Using Species Distribution Modeling to Guide Surveys for a Rare Plant (Cymopterus sessiliflorus): Climate and Landscape Variables Predict Potential Distribution

Rare species at the edge of their range often persist after range contractions, yet basic information is typically lacking. We created species distribution models (SDMs) to guide field surveys for a disjunct population of Sessileflower Indian parsley (Cymopterus sessiliflorus; Apiaceae). We used historical observations to produce an initial model that guided field surveys in 2023. We refined the model using new observations from these surveys and the best predictors were shrubs, rock outcrops, mean monthly precipitation of the warmest quarter and rock type (area under the curve = 0.97). Suitable habitat (moderate-high and high classes) was predicted in <2% of Wyoming. We discovered 11 new populations over 2 summers. We collected 17 bee genera (n = 272 individuals) during C. sessiliflorus flowering suggesting diverse potential pollinators may transport pollen. Our model highlighted other areas predicted suitable and surveys in these areas may reveal new populations of this rare plant. The SDMs demonstrated how sparse historical data on rare species can be used to direct surveys in an efficient and effective manner. The information we gathered provided basic data for a rare plant at the periphery of its range where the most robust populations may occur making them critical for conservation efforts.