Tipping point of a conifer forest ecosystem under severe drought

• Published in: Environmental research letters Vol. 10; no. 2; pp. 24011 - 24019
• Main Authors: Huang, Kaicheng, Yi, Chuixiang, Wu, Donghai, Zhou, Tao, Zhao, Xiang, Blanford, William J, Wei, Suhua, Wu, Hao, Ling, Du, Li, Zheng
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.02.2015
• Subjects: Anomalies; Atmospheric moisture; Climatic conditions; Coniferous forests; Coniferous trees; Conifers; Drought; Evapotranspiration; Forest ecosystems; Forests; Moisture content; NDVI; Pine trees; Pinus edulis; Pinus ponderosa; Regression models; Remote sensing; RWI; Soil moisture; Soil water; SPEI; tipping point; Water deficit; USA
• ISSN: 1748-9326; 1748-9326
• DOI: 10.1088/1748-9326/10/2/024011

Drought-induced tree mortality has recently received considerable attention. Questions have arisen over the necessary intensity and duration thresholds of droughts that are sufficient to trigger rapid forest declines. The values of such tipping points leading to forest declines due to drought are presently unknown. In this study, we have evaluated the potential relationship between the level of tree growth and concurrent drought conditions with data of the tree growth-related ring width index (RWI) of the two dominant conifer species (Pinus edulis and Pinus ponderosa) in the Southwestern United States (SWUS) and the meteorological drought-related standardized precipitation evapotranspiration index (SPEI). In this effort, we determined the binned averages of RWI and the 11 month SPEI within the month of July within each bin of 30 of RWI in the range of 0-3000. We found a significant correlation between the binned averages of RWI and SPEI at the regional-scale under dryer conditions. The tipping point of forest declines to drought is predicted by the regression model as SPEItp = −1.64 and RWItp = 0, that is, persistence of the water deficit (11 month) with intensity of −1.64 leading to negligible growth for the conifer species. When climate conditions are wetter, the correlation between the binned averages of RWI and SPEI is weaker which we believe is most likely due to soil water and atmospheric moisture levels no longer being the dominant factor limiting tree growth. We also illustrate a potential application of the derived tipping point (SPEItp = −1.64) through an examination of the 2002 extreme drought event in the SWUS conifer forest regions. Distinguished differences in remote-sensing based NDVI anomalies were found between the two regions partitioned by the derived tipping point.