Summary: The interiors of plants are colonized by diverse microorganisms that are referred to as endophytes. Endophytes have received much attention over the past few decades, yet many questions remain unanswered regarding patterns in their biodiversity at local to global scales. To characterize research effort to date, we synthesized results from ~600 published studies. Our survey revealed a global research interest and highlighted several gaps in knowledge. For instance, of the 17 biomes encompassed by our survey, 7 were understudied and together composed only 7% of the studies that we considered. We found that fungal endophyte diversity has been characterized in at least one host from 30% of embryophyte families, while bacterial endophytes have been surveyed in hosts from only 10.5% of families. We complimented our survey with a vote counting procedure to determine endophyte richness patterns among plant tissue types. We found that variation in endophyte assemblages in above‐ground tissues varied with host growth habit. Stems were the richest tissue in woody plants, whereas roots were the richest tissue in graminoids. For forbs, we found no consistent differences in relative tissue richness among studies. We propose future directions to fill the gaps in knowledge we uncovered and inspire further research.

The butterfly fauna of lowland Northern California has exhibited a marked decline in recent years that previous studies have attributed in part to altered climatic conditions and changes in land use. Here, we ask if a shift in insecticide use towards neonicotinoids is associated with butterfly declines at four sites in the region that have been monitored for four decades. A negative association between butterfly populations and increasing neonicotinoid application is detectable while controlling for land use and other factors, and appears to be more severe for smaller-bodied species. These results suggest that neonicotinoids could influence non-target insect populations occurring in proximity to application locations, and highlights the need for mechanistic work to complement long-term observational data.