Effect of tree species and soil texture on the Carbon stock, macronutrient content and physicochemical properties of regenerated post‐fire forest soils

2021 ◽  
Author(s):  
Bartłomiej Woś ◽  
Agnieszka Józefowska ◽  
Justyna Likus‐Cieślik ◽  
Marcin Chodak ◽  
Marcin Pietrzykowski
Keyword(s):  
Physicochemical Properties ◽  
Forest Soils ◽  
Soil Texture ◽  
Tree Species ◽  
Carbon Stock ◽  
Macronutrient Content

scholarly journals Carbon, nitrogen, and phosphorus stoichiometry of organic matter in Swedish forest soils and its relationship with climate, tree species, and soil texture

2021 ◽  
Author(s):  
Marie Spohn ◽  
Johan Stendahl
Keyword(s):  
Organic Matter ◽  
Boreal Forest ◽  
Forest Soils ◽  
Soil Texture ◽  
Tree Species ◽  
Mineral Soil ◽  
Stand Age ◽  
Organic Layer ◽  
Mean Annual Temperature ◽  
P Concentration

Abstract. While the carbon (C) content of temperate and boreal forest soils is relatively well studied, much less is known about the ratios of C, nitrogen (N), and phosphorus (P) of the soil organic matter, and the abiotic and biotic factors that shape them. Therefore, the aim of this study was to explore carbon, nitrogen, and organic phosphorus (OP) contents and element ratios in temperate and boreal forest soils and their relationships with climate, dominant tree species, and soil texture. For this purpose, we studied 309 forest soils with a stand age >60 years located all over Sweden between 56° N and 68° N. The soils are a representative subsample of Swedish forest soils with a stand age >60 years that were sampled for the Swedish Forest Soil Inventory. We found that the N stock of the organic layer increased by a factor of 7.5 from −2 °C to 7.5 °C mean annual temperature (MAT), it increased almost twice as much as the organic layer stock along the MAT gradient. The increase in the N stock went along with an increase in the N : P ratio of the organic layer by a factor of 2.1 from −2 °C to 7.5 °C MAT (R2 = 0.36, p < 0.001). Forests dominated by pine had higher C : N ratios in the litter layer and mineral soil down to a depth of 65 cm than forests dominated by other tree species. Further, also the C : P ratio was increased in the pine-dominated forests compared to forests dominated by other tree species in the organic layer, but the C : OP ratio in the mineral soil was not elevated in pine forests. C, N and OP contents in the mineral soil were higher in fine-textured soils than in coarse-textured soils by a factor of 2.3, 3.5, and 4.6, respectively. Thus, the effect of texture was stronger on OP than on N and C, likely because OP adsorbs very rigidly to mineral surfaces. Further, we found, that the P and K concentrations of the organic layer were inversely related with the organic layer stock. The C and N concentrations of the mineral soil were best predicted by the combination of MAT, texture, and tree species, whereas the OP concentration was best predicted by the combination of MAT, texture and the P concentration of the parent material in the mineral soil. In the organic layer, the P concentration was best predicted by the organic layer stock. Taken together, the results show that the N : P ratio of the organic layer was most strongly related to MAT. Further, the C : N ratio was most strongly related to dominant tree species, even in the mineral subsoil. In contrast, the C : P ratio was only affected by dominant tree species in the organic layer, but the C : OP ratio in the mineral soil was hardly affected by tree species due to the strong effect of soil texture on the OP concentration.

scholarly journals Mapping the Urban Atmospheric Carbon Stock by LiDAR and WorldView-3 Data

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 692
Author(s):  
MD Abdul Mueed Choudhury ◽  
Ernesto Marcheggiani ◽  
Andrea Galli ◽  
Giuseppe Modica ◽  
Ben Somers
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Tree Species ◽  
Carbon Stock ◽  
Dominant Species ◽  
Remote Sensing Data ◽  
Data Sources ◽  
Lidar Data ◽  
Urban Tree ◽  
Sensing Data

