林业科学 ›› 2021, Vol. 57 ›› Issue (8): 43-55.doi: 10.11707/j.1001-7488.20210805
王爱君1,路东晔1,张国盛1,*,黄海广1,2,王颖3,呼斯楞3,敖民3
收稿日期:
2020-10-16
出版日期:
2021-08-25
发布日期:
2021-09-30
通讯作者:
张国盛
基金资助:
Aijun Wang1,Dongye Lu1,Guosheng Zhang1,*,Haiguang Huang1,2,Ying Wang3,Sileng Hu3,Min Ao3
Received:
2020-10-16
Online:
2021-08-25
Published:
2021-09-30
Contact:
Guosheng Zhang
摘要:
目的: 叉子圆柏是欧洲、亚洲和美洲石质山坡、河谷及覆沙丘陵地区的重要防沙固土树种,对维持生态环境稳定具有重要意义。探讨限制叉子圆柏分布的主导环境变量,模拟气候变化下叉子圆柏潜在适宜分布区,可为叉子圆柏资源管理与恢复提供理论依据。方法: 基于欧亚大陆叉子圆柏267个现有种群分布地理信息以及环境变量(气候、海拔),采用MaxEnt、BioClim、DoMain 3种模型,模拟叉子圆柏潜在适宜分布区。通过受试者工作特征(ROC)曲线下方面积(AUC值)和Kappa值对3种模型进行比较分析与筛选。基于MaxEnt模型比较末次盛冰期、全新世中期、当前及未来(2070年)的潜在地理分布格局,探讨制约叉子圆柏地理分布的环境变量。结果: 1)基于MaxEnt模型综合环境变量贡献率、置换重要值以及刀切法检验的结果表明,叉子圆柏地理分布主要受年均温、海拔、温度季节性变化3个环境变量影响。2)基于MaxEnt模型气候变量模拟的欧亚大陆叉子圆柏当前适宜生境面积为663.115×103 km2,集中在30°~50° N之间,山地是叉子圆柏主适生区。3)基于MaxEnt模型不同地质历史时期预测的叉子圆柏适宜生境面积表明,亚洲是叉子圆柏的主分布区。亚洲的适生区面积在末次盛冰期占86.9%、全新世中期占87.0%、当前时期占57.8%、未来2070(RCP2.6)和2070(RCP8.5)时期分别占84.1%和79.2%。从末次盛冰期到当前至未来叉子圆柏适宜生境面积呈现先增加后减少的变化特征、分布中心具有从北到南再到北的迁移趋势。结论: 叉子圆柏地理分布不仅受气候环境变量(温度、降水)影响,也与海拔相关。分布区范围符合柏科分布带特征。本研究结果可为叉子圆柏种质资源管理、修复与重建提供重要参考。
中图分类号:
王爱君,路东晔,张国盛,黄海广,王颖,呼斯楞,敖民. 基于MaxEnt模拟欧亚大陆气候变化下叉子圆柏的潜在分布[J]. 林业科学, 2021, 57(8): 43-55.
Aijun Wang,Dongye Lu,Guosheng Zhang,Haiguang Huang,Ying Wang,Sileng Hu,Min Ao. Potential Distribution of Juniperus sabina under Climate Change in Eurasia Continent Based on MaxEnt Model[J]. Scientia Silvae Sinicae, 2021, 57(8): 43-55.
