基于Cubist模型的天山北坡草地鼠群密度时空分布特征

doi:10.12118/j.issn.1000-6060.2021.471

干旱区地理 ›› 2022, Vol. 45 ›› Issue (4): 1200-1211.doi: 10.12118/j.issn.1000-6060.2021.471

基于Cubist模型的天山北坡草地鼠群密度时空分布特征

潘群^1,²(),施海洋^2,³,张文强^2,³,罗格平^2,^3,⁴(),陈春波^2,³

1.新疆大学资源与环境科学学院,新疆乌鲁木齐 830046
2.中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室,新疆乌鲁木齐 830011
3.中国科学院大学,北京 100049
4.中国科学院中亚生态与环境研究中心,新疆乌鲁木齐 830011

收稿日期:2021-10-12 修回日期:2022-01-12 出版日期:2022-07-25 发布日期:2022-08-11
通讯作者: 罗格平
作者简介:潘群（1997-）,女,硕士研究生,主要从事干旱区草地生态系统资源与环境、遥感与GIS应用等方面的研究. E-mail: pq664x@outlook.com
基金资助:
高端外国专家项目(E0600101);2020年自治区创新环境（人才、基地）建设专项（天山青年计划）(2020Q084);2020年第一批中央财政林业草原生态保护恢复资金项目(XJCYZZ202001)

Spatiotemporal distribution of rat population density in grassland on the north slope of Tianshan Mountains based on Cubist model

PAN Qun^1,²(),SHI Haiyang^2,³,ZHANG Wenqiang^2,³,LUO Geping^2,^3,⁴(),CHEN Chunbo^2,³

1. College of Resources and Environmental Sciences, Xinjiang University, Urumqi 830046, Xinjiang, China
2. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
3. University of Chinese Academy of Sciences, Beijing 100049, China
4. Central Asia Center for Ecology and Environmental Research Center, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China

Received:2021-10-12 Revised:2022-01-12 Online:2022-07-25 Published:2022-08-11
Contact: Geping LUO

摘要/Abstract

摘要：

鼠害是影响草原生态健康的重要因素,了解小型啮齿动物种群密度时空分布特征,对精准的鼠害综合防治具有重要意义。以往对小型啮齿动物时空分布的研究多局限于静态的站点分布或小范围的种群密度时间变化分析,缺乏对较大时空尺度小型啮齿动物种群密度变化的分析。从已发表的文献中收集了天山北坡草地1982—2015年小尺度的有效洞口密度实地调查信息,同时结合环境因子数据,再根据海拔将研究区划分为≤900 m和>900 m 2类,运用Cubist模型和随机森林模型,分析有效洞口密度时空分布。结果表明：（1） 1982—2015年天山北坡海拔≤900 m地区的有效洞口密度总体呈增加趋势,而海拔>900 m的地区总体呈减少趋势。基于Cubist模型构建有效洞口密度与环境因子的模型拟合精度明显优于随机森林模型。（2）植被状况、气象因子和放牧强度是天山北坡有效洞口密度时空分布主要的环境驱动因素。在天山北坡内海拔≤900 m和>900 m的地区中,有效洞口密度的驱动机制存在着显著差异。（3）在海拔≤900 m地区,影响有效洞口密度时空分布主要是叶面积指数,而对于海拔>900 m地区为归一化植被指数。这可能是受到大沙鼠（Rhombomys opimus）和黄兔尾鼠（Eolagurus luteus）消耗不同类型植被的影响。

关键词: 有效洞口密度, 环境因子, Cubist模型, 随机森林模型, 天山北坡

Abstract:

Rodent damage is an important factor affecting grassland ecological health. Understanding the spatiotemporal distribution characteristics of small rodent population density is crucial for accurate comprehensive rodent control. Previous studies on the spatiotemporal distribution of small rodents were mostly limited to static site distribution or time change analysis of small-scale population density; investigation on the population density change of small rodents on a large temporal and spatial scale is lacking. In this study, the field survey information of small-scale active burrow entrance densities on the grassland on the north slope of Tianshan Mountains from 1982 to 2015 was collected from the literature and combined with environmental variable data. The study area was divided as areas with elevation of ≤900 m and >900 m. The spatiotemporal distribution of active burrow entrance densities was analyzed using the Cubist and random forest (RF) models. The following results were obtained. (1) From 1982 to 2015, the active burrow entrance densities increased in the area with an elevation of ≤900 m on the north slope of Tianshan Mountains, whereas that in the area with an elevation of >900 m decreased. The fitting accuracy of the Cubist model of active burrow entrance densities and environmental factors was better than that of the RF model. (2) Vegetation status, meteorological factors, and grazing intensity were found to be the primary environmental driving factors for the spatiotemporal distribution of active burrow entrance densities on the north slope of Tianshan Mountains. Significant differences in the driving mechanism of active burrow entrance densities were found between the areas with an elevation of ≤900 m and those with an elevation of >900 m on the north slope of Tianshan Mountains. (3) The main factor affecting the spatiotemporal distribution of active burrow entrance densities was the leaf area index and normalized difference vegetation index for the areas with elevation ≤900 m and >900 m, respectively. This difference may be affected by the consumption of different types of vegetation by gerbils (Rhombomys opimus) and yellow rabbit tail rats (Eolagurus luteus).

