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Forests
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Carbon-Nitrogen-Phosphorus Stoichiometry in the Dynamic Forest Ecosystem
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Carbon-Nitrogen-Phosphorus Stoichiometry in the Dynamic Forest Ecosystem

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

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 6702

Special Issue Editors

Dr. Kerong Zhang

E-Mail Website
Guest Editor
Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China
Interests: vegetation restoration and plantation cultivation; plant-soil-microbial interactions; C-N-P cycling
Dr. Xiaoli Cheng

E-Mail Website
Guest Editor
School of Ecology and Environmental Science, Yunnan University, Kunming, China
Interests: ecosystem ecology; soil ecology; global change ecology and biogeochemical cycles

Special Issue Information

Dear Colleagues,

Carbon, nitrogen, and phosphorus are tightly linked to forest growth, development, and ecological functions. The C:N:P stoichiometry of plants, litter, soils, and microbes provides insights into certain physiological activities, biogeochemical processes, and ecological phenomena in forest ecosystems. Understanding the ecological stoichiometric characteristics and associated driving mechanisms in forest ecosystems is imperative for forest management in the context of global change. The purpose of this Special Issue of Forests is to summarize the latest knowledge and report new findings on the dynamic of C:N:P stoichiometry in forest ecosystems at multiscales. We especially welcome submissions that focus on C:N:P stoichiometry in forest ecosystems involving deforestation, logging, disturbances, afforestation, or restoration. The main topics include but are not limited to the following: linking ecological stoichiometry to nutrient limitation, mechanisms of C:N:P stoichiometry in various ecosystems, responses of C:N:P stoichiometry to disturbances and restoration, changes in C:N:P stoichiometry under different forest management regimes, ecological stoichiometry related to forest functions, and responses of C:N:P stoichiometry to global change. We welcome both original research and review articles in this Special Issue.

Dr. Kerong Zhang
Dr. Xiaoli Cheng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Ecological stoichiometry 
  • C:N:P stoichiometry 
  • Afforestation 
  • Forest restoration 
  • Forest function 
  • Nutrient limitation 
  • Deforestation 
  • Global change 
  • Forest management

Published Papers (3 papers)

