Potential climate change effects on tree distributions in the Korean Peninsula: Understanding model & climate uncertainties

被引:30
作者
Koo, Kyung Ah [1 ]
Park, Seon Uk [1 ]
Kong, Woo-Seok [2 ]
Hong, Seungbum [1 ]
Jang, Inyoung [1 ]
Seo, Changwan [1 ]
机构
[1] Natl Inst Ecol, 1210 Geumgang Ro, Chungnam 33657, South Korea
[2] Kyung Hee Univ, Dept Geog, 26 Kyungheedae Ro, Seoul 02447, South Korea
关键词
Climate change; Species distribution model; Model uncertainty; Climate uncertainty; The Korean Peninsula; Machilus thunbergii; SPECIES DISTRIBUTION; LOCAL ADAPTATION; RANGE SHIFTS; FORECASTS; RESPONSES; IMPACTS; NICHES; AREAS; RISK;
D O I
10.1016/j.ecolmodel.2016.10.007
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The projections of species distribution models (SDMs) have provided critical knowledge for conservation planning under climate change in the Republic of Korea. However, uncertainty about the SDM projections has been criticized as a major challenge to reliable projections. The present research investigated uncertainty among competing models (Model uncertainty) and uncertainty of future climate conditions (climate uncertainty) driving from different GCMs and CO2 emission scenarios in predicting the future distributions of plants. For this purpose, using nine single-model algorithms and the pre-evaluation weighted ensemble method, we modeled the geographical distributions of Silver Magnolia (Machilus thunbergii Siebold & Zucc.), a warm-adapted evergreen broadleaved tree; furthermore, we predicted its future distributions under 20 climate change scenarios (5 global circulation models (GCMs) x 4 CO2 emission scenarios (RCPs)). The results showed a great variation in the accuracies of nine single-model projections: the mean AUC values of nine single-models ranged from 0.764 (SER) to 0.970 (RF), and the mean TSS ranged from 0.529 (SRE) to 0.852 (RF). RF (mean AUC= 0.970, mean TSS = 0.852) and the ensemble forecast (AUC= 0.968, TSS=0.804) showed the highest predictive power, while SRE showed the lowest. The future distributions of Silver Magnolia projected with the ensemble SDM clearly varied according to GCMs and RCPs. The twenty climate scenarios produced twenty different projections of the magnolia prospective distribution. GCMs commonly projected the maximum range expansion under RCP 8.5 in 2050 and 2070, but CO2 emission scenarios explaining the minimum expansions differed according to GCMs. In conclusion, our results show that GCMs, CO2 emission scenarios and SDM algorithms produce considerable variations in the SDM projections. Therefore, this research suggests that understanding of model and climate uncertainties is critical for an effective conservation planning in forest management under climate change on the Korean Peninsula. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:17 / 27
页数:11
相关论文
共 72 条
  • [1] Spatio-temporal analysis of alpine ecotones: A spatial explicit model targeting altitudinal vegetation shifts
    Alberto Diaz-Varela, Ramon
    Colombo, Roberto
    Meroni, Michele
    Silvia Calvo-Iglesias, Maria
    Buffoni, Armando
    Tagliaferri, Antonio
    [J]. ECOLOGICAL MODELLING, 2010, 221 (04) : 621 - 633
  • [2] Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS)
    Allouche, Omri
    Tsoar, Asaf
    Kadmon, Ronen
    [J]. JOURNAL OF APPLIED ECOLOGY, 2006, 43 (06) : 1223 - 1232
  • [3] Reducing uncertainty in projections of extinction risk from climate change
    Araújo, MB
    Whittaker, RJ
    Ladle, RJ
    Erhard, M
    [J]. GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2005, 14 (06): : 529 - 538
  • [4] Validation of species-climate impact models under climate change
    Araújo, MB
    Pearson, RG
    Thuiller, W
    Erhard, M
    [J]. GLOBAL CHANGE BIOLOGY, 2005, 11 (09) : 1504 - 1513
  • [5] Evaluating the effectiveness of conservation site networks under climate change: accounting for uncertainty
    Bagchi, Robert
    Crosby, Mike
    Huntley, Brian
    Hole, David G.
    Butchart, Stuart H. M.
    Collingham, Yvonne
    Kalra, Mohit
    Rajkumar, Jagadish
    Rahmani, Asad
    Pandey, Mitra
    Gurung, Hum
    Le Trong Trai
    Nguyen Van Quang
    Willis, Stephen G.
    [J]. GLOBAL CHANGE BIOLOGY, 2013, 19 (04) : 1236 - 1248
  • [6] Baker D.J., 2016, Glob. Chang. Biol
  • [7] Error and uncertainty in habitat models
    Barry, Simon
    Elith, Jane
    [J]. JOURNAL OF APPLIED ECOLOGY, 2006, 43 (03) : 413 - 423
  • [8] SmcHD1, containing a structural-maintenance-of-chromosomes hinge domain, has a critical role in X inactivation
    Blewitt, Marnie E.
    Gendrel, Anne-Valerie
    Pang, Zhenyi
    Sparrow, Duncan B.
    Whitelaw, Nadia
    Craig, Jeffrey M.
    Apedaile, Anwyn
    Hilton, Douglas J.
    Dunwoodie, Sally L.
    Brockdorff, Neil
    Kay, Graham F.
    Whitelaw, Emma
    [J]. NATURE GENETICS, 2008, 40 (05) : 663 - 669
  • [9] Random forests
    Breiman, L
    [J]. MACHINE LEARNING, 2001, 45 (01) : 5 - 32
  • [10] Briggs D., 1997, PLANT VARIATION EVOL