Key words: active burrow entrance densities, environmental factors, Cubist model, random forest model, northern slope of Tianshan Mountains

潘群,施海洋,张文强,罗格平,陈春波. 基于Cubist模型的天山北坡草地鼠群密度时空分布特征[J]. 干旱区地理, 2022, 45(4): 1200-1211.

PAN Qun,SHI Haiyang,ZHANG Wenqiang,LUO Geping,CHEN Chunbo. Spatiotemporal distribution of rat population density in grassland on the north slope of Tianshan Mountains based on Cubist model[J]. Arid Land Geography, 2022, 45(4): 1200-1211.

图/表 7

图1

表1

环境因子数据来源"

环境因子	空间分辨率	数据来源
海拔	30 m	美国地质勘探局全球卫星影像（USGS Earth Explorer, http://earthexplorer.usgs.gov）
坡度	30 m	美国地质勘探局全球卫星影像（USGS Earth Explorer, http://earthexplorer.usgs.gov）
坡向	30 m	美国地质勘探局全球卫星影像（USGS Earth Explorer, http://earthexplorer.usgs.gov）
粉砂含量	1 km	国家冰川冻土沙漠科学数据中心(http://www.ncdc.ac.cn)^[47]
砂土含量	1 km	国家冰川冻土沙漠科学数据中心(http://www.ncdc.ac.cn)^[47]
黏土含量	1 km	国家冰川冻土沙漠科学数据中心(http://www.ncdc.ac.cn)^[47]
归一化植被指数（NDVI）	8 km	美国国家航天航空局（NASA）的全球监测与模型研究组（GIMMS）提供的3g.v1数据（https://ecocast.arc.nasa.gov/data/pub/gimms/）
叶面积指数（LAI）	8 km	NOAA气候数据记录（CDR）的AVHRR叶面积指数（LAI）和吸收光合有效辐射的部分（FAPAR）数据集
年平均气温	1 km	中国1 km分辨率逐月平均气温数据集（1901—2017年）^[48-49]
年最低气温	1 km	中国1 km分辨率月最低温度数据集（1901—2017年）^[49-50]
年最高气温	1 km	中国1 km分辨率月最高温度数据集（1901—2017年）^[49,51]
月平均气温	1 km	中国1 km分辨率逐月平均气温数据集（1901—2017年）^[48-49]
月最高气温	1 km	中国1 km分辨率月最高温度数据集（1901—2017年）^[49,51]
月最低气温	1 km	中国1 km分辨率月最低温度数据集（1901—2017年）^[49-50]
年累积降水量	1 km	中国1 km分辨率逐月降水量数据集（1901—2017年）^[49,52]
调查前3月的平均降水量	1 km	中国1 km分辨率逐月降水量数据集（1901—2017年）^[49,52]
月累积降水量	1 km	中国1 km分辨率逐月降水量数据集（1901—2017年）^[49,52]
放牧强度	0.08333°	世界粮农组织（FAO, http://www.fao.org/livestock-systems/en/）野外实测数据、新疆统计年鉴^[22,53]
短波辐射	0.1°	中国区域地面气象要素驱动数据集（1979—2018年）^[54-55]

