Priming has proved to enhance seed germination, but most of the research dealing with this topic has been carried out with cultivated species. The potential applications that this process has on wild species, which can be useful for restoration, are usually overlooked. This study analyses the germination response after natural priming and hydropriming of Penstemon roseus and Castilleja tenuiflora, two perennial herbs growing in a protected area known as ‘Parque Ecológico de la Ciudad de México’. Photoblastism was evaluated for both species. Seeds were exposed to a hydration/dehydration cycle and then placed in germination chambers to determine responses to hydropriming. To identify the effects of natural priming, seeds were buried in natural conditions and then recovered every two months and placed in germination chambers. Germination percentages and rates were then quantified. Both species proved to have permeable seed coats. Penstemon roseus seeds are positive photoblastic whereas C. tenuiflora seeds are indifferent to light. Priming methods increased C. tenuiflora germination rates, but they did not affect germination capacity. For P. roseus, priming methods did not improve germination rates, and germination capacity of recovered seeds decreased after the rainy season, suggesting that P. roseus forms a short-term, transient, seed bank. The germination strategies of these two species allow them to occupy suitable microsites for germination and establishment. These responses can be helpful in developing restoration programmes based on the accelerated establishment of native and characteristic successional species.

Aim Species rarity is often used as a measure to assess the risk of extinction of species, and thus, different methods have been developed to describe the composition of rare species in biological communities. These methods usually depend on species attributes that are not always available and very often ignore imperfect species detection. In this work, we developed a new method to characterize species rarity in a community when species are detected imperfectly. Our modelling framework is based on Bayesian occupancy models to estimate species distributions under imperfect detection using presence‐nondetection data. Innovation We propose a finite mixture occupancy model to identify rare species based on their occupancy and class‐membership probabilities. Here, we explored a two‐class finite mixture model to distinguish between rare and common species classes and presented the general modelling framework for a problem with more than two classes. By using simulations, we were able to compare our model results under different scenarios obtaining a high‐classification performance across all of them. Additionally, we applied our model to a data set of Odonata occurrence records that were partially observed due to imperfect detection and quantified the proportion of rare species on a national scale across waterbodies in the United Kingdom. Main conclusions Nowadays, biodiversity conservation involves monitoring programmes that target multiple species within a community where individual species responses may vary widely. This high variability makes the task of identifying the ecological processes that drive distributions of rare species difficult. Thus, our method represents a new approach to characterize the composition of a community in terms of species rarity while correcting for detectability bias. Our modelling framework also suggests lines of research and future developments for the understanding of how species rarity can be measured in a wide range of scenarios.