表1
预测叉子圆柏地理分布的环境变量"
环境变量Environmental variable | |
Bio1 | 年均气温Annual mean temperature/℃ |
Bio2 | 昼夜温差月均值Monthly mean diurnal range/℃ |
Bio4 | 温度季节性变化Temperature seasonality/℃ |
Bio7 | 年温度变化范围Temperature annual range/℃ |
Bio8 | 最湿季平均温度Mean temperature of wettest quarter/℃ |
Bio9 | 最干季平均温度Mean temperature of driest quarter/℃ |
Bio12 | 年降水量Annual precipitation/mm |
Bio14 | 最干月降水量Precipitation of driest month/mm |
Bio15 | 降水量季节性变化Precipitation seasonality(%) |
Bio17 | 最干季降水量Precipitation of driest quarter/mm |
Bio18 | 最热季降水量Precipitation of warmest quarter/mm |
Bio19 | 最冷季降水量Precipitation of coldest quarter/mm |
Elev | 海拔Elevation/m |
表3
各环境变量贡献率"
环境变量 Environmental variable | 贡献率 Percent contribution(%) | 置换重要值 Permutation importance(%) | 环境变量 Environmental variable | 贡献率 Percent contribution(%) | 置换重要值 Permutation importance(%) | |
Bio1 | 28.80±0.86 | 18.70±2.12 | Bio15 | 2.90±0.98 | 7.70±1.50 | |
Elev | 29.00±0.36 | 45.70±5.67 | Bio9 | 2.50±0.43 | 6.20±1.08 | |
Bio4 | 13.00±0.98 | 8.00±7.08 | Bio12 | 2.10±0.59 | 5.20±1.51 | |
Bio14 | 7.10±2.14 | 0.30±1.25 | Bio7 | 0.70±2.42 | 2.30±0.65 | |
Bio18 | 5.70±0.49 | 2.10±0.24 | Bio2 | 0.70±0.28 | 0.80±0.40 | |
Bio17 | 3.60±1.63 | 0.10±0.17 | Bio19 | 0.60±0.19 | 0.30±0.05 | |
Bio8 | 3.50±0.12 | 2.70±0.62 |
表6
各时期叉子圆柏适生区的年均气温(Bio1)、海拔(Elev)、温度季节性变化(Bio4)、年降水量(Bio12)变化范围及均值"
时期 Period | 年均气温(Bio1) Annual average temperature/℃ | 海拔(Elev) Elevation/m | 温度季节性变化(Bio4) Seasonal variation of temperature/℃ | 年降水量(Bio12) Annual precipitation/mm | |||||||
范围Range | 均值Average | 范围Range | 均值Average | 范围Range | 均值Average | 范围Range | 均值Average | ||||
LGM | -14.5~2.2 | -1.42±4.78 | 110~3 100 | 1 254±824 | 4.1~15.9 | 9.58±3.50 | 90~2 000 | 552.95±389.24 | |||
MID | -9.0~7.6 | 4.69±4.45 | 800~3 000 | 1 254±824 | 6.2~16.4 | 10.07±3.03 | 150~1 700 | 611.56±343.50 | |||
当前Current | -8.0~13.0 | 5.31±4.39 | 100~2 900 | 1 254±824 | 5.5~15.5 | 9.16±2.76 | 120~1 700 | 597.85±328.66 | |||
未来Future RCP2.6 | -6.5~7.4 | 6.89±4.22 | 140~2 900 | 1 254±824 | 5.7~15.6 | 9.18±2.71 | 150~1 800 | 601.11±325.82 | |||
未来Future RCP8.5 | -3.8~12.3 | 9.12±4.01 | 900~2 900 | 1 254±824 | 6.0~16.4 | 9.37±2.51 | 150~1 400 | 585.33±309.56 |
陈新美, 雷渊才, 张雄清, 等. 样本量对MaxEnt模型预测物种分布精度和稳定性的影响. 林业科学, 2012, 48 (1): 53- 59. | |
Chen X M , Lei Y C , Zhang X Q , et al. Effects of sample sizes on accuracy and stability of Maximum Entropy model in predicting species distribution. Scientia Silvae Sinicae, 2012, 48 (1): 53- 59. | |
方精云, 朱江玲, 石岳. 生态系统对全球变暖的响应. 科学通报, 2018, 63 (2): 136- 140. | |
Fang J Y , Zhu J L , Shi Y . The responses of ecosystems to global warming. Chinese Science Bulletin, 2018, 63 (2): 136- 140. | |
管毕财, 陈微, 刘想, 等. 四照花物种分布格局及其冰期避难所推测. 西北植物学报, 2016, 36 (12): 2541- 2547. | |
Guan B C , Chen W , Liu X , et al. Distribution pattern and glacial refugia of Cornus kousa subsp. chinensis based on MaxEnt model and GIS. Acta Botanica Boreali-Occidentalia Sinica, 2016, 36 (12): 2541- 2547. | |
郭飞龙, 徐刚标, 卢孟柱, 等. 基于MaxEnt模型分析胡杨潜在适宜分布区. 林业科学, 2020, 56 (5): 184- 192. | |