表1

表2

图2

图3

图4

图5

参考文献 77

[1]	胡雷, 阿的鲁骥, 字洪标, 等. 高原鼢鼠扰动及恢复年限对高寒草甸土壤养分和微生物功能多样性的影响[J]. 应用生态学报, 2015, 26(9): 2794-2802. pmid: 26785563
	[ Hu Lei, Ade Luji, Zi Hongbiao, et al. Effects of highland rat disturbance and recovery on soil nutrients and microbial functional diversity in high-cold meadows[J]. Chinese Journal of Applied Ecology, 2015, 26(9): 2794-2802. ] pmid: 26785563
[2]	李燕妮, 袁帅, 付和平, 等. 典型草原啮齿动物密度与牧草损失量的关系[J]. 兽类学报, 2018, 38(4): 369-376.
	[ Li Yanni, Yuan Shuai, Fu Heping, et al. Relationship between the density of typical grassland rodents and the loss of pasture[J]. Acta Theriologica Sinica, 2018, 38(4): 369-376. ]
[3]	刘汉武, 王荣欣, 张凤琴, 等. 我国害鼠不育控制研究进展[J]. 生态学报, 2011, 31(19): 5484-5494.
	[ Liu Hanwu, Wang Rongxin, Zhang Fengqin, et al. Advances in the control of rodent sterility in China[J]. Acta Ecologica Sinica, 2011, 31(19): 5484-5494. ]
[4]	韩立辉, 尚占环, 任国华, 等. 青藏高原“黑土滩”退化草地植物和土壤对秃斑面积变化的响应[J]. 草业学报, 2011, 20(1): 1-6.
	[ Han Lihui, Shang Zhanhuan, Ren Guohua, et al. Responses of plants and soil to changes of bald spot area in degraded grassland of “black soil beach” in Qinghai Tibet Plateau[J]. Acta Prataculturae Sinica, 2011, 20(1): 1-6. ]
[5]	郭强, 王玉琴, 鲍根生, 等. 气象因子对高原鼢鼠种群数量的影响[J]. 草业学报, 2020, 29(8): 188-194.
	[ Guo Qiang, Wang Yuqin, Bao Gensheng, et al. Effects of meteorological factors on the population of Plateau Zokor[J]. Acta Prataculturae Sinica, 2020, 29(8): 188-194. ]
[6]	乔雪丽, 林峻, 吴建国, 等. 气候变化情景下大沙鼠潜在地理分布[J]. 生态学报, 2021, 41(17): 1-9. doi: 10.1016/j.chnaes.2020.10.007
	[ Qiao Xueli, Lin Jun, Wu Jianguo, et al. Potential geographical distribution of gerbils under climate change scenario[J]. Acta Ecologica Sinica, 2021, 41(17): 1-9. ] doi: 10.1016/j.chnaes.2020.10.007
[7]	何咏琪, 黄晓东, 侯秀敏, 等. 基于3S技术的草原鼠害监测方法研究[J]. 草业学报, 2013, 22(3): 33-40.
	[ He Yongqi, Huang Xiaodong, Hou Xiumin, et al. Monitoring grassland rodents with 3S techonlogies[J]. Acta Prataculturae Sinica, 2013, 22(3): 33-40. ]
[8]	Mohammadi S, Ebrahimi E, Moghadam M S, et al. Modelling current and future potential distributions of two desert jerboas under climate change in Iran[J]. Ecological Informatics, 2019, 52: 7-13. doi: 10.1016/j.ecoinf.2019.04.003
[9]	栗小东, 王晶, 杨春蕙, 等. 基于两种机器学习方法分析东海北部海域三疣梭子蟹(Portunus trituberculatus)时空分布[J]. 海洋与湖沼, 2021, 52(5): 1284-1292.
	[ Li Xiaodong, Wang Jing, Yang Chunhui, et al. Spatiotemporal distribution of Portunus trituberculatus in the northern East China Sea based on two machine learning methods[J]. Oceanologia et Limnologia Sinica, 2021, 52(5): 1284-1292. ]
[10]	Forney K A, Becker E A, Foley D G, et al. Habitat-based models of cetacean density and distribution in the central North Pacific[J]. Endangered Species Research, 2015, 27(1): 1-20. doi: 10.3354/esr00632
[11]	黄彬, 卫万荣, 张灵菲, 等. 环境条件对啮齿动物种群的影响[J]. 草业科学, 2013, 30(6): 949-953.
	[ Huang Bin, Wei Wanrong, Zhang Lingfei, et al. Impact of environmental conditions on rodent population[J]. Pratacultural Science, 2013, 30(6): 949-953. ]
[12]	马涛, 郑江华, 温阿敏, 等. 基于无人机低空遥感的荒漠林大沙鼠鼠洞分布与地形的关系--以新疆古尔通古特沙漠南缘局部为例[J]. 林业科学, 2018, 54(10): 180-188.
	[ Ma Tao, Zheng Jianghua, Wen Amin, et al. Relationship between the distribution of Rhombomys opimus holes and the topography in desert forest based on low altitude remote sensing with the unmanned aerial vehicle (UAV): A case study at the southern margin of the Gurbantunggut Desert in Xinjiang, China[J]. Scientia Silvae Sinicae, 2018, 54(10): 180-188. ]
