Foliar cover models for five common plant species in arctic Alaska circa 2014 (30 m)

• Main Authors: Timm Nawrocki, Matthew Carlson, Jeanne Osnas, Jamie Trammell, Frank Witmer
• Format: Dataset
• Language: unknown
• Published: Knowledge Network for Biocomplexity 2019
• Subjects: vegetation; abundance; foliar cover; distribution; arctic; Alaska; Carex aquatilis; Eriophorum vaginatum; Rhododendron tomentosum; Salix pulchra; Vaccinium vitis-idaea; aquatilis; vaginatum; tomentosum; pulchra; vitis-idaea; Arctic; Brooks Foothills; Eriophorum
• Online Access: https://search.dataone.org/view/urn:uuid:669ae30a-0388-401f-b70b-a5a2e6ace48c

We modeled foliar cover of five dominant and common vascular plant species in arctic Alaska: Carex aquatilis, Eriophorum vaginatum, Rhododendron tomentosum, Salix pulchra, and Vaccinium vitis-idaea. Unlike non-overlapping categorical vegetation types (i.e., typical vegetation and land cover maps), species-level gradients of foliar cover are consistent with the ecological theories of individualistic species response and niche space. We collected plant species foliar cover data and 17 environmental variables in the Beaufort Coastal Plain and Brooks Foothills of Alaska from 2012 to 2017. We integrated these data into a standardized database with 13 additional vegetation surveying and monitoring datasets in northern Alaska collected from 1998 to 2017. To map the species-level patterns of foliar cover for six dominant and widespread vascular plant species in arctic Alaska, we used statistical learning models to associate ground-based measurements of species distribution and foliar cover to environmental features and multi-season spectral features. For five of the six modeled species, our models predicted 35% to 65% of the observed species-level variation in foliar cover. Overall, our foliar cover gradients predicted significantly more of the observed spatial heterogeneity in species distribution and abundance than an existing categorical vegetation map. Our analysis of vegetation patterns enables quantifying and monitoring landscape level changes in species, vegetation communities, and wildlife habitat independently of subjective categorical vegetation types and facilitates integrating spatial patterns across multiple ecological scales.