Abstract
Introduction: Mounting evidence suggests that geographic ranges of tree species worldwide are shifting under global environmental changes. Little is known, however, about if and how these species’ range shifts may trigger the range shifts of various types of forests. Markowitz’s portfolio theory of investment and its broad application in ecology suggest that the range shift of a forest type could differ substantially from the range shifts of its constituent tree species. Methods: Here, we tested this hypothesis by comparing the range shifts of forest types and the mean of their constituent species between 1970–1999 and 2000–2019 across Alaska, Canada, and the contiguous United States using continent-wide forest inventory data. We first identified forest types in each period using autoencoder neural networks and K-means cluster analysis. For each of the 43 forest types that were identified in both periods, we systematically compared historical range shifts of the forest type and the mean of its constituent tree species based on the geographic centroids of interpolated distribution maps. Results: We found that forest types shifted at 86.5 km·decade-1 on average, more than three times as fast as the average of constituent tree species (28.8 km·decade-1). We showed that a predominantly positive covariance of the species range and the change of species relative abundance triggers this marked difference. Discussion: Our findings provide an important scientific basis for adaptive forest management and conservation, which primarily depend on individual species assessment, in mitigating the impacts of rapid forest transformation under climate change.
Original language | English |
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Article number | 1366568 |
Journal | Frontiers in Ecology and Evolution |
Volume | 12 |
DOIs | |
State | Published - 2024 |
Bibliographical note
Publisher Copyright:Copyright © 2024 Abbasi, Woodall, Gamarra, Hui, Picard, Ochuodho, de-Miguel, Sahay, Fei, Paquette, Chen, Catlin and Liang.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the U.S. Department of Agriculture\u2019s (USDA) Agricultural Marketing Service [grant numbers AM200100XXXXG007]; USDA National Institute of Food and Agriculture McIntire Stennis project 1017711; Start-up Fund provided by the Department of Forestry and Natural Resource and the College of Agriculture, Purdue University; Department of Forestry and Natural Resources, Purdue University; Takenaka Scholarship Foundation; Natural Sciences and Engineering Research Council of Canada [grant numbers RGPIN-2019\u201305109, STPGP506284]; and Serra-H\u00FAnter Fellowship provided by the Government of Catalonia.
Funders | Funder number |
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Purdue Climate Change Research Center, Purdue University | |
Takenaka Scholarship Foundation | |
University of Kentucky Department of Forestry and Natural Resources | |
ICREA Foundation-Generalitat de Catalunya | |
College of Agriculture, Purdue University | |
U.S. Department of Agriculture | |
Serra-Húnter Fellowship | |
Agricultural Marketing Service | AM200100XXXXG007 |
Agricultural Marketing Service | |
US Department of Agriculture National Institute of Food and Agriculture, Agriculture and Food Research Initiative | 1017711 |
US Department of Agriculture National Institute of Food and Agriculture, Agriculture and Food Research Initiative | |
Natural Sciences and Engineering Research Council of Canada | STPGP506284, RGPIN-2019–05109 |
Natural Sciences and Engineering Research Council of Canada |
Keywords
- forest classification
- machine learning
- portfolio effect
- range shift
- tree species
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Ecology