The Poweshiek skipperling (Oarisma poweshiek) is a critically endangered grassland butterfly with six populations remaining in the United States and Canada. The single Canadian population, with the largest remaining contiguous habitat, includes less than ~50 observed individuals and extirpation is potentially imminent. Captive breeding is underway and there is a need to locate suitable sites for reintroduction and habitat management. Species distribution models (SDMs) predict habitat quality and guide management decisions. Most SDMs rely on statistical validation as a surrogate metric for accuracy, with presence‐only SDMs usually reporting area under the curve (AUC). Although experts have long cautioned against relying on statistical validation alone, accuracy is rarely field‐validated. We developed a presence‐only SDM using the maximum entropy (Maxent) method to predict probability of occurrence for the Poweshiek skipperling and determine environmental covariates associated with high probability of occurrence. We collected two independent datasets to (a) calibrate our model to predict categories of habitat quality (using factor analysis) and (b) compare expected and observed habitat quality to calculate model accuracy. Statistical validation showed that we predicted presence‐absence of training data with high accuracy (AUC = 0.98). Covariates responsible for most of the variation in probability of occurrence included soil drainage, habitat patch size, and land use type. Only 0.4% of the study area was expected to represent good‐excellent habitat with the remaining 99.6% medium‐poor. Our model predicted novel habitat quality with 81% accuracy (better than chance). Poor‐medium habitat was predicted more accurately (92%) than good‐excellent habitat (54%). Our model showed better accuracy than most other field‐validated SDMs reviewed. We reiterate calls for greater field‐validation of SDMs: if we had relied on statistical validation alone, perceived accuracy of our model would be inflated. Finally, managers can use our results to reliably exclude predicted poor‐medium habitats as candidates for Poweshiek skipperling habitat management or reintroduction.

Fuscopannaria leucosticta is a rare and understudied cyanolichen with an interesting and unusual distribution in tertiary relict hotspots worldwide. There is a relatively large population in eastern North America, where it occurs mostly throughout the Appalachian Mountains and reaches its northernmost extent in New Brunswick and Nova Scotia, Canada. The ability to detect this species, and thus determine its habitat requirements, is critical for understanding how it might be affected by humaninduced environmental degradation. Maximum entropy modelling with MaxEnt was used to predict the distribution of suitable habitat for this species in Nova Scotia using 62 presence locations, 1405 pseudoabsence locations and four environmental covariates: depth to water table (a proxy for relative soil moisture), distance to the coast and mean annual temperature and precipitation. Our predictive maps identify important habitat features and areas of high suitability in Nova Scotia with an area under the curve value of 0·85. The predicted distribution of this lichen was most affected by temperature. This study elucidates locations as well as species-habitat relationships for F. leucosticta, providing land managers with baseline data that can aid in the discovery of additional populations and provide a better understanding of its ecological requirements which will support the development of sound conservation strategies for this rare lichen.