编号 010024703
推送时间 20200713
研究领域 森林生态
年份 2020
类型 期刊
语种 英语
标题 Spatial distribution of tree species in mountain national parks depends on geomorphology and climate
来源期刊 Forest Ecology and Management
期 第247期
发表时间 20201015
关键词 Forest ecosystem; Geomorphology; SoilBiomass; ClimateSudety; Carpathians; Forest productivity; Tree species composition;
摘要 During changing climates, tree species distribution and productivity are subject of dynamic changes. However, two other factors can play a role in forest development: human impact and terrain properties. Furthermore, terrain properties can frequently modify climatic limitation of tree species growth both positively and negatively. Here, we chose to study five national parks in southern Poland. We tested the impact of climate, soil type and geomorphic indices on the occurrence and biomass of tree species using random forest models. We assumed that despite the presence of human impact, fundamental relationships between landscape properties and climate were still detectable in the selected parks. Elevation and valley depth were the most important individual predictors of tree species distribution; site-specificity was an additional important factor. In addition to the strong age-dependency of aboveground biomass (mainly for Norway spruce Picea abies (L.) Karst and European beech Fagus sylvatica L.), elevation negatively impacted the productivity of all tree species. Additionally, the topographic wetness index negatively affected the biomass of F. sylvatica, while the slope positively influenced its biomass. Using partial dependence plots, we described how geomorphic variables modify climate-dependent elevational patterns of species studied distributions and biomass. Due to protection and preservation of these sites as provided by the national park system, we could separate the effects of particular variables on tree species studied. Our results broaden understanding of the influence of geomorphological variability on species distributions under similar climatic and soil conditions. This allows for predicting sites with a higher probability of species persistence under changing climates. Therefore, our results might be used to identify sites less vulnerable to climate change, therefore important for conservation prioritization.
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