[13]	冯峰, 贡保草, 牛克昌. 不同放牧模式下高原鼠兔密度与高寒植被和土壤的关系[J]. 草业科学, 2019, 36(11): 2915-2925.
	[ Gong Baocao, Niu Kechang. Relationship between plateau pika density and alpine vegetation and soil under different grazing modes[J]. Pratacultural Science, 2019, 36(11): 2915-2925. ]
[14]	Brown J H, Ernest S K M. Rain and rodents: complex dynamics of desert consumers[J]. BioScience, 2002, 52(11): 979-987. doi: 10.1641/0006-3568(2002)052[0979:RARCDO]2.0.CO;2
[15]	乌云嘎, 查木哈, 张晓东, 等. 荒漠区啮齿动物群落与植物因子的冗余分析[J]. 草业科学, 2014, 31(12): 2323-2332.
	[ Wu Yunga, Cha Muha, Zhang Xiaodong, et al. Redundancy analysis between rodent communities and plant factors in desert[J]. Pratacultural Science, 2014, 31(12): 2323-2332. ]
[16]	周立志, 马勇, 李迪强. 大沙鼠在中国的地理分布[J]. 动物学报, 2000, 46(2): 130-137.
	[ Zhou Lizhi, Ma Yong, Li Diqiang. Distribution of great gerbil (Rhombomys opimus) in China[J]. Acta Zoologica Sinica, 2000, 46(2): 130-137. ]
[17]	袁帅, 武晓东, 付和平, 等. 不同干扰下荒漠啮齿动物群落多样性的多尺度分析[J]. 生态学报, 2011, 31(7): 1982-1992.
	[ Yuan Shuai, Wu Xiaodong, Fu Heping, et al. Multi-scales analysis on diversity of desert rodent communities under different disturbances[J]. Acta Ecologica Sinica, 2011, 31(7): 1982-1992. ]
[18]	王利清, 武晓东, 付和平, 等. 人为不同干扰方式下荒漠啮齿动物群落格局年间变动趋势[J]. 干旱区资源与环境, 2011, 25(3): 146-151.
	[ Wang Liqing, Wu Xiaodong, Fu Heping, et al. The annual fluctuating tendency and patterns of desert rodent communities under human disturbance[J]. Journal of Arid Land Resources and Environment, 2011, 25(3): 146-151. ]
[19]	熊瑞东, 程武学, 熊钰丹, 等. 基于无人机的若尔盖高寒草地鼠害程度估算模型研究[J]. 中国农业信息, 2020, 32(6): 32-45.
	[ Xiong Ruidong, Cheng Wuxue, Xiong Yudan, et al. Estimation model of rodent damage degree in Zoige alpine grassland based on UAV[J]. China Agricultural Information, 2020, 32(6): 32-45. ]
[20]	Zhang M, Luo G, Cao X, et al. Numerical simulation of the irrigation effects on surface fluxes and local climate in typical mountain-oasis-desert systems in the Central Asia arid area[J]. Journal of Geophysical Research: Atmospheres, 2019(124): 12485-12506.
[21]	韩崇选, 李金钢, 杨学军, 等. 中国农林啮齿动物与科学管理[M]. 杨凌: 西北农林科技大学出版社, 2005: 183-186.
	[ Han Chongxuan, Li Jingang, Yang Xuejun, et al. Rodents and scientific management in agriculture and forestry in China[M]. Yangling: Northwest A & F University Press, 2005: 183-186. ]
[22]	张文强, 罗格平, 郑宏伟, 等. 基于随机森林模型的内陆干旱区植被指数变化与驱动力分析: 以北天山北坡中段为例[J]. 植物生态学报, 2020, 44(11): 1113-1126. doi: 10.17521/cjpe.2020.0111
	[ Zhang Wenqiang, Luo Geping, Zheng Hongwei, et al. Analysis of vegetation index change and driving force in inland arid area based on random forest model: A case study of the middle part of the northern slope of north Tianshan Mountains[J]. Chinese Journal of Plant Ecology, 2020, 44(11): 1113-1126. ] doi: 10.17521/cjpe.2020.0111
[23]	龚红花, 乌图那生. 新疆博州草原鼠害发生分布区域与防治的研究[J]. 草食家畜, 2011(4): 17-20.
	[ Gong Honghua, Wutu Nasheng. The research on prevention of rodent damage and its distribution in Bozhou[J]. Grass-Feeding Livestock, 2011(4): 17-20. ]
[24]	马良贤, 王学锋, 侯兰新, 等. 新疆东部草原鼠害的调查及危害类型的划分[J]. 西北民族学院学报, 1996(1): 47-50.
	[ Ma Liangxian, Wang Xuefeng, Hou Lanxin, et al. Investigation and classification of rodent damage in grassland in eastern Xinjiang[J]. Journal of Northwest Minzu University, 1996(1): 47-50. ]
[25]	杨东生. 用经验预测黄兔尾鼠种群数量的发生趋势[J]. 草食家畜, 2007(2): 15-17.
	[ Yang Dongsheng. Predicting the population trend of yellow rabbit tail rat by experience[J]. Grass-Feeding Livestock, 2007(2): 15-17. ]
