Forest Succession and Leaf Litter Decomposition

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Ecology and Management".

Deadline for manuscript submissions: closed (21 May 2023) | Viewed by 5222

Special Issue Editors


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Guest Editor
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences, Xianyang 712100, China
Interests: vegetation restoration; soil C cycling; soil nitrogen; soil microbiology; forest management
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Guest Editor
1. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China
2. Institute of Soil and Water Conservation, CAS & MWR, 26 Xilong Rd., Yangling 712100, China
Interests: forest management; litter decomposition; soil microbial community; carbon cycling; soil fertility
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Most of the world’s forests are naturally regenerated secondary forests, and forest succession is a very important ecological process for these secondary forests in the future. It is thereby vital to understand ecosystem functions and services that can be driven during forest succession. Ecosystem functioning refers to the joint effects of all processes that sustain an ecosystem, and ecosystem processes can be defined as fluxes of matter and energy over time and space. Biodiversity generally increases during forest succession, which has been thought to be one of the major drivers of ecosystem functioning. However, the underlying mechanisms are still highly debated, especially in the background of climate change. Litter decomposition is a biogeochemical process fundamental to nutrient, carbon and energy cycling within forest ecosystems, influencing tree productivity, species composition and carbon storage. Litter functional traits are proposed to provide the most direct link between biodiversity and litter decomposition, the reason for which we consider functional traits to represent biodiversity in this Special Issue: Forest Succession and Leaf Litter Decomposition. This Special Issue aims to synthesize current understanding of biotic and abiotic factors affecting litter decomposition rates and carbon fluxes, to present recent research on litter decomposition and their effects on forest carbon cycling, and to illustrate how this knowledge could be translated into forest or carbon management strategies in the context of global change.

Submitted manuscripts must be original contributions, not ones previously published or submitted to other journals. Papers published or submitted for publication in conference proceedings may be considered, provided that they are considerably extended and improved.

Dr. Lei Deng
Prof. Dr. Zhenhong Hu
Guest Editors

Manuscript Submission Information

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Keywords

  • succession
  • litter decomposition
  • biodiversity
  • carbon cycling

Published Papers (4 papers)

