张楚天

　　 　　

一、个人简介

张楚天，男，汉族，1989年5月出生于湖北省宜昌市。中共党员，博士，副教授，硕士生导师，咸阳市土地整治专家库专家。2016年8月起在西北农林科技大学资源环境学院地理科学系从事教学与科研工作。

二、教育和工作经历

2021.01至今，西北农林科技大学，资源环境学院，副教授

2021.08-2022.08，清华大学，万科公共卫生与健康学院，全健康课题组，访问学者

2016.09-2022.09，西北农林科技大学，农业资源与环境博士后科研流动站，在职博士后

2016.08-2020.12，西北农林科技大学，资源环境学院，讲师

2015.03-2016.07，浙江大学，海洋学院，George Christakos课题组，科研助理

2011.09-2016.06，华中农业大学，资源与环境学院，获资源环境信息工程专业博士学位

2007.09-2011.06，华中农业大学，资源与环境学院，获地理信息系统学士学位

三、研究方向

1. 环境健康风险评估与管理

2. 地理建模理论与方法

3. 数字土壤制图

近年来，主要聚焦于基于地理时空分析方法的人畜共患病传播模式及其风险因素研究。通过时空建模和数据驱动的分析技术，揭示了包括鼠疫、肾综合征出血热等多种人畜共患病在不同资源环境和气候背景下的历史和未来传播动态与空间分布特征，从而为精准的疾病风险评估和防控策略提供科学支持。

四、科研项目

1. 国家自然科学基金青年科学基金项目，县域尺度表层土壤有机碳密度空间格局及影响因素定量刻画，2018.01-2020.12，主持

2. 西北农林科技大学博士科研启动项目，基于贝叶斯最大熵的土壤属性空间定量分析研究，2016.09-2018.12，主持

五、学术成果

1. Wang YC^#, Zhang CT^#, Gao J^#, Chen ZQ, Liu Z, Huang JB, Chen YD, Li ZC, Chang N, Tao YX, Tang H, Gao XJ, Xu Y, Wang C, Li D, Liu XB, Pan JX, Cai Wj, Gong P, Luo Y, Liang WN, Liu QY, Stenseth NC, Yang RF, Xu L. 2024. Spatiotemporal trends of hemorrhagic fever with renal syndrome (HFRS) in China under climate variation.  Proceedings of the National Academy of Sciences of the United States of America  121(4), e2312556121. https://doi.org/10.1073/pnas.2312556121 

2. Stenseth NC^#, Tao YX^#, Zhang CT^#, Bramanti B, Büntgen U, Cong XB, Cui YJ, Zhou H, Dawson LA, Mooney SJ, Li D, Fell HG, Cohn S, Sebbane F, Slavin P, Liang WN, Tong H, Yang RF, Xu L. 2022. No evidence for persistent natural plague reservoirs in historical and modern Europe.  Proceedings of the National Academy of Sciences of the United States of America  119(51), e2209816119. https://doi.org/10.1073/pnas.2209816119 

3. Zheng YT, Zhao XN, Li XY, Chen HY, Li CC, Zhang CT^*. 2024. Mapping soil organic carbon density via geographically weighted regression with smooth terms: A case study in Shanxi Province.  Ecological Indicators  166, 112588. https://doi.org/10.1016/j.ecolind.2024.112588 

4. Gao J^#, Zhang CT^#, Wheelock ÅM, Xin SM, Cai H, Xu L, Wang XJ. 2024. Immunomics in one health: understanding the human, animal, and environmental aspects of COVID-19.  Frontiers in Immunology  15. https://doi.org/10.3389/fimmu.2024.1450380 

5. Zhou C, Wheelock SM, Zhang CT, Ma J, Li ZC, Liang WN, Xu L. 2024. Country-specific determinants for covid-19 case fatality rate and response strategies from a global perspective: an interpretable machine learning framework.  Population Health Metrics  22(1), 10. https://doi.org/10.1186/s12963-024-00330-4 

6. Zhao XN, Zheng YT, Wang W, Wang Z, Zhang QF, Liu JC, Zhang CT^*. 2023. Habitat Suitability Evaluation of Different Forest Species in Lvliang Mountain by Combining Prior Knowledge and MaxEnt Model.  Forests  14(2), 438. https://doi.org/10.3390/f14020438 

7. Stenseth NC, Bramanti B, Büntgen U, Fell HG, Cohn S, Sebbane F, Slavin P, Zhang CT, Yang RF, Xu L. 2023. Reply to Alfani: Reconstructing past plague ecology to understand human history.  Proceedings of the National Academy of Sciences of the United States of America  120(11), e2300760120. https://doi.org/10.1073/pnas.2300760120 