Guo F L , Xu G B , Lu M Z , et al. Prediction of potential suitable distribution areas for Populus euphratica using the MaxEnt model. Scientia Silvae Sinicae, 2020, 56 (5): 184- 192. | |
胡菀, 张志勇, 陈陆丹, 等. 末次盛冰期以来观光木的潜在地理分布变迁. 植物生态学报, 2020, 44 (3): 1- 12. | |
Hu W , Zhang Z Y , Chen L D , et al. Changes in potential geographical distribution of Tsoongiodendron odorum since the Last Glacial Maximum. Chinese Journal of Plant Ecology, 2020, 44 (3): 1- 12. | |
李文庆, 徐洲锋, 史鸣明, 等. 不同情景下四子柳的亚洲潜在地理分布格局变化预测. 生态学报, 2019, 39 (9): 3224- 3234. | |
Li W Q , Xu Z F , Shi M M , et al. Prediction of potential geographical distribution patterns of Salix tetrasperma Roxb. in Asia under different climate scenarios. Acta Ecologica Sinica, 2019, 39 (9): 3224- 3234. | |
李璇, 李垚, 方炎明. 基于优化的MaxEnt模型预测白栎在中国的潜在分布区. 林业科学, 2018, 54 (8): 153- 164. | |
Li X , Li Y , Fang Y M . Prediction of potential suitable distribution areas of Quercus fabri in China based on an optimized MaxEnt model. Scientia Silvae Sinicae, 2018, 54 (8): 153- 164. | |
刘超, 霍宏亮, 田路明, 等. 基于MaxEnt模型不同气候变化情景下的豆梨潜在地理分布. 应用生态学报, 2018, 29 (11): 3696- 3704. | |
Liu C , Huo H L , Tian L M , et al. Potential geographical distribution of Pyrus calleryana under different climate change scenarios based on the MaxEnt model. Chinese Journal of Applied Ecology, 2018, 29 (11): 3696- 3704. | |
刘建全. "整合物种概念"和"分化路上的物种". 生物多样性, 2016, 24 (9): 1004- 1008. | |
Liu J Q . "The integrative species concept" and "species on the speciation way". Biodiversity Science, 2016, 24 (9): 1004- 1008. | |
路东晔, 张磊, 郝蕾, 等. 臭柏叶绿体基因组结构与系统进化分析. 西北植物学报, 2018, 38 (8): 1464- 1475. | |
Lu D Y , Zhang L , Hao L , et al. Analysis of chloroplast genome structure and phylogenetic evolution of Juniperus sabina. Acta Botanica Boreali-Occidentalia Sinica, 2018, 38 (8): 1464- 1475. | |
路东晔, 张国盛, 李娅翔, 等. 臭柏天然居群遗传多样性及演变历史分析. 植物科学学报, 2020, 38 (2): 151- 161. | |
Lu D Y , Zhang G S , Li Y X , et al. Genetic diversity and evolutionary history analysis of natural populations of Juniperus sabina L. Plant Science Journal, 2020, 38 (2): 151- 161. | |
马松梅, 张明理, 张宏祥, 等. 利用最大熵模型和规则集遗传算法模型预测孑遗植物裸果木的潜在地理分布及格局. 植物生态学报, 2010, 34 (11): 1327- 1335.
doi: 10.3773/j.issn.1005-264x.2010.11.010 |
|
Ma S M , Zhang M L , Zhang H X , et al. Predicting potential geographical distributions and patterns of the relic plant Gymnocarpos przewalskii using Maximum Entropy and Genetic Algorithm for Rule-set prediction. Chinese Journal of Plant Ecology, 2010, 34 (11): 1327- 1335.
doi: 10.3773/j.issn.1005-264x.2010.11.010 |
|
毛康珊. 2010. 广义柏科的生物地理学研究-从板块漂移理论到冰期避难所. 甘肃: 兰州大学博士学位论文, 1-124. | |
Mao K S. 2010. Biogeography of Cupressaceae sensu lato: from Plate Tectonics to Glacial Refugia. Gansu: PhD thesis of Lanzhou University, 1-124. [in Chinese] | |
孟和, 姜真杰, 张国盛. 内蒙古臭柏不同分布区生长与生态因子的关联分析. 浙江林学院学报, 2010, 27 (1): 51- 56. | |
Meng H , Jiang Z J , Zhang G S . Using the Grey System Theory for analysis of relationship between Sabina vulgaris growth and ecological factors. Journal of Zhejiang Forestry College, 2010, 27 (1): 51- 56. | |
邱浩杰, 孙杰杰, 徐达, 等. 末次盛冰期以来红豆树在不同气候变化情景下的分布动态. 生态学报, 2020, 40 (9): 1- 11.