[26]	张小侠. 乌苏市草地鼠害生物防治措施[J]. 农村科技, 2013(6): 44-45.
	[ Zhang Xiaoxia. Biological control measures of grassland rodents in Wusu City[J]. Rural Science and Technology, 2013(6): 44-45. ]
[27]	党惠才, 郭正财. 大沙鼠种群数量动态及周期性[J]. 新疆畜牧业, 2010(11): 48-50.
	[ Dang Huicai, Guo Zhengcai. Population dynamics and periodicity of Rhombomys opimus[J]. Xinjiang Xumuye, 2010(11): 48-50. ]
[28]	张宏伟, 姚明琴, 林超波, 等. 2012年新疆兵团准噶尔盆地动物鼠疫监测分析[J]. 兵团医学, 2013, 37(3): 58-60.
	[ Zhang Hongwei, Yao Mingqin, Lin Chaobo, et al. Monitoring and analysis of animal plague in Junggar Basin of Xinjiang Bingtuan in 2012[J]. Journal of Bingtuan Medicine, 2013, 37(3): 58-60. ]
[29]	尹文江, 张宏伟, 解卫刚, 等. 2010年新疆五家渠准噶尔盆地大沙鼠鼠疫自然疫源地监测报告[J]. 兵团医学, 2012, 34(4): 54-56.
	[ Yin Wenjiang, Zhang Hongwei, Xie Weigang, et al. Monitoring report on natural foci of gerbils plague in Junggar Basin, Xinjiang, 2010[J]. Journal of Bingtuan Medicine, 2012, 34(4): 54-56. ]
[30]	徐满厚, 刘彤, 姜莉. 古尔班通古特沙漠南部梭梭鼠害特征及防治生态阈值研究[J]. 干旱区资源与环境, 2012, 26(6): 126-133.
	[ Xu Manhou, Liu Tong, Jiang Li. Study on damage characteristics and control ecological threshold of Haloxylon ammodendron in the south of Gurbantunggut Desert[J]. Journal of Arid Land Resources and Environment, 2012, 26(6): 126-133. ]
[31]	魏旭明, 杨钦环, 韩兵兵, 等. 兵团六师草原生态监测情况[J]. 中国畜牧业, 2014(4): 50-51.
	[ Wei Xuming, Yang Qinhuan, Han Bingbing, et al. Grassland ecological monitoring of the sixth division of Bingtuan[J]. China Animal Industry, 2014(4): 50-51. ]
[32]	解卫刚, 尹文江. 新疆兵团第六师103团准噶尔荒漠鼠疫监测分析[J]. 疾病预防控制通报, 2016, 31(6): 41-42, 82.
	[ Xie Weigang, Yin Wenjiang. Monitoring and analysis of plague in Junggar Basin of the 103 regiment of the sixth division of Xinjiang Bingtuan[J]. Bulletin of Disease Control and Prevention, 2016, 31(6): 41-42, 82. ]
[33]	姚明琴, 刘成刚, 陆志刚, 等. 八师石河子荒漠地区鼠疫疫源地现状调查[J]. 疾病监测与控制, 2016, 10(4): 304-306.
	[ Yao Mingqin, Liu Chenggang, Lu Zhigang, et al. Investigation on plague foci of eight divisions in Shihezi desert area[J]. Journal of Diseases Montor and Control, 2016, 10(4): 304-306. ]
[34]	林超波, 董思文, 谭华, 等. 2010-2012年新疆生产建设兵团农六师鼠疫监测结果分析[J]. 疾病预防控制通报, 2013, 28(5): 67-68.
	[ Lin Chaobo, Dong Siwen, Tan Hua, et al. Analysis of surveillance results of plague in six divisions of Xinjiang Production and Construction Corps from 2010 to 2012[J]. Bulletin of Disease Control and Prevention, 2013, 28(5): 67-68. ]
[35]	尹小平, 田延河, 骄娃, 等. 新疆北部边境口岸大沙鼠种群分布特征及活动规律调查[J]. 中国媒介生物学及控制杂志, 2015, 26(2): 196-199.
	[ Yin Xiaoping, Tian Yanhe, Jiao Wa, et al. The distribution characteristics and activity patterns of the Rhombomys opimus population in northern Xinjiang borders[J]. Chinese Journal of Vector Biology and Control, 2015, 26(2): 196-199. ]
[36]	阿帕尔, 沙依拉吾, 努尔古丽. 克拉玛依市鼠类的调查报告[J]. 新疆畜牧业, 2007(增刊1): 38-40.
	[ Apaer, Shayilawu, Nuerguli. Investigation report on rodents in Karamay City[J]. Xinjiang Xumuye, 2007(Suppl. 1): 38-40. ]
[37]	艾尼瓦尔·库尔班, 塞力汗, 马俊杰, 等. 乌鲁木齐戈壁荒漠动物鼠疫自然疫源地调查[J]. 地方病通报, 2009, 24(6): 20-21, 23.
	[ Kuerban Einiwaer, Sailihan, Ma Junjie, et al. Investigation on natural foci of desert animal plague in Gobi, Urumqi[J]. Endemic Diseases Bulletin, 2009, 24(6): 20-21, 23. ]
[38]	郭刚. 新疆北疆地区鼠类和体外寄生生物病原携带及遗传特征研究[D]. 乌鲁木齐: 新疆医科大学, 2016.
	[ Guo Gang. Distribution and genetic on the rodents, ectozoic parasites and associated pathogens in northern region of Xinjiang[D]. Urumqi: Xinjiang Medical University, 2016. ]
