Interactions with microbial symbionts have yielded great macroevolutionary innovations across the tree of life, like the origins of chloroplasts and the mitochondrial powerhouses of eukaryotic cells. There is also increasing evidence that host-associated microbiomes influence patterns of microevolutionary adaptation in plants and animals. Here we describe how microbes can facilitate adaptation in plants and how to test for and differentiate between the two main mechanisms by which microbes can produce adaptive responses in higher organisms: microbe-mediated local adaptation and microbe-mediated adaptive plasticity. Microbe-mediated local adaptation is when local plant genotypes have higher fitness than foreign genotypes because of a genotype-specific affiliation with locally important microbes. Microbe-mediated adaptive plasticity occurs when local plant phenotypes have higher fitness than foreign phenotypes as a result of interactions with locally important microbes. These microbial effects on adaptation can be difficult to differentiate from traditional modes of adaptation but may be prevalent. Ignoring microbial effects may lead to erroneous conclusions about the traits and mechanisms underlying adaptation, hindering management decisions in conservation, restoration, and agriculture.

An underdeveloped but potentially valuable molecular method in ecology is the ability to quantify the frequency with which foraging pollinators carry different plant pollens. Thus far, DNA metabarcoding has only reliably identified the presence/absence of a plant species in a pollen sample, but not its relative abundance in a mixed sample. Here we use a system of four congeneric, co-flowering plants in the genus Clarkia and their bee pollinators to (1) develop a molecular method to quantify different Clarkia pollens found on foraging bees; and (2) determine if bee pollinators carry Clarkia pollens in predictable ways, based on knowledge of their foraging behaviors. We develop a molecular method we call quantitative amplicon sequencing (qAMPseq) which varies cycling number (20, 25, 30, and 35 cycles) in polymerase chain reaction (PCR), individually indexing the same samples in different cycle treatments, and sequencing the resulting amplicons. These values are used to approximate an amplification curve for each Clarkia species in each sample, similar to the approach of quantitative PCR, which can then be used to estimate the relative abundance of the different Clarkia species in the sample. Using this method, we determine that bee visitation behaviors are generally predictive of the pollens that bees carry while foraging. We also show that some bees carry multiple species of Clarkia at the same time, indicating that Clarkia likely compete via interspecific pollen transfer. In addition to adding a ‘missing link’ between bee visitation behavior and actual pollen transfer, we suggest qAMPseq as another molecular method to add to the developing molecular ecology and pollination biology toolbox.