doi: 10.3969/j.issn.1673-1182.2020.09.001 |
|
Qiu H J , Sun J J , Xu D , et al. The distribution dynamics of Ormosia hosiei under different climate change scenarios since the Last Glacial Maximum. Acta Ecologica Sinica, 2020, 40 (9): 1- 11.
doi: 10.3969/j.issn.1673-1182.2020.09.001 |
|
山中典和, 王林和, 吉川賢. 中国内蒙古毛烏素沙地における臭柏(Sabina vulgaris Ant.)更新場所の微環境. 日本緑化工学会誌, 2000, 25 (4): 437- 442. | |
Yamanaka N , Wang L H , Yoshikawa K . Microenvironment of safe site for Sabina vulgaris Ant. seedlings in the Mu Us Desert, Inner Mongolia, China. Journal of the Japanese Society of Revegetation Technology, 2000, 25 (4): 437- 442. | |
王林和, 党宏忠, 张国盛, 等. 中国天然臭柏群落的分布与生物量特征. 内蒙古农业大学学报, 2014, 35 (1): 37- 45. | |
Wang L H , Dang H Z , Zhang G S , et al. Distribution and biomass of natural Juniperus sabina community in China. Journal of Inner Mongolia Agricultural University, 2014, 35 (1): 37- 45. | |
王茹琳, 李庆, 封传红, 等. 基于MaxEnt的西藏飞蝗在中国的适生区预测. 生态学报, 2017, 37 (24): 8556- 8566. | |
Wang R L , Li Q , Feng C H , et al. Predicting potential ecological distribution of Locusta migratoria tibetensis in China using MaxEnt ecological niche modeling. Acta Ecologica Sinica, 2017, 37 (24): 8556- 8566. | |
王绍武. 全新世气候变化. 北京: 气象出版社, 2011, 9 | |
Wang S W . Holocene climate change. Beijing: Meteorological Press, 2011, 9 | |
王哲, 张国盛, 王林和, 等. 毛乌素沙地天然臭柏群落种子产量、种子库及幼苗更新. 干旱区资源与环境, 2005, 19 (3): 195- 200.
doi: 10.3969/j.issn.1003-7578.2005.03.039 |
|
Wang Z , Zhang G S , Wang L H , et al. Seed yield, seed bank and regeneration of natural Sabina vulgaris community in Mu Us sandland. Journal of Arid Land Resources and Environment, 2005, 19 (3): 195- 200.
doi: 10.3969/j.issn.1003-7578.2005.03.039 |
|
杨芙蓉, 张琴, 孙成忠, 等. 蒙古黄芪潜在分布区预测的多模型比较. 植物科学学报, 2019, 37 (2): 136- 143. | |
Yang F R , Zhang Q , Sun C Z , et al. Comparative evaluation of multiple models for predicting the potential distribution areas of Astragalus membranaceus var. mongholicus. Plant Science Journal, 2019, 37 (2): 136- 143. | |
张国盛, 王哲, 王林和, 等. 毛乌素沙地天然臭柏居群有性更新幼苗动态研究. 林业科学, 2006, 42 (5): 62- 67. | |
Zhang G S , Wang Z , Wang L H , et al. Regenerative seedlings dynamics of natural Sabina vulgaris community in Mu Us sandland. Scientia Silvae Sinicae, 2006, 42 (5): 62- 67. | |
赵晓冏, 巩娟霄, 赵莎莎, 等. 样本量及其空间分布对物种分布模型的影响. 兰州大学学报: 自然科学版, 2018, 54 (2): 70- 77. | |
Zhao X J , Gong J X , Zhao S S , et al. Impact of sample size and spatial distribution on species distribution model. Journal of Lanzhou University: Natural Sciences, 2018, 54 (2): 70- 77. | |
郑益群, 于革, 薛滨, 等. 6 ka B. P.东亚区域气候模拟及其变化机制探讨. 第四纪研究, 2004, 24 (1): 28- 38.
doi: 10.3321/j.issn:1001-7410.2004.01.004 |
|
Zheng Y Q , Yu G , Xue B , et al. Simulations of east Asian climate at 6 ka B. P. Quaternary Sciences, 2004, 24 (1): 28- 38.