8. Gao J, Zhou C, Liang HW, Jiao R, Wheelock M, Jiao KD, Ma J, Zhang CT, Guo YM, Luo ST, Liang WN, Xu L. 2023. Monkeypox outbreaks in the context of the COVID-19 pandemic: Network and clustering analyses of global risks and modified SEIR prediction of epidemic trends.  Frontiers in Public Health  11. https://doi.org/10.3389/fpubh.2023.1052946 

9. Zhou C, Wheelock AM, Zhang CT, Ma J, Dong KX, Pan JX, Li ZC, Liang WN, Gao J, Xu L. 2023. The role of booster vaccination in decreasing COVID-19 age-adjusted case fatality rate: Evidence from 32 countries.  Frontiers in Public Health  11. https://doi.org/10.3389/fpubh.2023.1150095 

10. Yu XQ, Zhao YM, Zhang CT, Yang CF, Ouyang ZZ, Liu P, Guo XT, Zhu LY. 2022. Abundance and characteristics of microplastics in the surface water and sediment of parks in Xi'an city, Northwest China.  Science of the Total Environment  806, 150953. https://doi.org/10.1016/j.scitotenv.2021.150953 

11. Huang DF, Li XY, Ouyang Z, Zhao XN, Wu RR, Zhang CT, Lin C, Li YY, Guo XT. 2021. The occurrence and abundance of microplastics in surface water and sediment of the West River downstream, in the south of China.  Science of The Total Environment  756, 143857. https://doi.org/10.1016/j.scitotenv.2020.143857 

12. Li JL, Ouyang Z, Liu P, Zhao XN, Wu RR, Zhang CT, Lin C, Li YY, Guo XT. 2021. Distribution and characteristics of microplastics in the basin of Chishui River in Renhuai, China.  Science of The Total Environment  773, 145591. https://doi.org/10.1016/j.scitotenv.2021.145591 

13. Zhang CT, Yang Y. 2020. Modeling the spatial variations in anthropogenic factors of soil heavy metal accumulation by geographically weighted logistic regression.  Science of The Total Environment  717, 137096. https://doi.org/10.1016/j.scitotenv.2020.137096 

14. Ta N^#, Zhang CT^#, Ding HR, Zhang QF. 2020. Effect of tillage, slope, and rainfall on soil surface microtopography quantified by geostatistical and fractal indices during sheet erosion.  Open Geosciences  12(1), 232-241. https://doi.org/10.1515/geo-2020-0036 

15. Ding L, Zhang SY, Wang XY, Yang XM, Zhang CT, Qi YB, Guo XT. 2020. The occurrence and distribution characteristics of microplastics in the agricultural soils of Shaanxi Province, in north-western China.  Science of The Total Environment  720. https://doi.org/10.1016/j.scitotenv.2020.137525 

16. Liu KK, Hou X, Ren ZP, Lowe R, Wang YG, Li RY, Liu XB, Sun JM, Lu L, Song XP, Wu HX, Wang J, Yao WW, Zhang CT, Sang SW, Gao Y, Li J, Li JP, Xu L, Liu QY. 2020. Climate factors and the East Asian summer monsoon may drive large outbreaks of dengue in China.  Environmental Research  183, 109190. https://doi.org/10.1016/j.envres.2020.109190 

17. Xu CY, Zhou TT, Wang CL, Liu HY, Zhang CT, Hu FN, Zhao SW, Geng ZC. 2020. Aggregation of polydisperse soil colloidal particles: Dependence of Hamaker constant on particle size.  Geoderma  359, 113999. https://doi.org/10.1016/j.geoderma.2019.113999 

18. Zhang CT, Yang Y. 2019. Can the spatial prediction of soil organic matter be improved by incorporating multiple regression confidence intervals as soft data into BME method?  CATENA  178, 322-334. https://doi.org/10.1016/j.catena.2019.03.027

19. Zhang CT, Yang Y. 2019. Improving the spatial prediction of soil Zn by converting outliers into soft data for BME method.  Stochastic Environmental Research And Risk Assessment  33(3), 855-864. https://doi.org/10.1007/s00477-018-1641-y 

20. Christakos G, Yang Y, Wu JP, Zhang CT, Mei Y, He JY. 2018. Improved space-time mapping of PM2.5 distribution using a domain transformation method.  Ecological Indicators  85, 1273-1279. https://doi.org/10.1016/j.ecolind.2017.08.007 

21. Christakos G, Zhang CT, He JY. 2017. A traveling epidemic model of space-time disease spread.  Stochastic Environmental Research And Risk Assessment  31(2), 305-314. https://doi.org/10.1007/s00477-016-1298-3 

22. Yang Y, Mei Y, Zhang CT, Zhang RX, Liao XS, Liu YY. 2016. Heavy metal contamination in surface soils of the industrial district of Wuhan, China.  Human and Ecological Risk Assessment  22(1), 126-140. https://doi.org/10.1080/10807039.2015.1056291 

