气候变化领域集成服务门户(CCPortal): Modeling ingrowth for empirical forest prediction systems

CCPortal

DOI	10.1016/j.foreco.2018.11.052
	Modeling ingrowth for empirical forest prediction systems
	Zell J.; Rohner B.; Thürig E.; Stadelmann G.
发表日期	2019
ISSN	0378-1127
起始页码	771
结束页码	779
卷号	433
英文摘要	Accurate and representative prediction of ingrowth is essential for modeling forest development. Besides the number of ingrowth trees, the basic tree attributes diameter and species are also important. In this study, these three characteristics were modeled based on data from the Swiss National Forest Inventory (NFI). The study covered large gradients of stand conditions and climate variables, making the models suitable to predict ingrowth under climate change. As the number of ingrowth trees per plot included more zeros than is expected for a Poisson distribution, we used three alternative probability distributions: zero-inflated Poisson distribution (ZIP), negative binomial distribution (NB) and zero-inflated negative binomial distribution (ZINB). Models with each of the three variants were fitted with and without random effects, resulting in six different model types. Model selection was performed backward using the BIC criterion. Of the final models, ZIP showed the best predictions of independently observed number of ingrowth trees. Our results indicate that the number of ingrowth trees strongly depended on the development stage of forests and on stand basal area, while temperature and precipitation, nitrogen deposition and water holding capacity each had a lower but still significant and plausible effect. The Weibull function was used to describe the probability distribution of the diameter of ingrowth trees and parameters were estimated using the Likelihood approach. The diameter of ingrowth trees was larger where there was a better site index and decreased with increasing stand density. Further, twelve species groups of ingrowth trees were fitted with a multinomial regression approach and showed clear dependence on climate: the probability of spruce and larch ingrowth clearly decreased with increasing temperature, whilst all other tree species profited from warmer conditions. The probability of fir, beech and ash ingrowth increased with increasing basal area, demonstrating the relevance of shade tolerance. The most important variable for predicting the species of ingrowth was the leading tree species group in a plot. © 2018 Elsevier B.V.
英文关键词	Forest scenario model; Multinomial regression; Negative binomial distribution; Poisson distribution; Recruitment modeling; Swiss national forest inventory; Weibull distribution; Zero inflation
语种	英语
scopus关键词	Climate change; Climate models; Forecasting; Poisson distribution; Random processes; Weibull distribution; Multinomials; National forest inventories; Negative binomial distribution; Recruitment models; Scenario Modeling; Zero inflation; Forestry; basal area; climate change; deciduous tree; ecological modeling; empirical analysis; environmental factor; forest ecosystem; forest inventory; growth; prediction; shade tolerance; stand structure; tree; Weibull theory; Diameter; Forecasts; Forestry; Models; Probability; Random Processes; Statistical Distribution; Trees; Abies; Fagus; Larix; Picea
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156234
作者单位	Forest Resources and Management, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Switzerland
推荐引用方式 GB/T 7714	Zell J.,Rohner B.,Thürig E.,et al. Modeling ingrowth for empirical forest prediction systems[J],2019,433.
APA	Zell J.,Rohner B.,Thürig E.,&Stadelmann G..(2019).Modeling ingrowth for empirical forest prediction systems.Forest Ecology and Management,433.
MLA	Zell J.,et al."Modeling ingrowth for empirical forest prediction systems".Forest Ecology and Management 433(2019).