for enhanced collaboration between sustainability science and evolutionary biology to understand how integrating these disciplines can help achieve the sustainable future envisioned by the UN SDGs.

Every year monarch butterflies (Danaus plexippus (Linnaeus, 1758)) from the eastern North American population migrate from Mexico to southern Canada in the spring. This northward migration has been shown to reduce monarch infection with the host-specific parasite Ophryocystis elektroscirrha McLaughlin and Myers, 1970 (OE); yet, the prevalence of OE at their range limits and the mechanism(s) responsible are unknown. We assessed OE infection levels of monarchs at the northern edge of the eastern population distribution around Ottawa, Ontario, Canada, and found extremely low levels of infection (~1% with upper confidence intervals close to 3%). Low OE infection levels are likely due to low densities of monarchs in this region and (or) migratory escape effects, where migrating individuals leave behind areas with high density of conspecifics and high potential for parasite accumulation and transmission. Future work should aim to disentangle the relative contribution of these two mechanisms for governing the decrease in parasitism at the range limits of migratory populations. Key words: monarch butterflies, Danaus plexippus, OE, Ophryocystis elektroscirrha, range limit, host-specific parasite, prevalence, disease ecology, migration. Chaque annee, des monarques (Danaus plexippus (Linnaeus, 1758)) de la population de lest de lAmerique du Nord migrent du Mexique au sud du Canada au printemps. S'il a ete demontre que cette migration vers le Nord limite l'infection des monarques par le parasite specifique Ophryocystis elektroscirrha McLaughlin et Myers, 1970 (OE), la prevalence d'OE aux limites de leur aire de repartition et le ou les mecanismes en cause demeurent inconnus. Nous avons evalue les taux d'infection a OE chez les monarques a la limite septentrionale de l'aire de repartition de la population de lest autour d'Ottawa (Ontario, Canada) et releve des taux d'infection extremement faibles (~1 % pour des intervalles de confiance superieurs de pres de 3 %). Les faibles taux d'infection a OE sont vraisemblablement dus aux faibles densites de monarques dans cette region et (ou) aux effets de la fuite migratoire, les individus qui migrent laissant derriere eux des zones de forte densite de conspecifiques et de potentiel eleve d'accumulation et de transmission de parasites. Des travaux futurs devraient s'affairer a departager les contributions relatives de ces deux mecanismes a la reduction du parasitisme aux limites des aires de repartition des populations migratrices. [Traduit par la Redaction] Mots-cles : monarques, Danaus plexippus, OE, Ophryocystis elektroscirrha, limite de l'aire de repartition, parasite specifique, prevalence, ecologie des maladies, migration., Introduction Every spring, monarch butterflies (Danaus plexippus (Linnaeus, 1758)) of the eastern North America population depart their wintering grounds in the highlands of central Mexico (Urquhart and Urquhart 1978) and [...]

Classroom and staffroom floor swabs across six elementary schools in Ottawa, Canada were tested for SARS-CoV-2. Environmental test positivity did not correlate with student grade groups, school-level absenteeism, pediatric COVID-19-related hospitalizations, or community SARS-CoV-2 wastewater levels. Schools in neighbourhoods with historically elevated COVID-19 burden showed a negative but non-significant association with lower swab positivity. [ABSTRACT FROM AUTHOR]

Evolutionary biology was previously considered a historical science with predictions about evolutionary trajectories believed to be near impossible. The development of high throughput sequencing and data analysis technologies has challenged this belief, and provided an abundance of data that yields novel insights into evolutionary processes. Evolutionary predictions are now increasingly being used to develop fundamental knowledge of evolving systems and/or to demonstrate evolutionary control. Here we investigate the factors that make evolutionary repeatability more or less likely to increase the accuracy of evolutionary predictions. We identify outstanding questions and provide a potential starting point to determine how evolutionary repeatability is affected by genetic relatedness. [ABSTRACT FROM AUTHOR]

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations. [ABSTRACT FROM AUTHOR]

Genetic background has the potential to influence both the tempo and trajectory of adaptive change: Different genotypes of a given species may adopt varied solutions to the same environmental challenge, or they may approach the same solution at different rates. Laboratory selection has been widely used to experimentally examine the evolutionary consequences of variation in genetic background, although largely using genotypes differing by only a few mutations. Here, we leverage natural variation in the bacterium Pseudomonas aeruginosa to investigate whether different adaptive solutions are accessible from distant points of departure on an adaptive landscape. We evolved 17 diverse genotypes in a laboratory medium that partially mimics the lung sputum of cystic fibrosis patients, and we measured changes in 10 phenotypes as well as in fitness. Using phylogenetically informed analyses, we found that genetic background impacted the tempo, but not the trajectory, of phenotypic evolution: Different starting genotypes converged toward similar phenotypes, but at varying rates. Our findings add to a growing body of evidence supporting widespread diminishing return epistasis during adaptation. The importance of genetic background toward the trajectory of adaptation remains inconsistent across experimental systems and conditions. [ABSTRACT FROM AUTHOR]