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Title: Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars

Abstract

Previous studies have shown that switchgrass has a wide range of genetic variation and that productivity is linked to local adaptation to the location of origin for many cultivars. In this meta–analysis, we compiled and analyzed 900 observations associated with 41 field trials for four switchgrass cultivars (two lowlands, Alamo and Kanlow, and two uplands, Cave–In–Rock and Shelter). This extensive dataset and machine learning were used to identify the most influential variables impacting switchgrass productivity, to search for evidence of local adaptation to each cultivar's location of origin, and to predict change in productivity under future climate for each cultivar. In general, variables associated with climate and management are more important predictors of productivity relative to soil variables. Three climatic variables, annual mean temperature, annual precipitation, and precipitation in the wettest month, are identified as key environmental variables for productivity of all cultivars. Productivity under future climate (2041–2060) is predicted to stay stable for all cultivars relative to the prediction under current climate (1986–2005) across all trial locations and over a 20–year simulation period. However, the productivity of each cultivar varies from location to location and from year to year, although productivity varies more between locations than between years. Additionally,more » we observe shifts in the most productive cultivar at the local field scale depending on the combination of management practice and climates. The shape of the relationship between productivity and the annual mean temperature relative to the cultivar's location of origin is a bell–shaped curve for Kanlow, Cave–in–Rock, and Shelter, indicative of local adaptation. Identifying influential environmental variables and their relationships to productivity with respect to cultivar's location of origin help predicting productivity on the local field scale, and will help with the biofuel production planning through the selection of suitable cultivars for different locations under climate changes.« less

Authors:
ORCiD logo [1];  [1];  [2];  [1]
  1. Univ. of Texas, Austin, TX (United States)
  2. Michigan State Univ., East Lansing, MI (United States)
Publication Date:
Research Org.:
Univ. of Texas, Austin, TX (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Science Foundation (NSF)
OSTI Identifier:
1594756
Alternate Identifier(s):
OSTI ID: 1501750
Grant/Contract Number:  
SC0014156; IOS-1444533
Resource Type:
Accepted Manuscript
Journal Name:
Global Change Biology. Bioenergy
Additional Journal Information:
Journal Volume: 11; Journal Issue: 8; Journal ID: ISSN 1757-1693
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; biomass production; climate change; environmental factors; functional form; local adaptation; local field scale; location of origin; meta‐analysis; variable importance

Citation Formats

Zhang, Li, Juenger, Thomas E., Lowry, David B., and Behrman, Kathrine D. Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars. United States: N. p., 2019. Web. doi:10.1111/gcbb.12609.
Zhang, Li, Juenger, Thomas E., Lowry, David B., & Behrman, Kathrine D. Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars. United States. doi:10.1111/gcbb.12609.
Zhang, Li, Juenger, Thomas E., Lowry, David B., and Behrman, Kathrine D. Fri . "Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars". United States. doi:10.1111/gcbb.12609. https://www.osti.gov/servlets/purl/1594756.
@article{osti_1594756,
title = {Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars},
author = {Zhang, Li and Juenger, Thomas E. and Lowry, David B. and Behrman, Kathrine D.},
abstractNote = {Previous studies have shown that switchgrass has a wide range of genetic variation and that productivity is linked to local adaptation to the location of origin for many cultivars. In this meta–analysis, we compiled and analyzed 900 observations associated with 41 field trials for four switchgrass cultivars (two lowlands, Alamo and Kanlow, and two uplands, Cave–In–Rock and Shelter). This extensive dataset and machine learning were used to identify the most influential variables impacting switchgrass productivity, to search for evidence of local adaptation to each cultivar's location of origin, and to predict change in productivity under future climate for each cultivar. In general, variables associated with climate and management are more important predictors of productivity relative to soil variables. Three climatic variables, annual mean temperature, annual precipitation, and precipitation in the wettest month, are identified as key environmental variables for productivity of all cultivars. Productivity under future climate (2041–2060) is predicted to stay stable for all cultivars relative to the prediction under current climate (1986–2005) across all trial locations and over a 20–year simulation period. However, the productivity of each cultivar varies from location to location and from year to year, although productivity varies more between locations than between years. Additionally, we observe shifts in the most productive cultivar at the local field scale depending on the combination of management practice and climates. The shape of the relationship between productivity and the annual mean temperature relative to the cultivar's location of origin is a bell–shaped curve for Kanlow, Cave–in–Rock, and Shelter, indicative of local adaptation. Identifying influential environmental variables and their relationships to productivity with respect to cultivar's location of origin help predicting productivity on the local field scale, and will help with the biofuel production planning through the selection of suitable cultivars for different locations under climate changes.},
doi = {10.1111/gcbb.12609},
journal = {Global Change Biology. Bioenergy},
number = 8,
volume = 11,
place = {United States},
year = {2019},
month = {3}
}

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