The normalized difference vegetation index (NDVI) and tree-ring parameters are commonly used indicators in the research on forest ecology and responses to climate change. This paper compiles and analyzes the literature on vegetation index research on the basis of tree-ring information in the past 20 years and provides an overview of the relationship between tree-ring parameters and NDVI, as well as NDVI reconstruction. The research on the vegetation index based on tree-ring data is mainly concentrated in the middle and high latitudes, and relatively few studies are concentrated in the low latitudes. The tree-ring parameters have a strong correlation with the NDVI in the summer. In terms of tree-ring reconstruction NDVI, Sabina przewalskii is the tree with the longest reconstruction sequence so far, and the tree-ring width is the main proxy index. In addition, combining tree rings with the NDVI is useful for assessing forest decline, quantifying the forest response to drought, and monitoring forest productivity. In the future, it is necessary to consider a variety of environmental factors to find the optimal model construction parameters and carry out research on the climate response of forest tree growth and the reconstruction of the historical sequence of the vegetation index at large spatial scales.

Combining tree ring data with remote sensing data can help to gain a deeper understanding of the driving factors that influence vegetation change, identify climate events that lead to vegetation change, and improve the parameters of global vegetation index reconstruction models. However, it is currently not well understood how climate change at different elevations in the central Tianshan Mountains affects radial tree growth and the dynamics of forest canopy growth. We selected Schrenk spruce (Picea schrenkiana) tree core samples from different elevations in the central Tianshan Mountains. We analyzed the relationships of various tree-ring parameters, including tree-ring width, maximum latewood density (MXD), and minimum earlywood density (MID) chronologies, with 1982–2012 GIMMS (Global Inventory Modelling and Mapping Studies) NDVI (Normalized Difference Vegetation Index), 2001–2012 MODIS (moderate resolution imaging spectroradiometer) NDVI, and meteorological data. (1) There were strong correlations between tree-ring width chronologies and the lowest temperatures, especially in July. Tree-ring width chronologies at higher altitudes were positively correlated with temperature; the opposite pattern was observed at lower altitudes. MID chronologies were positively correlated with July temperature in high-altitude areas and mean temperature and highest temperature from May to September in low-altitude areas, and negatively correlated with precipitation during this period. MXD chronologies were mainly negatively correlated with precipitation. MXD chronologies were mainly positively correlated with temperature in April and May. (2) The correlations between MXD chronologies at each sampling point and NDVI in each month of the growing season were strong. Both MID and MXD chronologies were negatively correlated with GIMMS NDVI in July. The overall correlations between tree-ring parameters and MODIS NDVI were stronger than the correlations between tree-ring parameters and GIMMS NDVI in high-altitude areas; the opposite pattern was observed in low-altitude areas. Drought stress may be the main factor affecting tree ring parameters and NDVI. In the future, we should combine tree ring parameters with vegetation index to investigate a larger scale of forests.

Vegetation growth is influenced not only by current climatic conditions but also by growth-enhancing signals and preceding climate factors. Taking the dominant species, Juniperus seravschanica Kom, in Tajikistan as the research subject, this study combines tree-ring width data with early xylem growth season data (from the start of xylem growth to the first day of the NDVI peak month), simulated using the Vaganov–Shashkin (V-S) model, a process-based tree-ring growth model. This study aims to explore the effects of vegetation growth carryover (VGC) and lagged climatic effects (LCE) on tree rings and the early xylem growth season at two different scales by integrating tree-ring width data and xylem phenology simulations. A vector autoregression (VAR) model was employed to analyze the response intensity and duration of VGC and LCE. The results show that the VGC response intensity in the early xylem growth season is higher than that of tree-ring width. The LCE duration for both the early xylem growth season and tree-ring width ranges from 0 to 11 (years or seasons), with peak LCE response intensity observed at a lag of 2–3 (years or seasons). The persistence of the climate lag effect on vegetation growth has been underestimated, supporting the use of a lag of 0–3 (years or seasons) to study the long-term impacts of climate. The influence of VGC on vegetation growth is significantly stronger than that of LCEs; ultimately indicating that J. seravschanica adapts to harsh environments by modulating its growth strategy through VGC and LCE. Investigating the VGC and LCE of multi-scale xylem growth indicators enhances our understanding of forest ecosystem dynamics.

Vegetation growth is influenced not only by current climatic conditions but also by the growth-enhancing signals and preceding climate factors. In order to explore the effects of Vegetation growth carryover (VGC) and lagged climatic effect (LCE) on tree-rings and the early growth season of xylem at two different scales. Taking the dominant species Juniperus seravschanica in Tajikistan as the research subject, this study combines tree-ring width data with early of growth season of xylem data (from the start of xylem growth to the first day of the NDVI peak month) simulated using the Vaganov-Shashkin (V-S) model, a process-based tree-ring growth model. A vector autoregression (VAR) model was employed to analyze the response intensity and duration of vegetation growth carryover effect (VGC) and lagged climatic effect (LCE) to climate. The results show that the VGC response intensity in the early of growth season of xylem phase is higher than that of tree-ring width. The LCE duration for both early of growth season of xylem and tree-ring width ranges from 0 to 11 (year or season), with peak LCE response intensity observed at lag 2–3(year or season). The persistence of climate’s lag effect on vegetation growth has been underestimated, supporting the use of lag 0–3(year or season) to study the long-term impacts of climate. The influence of VGC on vegetation growth is significantly stronger than that of LCE；Ultimately, indicating that Juniperus seravschanica adapts to harsh environments by modulating its growth strategy through VGC and LCE. Investigating the VGC and LCE of multi-scale xylem growth indicators enhances our understanding of forest ecosystem dynamics.