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Abstract Scientific and public interest in the global status of insects has surged recently; however, understanding the relative importance of different stressors and their interconnections remains a crucial problem. We use a meta-synthetic approach to integrate recent hypotheses about insect stressors and responses into a network containing 3385 edges and 108 nodes. The network is highly interconnected, with agricultural intensification most often identified as a root cause. Habitat-related variables are highly connected and appear to be underdiscussed relative to other stressors. We also identify biases and gaps in the recent literature, especially those generated from a focus on economically important and other popular insects, especially pollinators, at the expense of non-pollinating and less charismatic insects. In addition to serving as a case study for how meta-synthesis can map a conceptual landscape, our results identify many important gaps where future meta-analyses will offer critical insights into understanding and mitigating insect biodiversity loss. 

Abstract Identifying patterns of pathogen infection in natural systems is crucial to understanding mechanisms of host–pathogen interactions. In this study, we explored how Junonia coenia densovirus (JcDV) infection varies over space and time in populations of the Melissa blue butterfly (Lycaeides melissa: Lycaenidae) using two different host plants. Collections ofL. melissaadults from multiple populations and years, along with host plant tissue and community samples of arthropods found on host plants, were screened to determine JcDV prevalence and load. Additionally, we sampled at multiple time points within a singleL. melissaflight season to investigate intra‐annual variation in infection patterns.We found population‐specific variation in viral prevalence ofL. melissaacross collection years, with historical samples potentially having higher viral prevalence than contemporary samples, although host plant diet was not informative for these patterns. Patterns of infection across multiple generations within a flight season showed that late‐season samples had a higher proportion of JcDV‐positive individuals, suggesting an accumulation of virus over the season. Sequence data from a segment of the JcDV capsid gene showed a lack of viral genetic diversity betweenL. melissacollected from different localities, and little to no viral particles were found in the surrounding environment.Our discovery of temporal variation in infection suggests that multiple sampling efforts must be made when describing pathogen prevalence in multivoltine hosts. Our findings represent an important first step towards further exploration of the ecological factors mediating disease prevalence and host‐specific variability of infection in wild insect populations. 

Abstract Climate change is contributing to declines of insects through rising temperatures, altered precipitation patterns, and an increasing frequency of extreme events. The impacts of both gradual and sudden shifts in weather patterns are realized directly on insect physiology and indirectly through impacts on other trophic levels. Here, we investigated direct effects of seasonal weather on butterfly occurrences and indirect effects mediated by plant productivity using a temporally intensive butterfly monitoring dataset, in combination with high‐resolution climate data and a remotely sensed indicator of plant primary productivity. Specifically, we used Bayesian hierarchical path analysis to quantify relationships between weather and weather‐driven plant productivity on the occurrence of 94 butterfly species from three localities distributed across an elevational gradient. We found that snow pack exerted a strong direct positive effect on butterfly occurrence and that low snow pack was the primary driver of reductions during drought. Additionally, we found that plant primary productivity had a consistently negative effect on butterfly occurrence. These results highlight mechanisms of weather‐driven declines in insect populations and the nuances of climate change effects involving snow melt, which have implications for ecological theories linking topographic complexity to ecological resilience in montane systems. 

Abstract Monarch butterflies are a species of conservation priority due to declining overwintering populations in both eastern and western North America. Declines in western overwintering monarchs—more than 99.9% since monitoring began—are especially acute. However, the degree to which western monarchs are a distinct biological entity is uncertain. In this review, we focus on phenotypic and genetic differentiation between eastern and western monarchs, with the goal of informing researchers and policy‐makers who are interested in monarch conservation. Eastern and western monarchs occupy distinct environments and show some evidence for phenotypic differentiation, particularly for migration‐associated traits, though population genetic and genomic studies suggest that they are indistinguishable from one another. We suggest future studies that could improve our understanding of differences between eastern and western monarchs. We also discuss the concept of adaptive capacity in eastern and western monarchs as well as non‐migratory populations outside of the monarch's primary North American range. Finally, we discuss the prospect of completely losing migratory monarchs from western North America and what this entails for monarch conservation. 

Summary To understand factors that influence the assembly of microbial communities, we inoculatedMedicago sativawith a series of nested bacterial synthetic communities and grew plants in distinct nitrogen concentrations. Two isolates in our eight‐member synthetic community,Williamsiasp. R60 andPantoeasp. R4, consistently dominate community structure across nitrogen regimes. WhilePantoeasp. R4 consistently colonizes plants to a higher degree compared to the other six organisms across each community and each nutrient level,Williamsiasp. R60 exhibits nutrient specific colonization differences.Williamsiasp. R60 is more abundant in plants grown at higher nitrogen concentrations, but exhibits the opposite trend when no plant is present, indicating plant‐driven influence over colonization. Our research discovered unique, repeatable colonization phenotypes for individual microbes during plant microbiome assembly, and identified alterations caused by the host plant, microbes, and available nutrients.