江苏奶牛热应激风险区划及其受气候变化的影响

doi:10.3864/j.issn.0578-1752.2022.22.015

Abstract

Abstract:

【Objective】 The aim of this study was to master the occurrence law of cow heat stress under the background of climate change to optimize the production management of pasture and to promote ecological and healthy breeding level of dairy cows, which could provide the reference for optimizing the layout of animal husbandry, intelligent management and control of pasture, site selection and transformation, benefit improvement and so on. 【Method】Taking Jiangsu Province as an example, the risk index (RI) was constructed based on the temperature humidity index (THI) by using the Era5 data set of global atmospheric reanalysis data from 1980 to 2020, which represented the degree of cow heat stress. The K-means clustering algorithm was selected to realize the risk zoning of heat stress of dairy cows, and the regional evaluation was carried out in combination with the characteristics of occurrence intensity, frequency, start and end time, as well as duration of heat stress. The climate tendency rate was calculated to analyze the change trend of the characteristics of cow heat stress in the different risk areas. Based on the cumulative temperature humidity index (CTHI), Mann-Kendall test was used to determine the climate mutation points in the different risk areas. Furthermore, the impacts of climate change on the occurrence characteristics of cow heat stress in different risk areas were analyzed from the daily and hourly time scales, respectively. 【Result】The risk of heat stress of dairy cows in Jiangsu Province presented the distribution features of "high in the southwest and low in the northeast". The low-risk areas mainly included Huaibei and the middle-eastern area of Yangtze River and Huai River valley. The regional averaged value of THI was 73.63, and the mild heat stress mainly occurred. The high-risk areas mainly included the areas along the southern Jiangsu and the west area of Yangtze River and Huai River valley. The regional averaged value of THI was 75.12, and the occurrence frequency of mild and moderate thermal stress was nearly the same. In the low-risk and high-risk areas, the start and end time of heat stress showed an advanced and delay trend, and the duration days showed an extended trend of 4.0 d/(10a) and 4.2 d/(10a), respectively, the values of THI all showed an increasing trend of 0.2/(10a), while the value of CTHI showed an increasing trend of 301.2/(10a) and 256.1/(10a), respectively. The frequencies of mild thermal stress were bimodal, which mainly occurred from the early-June to the mid-July, and from the early-August to the middle-September, while the frequency of moderate thermal stress was unimodal, which mainly occurred from mid-July to mid-August. The change of daily heat stress intensity basically presented a distribution of "sinusoidal", and the high incidence period was concentrated in 11:00-17:00. Affected by climate change, the heat stress of dairy cows in Jiangsu Province showed an obvious increasing trend, reaching a small peak in 2010. Then after a decline, it showed a steady strengthening trend, which exceeded the threshold of 0.05 significance level. In the low and high risk areas, the highly impacted periods of cow heat stress were prolonged, the occurrence frequency increased, the coverage increased, and the starting-time moved forward. The daily beginning time of the high incidence period of cow heat stress moved forward for about 1 hour, and the intensity of heat stress in high-risk areas was basically increased close to the medium level. 【Conclusion】 Based on THI, RI and CTHI, the risk zoning assessment and climate impact analysis of cow heat stress could be realized, the high-risk areas as well as key prevention and control periods of cow heat stress could be determined, and the climate change trend could be grasped. With the climate change, the heat stress of dairy cows in Jiangsu Province showed the characteristics of "earlier, stronger, longer and more", which should be actively dealt with.

Key words: Jiangsu Province, cow, heat stress, risk zoning assessment, climate change

REN Yifang,YANG ZhangPing,LING Fenghua,XIAO LiangWen. Risk Zoning of Heat Stress Risk Zoning of Dairy Cows in Jiangsu Province and Its Characteristics Affected by Climate Change[J].Scientia Agricultura Sinica, 2022, 55(22): 4513-4525.

