Feasibility of coupled empirical and dynamic modeling to assess climate change and air pollution impacts on temperate forest vegetation of the eastern United States

TitleFeasibility of coupled empirical and dynamic modeling to assess climate change and air pollution impacts on temperate forest vegetation of the eastern United States
Publication TypeJournal Article
Year of Publication2018
AuthorsMcDonnell, TC, Reinds, GJ, Sullivan, TJ, Clark, CM, Bonten, LTC, Mol-Dijkstra, JP, Wamelink, GWW, Dovciak, M
JournalEnvironmental Pollution
Volume234
Pagination902 - 914
Date Published2018/03/01/
ISBN Number0269-7491
Accession NumberHBR.2018-10
KeywordsAcidification, Biodiversity, Climate Change, Forest understory, Nitrogen
Abstract

Changes in climate and atmospheric nitrogen (N) deposition caused pronounced changes in soil conditions and habitat suitability for many plant species over the latter half of the previous century. Such changes are expected to continue in the future with anticipated further changing air temperature and precipitation that will likely influence the effects of N deposition. To investigate the potential long-term impacts of atmospheric N deposition on hardwood forest ecosystems in the eastern United States in the context of climate change, application of the coupled biogeochemical and vegetation community model VSD+PROPS was explored at three sites in New Hampshire, Virginia, and Tennessee. This represents the first application of VSD+PROPS to forest ecosystems in the United States. Climate change and elevated (above mid-19th century) N deposition were simulated to be important factors for determining habitat suitability. Although simulation results suggested that the suitability of these forests to support the continued presence of their characteristic understory plant species might decline by the year 2100, low data availability for building vegetation response models with PROPS resulted in uncertain results at the extremes of simulated N deposition. Future PROPS model development in the United States should focus on inclusion of additional foundational data or alternate candidate predictor variables to reduce these uncertainties.

URLhttp://www.sciencedirect.com/science/article/pii/S0269749117312484
DOI10.1016/j.envpol.2017.12.002
StartPage

902

EndPage

914

Short TitleEnvironmental Pollution