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Forests
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Modelling and Managing the Dynamics of Forest and Agroforest Ecosystems...
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Modelling and Managing the Dynamics of Forest and Agroforest Ecosystems Biomass and Carbon Pools

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".

Deadline for manuscript submissions: closed (20 September 2021) | Viewed by 19793

Special Issue Editor

Prof. Dr. Joana Amaral Paulo

E-Mail Website
Guest Editor
Centro de Estudos Florestais (CEF), Instituto Superior de Agronomia (ISA), Universidade de Lisboa (ISA), Tapada da Ajuda, 1349-017 Lisbon, Portugal
Interests: forest modeling; forest management; forest inventory; agroforestry; nonwood forest products; cork; cork oak; montado; statistical analysis; decision support tools
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biomass and carbon are crucial elements under the development of strategies for climate change mitigation, alternative and innovative management options, and sustainable bioeconomy. Under the forestry and agroforestry sectors, the large range of the temporal scale implies the collection of long-term data series and the development of tools that help to better understand and explain past records, as well as simulate future trends under a set of hypotheses resulting from the current cutting-edge knowledge. A diversity of tools, models, modeling procedures, and decision support tools have been developed and improved overtime in order to allow the inclusion of the temporal and spatial scales while observing biomass and carbon pools trends.

This Special Issue aims at presenting new or improved versions of resources that allow better modeling and understanding the dynamics of forest and agroforest ecosystems biomass and carbon pools, while discussing implications on forest and agroforestry areas management.

Considering the geographical scope of the Special Issue, papers focusing on different spatial levels will be accepted, ranging from the plot to the regional scales. Balance among countries and regions will also be considered as one of the objectives of this Special Issue.

Regarding the models and methodologies to be presented, they should include the interaction and relationship between several ecosystem pools are the ones aimed for in this Special Issue (e.g., aboveground and belowground; soil and tree; tree and crop).

Finally, papers discussing the management implications of their results for the ecosystems they are considering will be most appreciated.

Prof. Joana Amaral Paulo
Guest Editor

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

  • Process-based model
  • Empirical model
  • Simulator
  • Decision support tool
  • Natural forest
  • Planted forest
  • Agroforestry

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Published Papers (4 papers)