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References 39

[1]	江苏省农业农村厅. 我省奶业振兴取得阶段性成果.[EB/OL]. 南京:江苏省农业农村厅, [2021-02-19]. http://nynct.jiangsu.gov.cn/art/ 2021/2/19/art_12130_9674632.html.
	Department of agriculture and rural areas of Jiangsu Province. Phased achievements have been made in the revitalization of dairy industry in our province. [EB / OL]. Nanjing: Department of agriculture and rural areas of Jiangsu Province, [2021-02-19]. http://nynct.jiangsu.gov.cn/art/ 2021/2/19/art_12130_9674632.html. (in Chinese)
[2]	孙宏进. 推动江苏奶业高质量发展. 中国畜牧业, 2019(14): 40-41.
	SUN H J. Promote high quality development of dairy industry in Jiangsu. China Animal Industry, 2019(14): 40-41. (in Chinese)
[3]	单强, 马峰涛, 魏婧雅, 郝丽媛, 孙鹏. 热应激影响荷斯坦奶牛泌乳机制的研究进展. 中国畜牧杂志, 2019, 55(3): 29-33. doi:10.19556/j.0258-7033.2019-03-029. doi: 10.19556/j.0258-7033.2019-03-029
	SHAN Q, MA F T, WEI J Y, HAO L Y, SUN P. Research progress on the effect of heat stress on lactating mechanism of Holstein cows. Chinese Journal of Animal Science, 2019, 55(3): 29-33. doi:10.19556/j.0258-7033.2019-03-029. (in Chinese) doi: 10.19556/j.0258-7033.2019-03-029
[4]	赵琨发, 陈琪, 王争光. 浙江地区热应激对奶牛的危害及其防控措施. 中国奶牛, 2017(12): 7-12. doi:10.19305/j.cnki.11-3009/s.2017.12.002. doi: 10.19305/j.cnki.11-3009/s.2017.12.002.
	ZHAO K F, CHEN Q, WANG Z G. The harm effects of heat stress on dairy cows in Zhejiang Province and its solving measures. China Dairy Cattle, 2017(12): 7-12. doi:10.19305/j.cnki.11-3009/s.2017.12.002. (in Chinese) doi: 10.19305/j.cnki.11-3009/s.2017.12.002.
[5]	李晗, 王宇, 高景, 齐智利. 热应激对瘤胃微生物的影响及其与奶牛生产性能的关系. 动物营养学报, 2019, 31(10): 4458-4463. doi:10.3969/j.issn.1006? 267x.2019.10.007. doi: 10.3969/j.issn.1006? 267x.2019.10.007.
	LI H, WANG Y, GAO J, QI Z L. Effects of heat stress on rumen microbiota and its relationship with performance of dairy cows. Chinese Journal of Animal Nutrition, 2019, 31(10): 4458-4463. doi:10.3969/j.issn.1006? 267x.2019.10.007. (in Chinese) doi: 10.3969/j.issn.1006? 267x.2019.10.007.
[6]	KADZERE C T, MURPHY M R, SILANIKOVE N, MALTZ E. Heat stress in lactating dairy cows: a review. Livestock Production Science, 2002, 77(1): 59-91. doi:10.1016/S0301-6226(01)00330-X. doi: 10.1016/S0301-6226(01)00330-X.
[7]	RHOADS M L, RHOADS R P, VANBAALE M J, COLLIER R J, SANDERS S R, WEBER W J, CROOKER B A, BAUMGARD L H. Effects of heat stress and plane of nutrition on lactating Holstein cows: I. Production, metabolism, and aspects of circulating somatotropin. Journal of Dairy Science, 2009, 92(5): 1986-1997. doi:10.3168/jds.2008-1641. doi: 10.3168/jds.2008-1641 pmid: 19389956
[8]	WEST J W. Effects of heat-stress on production in dairy cattle. Journal of Dairy Science, 2003, 86(6): 2131-2144. doi:10.3168/jds.S0022-0302(03)73803-X. doi: 10.3168/jds.S0022-0302(03)73803-X. pmid: 12836950
[9]	王建平, 王加启, 卜登攀, 霍小凯, 郭同军, 梁建光, 王光文, 袁耀明, 李发弟. 热应激对奶牛影响的研究进展. 中国奶牛, 2008(7): 21-24. doi:10.3969/j.issn.1004-4264.2008.07.010. doi: 10.3969/j.issn.1004-4264.2008.07.010.
	WANG J P, WANG J Q, BU D P, HUO X K, GUO T J, LIANG J G, WANG G W, YUAN Y M, LI F D.Research advance in the influence of heat stress on dairy cow. China Dairy Cattle, 2008(7): 21-24. doi:10.3969/j.issn.1004-4264.2008.07.010. (in Chinese) doi: 10.3969/j.issn.1004-4264.2008.07.010.
