Inferring National and Regional Declines of Rare Orchid Species with Probabilistic Models

Fragmentation of natural habitats can increase numbers of rare species. Conservation of rare species requires experts and resources, which may be lacking for many species. In the absence of regular surveys and expert knowledge, historical sighting records can provide data on the distribution of a species. Numerous models have been developed recently to make inferences regarding the threat status of a taxon on the basis of variation in trends of sightings over time. We applied 5 such models to national and regional (county) data on 3 red-listed orchid species (Cephalanthera longifolia, Hammarbya paludosa, and Pseudorchis albida) and 1 species that has recently come to the attention of conservation authorities (Neotinea maculata) in the Republic of Ireland. In addition, we used an optimal linear estimate to calculate the time of extinction for each species overall and within each county. To account for bias in recording effort over time, we used rarefaction analysis. On the basis of sighting records, we inferred that these species are not threatened with extinction and, although there have been declines, there is no clear geographical pattern of decline in any species. Most counties where these orchid species occurred had a low number of sightings; hence, we were cautious in our interpretation of output from statistical models. We suggest the main drivers of decline in these species in Ireland are modification of habitats for increased agricultural production and lack of appropriate management. Our results show that the application of probabilistic models can be used even when sighting data are scarce, provided multiple models are used simultaneously and rarefaction is used to account for bias in recording effort among species over time. These models could be used frequently when making an initial conservation assessment of species in a region, particularly if there is a relatively constant recording rate and some knowledge of the underlying recording process. Regional-scale analyses, such as ours, complement World Conservation Union criteria for assessment of the extinct category and are useful for highlighting areas of under recording and focusing conservation efforts of rare and endangered species.