气候变化领域集成服务门户(CCPortal): Application of the Global Uncertainty and Sensitivity Analysis to assess the importance of deadwood characteristics for forest biodiversity

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DOI	10.1007/s00477-023-02655-2
	Application of the Global Uncertainty and Sensitivity Analysis to assess the importance of deadwood characteristics for forest biodiversity
	Mazziotta, Adriano; Kangas, Annika; Llorente, Irene De Pellegrin; Tikkanen, Olli-Pekka; Eyvindson, Kyle
发表日期	2024
ISSN	1436-3240
EISSN	1436-3259
起始页码	38
结束页码	5
卷号	38 期号:5
英文摘要	Data acquisition for sustainable forest management has focused on obtaining high quality information to estimate biomass. Improving the quality of non-timber sustainability indicators, like deadwood volume, has been a minor interest. To explore how inventory approaches could be improved, we applied a Global Uncertainty and Sensitivity Analysis (GUSA) to evaluate which factors propagate more errors in deadwood modelling and how better data collection can minimize them. The impact of uncertainty on deadwood characteristics (diameter, collapse ratio, decay class, tree species, and position) was explored under stakeholders ' preferences, management actions, and climate change scenarios. GUSA showed that removing the prediction error in deadwood tree species and diameter would alter the most the total uncertainty in deadwood volume. We found that assessment of high deadwood volume was less uncertain for the scenarios where small deadwood items were left decaying on the forest floor (BAU) and for high-end climate change scenario (RCP8.5) which resulted in lower deadwood accumulation in forest stands and therefore also in lower likelihood of erroneous estimates. Reduced uncertainty in tree species and diameter class will elevate the certainty of deadwood volume to a similar level achieved in living biomass estimation. Our uncertainty and sensitivity analysis was successful in ranking factors propagating errors in estimate of deadwood and identified a strategy to minimize uncertainty in predicting deadwood characteristics. The estimation of uncertainty in deadwood levels under the scenarios developed in our study can help decision makers to evaluate risk of decreasing deadwood value for biodiversity conservation and climate change mitigation.
英文关键词	Biodiversity; Boreal; Deadwood; Finland; Global Uncertainty and Sensitivity Analysis; Laser-scanning; Prediction errors
语种	英语
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Mathematics ; Water Resources
WOS类目	Engineering, Environmental ; Engineering, Civil ; Environmental Sciences ; Statistics & Probability ; Water Resources
WOS记录号	WOS:001148817900001
来源期刊	STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/308414
作者单位	Natural Resources Institute Finland (Luke); Natural Resources Institute Finland (Luke); Swedish University of Agricultural Sciences; University of Minnesota System; University of Minnesota Twin Cities; University of Eastern Finland; Norwegian University of Life Sciences
推荐引用方式 GB/T 7714	Mazziotta, Adriano,Kangas, Annika,Llorente, Irene De Pellegrin,et al. Application of the Global Uncertainty and Sensitivity Analysis to assess the importance of deadwood characteristics for forest biodiversity[J],2024,38(5).
APA	Mazziotta, Adriano,Kangas, Annika,Llorente, Irene De Pellegrin,Tikkanen, Olli-Pekka,&Eyvindson, Kyle.(2024).Application of the Global Uncertainty and Sensitivity Analysis to assess the importance of deadwood characteristics for forest biodiversity.STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,38(5).
MLA	Mazziotta, Adriano,et al."Application of the Global Uncertainty and Sensitivity Analysis to assess the importance of deadwood characteristics for forest biodiversity".STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 38.5(2024).