[10]	刘梅, 高苹, 王静苒, 俞剑蔚, 曹舒娅. 江苏夏季逐月高温日数与西太平洋海温场相关分析及预测模型建立. 气象, 2011, 37(12): 1553-1559.
	LIU M, GAO P, WANG J R, YU J W, CAO S Y. Study on remote correlation between summer monthly high temperature days in Jiangsu and west Pacific SST and its long-term prediction models. Meteorological Monthly, 2011, 37(12): 1553-1559. (in Chinese)
[11]	王春乙, 张继权, 霍治国, 蔡菁菁, 刘兴朋, 张琪. 农业气象灾害风险评估研究进展与展望. 气象学报, 2015, 73(1): 1-19.
	WANG C Y, ZHANG J Q, HUO Z G, CAI J J, LIU X P, ZHANG Q. Prospects and progresses in the research of risk assessment of agro-meteorological disasters. Acta Meteorologica Sinica, 2015, 73(1): 1-19. (in Chinese)
[12]	邱美娟, 刘布春, 刘园, 王珂依, 庞静漪, 张晓男, 贺金娜. 中国北方主产地苹果始花期模拟及晚霜冻风险评估. 农业工程学报, 2020, 36(21): 154-163.
	QIU M J, LIU B C, LIU Y, WANG K Y, PANG J Y, ZHANG X N, HE J N. Simulation of first flowering date for apple and risk assessment of late frost in main producing areas of Northern China. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(21): 154-163. (in Chinese)
[13]	鲁天平, 郭靖, 陈梦, 李宏, 玉苏普江·艾麦提, 刘永萍. 新疆林果产业大风沙尘灾害风险评估模型构建及区划. 农业工程学报, 2016, 32(S2): 169-176.
	LU T P, GUO J, CHEN M, LI H, YUSUPUJIANG·AIMAITI, LIU Y P. Model establishment and zoning of wind—dust risk assessment to featured forestry and fruit industry in Xinjiang. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(S2): 169-176. (in Chinese)
[14]	任义方, 张旭晖, 陈焕根, 时冬头, 陈翔, 钱钰林, 潘云生. 江苏河蟹高温热害时空变化特征及影响. 生态学杂志, 2020, 39(11): 3704-3714. doi:10.13292/j.1000-4890.202011.027. doi: 10.13292/j.1000-4890.202011.027.
	REN Y F, ZHANG X H, CHEN H G, SHI D T, CHEN X, QIAN Y L, PAN Y S. Spatiotemporal variation and impacts of high temperature heat damage on river crab in Jiangsu Province. Chinese Journal of Ecology, 2020, 39(11): 3704-3714. doi:10.13292/j.1000-4890.202011.027. (in Chinese) doi: 10.13292/j.1000-4890.202011.027.
[15]	中华人民共和国农业部. 奶牛热应激评价技术规范: NY/T 2363—2013[S]. 北京: 中国农业出版社, 2013.
	Ministry of Agriculture of the People's Republic of China. Technical specification for heat of dairy cows: NY/T 2363—2013[S]. Beijing: Chinese Agriculture Press, 2013. (in Chinese)
[16]	王树廷. 关于日平均气温稳定通过各级界限温度初终日期的统计方法. 气象, 1982, 8(6): 29-30.
	WANG S T. Statistical method for the initial and final dates of the daily average temperature passing through the boundary temperatures at all levels. Meteorological Monthly, 1982, 8(6): 29-30. (in Chinese)
[17]	GENOLINI C, FALISSARD B. KmL: k-means for longitudinal data. Computational Statistics, 2010, 25(2): 317-328. doi:10.1007/s00180-009-0178-4. doi: 10.1007/s00180-009-0178-4.
[18]	ZHANG T F, MA F M. Improved rough k-means clustering algorithm based on weighted distance measure with Gaussian function. International Journal of Computer Mathematics, 2017, 94(4): 663-675. doi:10.1080/00207160.2015.1124099. doi: 10.1080/00207160.2015.1124099.
[19]	魏凤英. 现代气候统计诊断与预测技术. 2版. 北京: 气象出版社, 2007: 69-72.
	WEI F Y. Effects of heat stress on physiological indexes and production performance of lactating dairy cows. Beijing: China Meteorological Press, 2007: 69-72. (in Chinese)
