Predicting the impacts of climate change on the potential distribution of major native non-food bioenergy plants in China
Open accessAbstract
Planting non-food bioenergy crops on marginal lands is an alternative bioenergy development solution in China. Native non-food bioenergy plants are also considered to be a wise choice to reduce the threat of invasive plants. In this study, the impacts of climate change (a consensus of IPCC scenarios A2a for 2080) on the potential distribution of nine non-food bioenergy plants native to China (viz., Pistacia chinensis, Cornus wilsoniana, Xanthoceras sorbifolia, Vernicia fordii, Sapium sebiferum, Miscanthus sinensis, M. floridulus, M. sacchariflorus and Arundo donax) were analyzed using a MaxEnt species distribution model. The suitable habitats of the nine non-food plants were distributed in the regions east of the Mongolian Plateau and the Tibetan Plateau, where the arable land is primarily used for food production. Thus, the large-scale cultivation of those plants for energy production will have to rely on the marginal lands. The variables of "precipitation of the warmest quarter" and "annual mean temperature" were the most important bioclimatic variables for most of the nine plants according to the MaxEnt modeling results. Global warming in coming decades may result in a decrease in the extent of suitable habitat in the tropics but will have little effect on the total distribution area of each plant. The results indicated that it will be possible to grow these plants on marginal lands within these areas in the future. This work should be beneficial for the domestication and cultivation of those bioenergy plants and should facilitate land-use planning for bioenergy crops in China.
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Many native plants (e.g., oil-bearing plants or trees) may become suitable for energy production on marginal land.
“A lot of native plants (e.g., oil-bearing plants or trees), may become suitable for energy production on marginal land [116,117].”
From Biomass and biofuels in China: Toward bioenergy resource potentials and their impacts on the environment (2018) · cites this paper as [116]
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- Authors
- Wang, W., Tang, X., Zhu, Q., Pan, K., Hu, Q., He, M., & Li, J.
- Affiliations
- Biogas Institute of Ministry of Agriculture (CN)
- Corresponding author
- Wang, Wenguo
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-11-03
- Volume
- 9
- Issue
- 11
- Pages
- e111587
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4218772
- OpenAlex
- W1994957368
- Cited by
- 32
- References
- 58
- Citations by year
- 2025: 5 · 2024: 2 · 2023: 1 · 2022: 3 · 2021: 2 · 2020: 7 · 2019: 5 · 2018: 3 · 2017: 3 · 2015: 1
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Greater South Information System
- Funders
- National Natural Science Foundation of China (51108239)
- Topics
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Bioenergy crop production and management
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Botany and Plant Ecology Studies
- Keywords
- climate change impacts, native plants, species distribution modeling, MaxEnt, marginal land, invasive plants, habitat suitability, bioclimatic variables, Miscanthus, Arundo donax, Pistacia chinensis, Xanthoceras sorbifolia, Vernicia fordii, Sapium sebiferum, China
- MeSH terms
- China, Geography, Models, Theoretical, Plants, Ecosystem, Crops, Agricultural, Climate Change
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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