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Abstract Premise Pollen movement is a crucial component of dispersal in seed plants. Although pollen dispersal is well studied, methodological constraints have made it challenging to directly track pollen flow within multiple populations across landscapes. We labeled pollen with quantum dots, a new technique that overcomes past limitations, to evaluate the spatial scale of pollen dispersal and its relationship with conspecific density within 11 populations of Clarkia xantiana subsp. xantiana , a bee‐pollinated annual plant. Methods We used experimental arrays in two years to track pollen movement across distances of 5–35 m within nine populations and across distances of 10–70 m within two additional populations. We tested for distance decay of pollen dispersal, whether conspecific density modulated dispersal distance, and whether dispersal kernels varied among populations across an environmentally complex landscape. Results Labeled pollen receipt did not decline with distance over 35 m within eight of nine populations or over 70 m within either of two populations. Pollen receipt increased with conspecific density. Overall, dispersal kernels were consistent across populations. Conclusions The surprising uniformity in dispersal distance within different populations was likely influenced by low precipitation and plant density in our study years. This suggests that spatiotemporal variation in the abiotic environment substantially influences the extent of gene flow within and among populations. 

Abstract The increasing availability and complexity of next-generation sequencing (NGS) data sets make ongoing training an essential component of conservation and population genetics research. A workshop entitled “ConGen 2018” was recently held to train researchers in conceptual and practical aspects of NGS data production and analysis for conservation and ecological applications. Sixteen instructors provided helpful lectures, discussions, and hands-on exercises regarding how to plan, produce, and analyze data for many important research questions. Lecture topics ranged from understanding probabilistic (e.g., Bayesian) genotype calling to the detection of local adaptation signatures from genomic, transcriptomic, and epigenomic data. We report on progress in addressing central questions of conservation genomics, advances in NGS data analysis, the potential for genomic tools to assess adaptive capacity, and strategies for training the next generation of conservation genomicists.