[20]	姚焰础, 江山, 肖融, 黄健, 杜瑞平, 高民. 热应激对荷斯坦奶牛体温和呼吸的影响. 中国畜牧杂志, 2012, 48(11): 59-62, 75. doi:10.3969/j.issn.0258-7033.2012.11.015. doi: 10.3969/j.issn.0258-7033.2012.11.015.
	YAO Y C, JIANG S, XIAO R, HUANG J, DU R P, GAO M. Effect of heat stress on body temperature and respiration of dairy cows. Chinese Journal of Animal Science, 2012, 48(11): 59-62, 75. doi:10.3969/j.issn.0258-7033.2012.11.015. (in Chinese) doi: 10.3969/j.issn.0258-7033.2012.11.015.
[21]	张志登, 敬盈嘉, 刘影, 杨玉东, 刘敏, 王玲. 热应激对泌乳奶牛生理指标及生产性能的影响. 中国畜牧杂志, 2020, 56(4): 169-172. doi:10.19556/j.0258-7033.20190613-02. doi: 10.19556/j.0258-7033.20190613-02.
	ZHANG Z D, JING Y J, LIU Y, YANG Y D, LIU M, WANG L. Effects of heat stress on physiological indexes and production performance of lactating dairy cows. Chinese Journal of Animal Science, 2020, 56(4): 169-172. doi:10.19556/j.0258-7033.20190613-02. (in Chinese) doi: 10.19556/j.0258-7033.20190613-02.
[22]	李林, 艾阳, 谢正露, 曹洋, 张源淑. 热应激状态下泌乳奶牛通过激活GHIGF-I轴增强糖异生变化. 中国农业科学, 2016, 49(15): 3046-3053.
	LI L, AI Y, XIE Z L, CAO Y, ZHANG Y S. Lactating dairy cows under heat stress enhanced gluconeogenesis by activating the GHIGF-I axis. Scientia Agricultura Sinica, 2016, 49(15): 3046-3053. (in Chinese)
[23]	胡丽蓉, 康玲, 王淑慧, 李玮, 鄢新义, 罗汉鹏, 董刚辉, 王新宇, 王雅春, 徐青. 冷热应激对北京地区荷斯坦牛产奶性能及血液生化指标的影响. 中国农业科学, 2018, 51(19): 3791-3799.
	HU L R, KANG L, WANG S H, LI W, YAN X Y, LUO H P, DONG G H, WANG X Y, WANG Y C, XU Q. Effects of cold and heat stress on milk production traits and blood biochemical parameters of Holstein cows in Beijing area. Scientia Agricultura Sinica, 2018, 51(19): 3791-3799. (in Chinese)
[24]	薛白, 王之盛, 李胜利, 王立志, 王祖新. 温湿度指数与奶牛生产性能的关系. 中国畜牧兽医, 2010, 37(3): 153-157.
	XUE B, WANG Z S, LI S L, WANG L Z, WANG Z X. Temperature- humidity index on performance of cows. China Animal Husbandry ＆ Veterinary Medicine, 2010, 37(3): 153-157. (in Chinese)
[25]	CARTMILL J A, EL-ZARKOUNY S Z, HENSLEY B A, ROZELL T G, SMITH J F, STEVENSON J S. An alternative AI breeding protocol for dairy cows exposed to elevated ambient temperatures before or after calving or both. Journal of Dairy Science, 2001, 84(4): 799-806. doi:10.3168/jds.S0022-0302(01)74536-5. doi: 10.3168/jds.S0022-0302(01)74536-5. pmid: 11352155
[26]	《江苏省气候变化评估报告》编写委员会. 江苏省气候变化评估报告. 北京: 气象出版社, 2017:16-18.
	COMPILATION COMMITTEE OF JIANGSU CLIMATE CHANGE ASSESSMENT REPORT. Climate change assessment report of Jiangsu Province. Beijing: Meteorological Press, 2017:16-18. (in Chinese)
[27]	董晓霞, 刘浩淼, 张超, 于海鹏, 马翀, 易晓燕, 李哲敏. 北京市气候变化对奶牛热冷应激的影响. 农业工程学报, 2013, 29(16): 198-205.
	DONG X X, LIU H M, ZHANG C, YU H P, MA C, YI X Y, LI Z M. Impact of climate change on heat and cold stress of cow breeding in Beijing. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(16): 198-205. (in Chinese)
[28]	史军, 丁一汇, 崔林丽. 华东极端高温气候特征及成因分析. 大气科学, 2009, 33(2): 347-358.
	SHI J, DING Y H, CUI L L. Climatic characteristics of extreme maximum temperature in East China and its causes. Chinese Journal of Atmospheric Sciences, 2009, 33(2): 347-358. (in Chinese)
[29]	SUN Y, ZHANG X B, ZWIERS F W, SONG L C, WAN H, HU T, YIN H, REN G Y. Rapid increase in the risk of extreme summer heat in Eastern China. Nature Climate Change, 2014, 4(12): 1082-1085. doi:10.1038/nclimate2410. doi: 10.1038/nclimate2410.
