The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here, we present and evaluate a method of SNP discovery using RNA sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has as experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all-in-one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other nonmodel systems.

The timing of life events (phenology) can be influenced by climate. Studies from around the world tell us that climate cues and species responses can vary greatly. If variation in climate effects on phenology is strong within a single ecosystem, climate change could lead to ecological disruption, but detailed data from diverse taxa within a single ecosystem are rare. We collated first sighting and median activity within a high-elevation environment for plants, insects, birds, mammals and an amphibian across 45 years (1975-2020). We related 10 812 phenological events to climate data to determine the relative importance of climate effects on species phenologies. We demonstrate significant variation in climate-phenology linkage across taxa in a single ecosystem. Both current and prior climate predicted changes in phenology. Taxa responded to some cues similarly, such as snowmelt date and spring temperatures; other cues affected phenology differently. For example, prior summer precipitation had no effect on most plants, delayed first activity of some insects, but advanced activity of the amphibian, some mammals, and birds. Comparing phenological responses of taxa at a single location, we find that important cues often differ among taxa, suggesting that changes to climate may disrupt synchrony of timing among taxa.