Assessing poison ivy (Toxicodendron radicans) presence and functional traits in relation to land cover and biophysical factors. (3rd September 2022)

• Record Type: Journal Article
• Authors: Resler, Lynn M.; Fry, J. T.; Leman, Scotland; Jelesko, John G.
• Is Part Of: Physical geography. Volume 43:Number 5(2022)
• Page Start: 614
• Page End: 637
• Publication Date: 2022-09-03
• Subjects: Poison ivy -- Toxicodendron radicans -- spatial Gaussian model -- functional traits -- Appalachian Mountains -- growth habit; Physical geography -- Periodicals; 910.02
• DOI: 10.1080/02723646.2021.1883802
• Languages: English
• ISSNs: 0272-3646

Abstract

ABSTRACT: Understanding species distributions remains central to research in ecology and biogeography. Emphasis is placed on the spatial presence/absence of plants as related to underlying environmental factors; however, distributions result from both abiotic factors and adaptations to the abiotic environment. We analyzed poison ivy ( Toxicodendron radicans (L.) Kuntze), which has high intraspecies variability in the plant functional trait of growth habit, to assess implications of plant strategies for spatial distributions. Our objectives were to: 1) determine whether anthropogenic habitats are statistically overrepresented in poison ivy incidence and growth habits (shrub, climbing liana, crawling liana), and 2) model biophysical parameters that constitute preferred poison ivy habitat and the three growth habits. We collected poison ivy field data along a trail-transect with corresponding geospatially indexed parameters, subsequently analyzed using Bayesian spatial modeling. Model results revealed poison ivy preference for human-modified habitat; Developed and Planted/Cultivated land use categories showed the largest marginal posterior probabilities for crawling and climbing lianas. Increasing temperature and elevation preferentially benefit the climbing growth habit. Our results suggest that variability in functional traits may impact species geographic distributions by expanding niche breadth. Incorporation of functional traits may thus advance predictive niche models of species distributions.