[30]	梁梅, 吴立广. 中国东部地区夏季极端高温的特征分析. 气象科学, 2015, 35(6): 701-709.
	LIANG M, WU L G. Analysis on features of summer extreme high temperature in Eastern China. Journal of the Meteorological Sciences, 2015, 35(6): 701-709. (in Chinese)
[31]	任义方, 赵艳霞, 张旭晖, 王平, 何浪. 江苏水稻高温热害气象指数保险风险综合区划. 中国农业气象, 2019, 40(6): 391-401.
	REN Y F, ZHAO Y X, ZHANG X H, WANG P, HE L. Comprehensive risk regionalization of meteorological index insurance for high temperature heat damage of rice in Jiangsu Province. Chinese Journal of Agrometeorology, 2019, 40(6): 391-401. (in Chinese)
[32]	刘佶鹏. 我国政策性奶牛保险十年发展回顾及思考. 中国奶牛, 2019(10): 61-63. doi:10.19305/j.cnki.11-3009/s.2019.10.014. doi: 10.19305/j.cnki.11-3009/s.2019.10.014.
	LIU J P. Review and Reflection on the development of policy based cow insurance in China in the past ten years. China Dairy Cattle, 2019(10): 61-63. doi:10.19305/j.cnki.11-3009/s.2019.10.014. (in Chinese) doi: 10.19305/j.cnki.11-3009/s.2019.10.014.
[33]	王丽媛, 于飞. 农业气象灾害风险分析及区划研究进展. 贵州农业科学, 2011, 39(11): 84-88.
	WANG L Y, YU F. Advances in risk analysis and zoning on agro-meteorological disasters. Guizhou Agricultural Sciences, 2011, 39(11): 84-88. (in Chinese)
[34]	张慢, 王湘阳, 易建明. 牛舍温热环境对奶牛生产和健康影响的研究进展. 家畜生态学报, 2018, 39(2): 6-11.
	ZHANG M, WANG X Y, YI J M. Research progress of barn microclimate on dairy cow production and health. Journal of Domestic Animal Ecology, 2018, 39(2): 6-11. (in Chinese)
[35]	杨志强, 刘李萍, 张峥臻, 金宜全, 周期, 刘军彪, 赵金鹏, 吴洁, 苏衍菁. 环境温度应激对奶牛的影响. 中国奶牛, 2020(7): 13-17. doi:10.19305/j.cnki.11-3009/s.2020.07.003. doi: 10.19305/j.cnki.11-3009/s.2020.07.003.
	YANG Z Q, LIU L P, ZHANG Z Z, JIN Y Q, ZHOU Q, LIU J B, ZHAO J P, WU J, SU Y J. Effects of ambient temperature stress on dairy cows. China Dairy Cattle, 2020(7): 13-17. doi:10.19305/j.cnki.11-3009/s.2020.07.003. (in Chinese) doi: 10.19305/j.cnki.11-3009/s.2020.07.003.
[36]	魏学占, 唐红艳, 杨忠霞, 蔡敬东. 气象条件对奶牛产奶量的影响及对策. 内蒙古气象, 2009(3): 23-26.
	WEI X Z, TANG H Y, YANG Z X, CAI J D. The influence of meteorological condition on milk yield of dairy cow and countermeasures. Meteorology Journal of Inner Mongolia, 2009(3): 23-26. (in Chinese)
[37]	徐明, 刘桂瑞, 王斯日古楞, 玲喜, 李珺, 李文博. 牧场不同区域和奶牛生理阶段对夏季奶牛热应激程度的影响. 中国奶牛, 2016(6): 15-18. doi:10.19305/j.cnki.11-3009/s.2016.06.002. doi: 10.19305/j.cnki.11-3009/s.2016.06.002.
	XU M, LIU G R, WANG S, LING X, LI J, LI W B. Effect of farm locations and cow stages on heat stress of dairy cows. China Dairy Cattle, 2016(6): 15-18. doi:10.19305/j.cnki.11-3009/s.2016.06.002. (in Chinese) doi: 10.19305/j.cnki.11-3009/s.2016.06.002.
[38]	杨敏, 李亚南, 田雨, 连红, 李莲. 夏季不同类型牛舍对泌乳中期奶牛热应激和生产性能的影响. 畜牧与兽医, 2021, 53(5): 37-41.
	YANG M, LI Y N, TIAN Y, LIAN H, LI L. Effects of different types of cowsheds in summer on heat stress and production performance of dairy cows in the middle lactation period. Animal Husbandry ＆ Veterinary Medicine, 2021, 53(5): 37-41. (in Chinese)
[39]	贾永全. 奶牛生产风险评价方法研究. 中国生态农业学报, 2007, 15(4): 174-176.
	JIA Y Q. Cow product evaluation methods of risk analysis. Chinese Journal of Eco-Agriculture, 2007, 15(4): 174-176. (in Chinese)