doi: 10.3321/j.issn:1001-7410.2004.01.004 |
|
中国第四纪孢粉数据库小组. 中国中全新世(6 ka BP)和末次盛冰期(18 ka BP)生物群区的重建. 植物学报, 2000, 42 (11): 1201- 1209.
doi: 10.3321/j.issn:1672-9072.2000.11.018 |
|
Members of China Quaternary Pollen Data Base . Pollen-based biome reconstruction at Middle Holocene(6 ka BP) and Last Glacial Maximum(18 ka BP) in China. Acta Botanica Sinica, 2000, 42 (11): 1201- 1209.
doi: 10.3321/j.issn:1672-9072.2000.11.018 |
|
朱井丽, 高忠斯, 邹红菲, 等. 基于MAXENT模型的松嫩平原丹顶鹤秋迁期生境适宜性评价. 野生动物学报, 2018, 39 (4): 852- 857.
doi: 10.3969/j.issn.1000-0127.2018.04.018 |
|
Zhu J L , Gao Z S , Zou H F , et al. Habitat suitability assessment of the Songnen plain for Grus japonensis based on MAXENT modeling. Chinese Journal of Wildlife, 2018, 39 (4): 852- 857.
doi: 10.3969/j.issn.1000-0127.2018.04.018 |
|
朱耿平, 刘国卿, 卜文俊, 等. 生态位模型的基本原理及其在生物多样性保护中的应用. 生物多样性, 2013, 21 (1): 90- 98. | |
Zhu G P , Liu G Q , Bu W J , et al. The basic principle of niche model and its application in biodiversity conservation. Biodiversity Science, 2013, 21 (1): 90- 98. | |
庄鸿飞, 张殷波, 王伟, 等. 基于最大熵模型的不同尺度物种分布概率优化热点分析: 以红色木莲为例. 生物多样性, 2018, 26 (9): 931- 940. | |
Zhuang H F , Zhang Y B , Wang W , et al. Optimized hot spot analysis for probability of species distribution under different spatial scales based on MaxEnt model: Manglietia insignis case. Biodiversity Science, 2018, 26 (9): 931- 940. | |
Adams R P , Boratynski A , Marcysiak K , et al. Discovery of Juniperus sabina var. balkanensis R. P. Adams and A. N. Tashev in Macedonia, Bosnia-Herzegovina, Croatia and Central and Southern Italy and relictual polymorphisms found in nrDNA. Phytologia, 2018, 100 (2): 117- 127. | |
Adams R P , Boratynski A , Mataraci T , et al. Discovery of Juniperus sabina var. balkanensis R. P. Adams and A. N. Tashev in western Turkey. Phytologia, 2017, 99 (1): 22- 31. | |
Ahmed S E , Mcinerny G , O'Hara K , et al. Scientists and software-surveying the species distribution modeling community. Diversity and Distributions, 2015, 21 (3): 258- 267.
doi: 10.1111/ddi.12305 |
|
Alexander L, Allen S, Bindoff N L. 2013. Climate change 2013: the physical science basis-summary for policymakers. Intergovernmental Panel on Climate Change. | |
Barbosa F G , Schneck F . Characteristics of the top-cited papers in species distribution predictive models. Ecological Modelling, 2015, 313, 77- 83.
doi: 10.1016/j.ecolmodel.2015.06.014 |
|
Bellard C , Bertelsmeier C , Leadley P , et al. Impacts of climate change on the future of biodiversity. Ecology Letters, 2012, 15 (4): 365- 377.
doi: 10.1111/j.1461-0248.2011.01736.x |
|
Bertrand R , Perez V , Gegout J C . Disregarding the edaphic dimension in species distribution models leads to the omission of crucial spatial information under climate change: the case of Quercus pubescens in France. Global Change Biology, 2012, 18 (8): 2648- 2660.
doi: 10.1111/j.1365-2486.2012.02679.x |
|
Chen I C , Hill J K , Ohlemuller R , et al. Rapid range shifts of species associated with high levels of climate warming. Science, 2011, 333 (6045): 1024- 1026.
doi: 10.1126/science.1206432 |
|
Dieleman C M , Branfireun B A , McLaughlin J W , et al. Climate change drives a shift in peat land ecosystem plant community: implications for ecosystem function and stability. Global Change Biology, 2015, 21 (1): 388- 395.
