Different Temporal Stability and Responses to Droughs between Needleleaf Forests and Broadleaf Forests in North China during 2001-2018  
[PERSON]  
1 Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China;  
1 [EMAIL_ADDRESS] (X.L.); [EMAIL_ADDRESS] (M.L.)  
[PERSON]  
1 Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province, College of Urban & Environmental Sciences, Central China Normal University, Wuhan 430079, China;  
1 [EMAIL_ADDRESS] (X.L.); [EMAIL_ADDRESS] (M.L.)  
[PERSON]  
2 Graduate Degree Program in Ecology, Department of Biology, Colorado State University, Fort Collins, CO 80523, USA; [PERSON]SS]  
[PERSON]  
3 eBeijing Normal University University, Beijing 100875, China  
3 eBeijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, College of Water Sciences,in this time lag based on forest types and tree species, but a quantitative comparison is still needed.  
Using tree-ring data is one of the most popular methods for studying forest stability [16; 17]. As a field measurement, tree-ring records can show from decades to hundreds of years of tree growth. These long records reflect multiple environmental conditions over many years. Thus, scientists have used tree-ring data to reconstruct historical climates [18]. However, in situ measurements such as tree-ring records are difficult at a regional scale. Even the world's largest public tree-ring database, the International Tree-Ring Data Bank (ITRDB) [14], lacks records in many regions, including North China. As a result, studies about forest stability against droughts at a global or hemispheric scale might lack data for forests in this region [2; 16]. As such, remote sensing data sources serve as another major tool for studying forest stability. Although remote sensing datasets do not cover as long a period as the tree-ring records, they are good compliments for decadal analyses, which can cover the whole globe [19]. Further, remote sensing-based vegetation indices have been used to quantify resilience across biomes [11], to measure leaf and canopy level activities [20], and to study the responses of forests to droughts at a regional scale [21]. The key limitation with remote sensing data is that they only record the spectral information; thus, they are generally an indirect measurement of the structural and physical characteristics of vegetation. Therefore, the vegetation characteristics reflected by different remote sensing products need to be carefully considered when using these datasets. There is still an outstanding need for research in this area to be fully developed.  
North China has experienced several severe-to-extreme drought events in the last two decades [22; 23]. To the best of our knowledge, research that has been conducted on the forests in this area includes using tree-ring data to study the effect of historical extreme droughts on forests [24], the response of the forest phenology to preseason droughts [25], and the influence of forest coverage during droughts [21]. However, ecosystem stability for different forest types and their response time lag to droughts remain unclear. Using two remote sensing-based datasets and one meteorological drought index, we tried to answer two questions: (1) was there any difference between the temporal stability of deciduous broadleaf forests and deciduous needleleaf forests in North China during 2001-2018, and (2) how long did it take the two types of forests to respond to droughts? The answers to these questions provide more information for quantifying ecosystem stability and clarifying the impact of the forest type in response to droughts. These results benefit forest modeling, management, and conservation.