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	轻Slight	中Moderate	重Severe
热应激等级 Grade of heat stress (k)	1	2	3
温湿指数 Temperature humidity index (THI)	72≤THI≤79	79<THI≤88	THI>88

区域 Area	风险度 Risk index	温湿指数多年均值 Multi-year average value of temperature humidity index	轻度热应激发生频率 Occurrence frequency of slight heat stress	中度热应激发生频率 Occurrence frequency of moderate heat stress	开始时间 Begin time	结束时间 End time	持续时间 Duration (d)
低风险区Low risk	47.95	73.63	0.41	0.20	6月11日	9月16日	97
高风险区High risk	54.42	75.12	0.38	0.30	6月8日	9月16日	100

		低风险区Low-risk areas		高风险区High-risk areas
		气候突变前 Before climate mutation	气候突变后 After climate mutation	气候突变前 Before climate mutation	气候突变后 After climate mutation
Feq_shs第一高峰期 First peak period of Feq_shs	起止日期Start-end dates	6/16-7/19	6/6-7/17	6/8-7/13	6/6-7/16
	覆盖度Coverage (%)	25.5	29.8	24.8	27.6
	均值Average	0.62	0.63	0.52	0.56
Feq_shs第二高峰期 Second peak period of Feq_shs	起止日期Start-end dates	8/4-9/8	8/15-9/10	8/12-9/13	8/20-9/18
	覆盖度Coverage (%)	24.1	18.4	21.9	0.20
	均值Average	0.61	0.54	0.58	0.58
Feq_{_mhs}高峰期 Peak period of Feq_mhs	起止日期Start-end dates	7/23-8/3	7/18-8/13	7/14-8/10	7/10-8/19
	覆盖度Coverage (%)	5.7	16.0	72	77.3
	均值Average	0.65	0.67	0.72	0.8
THI高峰时段 Peak period of THI	起止日期Start-end dates	11:00-17:00	10:00-17:00	11:00-17:00	10:00-17:00
THI高峰时段 Peak period of THI	均值Average	76.5	77.0	77.0	77.7

Risk Zoning of Heat Stress Risk Zoning of Dairy Cows in Jiangsu Province and Its Characteristics Affected by Climate Change

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