Abstract
ESR Endangered Species Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials ESR 15:115-127 (2011) - DOI: https://doi.org/10.3354/esr00374 Predictive distribution model for the boreal felt lichen Erioderma pedicellatum in Newfoundland, Canada Yolanda F. Wiersma1,*, Randolph Skinner1,2 1Department of Biology, Memorial University, St. John’s, Newfoundland A1B 3X9, Canada 2Present address: Atlantic Canada Conservation Data Centre, Corner Brook, Newfoundland A2H 751, Canada *Email: ywiersma@mun.ca ABSTRACT: The worldwide population of the boreal felt lichen Erioderma pedicellatum is currently listed as Critically Endangered by the IUCN, with over 95% of the current population residing on the island of Newfoundland, Canada. Surveys of E. pedicellatum habitats and populations have primarily been opportunistic, rather than systematic, in nature. We used a geographic information system and compiled occurrence data and pseudo-absence data to develop the first predictive spatial distribution model for E. pedicellatum in Newfoundland. Of the suite of 19 models using 4 different parameters examined, the model with distance from coastline and topographic aspect was the best candidate. The final model had low sensitivity (i.e. a low ability to predict false presence), but high specificity (a strong ability to predict true absence). The final predictive model can contribute to future species status assessments and provincial conservation management decisions that require information on probable species distribution. KEY WORDS: Habitat · Lichen · Predictive habitat model · Species distribution · Rare species · Generalized additive model · Newfoundland Full text in pdf format PreviousNextCite this article as: Wiersma YF, Skinner R (2011) Predictive distribution model for the boreal felt lichen Erioderma pedicellatum in Newfoundland, Canada. Endang Species Res 15:115-127. https://doi.org/10.3354/esr00374 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in ESR Vol. 15, No. 2. Online publication date: November 10, 2011 Print ISSN: 1863-5407; Online ISSN: 1613-4796 Copyright © 2011 Inter-Research.
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