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Research

15 pages, 3389 KiB  
Article
Carbon and Nutrient Stoichiometric Relationships in the Soil–Plant Systems of Disturbed Boreal Forest Peatlands within Athabasca Oil Sands Region, Canada
by Felix Nwaishi, Matthew Morison, Janina Plach, Merrin Macrae and Richard Petrone
Forests 2022, 13(6), 865; https://0-doi-org.brum.beds.ac.uk/10.3390/f13060865 - 31 May 2022
Cited by 1 | Viewed by 1481
Abstract
Peatlands store carbon (C), nitrogen (N), and phosphorus (P), and the stoichiometric relationship among them may be modified by ecosystem disturbances, with major implications for boreal peatland ecosystem functions. To understand the potential impact of landscape fragmentation on peatland nutrient stoichiometry, we characterize [...] Read more.
Peatlands store carbon (C), nitrogen (N), and phosphorus (P), and the stoichiometric relationship among them may be modified by ecosystem disturbances, with major implications for boreal peatland ecosystem functions. To understand the potential impact of landscape fragmentation on peatland nutrient stoichiometry, we characterize the stoichiometric ratios of C, N and P in the soil–plant systems of disturbed boreal forest peatlands and also assessed relationships among site conditions, nutrient availability, stoichiometric ratios (C:N:P) and C storage in four sites that represent the forms of disturbed peatlands in the Athabasca oil sands region. Our results showed that nutrient stoichiometric balance differed across and within these peatlands, among plants, peat, and groundwater. Ratios of C:N and C:P in peat is a function of nutrient and moisture conditions, increasing from nutrient-rich (C:N = 28; C:P = 86) to nutrient-poor fens (C:N = 82; C:P = 1061), and were lower in moist hollows relative to drier hummock microforms. In groundwater, the drier nutrient-rich fen had higher N:P ratios relative to the nutrient-poor fen, reflecting interactions between dominant hydrologic conditions and stoichiometric relationships. The N:P ratio of plants was more similar to those of peat than groundwater pools, especially in the most recently disturbed nutrient-poor fen, where plant C:N:P ratios were greater compared to older disturbed sites in the region. These findings suggest that disturbances that modify moisture and nutrient regimes could potentially upset the C:N:P stoichiometric balance of boreal forest peatlands. It also provides valuable insights and essential baseline data to inform our understanding of how peatland C:N:P stoichiometry would respond to disturbance and restoration interventions in a boreal forest region at the tipping point of environmental change. Full article
(This article belongs to the Special Issue Carbon-Nitrogen-Phosphorus Stoichiometry in the Dynamic Forest Ecosystem)
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12 pages, 1921 KiB  
Article
Differential Responses of Soil Extracellular Enzyme Activity and Stoichiometric Ratios under Different Slope Aspects and Slope Positions in Larix olgensis Plantations
by Mingwei Wang, Li Ji, Fangyuan Shen, Jun Meng, Junlu Wang, Chengfeng Shan and Lixue Yang
Forests 2022, 13(6), 845; https://0-doi-org.brum.beds.ac.uk/10.3390/f13060845 - 28 May 2022
Cited by 7 | Viewed by 2144
Abstract
Soil enzymes play an important role in nutrient biogeochemical cycling in terrestrial ecosystems. Previous studies have emphasized the variability of soil enzyme activities and stoichiometric ratios in forest ecosystems in northern China. However, much less is known about soil enzyme activity, enzymatic stoichiometry [...] Read more.
Soil enzymes play an important role in nutrient biogeochemical cycling in terrestrial ecosystems. Previous studies have emphasized the variability of soil enzyme activities and stoichiometric ratios in forest ecosystems in northern China. However, much less is known about soil enzyme activity, enzymatic stoichiometry ratios and microbial nutrient limitations in Larix olgensis plantations under different microsites. In this study, four specific extracellular enzyme activities (β-glucosidase, β-1,4-N-acetylglucosaminidase, L-leucine aminopeptidase, Acid phosphatase), and soil physicochemical properties were measured in the 0–20 cm soil layer. The results showed that slope aspect and slope position had a significant effect on soil moisture, soil bulk density, soil porosity, soil organic matter, ammonium nitrogen and nitrate-nitrogen. Meanwhile, slope aspect and slope position had a significant effect on β-glucosidase, β-1,4-N-acetylglucosaminidase, L-leucine aminopeptidase and Acid phosphatase activities while the highest activity of β-glucosidase (or β-1,4-N-acetylglucosaminidase), L-leucine aminopeptidase, and Acid phosphatase was observed in the upper slope of the east, the upper slope of the south, and the upper slope of the north; soil porosity, pH and soil organic matter were the main factors affecting soil extracellular enzyme activities. The log-transformed ratios of soil C-, N-, and P-acquiring enzyme activities were 1.00:1.06:1.17, indicating that soil microbial growth in this region was limited by N and P. Therefore, these findings highlight that N and P inputs should be considered in the management of L. olgensis plantations to improve soil microbial enzyme activity, alleviating N and P limitations. Full article
(This article belongs to the Special Issue Carbon-Nitrogen-Phosphorus Stoichiometry in the Dynamic Forest Ecosystem)
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17 pages, 4064 KiB  
Article
Modeling and Prediction of Soil Organic Matter Content Based on Visible-Near-Infrared Spectroscopy
by Chunxu Li, Jinghan Zhao, Yaoxiang Li, Yongbin Meng and Zheyu Zhang
Forests 2021, 12(12), 1809; https://0-doi-org.brum.beds.ac.uk/10.3390/f12121809 - 20 Dec 2021
Cited by 12 | Viewed by 2369
Abstract
In order to explore the ever-changing law of soil organic matter (SOM) content in the forest of the Greater Khingan Mountains, a prediction model of the SOM content with a high accuracy and stability has been developed based on visible near-infrared (VIS-NIR) technology [...] Read more.
In order to explore the ever-changing law of soil organic matter (SOM) content in the forest of the Greater Khingan Mountains, a prediction model of the SOM content with a high accuracy and stability has been developed based on visible near-infrared (VIS-NIR) technology and multiple regression analysis. A total of 105 soil samples were collected from Cuifeng forest farm in Jagdaqi City, Greater Khingan Mountains region, Heilongjiang Province, China. Five classical preprocessing algorithms, including Savitzky−Golay convolution smoothing (S-G smoothing), standard normal variate transformation (SNV), multiplicative scatter correction (MSC), first derivative, second derivative, and the combinations of the above five methods were applied to the raw spectra. Wavelengths were optimized with five methods of competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), uninformative variable elimination (UVE), synergy interval partial least square (SiPLS), and their combinations, and PLS models were developed accordingly. The results showed that when S-G smoothing is combined with SNV or MSC, both preprocessing strategies can improve the performance of the model. The prediction accuracy of SiPLS-PLS model and SiPLS-UVE-PLS model for the SOM content is higher than for other models, withan Rc2 of 0.9663 and 0.9221, RMSEC of 0.0645 and 0.0981, Rv2 of 0.9408 and 0.9270, and RMSEV of 0.0615 and 0.0683, respectively. The pretreatment strategies and characteristic variable selection methods used in this study could significantly improve the model performance and predicting efficiency. Full article
(This article belongs to the Special Issue Carbon-Nitrogen-Phosphorus Stoichiometry in the Dynamic Forest Ecosystem)
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