[39]	周旭东, 张永军, 黄健, 等. 新疆甘家湖自然保护区啮齿动物群落结构与时间动态分析[J]. 动物学杂志, 2004, 39(6): 58-61.
	[ Zhou Xudong, Zhang Yongjun, Huang Jian, et al. Analysis of community structure and change of the rodents at Ganjiahu Nature Reserve in Xinjiang[J]. Chinese Journal of Zoology, 2004, 39(6): 58-61. ]
[40]	靳新霞, 张大铭. 莫索湾垦区啮齿动物群落结构与物种多样性分析[J]. 动物学杂志, 2005, 40(6): 30-37.
	[ Jin Xinxia, Zhang Daming. Rodent community structure and species diversity of analysis in Mosuowan reclamation[J]. Chinese Journal of Zoology, 2005, 40(6): 30-37. ]
[41]	张大铭, 艾尼瓦尔. 呼图壁种牛场草原生态站鼠类群落初步研究[J]. 新疆大学学报(自然科学版), 1997, 14(3): 53-56.
	[ Zhang Daming, Einiwaer. Preliminary study on rodent community in grassland ecological station of Hutubi cattle farm[J]. Journal of Xinjiang University (Natural Science Edition), 1997, 14(3): 53-56. ]
[42]	张大铭, 姜涛, 马合木提, 等. 阿拉山口啮齿动物群落结构及其变化[J]. 兽类学报, 1998, 18(2): 75-76, 57.
	[ Zhang Daming, Jiang Tao, Mahemuti, et al. The community structure and changes of rodents in Alataw pass[J]. Acta Theriologica Sinica, 1998, 18(2): 75-76, 57. ]
[43]	陶双庆, 侯兰新, 赵新春, 等. 对黄兔尾鼠生态的一些观察[J]. 干旱区研究, 1985, 2(3): 42-45.
	[ Tao Shuangqing, Hou Lanxin, Zhao Xinchun, et al. Some observations on the ecology of Lagurus luteus[J]. Arid Zone Research, 1985, 2(3): 42-45. ]
[44]	党惠才, 郭正财, 康淑红. 草原兔尾鼠种群数量分布及周期性初探[J]. 新疆畜牧业, 2007(增刊1): 21-22.
	[ Dang Huicai, Guo Zhengcai, Kang Shuhong. Population distribution and periodicity of Lagurus lagurus[J]. Xinjiang Xumuye, 2007(Suppl. 1): 21-22. ]
[45]	李小锋, 刘秀梅, 李建明, 等. 天山北坡不同类型草地产草量变化原因分析[J]. 新疆畜牧业, 2011(5): 30-33.
	[ Li Xiaofeng, Liu Xiumei, Li Jianming, et al. Analysis on the change of grass yield in different types of grassland on the north slope of Tianshan Mountain[J]. Xinjiang Xumuye, 2011(5): 30-33. ]
[46]	刘洋, 石娟. 气候变化背景下埃及吹绵蚧在中国的适生区预测[J]. 植物保护, 2020, 46(1): 108-117.
	[ Liu Yang, Shi Juan. Prediction of potential geographical distribution of Icerya aegyptiaca in China under climate change[J]. Plant Protection, 2020, 46(1): 108-117. ]
[47]	卢玲, 刘超. 基于世界土壤数据库(HWSD)的中国土壤数据集(v1.1)[DB/OL]. [2019-09-21]. http://www.ncdc.ac.cn.
	[ Lu Ling, Liu Chao. Chinese soil dataset based on Harmonized World Soil Database version 1.1[DB/OL]. [2019-09-21]. http://www.ncdc.ac.cn. ]
[48]	彭守璋. 中国1 km分辨率逐月平均气温数据集(1901-2017)[DB/OL]. [2019-05-17]. https://doi.org/10.11888/Meteoro.tpdc.270961.
	[ Peng Shouzhang. 1-km monthly mean temperature dataset for china (1901-2017)[DB/OL]. [2019-05-17]. https://doi.org/10.11888/Meteoro.tpdc.270961. ]
[49]	Peng S Z, Ding Y X, Liu W Z, et al. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017[J]. Earth System Science Data, 2019, 14(4): 1931-1946.
[50]	彭守璋. 中国1 km分辨率月最低温度数据集(1901-2017)[DB/OL]. [2019-05-17]. http://data.tpdc.ac.cn/zh-hans/data/5b644091-5fbf-4cd8-9324-6a543c9c369f.
	[ Peng Shouzhang. 1-km monthly minimum temperature dataset for China (1901-2017)[DB/OL]. [2019-05-17]. http://data.tpdc.ac.cn/zh-hans/data/5b644091-5fbf-4cd8-9324-6a543c9c369f. ]
[51]	彭守璋. 中国1 km分辨率月最高温度数据集(1901-2017)[DB/OL]. [2020-04-09]. http://data.tpdc.ac.cn/zh-hans/data/35ffff9f-8e1b-4296-801f-d8231e4f8dc3.
	[ Peng Shouzhang. 1-km monthly maximum temperature dataset for China (1901-2017)[DB/OL]. [2020-04-09]. http://data.tpdc.ac.cn/zh-hans/data/35ffff9f-8e1b-4296-801f-d8231e4f8dc3. ]
[52]	彭守璋. 中国1 km分辨率逐月降水量数据集(1901-2017)[DB/OL]. [2020-04-09]. http://data.tpdc.ac.cn/zh-hans/data/faae7605-a0f2-4d18-b28f-5cee413766a2.
