1.杨凌职业技术学院, 陕西 杨凌 712100
2.西北农林科技大学 水土保持科学与;工程学院, 陕西 杨凌 712100
3.西北农林科技大学 资源环境学院, 陕西 杨凌 712100
付晨星(1992—),女(汉族),山西省太原市人,硕士,工程师,主要从事极端气候事件研究。Email:455189442@qq.com。
何晓玲(1986—),女(汉族),甘肃省张掖市人,博士,副教授,主要从事土壤侵蚀与水土保持方面的研究。Email:xiaolinghe@nwafu.edu.cn。
收稿:2024-12-09,
修回:2025-01-15,
纸质出版:2025-06-10
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付晨星, 王雪梅, 李特, 等.考虑滞后效应的气温胁迫下植被损失风险评估[J].水土保持通报,2025,45(3):179-186.
Fu Chenxing, Wang Xuemei, Li Te, et al. Vegetation loss risk assessment under temperature stress considering lag effects [J]. Bulletin of Soil and Water Conservation,2025,45(3):179-186.
付晨星, 王雪梅, 李特, 等.考虑滞后效应的气温胁迫下植被损失风险评估[J].水土保持通报,2025,45(3):179-186. DOI: 10.13961/j.cnki.stbctb.2025.03.013. CSTR: 32312.14.stbctb.2025.03.013..
Fu Chenxing, Wang Xuemei, Li Te, et al. Vegetation loss risk assessment under temperature stress considering lag effects [J]. Bulletin of Soil and Water Conservation,2025,45(3):179-186. DOI: 10.13961/j.cnki.stbctb.2025.03.013. CSTR: 32312.14.stbctb.2025.03.013..
目的
2
对考虑滞后效应的气温胁迫下植被损失风险进行评估,为制定区域适应性管理措施提供科学依据。
方法
2
以黑龙江省为例,基于周尺度归一化植被指数(NDVI)和温度数据,提出了考虑滞后效应的气温胁迫下植被损失风险评价方法。对黑龙江省不同陆地生态系统的增温和降温胁迫风险概率进行量化。
结果
2
生长季的植被与气温变化的关联密切,分别在滞后9周与23周左右达到最敏感状态,且具有较高的空间一致性。研究区的东部和西部是植被损失的高风险区域,西北和中部地区的风险较低。平均气温每升温1 ℃,风险概率增加了0.5%左右,每降温1 ℃,风险概率增加了0.70%左右。表明降温比升温对植被的影响更大。农田生态系统对气温胁迫的风险变化更显著,森林生态系统最小。
结论
2
黑龙江省东部与西部是植被损失风险的高风险区域,降温比升温对植被的影响更大,凸显了气候变化背景下综合评估滞后效应对植被健康管理的关键作用。
Objective
2
The risk of vegetation loss under temperature stress considering lag effects was assessed to provide a scientific basis for formulating regional adaptive management measures.
Methods
2
Using Heilongjiang Province as an example, a risk assessment method for vegetation loss under temperature stress considering lag effects was proposed based on weekly normalized difference vegetation index (NDVI) and temperature data. Quantifying the probability of warming and cooling stress risk in different terrestrial ecosystems in Heilongjiang Province. were quantified.
Results
2
Vegetation during the growing season is closely associated with temperature changes, reaching the most sensitive state at approximately 9 and 23 weeks of lag, respectively, and with high spatial consistency. The eastern and western regions of the study area are high-risk regions for vegetation loss, whereas the northwestern and central regions have a lower risk. For every 1 ℃ increase in the average temperature, the risk probability increased by approximately 0.5%, and for every 1 ℃ decrease, the risk increased by approximately 0.70%, indicating that cooling had a greater impact on vegetation than warming. The risk variation under temperature stress was higher in farmland ecosystems and lower in forest ecosystems.
Conclusion
2
The eastern and western regions of Heilongjiang Province are high-risk areas for vegetation loss, and cooling has a greater impact on vegetation than warming. This highlights the practical significance of comprehensively considering the lag effects of temperature stress to accurately assess vegetation health in the context of global climate change.
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