Understanding local variation in forest biomass allows for a better evaluation of broad-scale patterns and interpretation of forest ecosystems’role in carbon dynamics.This study focuses on patterns of aboveground tre...Understanding local variation in forest biomass allows for a better evaluation of broad-scale patterns and interpretation of forest ecosystems’role in carbon dynamics.This study focuses on patterns of aboveground tree biomass within a fully censused 20 ha forest plot in a temperate forest of northern Alabama,USA.We evaluated the relationship between biomass and topography using ridge and valley landforms along with digitally derived moisture and solar radiation indices.Every live woody stem over 1 cm diameter at breast height within this plot was mapped,measured,and identified to species in 2019-2022,and diameter data were used along with speciesspecific wood density to map the aboveground biomass at the scale of 20 m×20 m quadrats.The aboveground tree biomass was 211 Mg·ha^(-1).Other than small stream areas that experienced recent natural disturbances,the total stand biomass was not associated with landform or topographic indices.Dominant species,in contrast,had strong associations with topography.American beech(Fagus grandifolia)and yellow-poplar(Liriodendron tulipfera)dominated the valley landform,with 37% and 54% greater biomass in the valley than their plot average,respectively.Three other dominant species,white oak(Quercus alba),southern shagbark hickory(Carya carolinaeseptentrionalis),and white ash(Fraxinus americana),were more abundant on slopes and benches,thus partitioning the site.Of the six dominant species,only sugar maple(Acer saccharum)was not associated with landform.Moreover,both topographic wetness and potential radiation indices were significant predictors of dominant species biomass within each of the landforms.The study highlights the need to consider species when examining forest productivity in a range of site conditions.展开更多
基金supported in part by the intramural research program of the US Department of Agriculture,National Institute of Food and Agriculture,Evans-Allen#1024525,and Capacity Building Grant#006531supported in part by the US National Science Foundation RII Track 2 FEC:Leveraging Intelligent Informatics and Smart Data for Improved Understanding of Northern Forest Ecosystem Resiliency(INSPIRES)#1920908by The Lyndhurst Foundation.
文摘Understanding local variation in forest biomass allows for a better evaluation of broad-scale patterns and interpretation of forest ecosystems’role in carbon dynamics.This study focuses on patterns of aboveground tree biomass within a fully censused 20 ha forest plot in a temperate forest of northern Alabama,USA.We evaluated the relationship between biomass and topography using ridge and valley landforms along with digitally derived moisture and solar radiation indices.Every live woody stem over 1 cm diameter at breast height within this plot was mapped,measured,and identified to species in 2019-2022,and diameter data were used along with speciesspecific wood density to map the aboveground biomass at the scale of 20 m×20 m quadrats.The aboveground tree biomass was 211 Mg·ha^(-1).Other than small stream areas that experienced recent natural disturbances,the total stand biomass was not associated with landform or topographic indices.Dominant species,in contrast,had strong associations with topography.American beech(Fagus grandifolia)and yellow-poplar(Liriodendron tulipfera)dominated the valley landform,with 37% and 54% greater biomass in the valley than their plot average,respectively.Three other dominant species,white oak(Quercus alba),southern shagbark hickory(Carya carolinaeseptentrionalis),and white ash(Fraxinus americana),were more abundant on slopes and benches,thus partitioning the site.Of the six dominant species,only sugar maple(Acer saccharum)was not associated with landform.Moreover,both topographic wetness and potential radiation indices were significant predictors of dominant species biomass within each of the landforms.The study highlights the need to consider species when examining forest productivity in a range of site conditions.