	[ Peng Shouzhang. 1-km monthly precipitation dataset for China (1901-2017)[DB/OL]. [2020-04-09]. http://data.tpdc.ac.cn/zh-hans/data/faae7605-a0f2-4d18-b28f-5cee413766a2. ]
[53]	Gilbert M, Nicolas G, Cinardi G, et al. Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010[J]. Scientific Data, 2018, 5(1): 180227, doi: 10.1038/sdata.2018.227. doi: 10.1038/sdata.2018.227
[54]	阳坤, 何杰. 中国区域地面气象要素驱动数据集(1979-2018)[DB/OL]. [2019-05-09]. http://data.tpdc.ac.cn/zh-hans/data/8028b944-daaa-4511-8769-965612652c49.
	[ Yang Kun, He Jie. China meteorological forcing dataset (1979-2018)[DB/OL]. [2019-05-09]. http://data.tpdc.ac.cn/zh-hans/data/8028b944-daaa-4511-8769-965612652c49. ]
[55]	Yung K, He J, Tang W J, et al. On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau[J]. Agricultural and Forest Meteorology, 2010, 150(1): 38-46. doi: 10.1016/j.agrformet.2009.08.004
[56]	Breiman L. Random forests[J]. Machine Learning, 2001, 45(1): 5-32. doi: 10.1023/A:1010933404324
[57]	Lujan-Moreno G A, Howard P R, Rojas O G, et al. Design of experiments and response surface methodology to tune machine learning hyperparameters, with a random forest case-study[J]. Expert Systems with Applications, 2018, 109: 195-205. doi: 10.1016/j.eswa.2018.05.024
[58]	方馨蕊, 温兆飞, 陈吉龙, 等. 随机森林回归模型的悬浮泥沙浓度遥感估算[J]. 遥感学报, 2019, 23(4): 756-772.
	[ Fang Xinrui, Wen Zhaofei, Chen Jilong, et al. Remote sensing estimation of suspended sediment concentration based on stochastic forest regression model[J]. Journal of Remote Sensing, 2019, 23(4): 756-772. ]
[59]	Quinlan J R. Combining instance-based and model-based learning[C]// Machine Learning, Proceedings of the Tenth International Conference. Amherst: University of Massachusetts, 1993: 236-243.
[60]	Goh K M, Maulidiani M, Rudiyanto R, et al. Rapid assessment of total MCPD esters in palm-based cooking oil using ATR-FTIR application and chemometric analysis[J]. Talanta, 2019, 198: 215-223. doi: 10.1016/j.talanta.2019.01.111
[61]	戴舒, 付迎春, 赵耀龙. 基于Cubist模型树的城市不透水面百分比遥感估算模型[J]. 地球信息科学学报, 2016, 18(10): 1399-1409. doi: 10.3724/SP.J.1047.2016.01399
	[ Dai Shu, Fu Yingchun, Zhao Yaolong. The remote sensing model for estimating urban impervious surface percentage based on the cubic model tree[J]. Journal of Geo-Information Science, 2016, 18(10): 1399-1409. ] doi: 10.3724/SP.J.1047.2016.01399
[62]	王玮, 冯琦胜, 于惠, 等. “3S”技术在草地鼠虫害监测与预测中的应用[J]. 草业科学, 2010, 27(3): 31-39.
	[ Wang Wei, Feng Qisheng, Yu Hui, et al. Application of “3S” technology on monitoring and prediction of the grassland rodents and insects[J]. Pratacultural Science, 2010, 27(3): 31-39. ]
[63]	陈家乐, 唐林茜, 相满城, 等. 区域土壤-水稻籽粒镉耦合关系模型的构建和验证[J]. 生态学杂志, 2021, 40(8): 2341-2347.
	[ Chen Jiale, Tang Linxi, Xiang Mancheng, et al. Model constructions and verifications for regional cadmium coupling relationships in soil-rice grain[J]. Chinese Journal of Ecology, 2021, 40(8): 2341-2347. ]
[64]	Turchin P, Batzli G O. Availability of food and the population dynamics of arvicoline rodents[J]. Ecology, 2001, 82(6): 1521-1534. doi: 10.1890/0012-9658(2001)082[1521:AOFATP]2.0.CO;2
[65]	马久, 袁帅, 郭乾伟, 等. 典型草原啮齿动物群落与植物群落相关性分析[J]. 草原与草业, 2021, 33(3): 28-35.
	[ Ma Jiu, Yuan Shuai, Guo Qianwei, et al. Correlation analysis of main populations of rodent communities and plant communities under different grazing disturbance in typical steppe[J]. Grassland and Prataculture, 2021, 33(3): 28-35. ]
[66]	张军, 葛庆征, 张卫国, 等. 植被性状与高原鼢鼠栖息地适合度的关系[J]. 草业科学, 2011, 28(5): 836-840.