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Research

14 pages, 2470 KiB  
Article
Influences of Wood Decomposition Associated with Tree Types on Soil Nutrient Concentrations and Enzyme Activities
by Xiang-Yu Ji, Qian Xu, Zhu-Qi Zhao, Yu-Xiong Zheng, Lei Deng and Zhen-Hong Hu
Forests 2023, 14(9), 1846; https://doi.org/10.3390/f14091846 - 11 Sep 2023
Viewed by 993
Abstract
Wood decomposition is a biogeochemical process fundamental to element cycling in forest ecosystems, which could alter the nutrient concentrations and enzyme activities of the underlying forest soils. Wood traits, which vary by tree species, can influence decomposition aboveground, but it is not well [...] Read more.
Wood decomposition is a biogeochemical process fundamental to element cycling in forest ecosystems, which could alter the nutrient concentrations and enzyme activities of the underlying forest soils. Wood traits, which vary by tree species, can influence decomposition aboveground, but it is not well understood how wood decomposition associated with different tree types (i.e., angiosperm and gymnosperm species) influences underlying soil nutrient concentrations and enzyme activities. In this study, we evaluated how tree type (for four angiosperm vs. four gymnosperm species) affects underlying soil total carbon (C), nitrogen (N), and phosphorus (P) concentrations; microbial biomass C, N, and P concentrations; and C-, N-, and P-acquiring enzymes activities. We found that decomposing wood significantly increased soil total P, and microbial biomass C and P concentrations. However, the differences in the nutrient concentrations of soil and microbial biomass beneath decomposing wood were not different between angiosperm and gymnosperm species. Surprisingly, the activities of soil C-, N-, and P-acquiring enzymes beneath the decomposing wood differed significantly between angiosperm and gymnosperm species. The soils beneath decomposing angiosperm wood had higher P-acquiring enzyme activity, while the soils beneath gymnosperm wood had higher C- and N-acquiring enzyme activities. The soils beneath angiosperm and gymnosperm wood had a similar C-limitation for microbial metabolism, but the microbial metabolism in soils beneath angiosperm wood was more P-limited compared to soils beneath gymnosperm wood. In conclusion, our findings highlight that the tree types of decomposing wood may affect underlying soil enzyme activities and enzyme characteristics, improving our ability to accurately predict the role of wood decomposition on forest nutrient cycles. Full article
(This article belongs to the Special Issue Forest Succession and Leaf Litter Decomposition)
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18 pages, 2425 KiB  
Article
Factors Affecting Long-Term Soil Organic Carbon Storage in Greek Forests
by Petros Ganatsas, Marianthi Tsakaldimi and Lydia-Maria Petaloudi
Forests 2023, 14(8), 1518; https://doi.org/10.3390/f14081518 - 26 Jul 2023
Cited by 1 | Viewed by 1006
Abstract
The recent Glasgow Climate Pact has recognized the contribution of ecosystems as sinks and reservoirs of greenhouse gases and their importance to achieve the objective of a maximum temperature increase of 1.5 °C. Thus, the knowledge of the long-term storage capacity of the [...] Read more.
The recent Glasgow Climate Pact has recognized the contribution of ecosystems as sinks and reservoirs of greenhouse gases and their importance to achieve the objective of a maximum temperature increase of 1.5 °C. Thus, the knowledge of the long-term storage capacity of the soil organic carbon (C) in forest soils, and the driving factors, are considered of great importance for the mitigation of global climate changes. A database of published data in a ‘grey’ Greek bibliography, concerning the long-term storage of soil organic C in soil profiles for Greek forests, was compiled, including 307 full soil profiles, distributed between 21 types of forest ecosystem throughout the country (Greece). The data collected concerned the amount of long-term stored carbon in the full soil profile, per soil horizon, up to the uncracked bedrock. These also contained information on the sampling location, the type of forest ecosystem, the soil depth, the type of land management, the forest origin, the floristic zone, the altitude, and the climate type. According to the results analysis, the average soil organic C stored was 108.19 Mg ha−1, and ranged greatly between 11.49 and 409.26 Mg ha−1. The type of forest ecosystem, soil depth, land management practices, forest origin, floristic zone, and climate type played an important role in the carbon sequestration process, greatly influencing the long-term amount of stored carbon. Under the demands for mitigating climate change and reducing the rates of global warming, data evaluation indicates the directions to be followed for increasing the long-term storage of carbon, named systematic forest management, and the exclusion of the drivers responsible for the low carbon storage of soil, such as human pressure and overgrazing. Restoration actions such as reforestation and rehabilitation of the degraded forest ecosystems, which were found to store low carbon amounts, can be also considered as effective tools for increasing the long-term carbon storage in forest ecosystems. Full article
(This article belongs to the Special Issue Forest Succession and Leaf Litter Decomposition)
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19 pages, 4058 KiB  
Article
Forest Gaps Slow the Humification Process of Fir (Abies faxoniana Rehder & E.H.Wilson) Twig Litter during Eight Years of Decomposition in an Alpine Forest
by Aomiao Wu, Chengming You, Rui Yin, Zhenfeng Xu, Li Zhang, Yang Liu, Han Li, Lixia Wang, Lin Xu, Hongwei Xu, Guirong Hou, Sining Liu and Bo Tan
Forests 2023, 14(5), 868; https://doi.org/10.3390/f14050868 - 24 Apr 2023
Cited by 1 | Viewed by 1241
Abstract
Litter humification plays a crucial role in organic matter formation and soil carbon sequestration in forest ecosystems. However, how forest gap formation and gap size variation affect the litter humification process remains poorly understood. An eight-year in situ decomposition experiment was conducted to [...] Read more.
Litter humification plays a crucial role in organic matter formation and soil carbon sequestration in forest ecosystems. However, how forest gap formation and gap size variation affect the litter humification process remains poorly understood. An eight-year in situ decomposition experiment was conducted to evaluate humus accumulation (humic substances, humic and fulvic acid), humification degrees, humification ratios and optical properties (ΔlogK, E4/E6 and A600/C) of Minjiang fir (Abies faxoniana Rehder & E.H.Wilson) twig litter in four gap size treatments in an alpine primitive forest on the eastern Tibetan Plateau, including (1) closed canopies, (2) small gaps (38–46 m2 in size), (3) medium gaps (153–176 m2 in size),and (4) large gaps (255–290 m2 in size). The results indicated that the accumulation of humic substances and humic acid in the closed canopies was significantly higher than that in the large gaps during the first two years of decomposition. After eight years of decomposition, there were significant differences in the humic substance accumulations and the values of ΔlogK and A600/C among the different gap sizes. Furthermore, twig litter was humified in the first 2 years of incubation, and the net accumulation of humic substances was ranged from −23.46% to −44.04% of the initial level at the end of the experiment. The newly accumulated humus was young (mature (type Rp) humus) and transformed to mature (type A) humus after 4–6 years of decomposition. Partial least squares (PLS) suggested that gap-induced variations in twig litter chemistry (i.e., contents of cellulose, lignin, nitrogen (N) and phosphorus (P), and the ratios of C/N N/P) mainly drove the process of twig litter humification. Our results presented here denote that the formation of forest gaps retard twig litter humification process, which might be detrimental to carbon sequestration in the alpine forest ecosystems. Full article
(This article belongs to the Special Issue Forest Succession and Leaf Litter Decomposition)
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14 pages, 3250 KiB  
Article
The Classification of Log Decay Classes and an Analysis of Their Physical and Chemical Characteristics Based on Artificial Neural Networks and K-Means Clustering
by Wen Wen, Wenjun Zhang, Shirong He, Haitao Hu, Hailiang Qiao, Xiao Wang, Nan Rao and Jie Yuan
Forests 2023, 14(4), 852; https://doi.org/10.3390/f14040852 - 21 Apr 2023
Cited by 1 | Viewed by 1368
Abstract
Most existing methods for determining log decay levels normally use variations in log surface characteristics, and the results are subject to human subjectivity, which is uncertain and inaccurate. In order to investigate a novel method for the quantitative determination of log decay levels, [...] Read more.
Most existing methods for determining log decay levels normally use variations in log surface characteristics, and the results are subject to human subjectivity, which is uncertain and inaccurate. In order to investigate a novel method for the quantitative determination of log decay levels, we randomly selected log samples from four species (Pinus tabulaeformis, Larix principis-ruprechtii, Betula albosinensis and Quercus aliena var. acuteserrata) with different levels of decay and determined their basic physicochemical characteristics in the laboratory. An artificial neural network (ANN) model was used to predict the hardness values of the log samples with different levels of decay at different moisture contents. The hardness was then used as a clustering factor to quantify the decay levels of the log via K-means clustering analysis. The variations in and correlations between the basic physicochemical factors of the log specimens were investigated between the different decay classes and between the different tree species, and then ANOVA and correlation analysis were used to verify the reliability of the clustering results. The results showed that the prediction of the hardness of the decayed log by the ANN was very effective and that the highly significant variability in the dry matter content, basic density and some basic chemical element contents between the log samples that were classified into different decay grades confirmed the reliability of the clustering results. This study explores an innovative method for the quantitative determination of log decay classes. Full article
(This article belongs to the Special Issue Forest Succession and Leaf Litter Decomposition)
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