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Emission of CO 2 and CH 4 From 13 Deadwood Tree Species Is Linked to Tree Species Identity and Management Intensity in Forest and Grassland Habitats
Author(s) -
Kipping Lydia,
Gossner Martin M.,
Koschorreck Matthias,
Muszynski Sarah,
Maurer Florian,
Weisser Wolfgang W.,
Jehmlich Nico,
Noll Matthias
Publication year - 2022
Publication title -
global biogeochemical cycles
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.512
H-Index - 187
eISSN - 1944-9224
pISSN - 0886-6236
DOI - 10.1029/2021gb007143
Subject(s) - environmental science , grassland , habitat , carbon dioxide , greenhouse gas , ecology , carbon fibers , biology , materials science , composite number , composite material
Abstract Deadwood is an important component of the global carbon cycle, and its decomposition releases carbon dioxide (CO 2 ) and methane (CH 4 ) into the atmosphere. However, the main drivers of these greenhouse gas emissions from deadwood are not well understood. We investigated drivers that govern the CO 2 and CH 4 emission rates of 793 deadwood specimens from 13 different tree species, which were exposed on 27 forest and 38 grassland plots at Schorfheide‐Chorin (Germany) for one year. Tree species identity was an important driver for emissions of both gases, whereas habitat type and management intensity were only important for CO 2 emission rate. CO 2 emission rates were positively linked to mass loss and were one‐third higher in forest compared to grassland habitats. The wood traits organic extractives, lignin, and sulfur content were negatively associated with CO 2 emission rates, whereas carbon, nitrogen, and magnesium content showed the opposite effect. Among climate variables, air humidity in forest and soil moisture in grassland habitats positively affected CO 2 emission rates. CH 4 emission rates showed a negative relationship with increasing wood density exposed in both habitat types but were positively related to tree species with higher sulfur contents. Taken together, CO 2 emission rates from deadwood were well predicted by wood traits, management intensity and climatic variables, whereas CH 4 emission rates were less well predictable and were influenced only by wood traits that differed from those of CO 2 emissions. Our results provide a deeper insight into the mineralization processes of deadwood and should be considered in further carbon cycle assessments.

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