23. Yang Y, Zhang CT, Zhang RX. 2016. BME prediction of continuous geographical properties using auxiliary variables.  Stochastic Environmental Research And Risk Assessment  30(1), 9-26. https://doi.org/10.1007/s00477-014-1005-1 

24. Zhang CT, Yang Y, Li WD, Zhang CR, Zhang RX, Mei Y, Liao XS, Liu YY. 2015. Spatial distribution and ecological risk assessment of trace metals in urban soils in Wuhan, central China.  Environmental Monitoring and Assessment  187(9), 1-16. https://doi.org/10.1007/s10661-015-4762-5 

25. Yang Y, Zhang CT, Zhang RX, Christakos G. 2015. Improving environmental prediction by assimilating auxiliary information.  Journal of Environmental Informatics  26(2), 91-105. https://doi.org/10.3808/jei.201500316 

26. Zhang CT, Yang Y. 2013. Spatial prediction of soil organic matter using Bayesian maximum entropy with histogram soft data. In: F. Bian, Y. Xie, X. Cui, Y. Zeng (Eds.), Geo-Informatics in Resource Management and Sustainable Ecosystem: International Symposium, GRMSE 2013, Wuhan, China, November 8-10, 2013, Proceedings, Part I. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 674-683. https://doi.org/10.1007/978-3-642-45025-9_66 

27. 冯晓琳，闫雨阳，张欣然，张楚天，耿增超，胡斐南，许晨阳．2024. 近30年陕西土壤有机碳的时空变化特征及影响因素[J/OL]．环境科学. https://doi.org/10.13227/j.hjkx.202311169 

28. 冯晓琳, 张楚天, 许晨阳, 耿增超, 胡斐南, 杜伟. 2024. 陕西省土壤无机碳的时空分布特征及影响因素. 中国农业科学, 57(8), 1517-1532.

29. 梅杨, 党丽娜, 杨勇, 刘颖颖, 张若兮, 廖祥森, 张楚天. 2016. 基于时空克里格的PM_(2.5)时空预测及分析. 环境科学与技术 (07), 157-163.

30. 张若兮, 杨勇, 张楚天. 2015. 基于范畴型变量和贝叶斯最大熵的土壤有机质空间预测. 土壤通报 46(02), 312-318.

31. 张楚天, 杨勇, 贺立源, 季世民, 刘颖颖. 2014. 基于环境因子和联合概率方法的土壤有机质空间预测. 土壤学报 (03), 666-673.

32. 杨勇, 梅杨, 张楚天, 张若兮, 廖祥森. 2014. 基于时空克里格的土壤重金属时空建模与预测. 农业工程学报 (21), 249-255.

33. 张楚天, 杨勇, 杨中华, 黄丰. 2013. 江河突发性水污染事故动态模拟与预警——以长江武汉段为例. 长江流域资源与环境 (10), 1363-1368.

34. 杨勇, 张楚天, 贺立源. 2013. 基于贝叶斯最大熵的多因子空间属性预测新方法. 浙江大学学报(农业与生命科学版) 39(06), 636-644.

35. 龙腾, 王景凯, 张楚天, 徐作鹏, 苗洁. 2011. 基于GIS和RS技术的测土配方施肥系统设计与实现. 安徽农业科学 39(28), 17588-17593.

36. 杨勇，张楚天，蒋娟. 联合概率空间预测系统V1.0. 2013，国家版权局，软著登字第0593749号

37. 张楚天，杨勇，赵明登，杨中华. 河流水质动态演示系统V1.0. 2012，国家版权局，软著登字第0588740号

六、教育教学

1. 本科课程：主讲《环境遥感技术》、《GIS技术及其应用》、《地理信息系统》、《地理信息系统实习》，参与讲授《遥感与地理信息技术》等课程

2. 研究生课程：主讲《计量土壤学》，参与讲授《现代地理信息系统技术》和《社会经济空间数据统计分析》等课程

3. 陕西省课程思政示范课程和教学团队（研究生教育类）成员

4. 参编《地理信息原理》、《水土保持规划学》等教材

七、获奖情况

1. 西北农林科技大学“思政课教师大练兵与课程思政建设”课程思政教学骨干，2023年

2. 第三届全国教学创新大赛二等奖（排名3/4），2023年

3. 第十二届全国大学生电子商务“创新、创意及创业”挑战赛陕西赛区省级选拔赛“优秀指导老师”称号，2022年

4. 第二届“智慧树杯”课程思政示范案例大赛一等奖（排名3/3），2021年

5. 西北农林科技大学青年教师讲课比赛一等奖及课程思政单项奖，2020年

6. 西北农林科技大学资源环境学院青年教师讲课比赛一等奖，2020年

八、联系方式

通讯地址：陕西杨凌邰城路西北农林科技大学南校区子校楼307室；邮编：712100

电子邮箱: zhangchutian@nwafu.edu.cn