Vegetation-based bioindication of humus forms in coniferous mountain forests  

作　　者：Kerstin ANSCHLAG Dylan TATTI Niels HELLWIG Giacomo SARTORI Jean-Michel GOBAT Gabriele BROLL 

机构地区：[1]Institute of Geography,University of Osnabrueck,Seminarstrafte 19ab,49074 Osnabrueck,Germany [2]Functional Ecology Laboratory,University of Neuchatel,Rue Emile-Argand 11,2000 Neuchatel,Switzerland [3]School of Agricultural,Forest and Food Sciences HAFL,Bern University of Applied Sciences,Langgasse 85,3052 Zollikofen,Switzerland [4]MUSE,Corso del Lavoro e della Scienza 3,38122 Trento,Italy

出　　处：《Journal of Mountain Science》2017年第4期662-673,共12页山地科学学报（英文）

基　　金：funded by the German Research Foundation(DFG)(Grant No.Br1106/23-1);the Swiss National Science Foundation(SNF)(Grant No.205321L_141186);the Austrian Science Fund(FWF)

摘　　要：Humus forms, especially the occurrence and the thickness of the horizon of humified residues （OH）, provide valuable information on site conditions. In mountain forest soils, humus forms show a high spatial variability and data on their spatial patterns is often scarce. Our aim was to test the applicability of various vegetation features as proxy for OH thickness. Subalpine coniferous forests dominated by Picea abies （L.） H. Karst. and Larix decidua Mill. were studied in the Province of Trento, Italian Alps, between ca. 900 and 22o0 m a.s.1. Braun-Blanquet vegetation relevds and OH thickness were recorded at 152 plots. The vegetation parameters, tested for their suitability as indicators of OH thickness, encompassed mean Landolt indicator values of the herb layer （both unweighted and cover-weighted means） as well as parameters of vegetation structure （cover values of plant species groups） calculated from the releves. To our knowledge, the predictive power of Landolt indicator values （LIVs） for humus forms had not been tested before. Correlations between OHthickness and mean LIVs were strongest for the soil reaction value, but indicator values for humus, nutrients, temperature and light were also significantly correlated with OH thickness. Generally, weighting with species cover reduced the indicator quality of mean LIVs for OH thickness. The strongest relationships between OH thickness and vegetation structure existed in the following indicators： the cover of forbs （excluding graminoids and ferns） and the cover of Erieaeeae in the herb layer. Regression models predicting OH thickness based on vegetation structure had almost as much predictive power as models based on LIVs. We conclude that LIVs analysis can produce fairly reliable information regarding the thickness of the OH horizon and, thus, the humus form. If no releve data are readily available, a field estimation of the cover values of certain easily distinguishable herb layer species groups is much faster than a vegetation survey w

关 键 词：Landolt indicator values OH horizon Forest ecosystem Montane forest  Italian Alps 

分 类 号：S714[农业科学—林学]