Open AccessThe forest recovery path after drought dependence on forest type and stock volume
Author(s) -
Hui Luo,
Tao Zhou,
Pingrong Yu,
Chuixiang Yi,
Xia Liu,
Yajie Zhang,
Pengyu Zhou,
Jingzhou Zhang,
Yixin Xu
Publication year - 2022
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/ac57e5
Subject(s) - environmental science , stock (firearms) , forest ecology , evapotranspiration , forest management , ecosystem , agroforestry , forestry , ecology , geography , biology , archaeology
Drought legacy effects of forest ecosystems have been widely observed. However, the influence of forest type and stock volume on its recovery path is poorly understood. In this research, we first used the Standardized Precipitation Evapotranspiration Index to identify a drought event. Then, we applied the normalized difference vegetation index deficit and forest property maps derived from forest inventories to investigate the potential impacts of forest properties on forest recovery paths. The results showed that the legacy effects 1–3 years after a drought event were pervasive, but the forest recovery path was highly dependent on the forest type and forest stock volume. The recovery of forests with low stock volume densities (<60 m 3 ha −1 ) was mostly stronger than that of forests with high stock volume densities (≥60 m 3 ha −1 ) by the second year. Although all forests with different stock volume densities approximately returned to a normal status by the third year, they followed various paths to recovery. Natural coniferous forests in China that have a similar stock volume density (<60 m 3 ha −1 ) took longer to recover than planted coniferous forests and exhibited a lower magnitude of recovery. These findings highlight that drought legacy effects are greater for natural coniferous forests with high stock volume densities, which provides insightful forest management information on how to speed up forest recovery with forest density control and type control.