Currently, the worsening impacts of urbanizations have been impelled to the importance of monitoring and management of existing urban trees, securing sustainable use of the available green spaces. Urban tree species identification and evaluation of their roles in atmospheric Carbon Stock (CS) are still among the prime concerns for city planners regarding initiating a convenient and easily adaptive urban green planning and management system. A detailed methodology on the urban tree carbon stock calibration and mapping was conducted in the urban area of Brussels, Belgium. A comparative analysis of the mapping outcomes was assessed to define the convenience and efficiency of two different remote sensing data sources, Light Detection and Ranging (LiDAR) and WorldView-3 (WV-3), in a unique urban area. The mapping results were validated against field estimated carbon stocks. At the initial stage, dominant tree species were identified and classified using the high-resolution WorldView3 image, leading to the final carbon stock mapping based on the dominant species. An object-based image analysis approach was employed to attain an overall accuracy (OA) of 71% during the classification of the dominant species. The field estimations of carbon stock for each plot were done utilizing an allometric model based on the field tree dendrometric data. Later based on the correlation among the field data and the variables (i.e., Normalized Difference Vegetation Index, NDVI and Crown Height Model, CHM) extracted from the available remote sensing data, the carbon stock mapping and validation had been done in a GIS environment. The calibrated NDVI and CHM had been used to compute possible carbon stock in either case of the WV-3 image and LiDAR data, respectively. A comparative discussion has been introduced to bring out the issues, especially for the developing countries, where WV-3 data could be a better solution over the hardly available LiDAR data. This study could assist city planners in understanding and deciding the applicability of remote sensing data sources based on their availability and the level of expediency, ensuring a sustainable urban green management system.

Atlantic Forest recovery after long-term eucalyptus plantations: The role of zoochoric and shade-tolerant tree species on carbon stock

2022 ◽  
Vol 503 ◽  
pp. 119789
Author(s):  
Alex Josélio Pires Coelho ◽  
Pedro Manuel Villa ◽  
Fabio Antônio Ribeiro Matos ◽  
Gustavo Heringer ◽  
Marcelo Leandro Bueno ◽  
...  
Keyword(s):  
Atlantic Forest ◽  
Tree Species ◽  
Carbon Stock ◽  
Forest Recovery ◽  
Eucalyptus Plantations

scholarly journals Pedogenic Threshold in Acidity Explains Context-Dependent Tree Species Effects on Soil Carbon

2021 ◽  
Vol 4 ◽  
Author(s):  
Ellen Desie ◽  
Bart Muys ◽  
Boris Jansen ◽  
Lars Vesterdal ◽  
Karen Vancampenhout
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Forest Soils ◽  
Tree Species ◽  
Litter Quality ◽  
Species Selection ◽  
Species Effects ◽  
Tree Species Effects ◽  
Soc Stocks ◽  
The Way

Despite the general agreement that maximizing carbon storage and its persistence in forest soils are top priorities in the context of climate change mitigation, our knowledge on how to steer soil organic carbon (SOC) through forest management remains limited. For some soils, tree species selection based on litter quality has been shown a powerful measure to boost SOC stocks and stability, whereas on other locations similar efforts result in insignificant or even opposite effects. A better understanding of which mechanisms underpin such context-dependency is needed in order to focus and prioritize management efforts for carbon sequestration. Here we discuss the key role of acid buffering mechanisms in belowground ecosystem functioning and how threshold behavior in soil pH mediates tree species effects on carbon cycling. For most forests around the world, the threshold between the exchange buffer and the aluminum buffer around a pH-H2O of 4.5 is of particular relevance. When a shift between these buffer domains occurs, it triggers changes in multiple compartments in the soil, ultimately altering the way carbon is incorporated and transformed. Moreover, the impact of such a shift can be amplified by feedback loops between tree species, soil biota and cation exchange capacity (CEC). Hence, taking into account non-linearities related to acidity will allow more accurate predictions on the size and direction of the effect of litter quality changes on the way soil organic carbon is stored in forest soils. Consequently, this will allow developing more efficient, context-explicit management strategies to optimize SOC stocks and their stability.

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