Identifying ecological and evolutionary research targets and risks in climate change studies to break barriers to broad inference
Fig 5
Conceptual framework for maximizing broad inference in climate change studies on plants, microbes and their interactions.
To optimize the robustness of a study, each of the following components should be considered, measured, or incorporated. (A) Especially in studies across multiple species or populations, accounting for evolutionary history or genetic hierarchy reduces the possibility of effect size inflation due to phylogenetic relatedness and informs the researcher of the effect of genetic variation on phenotypic responses. (B) Ideally, sampling should take place across the entire range of the species examined. At the very least, where in the species’ range sampling took place should be noted and accounted for in analyses. Here, we are assuming that Species A (flower) and Species B (microbe) have overlapping ranges (blue and red background) for graphical simplicity. Across the range, multiple environmental variables should be assessed for analyses (again, only one, mean annual temperature, is shown for simplicity). Sequencing and genotyping field samples can assess the strength and type of meta-community effects driving population and community patterns. (C) Examples of cross-validating experimental methods. Field observations can validate or inform experimental manipulations, as well as resurrection or paleoecological studies. Note that to our knowledge, resurrection and paleoecological studies are only possible for plants and not microorganisms at this time. Base map shapefile downloaded from: https://gadm.org/download_country_v3.html. Base map license information: https://gadm.org/license.html.