doi: 10.1111/gcb.12643 |
|
Dülgeroğlu C , Aksoy A . Assessing impacts of climate change on Campanula yaltirikii H. Duman(Campanulaceae), a critically endangered endemic species in Turkey. Turkish Journal of Botany, 2019, 43 (2): 243- 252.
doi: 10.3906/bot-1809-14 |
|
Elith J , Graham C H , Anderson R P , et al. Novel methods improve prediction of species' distributions from occurrence data. Ecography, 2006, 29 (2): 129- 151.
doi: 10.1111/j.2006.0906-7590.04596.x |
|
Elith J , Phillips S J , Hastie T , et al. A statistical explanation of MaxEnt for ecologists. Diversity & Distributions, 2011, 17 (1): 43- 57. | |
García-Cervigón A I , Linares J C , García-Hidalgo M , et al. Growth delay by winter precipitation could hinder Juniperus sabina persistence under increasing summer drought. Dendrochronologia, 2018, 51
doi: 10.1016/j.dendro.2018.07.003 |
|
Gibson L , Lee T M , Koh L P , et al. Primary forests are irreplaceable for sustaining tropical biodiversity. Nature, 2011, 478 (7369): 378- 381.
doi: 10.1038/nature10425 |
|
Graham C H , Elith J , Hijmans R J , et al. The influence of spatial errors in species occurrence data used in distribution models. Journal of Applied Ecology, 2008, 45 (1): 239- 247. | |
Hewitt G M . Genetic consequences of climatic oscillations in the Quaternary. Philosophical Transactions of the Royal Society B: Biological Sciences, 2004, 359 (1442): 183- 195.
doi: 10.1098/rstb.2003.1388 |
|
Hughes G , Madden L V . Evaluating predictive models with application in regulatory policy for invasive weeds. Agricultural Systems, 2003, 76 (2): 755- 774.
doi: 10.1016/S0308-521X(02)00164-6 |
|
Kumar S , Stohlgren T J . Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. Journal of Ecology and the Natural Environment, 2009, 1 (4): 94- 98. | |
Manel S , Williams H C , Ormerod S J . Evaluating presence-absence models in ecology: the need to account for prevalence. Journal of Applied Ecology, 2010, 38 (5): 921- 931. | |
Otto-Bliesner B L , Marshall S J , Overpeck J T , et al. Simulating Arctic climate warmth and icefield retreat in the last interglaciation. Science, 2006, 311 (5768): 1751- 1753.
doi: 10.1126/science.1120808 |
|
Phillips S J . A brief tutorial on Maxent. Lessons in Conservation, 2010, 3, 108- 135. | |
Qiao H J , Lin C T , Ji L Q , et al. mMWeb-an online platform for employing multiple ecological niche modeling algorithms. PLoS ONE, 2012, 7 (8) | |
Segurado P , Araujo M B . An evaluation of methods for modelling species' distributions. Journal of Biogeography, 2004, 31 (10): 1555- 1568.
doi: 10.1111/j.1365-2699.2004.01076.x |
|
Sekercioglu C H , Schneider S H , Fay J P , et al. Climate change, elevational range shifts, and bird extinctions. Conservation Biology, 2008, 22 (1): 140- 150.
doi: 10.1111/j.1523-1739.2007.00852.x |
|
Soberón J , Peterson A T . Interpretation of models of fundamental ecological niches and species' distributional areas. Biodiversity Informatics, 2005, 2, 1- 10. | |
Soberón J , Nakamura M . Niches and distributional areas: concepts, methods and assumptions. Proceedings of the National Academy of Sciences, 2009, 106 (17): 19644- 19650. | |
Stocker T F , Qin D , Plattner G K , et al. Climate Change 2013:The Physical Science Basis. Cambridge, UK: Cambridge University Press, 2014. | |
Swets J A . Measuring the accuracy of diagnostic systems. Science, 1988, 240 (4857): 1285- 1293.
doi: 10.1126/science.3287615 |
|
Van Proosdij A S , Sosef M S M , Wieringa J J , et al. Minimum required number of specimen records to develop accurate specices distribution models. Ecography, 2016, 39 (6): 542- 552.
