期刊
ECOSPHERE
卷 13, 期 4, 页码 -出版社
WILEY
DOI: 10.1002/ecs2.4016
关键词
Abies balsamea; climate change; historical data; occurrence; Picea glauca; Picea mariana; Picea rubens; species distribution models; spruce-fir forest
类别
资金
- NASA [15-EARTH15R-0097]
- National Science Foundation [1920908]
- USDA AFRI [ME0-2011-00832]
- Department of Interior Northeast Climate Adaptation Science Center
- Office of Integrative Activities
- Office Of The Director [1920908] Funding Source: National Science Foundation
This study assessed the bioclimatic distribution of spruce-fir forests in the North American Acadian Forest Region using new species distribution models that incorporated historical data and seasonal climate interactions. The results showed that including historical data and considering seasonal climate interactions improved the prediction of species distributions and provided more accurate forecasts.
Spruce-fir (Picea-Abies) forests of the North American Acadian Forest Region are at risk of disappearing from the northeastern United States and Canada due to climate change. Species distribution models (SDMs) have been used to predict changes in this critical transitional ecosystem in the past, but none have addressed how seasonal patterns of temperature and precipitation interact to influence tree species abundance. Inferences have also been limited by contemporary inventory data that could not fully characterize species ranges because they either, (1) only sampled species occurrence after large-scale human disturbance and settlement, or (2) did not span critical geopolitical boundaries (e.g., the US-Canadian border) that intersect the focal species' range(s). Here, we built new SDM models to better assess the bioclimatic distribution of four spruce-fir species and to test the importance of seasonal climate interactions. We compiled an extensive database of tree occurrence and abundance from recent (similar to 1955-2012) and historical time periods (1623-1869) to model current species distributions and to predict how these might change under future climate. We found that including historical tree data in our SDMs revealed previously unrecognized suitable habitat along the southern edge of species' contemporary ranges. Random forest models predicted occurrence with high accuracy (area under receiver operator curve >0.98), and the seasonal climate variables that emerged as most important for these cold-adapted species all included interactions that reflected sensitivity to colder temperatures, and preferences for wet weather concentrated in the winter months. Under moderate climate warming (representative concentration pathway 6.0), the northeastern United States retained additional suitable habitat when historical data were included through 2060 for three of the four species: red spruce (Picea rubens), black spruce (Picea mariana), and balsam fir (Abies balsamea), while white spruce (Picea glauca) habitat contracted into Canada. In contrast, future predictions from models that used contemporary data alone forecast extirpation for all four species from the northeastern United States. Overall, these findings highlight that prediction of species ranges in transitional ecosystems that span geopolitical boundaries and gradients of intense land use are improved when historical data and seasonal climate interactions of both temperature and precipitation variables are incorporated.
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