Literature DB >> 36267685

Predicting the distribution of plant associations under climate change: A case study on Larix gmelinii in China.

Chen Chen1,2, Xi-Juan Zhang1,2, Ji-Zhong Wan3, Fei-Fei Gao1,2, Shu-Sheng Yuan1, Tian-Tian Sun1,2, Zhen-Dong Ni1, Jing-Hua Yu1.   

Abstract

Association is the basic unit of plant community classification. Exploring the distribution of plant associations can help improve our understanding of biodiversity conservation. Different associations depend on different habitats and studying the association level is important for ecological restoration, regional ecological protection, regulating the ecological balance, and maintaining biodiversity. However, previous studies have only focused on suitable distribution areas for species and not on the distribution of plant associations. Larix gmelinii is a sensitive and abundant species that occurs along the southern margin of the Eurasian boreal forests, and its distribution is closely related to permafrost. In this study, 420 original plots of L. gmelinii forests were investigated. We used a Maxent model and the ArcGIS software to project the potential geographical distribution of L. gmelinii associations in the future (by 2050 and 2070) according to the climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. We used the multi-classification logistic regression analysis method to obtain the response of the suitable area change for the L. gmelinii alliance and associations to climate change under different climate scenarios. Results revealed that temperature is the most crucial factor affecting the distribution of L. gmelinii forests and most of its associations under different climate scenarios. Suitable areas for each association type are shrinking by varying degrees, especially due to habitat loss at high altitudes in special terrains. Different L. gmelinii associations should have different management measures based on the site conditions, composition structure, growth, development, and renewal succession trends. Subsequent research should consider data on biological factors to obtain more accurate prediction results.
© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Entities:  

Keywords:  Larix gmelinii associations; Maxent; climate change; spatial distribution; temperature

Year:  2022        PMID: 36267685      PMCID: PMC9576964          DOI: 10.1002/ece3.9374

Source DB:  PubMed          Journal:  Ecol Evol        ISSN: 2045-7758            Impact factor:   3.167


  30 in total

Review 1.  Ecological responses to recent climate change.

Authors:  Gian-Reto Walther; Eric Post; Peter Convey; Annette Menzel; Camille Parmesan; Trevor J C Beebee; Jean-Marc Fromentin; Ove Hoegh-Guldberg; Franz Bairlein
Journal:  Nature       Date:  2002-03-28       Impact factor: 49.962

2.  Multinomial goodness-of-fit tests for logistic regression models.

Authors:  Morten W Fagerland; David W Hosmer; Anna M Bofin
Journal:  Stat Med       Date:  2008-09-20       Impact factor: 2.373

3.  How much does climate change threaten European forest tree species distributions?

Authors:  Marcin K Dyderski; Sonia Paź; Lee E Frelich; Andrzej M Jagodziński
Journal:  Glob Chang Biol       Date:  2017-10-30       Impact factor: 10.863

4.  Changes in forest biomass carbon storage in China between 1949 and 1998.

Authors:  J Fang; A Chen; C Peng; S Zhao; L Ci
Journal:  Science       Date:  2001-06-22       Impact factor: 47.728

5.  [Responses of Larix gmelinii geographical distribution to future climate change: a simulation study].

Authors:  Feng Li; Guangsheng Zhou; Mingcang Cao
Journal:  Ying Yong Sheng Tai Xue Bao       Date:  2006-12

6.  Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2.

Authors:  Andrew D Friend; Wolfgang Lucht; Tim T Rademacher; Rozenn Keribin; Richard Betts; Patricia Cadule; Philippe Ciais; Douglas B Clark; Rutger Dankers; Pete D Falloon; Akihiko Ito; Ron Kahana; Axel Kleidon; Mark R Lomas; Kazuya Nishina; Sebastian Ostberg; Ryan Pavlick; Philippe Peylin; Sibyll Schaphoff; Nicolas Vuichard; Lila Warszawski; Andy Wiltshire; F Ian Woodward
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-16       Impact factor: 11.205

7.  Predicting the current and future distribution of three Coptis herbs in China under climate change conditions, using the MaxEnt model and chemical analysis.

Authors:  Junjun Li; Gang Fan; Yang He
Journal:  Sci Total Environ       Date:  2019-09-04       Impact factor: 7.963

8.  Community-level phenological response to climate change.

Authors:  Otso Ovaskainen; Svetlana Skorokhodova; Marina Yakovleva; Alexander Sukhov; Anatoliy Kutenkov; Nadezhda Kutenkova; Anatoliy Shcherbakov; Evegeniy Meyke; Maria del Mar Delgado
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-30       Impact factor: 11.205

9.  SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses.

Authors:  Jason L Brown; Joseph R Bennett; Connor M French
Journal:  PeerJ       Date:  2017-12-05       Impact factor: 2.984

10.  Distributional responses to climate change for alpine species of Cyananthus and Primula endemic to the Himalaya-Hengduan Mountains.

Authors:  Xie He; Kevin S Burgess; Lian-Ming Gao; De-Zhu Li
Journal:  Plant Divers       Date:  2019-02-07
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.