	[ Zhang Jun, Ge Qingzheng, Zhang Weiguo, et al. Correlations between vegetation properties and fitness of Plateau Zoker habitat[J]. Prataculltural Science, 2011, 28(5): 836-840. ]
[67]	边疆晖, 樊乃昌, 景增春, 等. 高寒草甸地区小哺乳动物群落与植物群落演替关系的研究[J]. 兽类学报, 1994(3): 209-216.
	[ Bian Jianghui, Fan Naichang, Jing Zengchun, et al. Study on the succession relationship between small mammal community and plant community in alpine meadow area[J]. Acta Theriologica Sinica, 1994(3): 209-216. ]
[68]	岳健, 穆桂金, 唐自华, 等. 基于NDVI的新疆荒漠地区植被覆盖度遥感估算经验模型研究[J]. 干旱区地理, 2020, 43(1): 153-160.
	[ Yue Jian, Mu Guijin, Tang Zihua, et al. Remote sensing estimation models for vegetation coverage in desert regions of Xinjiang based on NDVI[J]. Arid Land Geography, 2020, 43(1): 153-160. ]
[69]	姜萍, 丁文广, 肖静, 等. 新疆植被NPP及其对气候变化响应的海拔分异[J]. 干旱区地理, 2021, 44(3): 849-857.
	[ Jiang Ping, Ding Wenguang, Xiao Jing, et al. Altitudinal difference of vegetation NPP and its response to climate change in Xinjiang[J]. Arid Land Geography, 2021, 44(3): 849-857. ]
[70]	李杨, 刘艳, 马丽, 等. 天山北坡气候因子对植被影响的空间分异性研究[J]. 干旱区资源与环境, 2011, 25(7): 91-95.
	[ Li Yang, Liu Yan, Ma Li, et al. Spatial variation of the vegetation effected by climatic factors in the north slope of Tianshan Mountains[J]. Journal of Arid Land Resources and Environment, 2011, 25(7): 91-95. ]
[71]	陈云浩, 李晓兵, 史培军. 基于遥感的NDVI与气候关系图式研究[J]. 中国图象图形学报, 2002(4): 22-25, 107.
	[ Chen Yunhao, Li Xiaobing, Shi Peijun. The image forms of correlation between NDVI and climate factors in China using remotely sensed data[J]. Journal of Image and Graphics, 2002(4): 22-25, 107. ]
[72]	钟文勤, 樊乃昌. 我国草地鼠害的发生原因及其生态治理对策[J]. 生物学通报, 2002, 37(7): 1-4.
	[ Zhong Wenqin, Fan Naichang. Causes of grassland rodent damage and its ecological control countermeasures in China[J]. Bulletin of Biology, 2002, 37(7): 1-4. ]
[73]	Li G L, Yin B F, Wan X R, et al. Successive sheep grazing reduces population density of Brandt’s voles in steppe grassland by altering food resources: A large manipulative experiment[J]. Oecologia, 2016, 180(1): 149-159. doi: 10.1007/s00442-015-3455-7
[74]	袁帅, 付和平, 武晓东, 等. 基于结构方程模型分析荒漠啮齿动物优势种对不同放牧干扰的响应[J]. 生态学报, 2017, 37(14): 4795-4806.
	[ Yuan Shuai, Fu Heping, Wu Xiaodong, et al. Response of dominant desert rodent species to grazing disturbances: A structural equation modeling analysis[J]. Acta Ecologica Sinica, 2017, 37(14): 4795-4806. ]
[75]	罗泽珣, 陈卫, 高武, 等. 中国动物志,兽纲第六卷啮齿目下册(仓鼠科)[M]. 北京: 科学出版社, 2000: 325-329.
	[ Luo Zexun, Chen Wei, Gao Wu, et al. Fauna Sinica, Mammalia Vol.6 Rodentia Part Ⅲ: Cricetidae[M]. Beijing: Science Press, 2000: 325-329. ]
[76]	李俊, 阿布力米提·阿不都卡迪尔. 红尾沙鼠(Meriones libycus)的年龄鉴定及种群年龄组成[J]. 干旱区研究, 2007, 24(1): 43-48.
	[ Li Jun, Abudukadier Abulimiti. Study on the age identification and the population age composition of Meriones libycus[J]. Arid Zone Research, 2007, 24(1): 43-48. ]
[77]	Randall J A, Konstantin R, Parker P G, et al. Flexible social structure of a desert rodent, Rhombomys opimus: Philopatry, kinship, and ecological constraints[J]. Behavioral Ecology, 2005(6): 961-973.

数据类型	样本数	最小值/个·hm^-2	最大值/个·hm^-2	平均值/个·hm^-2	标准差
全部数据	275	1	1370	254.23	254.23
海拔≤900 m地区数据	190	4	1220	251.76	222.54
海拔>900 m地区数据	85	1	1370	259.73	253.62

基于Cubist模型的天山北坡草地鼠群密度时空分布特征

Spatiotemporal distribution of rat population density in grassland on the north slope of Tianshan Mountains based on Cubist model

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