Abstract
In the first section of this study, we explored the relationship between ring width index (RWI) and normalized difference vegetation index (NDVI) time series on varying timescales and spatial resolutions, hypothesizing positive associations between RWI and current and previous- year NDVI at 69 forest sites scattered in the Northern Hemisphere. We noted that the relationship between RWI and NDVI varies over space and between tree types (deciduous versus coniferous), bioclimatic zones, cumulative NDVI periods, and spatial resolutions. The high-spatial-resolution NDVI (MODIS) reflected stronger growth patterns than those with coarse-spatial-resolution NDVI (GIMMS3g). In the second section, we explore the link between RWI, climate and NDVI phenological metrics (in place of NDVI) for the same forest sites using random forest models to assess the complicated and nonlinear relationships among them. The results are as following (a) The model using high-spatial-resolution NDVI time series explained a higher proportion of the variance in RWI than that of the model using coarse-spatial-resolution NDVI time series. (b) Amongst all NDVI phenological metrics, summer NDVI sum could best explain RWI followed by the previous year’s summer NDVI sum and the previous year’s spring NDVI sum. (c) We demonstrated the potential of NDVI metrics derived from phenology to improve the existing RWI-climate relationships. However, further research is required to investigate the robustness of the relationship between NDVI and RWI, particularly when more tree-ring data and longer records of the high-spatial-resolution NDVI become available.
Highlights
Remote sensing and dendroecology are considered instrumental in monitoring net primary productivity [1,2]
normalized difference vegetation index (NDVI) sum could best explain ring width index (RWI) followed by the previous year’s summer NDVI sum and the previous year’s spring NDVI sum. (c) We demonstrated the potential of NDVI metrics derived from phenology to improve the existing RWI-climate relationships
Our results indicate a relatively better performance of the MODIS NDVI model compared to the GIMMS3g NDVI model, and this is in line with the findings of Kern et al [54]
Summary
Remote sensing and dendroecology are considered instrumental in monitoring net primary productivity [1,2]. Dendroecologists have successfully used samples of tree growth from radial increments to quantify long-term variability in forest productivity [3,4]. Tree-ring width or annual radial growth increment is a widely used proxy for tree vitality [5], and its connections to climate and extreme climatic events, such as drought, are well established [5,6]. Preparing tree-ring chronologies involves time-consuming field and laboratory work, thereby undermining the technique’s potential to be used for monitoring real-time forest growth over large spatial scales [7,8,9]. Real-time observations based on remote sensing are not feasible; at the end of the growing season, a solid assessment of the past annual growth should be possible.
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