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Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change

Authors:

Wen Wang

Hong He

Frank Thompson

Martin Spetich

Jacob Fraser

Publication Type:
Journal Article
Year of Publication:
2018
Secondary Title:
Science of The Total Environment
ISSN:
00489697
DOI:
10.1016/j.scitotenv.2018.03.353
Pages:
1214-1221
Volume:
634
Year:
2018
Date:
Jan-09-2018

Abstract

Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are not well represented in current climate-distribution models (e.g., niche and biophys- ical process models) and constitute a large uncertainty in projections of future tree species distribution shifts. We investigate how species biological traits and environmental heterogeneity affect species distribution shifts. We used a species-specific, spatially explicit forest dynamic model LANDIS PRO, which incorporates site-scale tree species demography and competition, landscape-scale dispersal and disturbances, and regional-scale abiotic con- trols, to simulate the distribution shifts of four representative tree species with distinct biological traits in the cen- tral hardwood forest region of United States. Our results suggested that biological traits (e.g., dispersal capacity, maturation age) were important for determining tree species distribution shifts. Environmental heterogeneity, on average, reduced shift rates by 8% compared to perfect environmental conditions. The average distribution shift rates ranged from 24 to 200 m year-1 under climate change scenarios, implying that many tree species may not able to keep up with climate change because of limited dispersal capacity, long generation time, and en- vironmental heterogeneity. We suggest that climate-distribution models should include species demographic processes (e.g., fecundity, dispersal, colonization), biological traits (e.g., dispersal capacity, maturation age), and environmental heterogeneity (e.g., habitat fragmentation) to improve future predictions of species distribu- tion shifts in response to changing climates.