Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

被引:25
|
作者
Shafer, Sarah L. [1 ]
Bartlein, Patrick J. [2 ]
Gray, Elizabeth M. [3 ]
Pelltier, Richard T. [4 ]
机构
[1] US Geol Survey, Corvallis, OR USA
[2] Univ Oregon, Dept Geog, Eugene, OR 97403 USA
[3] Nature Conservancy, Maryland DC, Bethesda, MD USA
[4] US Geol Survey, Denver, CO 80225 USA
来源
PLOS ONE | 2015年 / 10卷 / 10期
关键词
INCORPORATING CLIMATE-CHANGE; SPECIES DISTRIBUTION; WILLAMETTE VALLEY; ECOSYSTEM; FIRE; HISTORY; OREGON; IMPACT; SHIFTS; RISK;
D O I
10.1371/journal.pone.0138759
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0 degrees N latitude by 136.6-103.0 degrees W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (similar to 1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.
引用
收藏
页数:21
相关论文
共 50 条
  • [41] Future changes of the terrestrial ecosystem based on a dynamic vegetation model driven with RCP8.5 climate projections from 19 GCMs
    Miao Yu
    Guiling Wang
    Dana Parr
    Kazi Farzan Ahmed
    Climatic Change, 2014, 127 : 257 - 271
  • [42] Future changes of the terrestrial ecosystem based on a dynamic vegetation model driven with RCP8.5 climate projections from 19 GCMs
    Yu, Miao
    Wang, Guiling
    Parr, Dana
    Ahmed, Kazi Farzan
    CLIMATIC CHANGE, 2014, 127 (02) : 257 - 271
  • [43] Changes in future precipitation over South Korea using a global high-resolution climate model
    Lee, Sanghun
    Bae, Deg-Hyo
    Cho, Chun-Ho
    ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES, 2013, 49 (05) : 619 - 624
  • [44] Changes in future precipitation over South Korea using a global high-resolution climate model
    Sanghun Lee
    Deg-Hyo Bae
    Chun-Ho Cho
    Asia-Pacific Journal of Atmospheric Sciences, 2013, 49 : 619 - 624
  • [45] Using High-Spatial Resolution UAV-Derived Data to Evaluate Vegetation and Geomorphological Changes on a Dune Field Involved in a Restoration Endeavour
    Fabbri, Stefano
    Grottoli, Edoardo
    Armaroli, Clara
    Ciavola, Paolo
    REMOTE SENSING, 2021, 13 (10)
  • [46] Using fine scale resolution vegetation data from LiDAR and ground-based sampling to predict Pacific marten resting habitat at multiple spatial scales
    Tweedy, Patrick J.
    Moriarty, Katie M.
    Bailey, John D.
    Epps, Clinton W.
    FOREST ECOLOGY AND MANAGEMENT, 2019, 452
  • [47] Evaluating aspects of the community land and atmosphere models (CLM3 and CAM3) using a Dynamic Global Vegetation Model
    Bonan, Gordon B.
    Levis, Samuel
    JOURNAL OF CLIMATE, 2006, 19 (11) : 2290 - 2301
  • [48] Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs)
    Sitch, S.
    Huntingford, C.
    Gedney, N.
    Levy, P. E.
    Lomas, M.
    Piao, S. L.
    Betts, R.
    Ciais, P.
    Cox, P.
    Friedlingstein, P.
    Jones, C. D.
    Prentice, I. C.
    Woodward, F. I.
    GLOBAL CHANGE BIOLOGY, 2008, 14 (09) : 2015 - 2039
  • [49] PROJECTION OF SOIL CARBON CHANGES AND FOREST PRODUCTIVITY FOR 100 YEARS IN MALAYSIA USING DYNAMIC VEGETATION MODEL LUND-POTSDAM-JENA
    Azian, M.
    Nizam, M. S.
    Nik-Norafida, N. A.
    Ismail, P.
    Samsudin, M.
    Noor-Farahanizan, Z.
    JOURNAL OF TROPICAL FOREST SCIENCE, 2022, 34 (03) : 274 - 283
  • [50] Research on Vegetation Dynamic Change Simulation Based on Spatial Data Mining of ANN-CA Model Using Time Series of Remote Sensing Images
    Cai, Zhenyu
    Wang, Xiaohua
    COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE III, 2010, 317 : 551 - 557