doi: 10.1111/ecog.01509 |
|
Van Vuuren D P , Edmonds J , Kainuma M , et al. The representative concentration pathways: an overview. Climatic Change, 2011, 109 (1/2): 5- 31. | |
Vaz U L , Cunha H F , Nabout J C . Trends and biases in global scientific literature about ecological niche models. Brazilian Journal of Biology, 2015, 75 | |
Wang J R , Hawkins C D B , Letchford T . Photosynthesis, water and nitrogen use efficiencies of four paper birch(Betula papyrifera) populations grown under different soil moisture and nutrient regimes. Forest Ecology and Management, 1998, 112 (3): 233- 244.
doi: 10.1016/S0378-1127(98)00407-1 |
|
Wang Y H , Jiang W M , Comes H P , et al. Molecular phylogeography and ecological niche modeling of a widespread herbaceous climber, Tetrastigma hemsleyanum(Vitaceae): insights into Plio-Pleistocene range dynamics of evergreen forest in subtropical China. New Phytologist, 2015, 206 (2): 852- 867.
doi: 10.1111/nph.13261 |
|
Wisz M S , Hijmans R J , Li J , et al. Effects of sample size on the performance of species distribution models. Diversity and Distributions, 2008, 14 (5): 763- 773.
doi: 10.1111/j.1472-4642.2008.00482.x |
[1] | 白蕤,李宁,刘少军,陈小敏,邹海平,吕润. 未来气候变化背景下橡胶树白根病在中国的风险分析[J]. 林业科学, 2021, 57(6): 37-45. |
[2] | 赵光华,崔馨月,王智,荆红利,樊保国. 气候变化背景下我国酸枣潜在适生区预测[J]. 林业科学, 2021, 57(6): 158-168. |
[3] | 张丹妮,陈西雅,臧传富. 三北防护林体系建设工程区宜林潜力[J]. 林业科学, 2021, 57(5): 184-194. |
[4] | 于健,陈佳佳,周光,刘国华,王永平,李俊清,刘琪璟. 横断山脉中部川滇冷杉和丽江云杉径向生长对气象因子的响应[J]. 林业科学, 2020, 56(12): 28-38. |
[5] | 潘天天,李彦,王忠媛,陆世通,叶琳峰,陈森,谢江波. 湿润区3种杉科植物枝和根木质部的水力功能与解剖结构的关系[J]. 林业科学, 2020, 56(12): 49-59. |
[6] | 李亚藏, 冯仲科. 气候敏感的马尾松生物量相容性方程系统研建[J]. 林业科学, 2019, 55(5): 65-73. |
[7] | 王晓玮, 任雪燕, 梁英梅. 基于MaxEnt模型的松针红斑病在中国的潜在分布区及适生性预测分析[J]. 林业科学, 2019, 55(4): 160-170. |
[8] | 吕振刚, 李文博, 黄选瑞, 张志东. 气候变化情景下河北省3个优势树种适宜分布区预测[J]. 林业科学, 2019, 55(3): 13-21. |
[9] | 欧阳林男,陈少雄,刘学锋,何沙娥,张维耀. 赤桉在中国的适生地理区域及其对气候变化的响应[J]. 林业科学, 2019, 55(12): 1-11. |
[10] | 厉静文,郭浩,王雨生,辛智鸣,吕永军. 基于MaxEnt模型的胡杨潜在适生区预测[J]. 林业科学, 2019, 55(12): 133-139. |
[11] | 吕振刚,李文博,黄选瑞,张志东. 气候变化情景下基于潜在NPP的河北省华北落叶松生长适宜性[J]. 林业科学, 2019, 55(11): 37-44. |
[12] | 王婧如, 王明浩, 张晓玮, 孙杉, 赵长明. 同倍体杂交物种紫果云杉的生态位分化及其未来潜在分布区预测[J]. 林业科学, 2018, 54(6): 63-72. |
[13] | 路伟伟, 余新晓, 贾国栋, 李瀚之, 刘自强. 密云山区油松树轮δ13C对气温和降水量变化的响应[J]. 林业科学, 2018, 54(3): 1-7. |
[14] | 苑冉, 李欣悦, 吴韶平, 曹传旺. CO2浓度升高对舞毒蛾生长发育和体内解毒酶及保护酶活性的影响[J]. 林业科学, 2018, 54(12): 102-109. |
[15] | 钱杨, 孙洪刚, 董汝湘, 姜景民. 针叶树碳水化合物分配研究进展[J]. 林业科学, 2018, 54(1): 141-153. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||