Tree spatial pattern and mortality prediction in burned patches of Dahurian larch (Larix gmelinii Rupr.) forest that experienced a mixed-severity wildfire
Jili Zhang A , Lifu Shu B * , Mingyu Wang B , Rui Wei A , Lizhong Wang C , Shuo Wang A * and Guang Yang D *
+ Author Affiliations
- Author Affiliations
A Research Center of Cold Temperate Forestry, Chinese Academy of Forestry, Harbin, 150086, PR China.
B Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing, 100091, PR China.
C Nenjiangyuan Forest Ecosystem Research Station, Jagedaqi, 165000, PR China.
D College of Forestry, Northeast Forestry University, Harbin, 150040, PR China.
International Journal of Wildland Fire 32(2) 262-276 https://doi.org/10.1071/WF22057
Submitted: 18 October 2021 Accepted: 27 October 2022 Published: 21 November 2022
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF.
Abstract
Background: Fire-caused tree mortality and spatial pattern are crucial for evaluating forest dynamics and developing management prescriptions.
Aims: We investigated direct fire effects on spatial distribution and mortality of Dahurian larch (Larix gmelinii Rupr.) and assessed the Ryan and Amman (R–A) model performance and the importance of immediate mortality predictors.
Methods: We analysed spatial patterns of fire-killed and surviving trees of three size classes in plots that burned at low- to high-severity using pair-correlation functions and tree mortality with the R–A model and generalised linear mixed models.
Key results: The mixed-severity fire caused strong density-dependent mortality and more aggregated surviving tree patterns at short distances. The R–A model generally performed acceptably, and crown scorch and bole char height were critical predictors determining post-fire tree mortality.
Conclusions: Fire-caused tree mortality and spatial patterns are controlled primarily by spatial variation in tree size and biological and structural characteristics. The prediction biases of the R–A model arose primarily from the intrinsic traits of Dahurian larch and the imbalanced dataset. Fine-scale neighbourhood density might be a fundamental priority for fire management and restoration.
Implications: This study could possibly improve mechanistic understanding of spatial pattern development and tree mortality in similar fire-prone conifer forests.
Keywords: crown scorch, density-dependent mortality, fire effect, fire severity, fire-prone forest, Larix gmelinii, mixed-severity fire, mortality modelling, spatial pattern, the Great Xing’an Mountains.
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