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Research

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20 pages, 5192 KiB  
Article
Prediction Comparison of Stand Parameters and Two Ecosystem Services through New Growth and Yield Model System for Mixed Nothofagus Forests in Southern Chile
by Paulo Moreno-Meynard, Sebastian Palmas and Salvador A. Gezan
Forests 2021, 12(9), 1236; https://doi.org/10.3390/f12091236 - 13 Sep 2021
Viewed by 1857
Abstract
Forest managers need tools to predict the behavior of forests not only for the main stand parameters, such as basal area and volume, but also for ecosystem services such as timber volume and carbon sequestration. Useful tools to predict these parameters are growth [...] Read more.
Forest managers need tools to predict the behavior of forests not only for the main stand parameters, such as basal area and volume, but also for ecosystem services such as timber volume and carbon sequestration. Useful tools to predict these parameters are growth and yield model systems with several possible options for modeling, such as the whole stand-level model, with or without diameter distribution generation, individual tree-level model, and compatibility models. However, those tools are scarce or developed mainly for forest plantations that are mostly located in the northern hemisphere. Thus, this study focuses on analyzing predictions of several growth and yield models built for native mixed Nothofagus forests from southern Chile, using the simulator Nothopack. A dataset of 19 permanent plots with three measurements were used for comparing the different models. Individual tree-level simulation presented the best goodness-of-fit statistics for stand parameters and ecosystem services. For example, the basal area gave an R2emp of 0.97 and 0.87 at 6 and 12 years of projection. However, the stand-level simulations with a generation of diameter distribution and both compatibility models showed satisfactory performance, both in accuracy and bias control. The simulator Nothopack, which has the capability of obtaining detailed outputs, is a useful tool to support management plans for these forest ecosystems. Full article
(This article belongs to the Special Issue Modelling and Managing the Dynamics of Forest and Agroforest Ecosystems Biomass and Carbon Pools)
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12 pages, 3704 KiB  
Article
Biomass Estimation Models for Six Shrub Species in Hunshandake Sandy Land in Inner Mongolia, Northern China
by Xueling Yao, Guojing Yang, Bo Wu, Lina Jiang and Feng Wang
Forests 2021, 12(2), 167; https://doi.org/10.3390/f12020167 - 31 Jan 2021
Cited by 17 | Viewed by 2911
Abstract
Shrub biomass estimation is valuable in assessing ecological health, soil, and water conservation capacity, and carbon storage in arid areas, where trees are scattered, and shrubs are usually dominant. Most shrub biomass estimation models are derived from trees designed for trees, yet shrubs [...] Read more.
Shrub biomass estimation is valuable in assessing ecological health, soil, and water conservation capacity, and carbon storage in arid areas, where trees are scattered, and shrubs are usually dominant. Most shrub biomass estimation models are derived from trees designed for trees, yet shrubs and trees show significant differences in morphology. However, current biomass estimation methods specifically for shrubs are still lacking. This study aimed to test various predictors’ performance in estimating shrub biomass, particularly providing an improved cone frustum volume model as a new predictor. Seven different variables, including three univariates and four composite variables, were selected as predictors in allometric models. Six dominant shrub species of different sizes and morphology in the semi-arid Hunshandake Sandy Land in Inner Mongolia were selected as samples to test the seven predictors’ performances in above-ground biomass estimation. Results showed that the single measurements performed poorly and were not suitable for shrub biomass estimation. The allometric models, including crown-related volumes as predictors, performed much better and were considered ideal for common shrub biomass estimation. The improved cone frustum volume model had more flexible geometric for shrubs of different shapes and sizes, with high fitting accuracy and stability among all the volume predictors. Therefore, we recommend the volume of an inverted cone frustum with a crown diameter and ground diameter as the long and short diameters as an excellent predictor of shrub biomass estimation, especially when studies involve various shrub species, and a general model would be needed. Full article
(This article belongs to the Special Issue Modelling and Managing the Dynamics of Forest and Agroforest Ecosystems Biomass and Carbon Pools)
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16 pages, 2101 KiB  
Article
Land-Cover and Elevation-Based Mapping of Aboveground Carbon in a Tropical Mixed-Shrub Forest Area in West Java, Indonesia
by Elham Sumarga, Nuruddin Nurudin and Ichsan Suwandhi
Forests 2020, 11(6), 636; https://doi.org/10.3390/f11060636 - 4 Jun 2020
Cited by 6 | Viewed by 2937
Abstract
Carbon sequestration and storage are among the most important ecosystem services provided by tropical forests. Improving the accuracy of the carbon mapping of tropical forests has always been a challenge, particularly in countries and regions with limited resources, with limited funding to provide [...] Read more.
Carbon sequestration and storage are among the most important ecosystem services provided by tropical forests. Improving the accuracy of the carbon mapping of tropical forests has always been a challenge, particularly in countries and regions with limited resources, with limited funding to provide high-resolution and high-quality remote sensing data. This study aimed to examine the use of land-cover and elevation-based methods of aboveground carbon mapping in a tropical forest composed of shrubs and trees. We tested a geostatistical method with an ordinary kriging interpolation using three stratification types: no stratification, stratification based on elevation, and stratification based on land-cover type, and compared it with a simple mapping technique, i.e., a lookup table based on a combination of land cover and elevation. A regression modelling with land cover and elevation as predictors was also tested in this study. The best performance was shown by geostatistical interpolation without stratification and geostatistical interpolation based on land cover, with a coefficient of variation (CV) of the root mean square error (RMSE) of 0.44, better than the performance of lookup table techniques (with a CV of the RMSE of more than 0.48). The regression modeling provided a significant model, but with a coefficient of determination (R2) of only 0.29, and a CV of the RMSE of 0.49. The use of other variables should thus be further investigated. We discuss improving aboveground carbon mapping in the study area and the implications of our results for forest management. Full article
(This article belongs to the Special Issue Modelling and Managing the Dynamics of Forest and Agroforest Ecosystems Biomass and Carbon Pools)
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Review

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20 pages, 15379 KiB  
Review
Forest Aboveground Biomass Estimation and Mapping through High-Resolution Optical Satellite Imagery—A Literature Review
by Adeel Ahmad, Hammad Gilani and Sajid Rashid Ahmad
Forests 2021, 12(7), 914; https://doi.org/10.3390/f12070914 - 14 Jul 2021
Cited by 34 | Viewed by 10499
Abstract
This paper provides a comprehensive literature review on forest aboveground biomass (AGB) estimation and mapping through high-resolution optical satellite imagery (≤5 m spatial resolution). Based on the literature review, 44 peer-reviewed journal articles were published in 15 years (2004–2019). Twenty-one studies were conducted [...] Read more.
This paper provides a comprehensive literature review on forest aboveground biomass (AGB) estimation and mapping through high-resolution optical satellite imagery (≤5 m spatial resolution). Based on the literature review, 44 peer-reviewed journal articles were published in 15 years (2004–2019). Twenty-one studies were conducted in Asia, eight in North America and Africa, five in South America, and four in Europe. This review article gives a glance at the published methodologies for AGB prediction modeling and validation. The literature review suggested that, along with the integration of other sensors, QuickBird, WorldView-2, and IKONOS satellite images were most widely used for AGB estimations, with higher estimation accuracies. All studies were grouped into six satellite-derived independent variables, including tree crown, image textures, tree shadow fraction, canopy height, vegetation indices, and multiple variables. Using these satellite-derived independent variables, most of the studies used linear regression (41%), while 30% used linear multiple regression and 18% used non-linear (machine learning) regression, while very few (11%) studies used non-linear (multiple and exponential) regression for estimating AGB. In the context of global forest AGB estimations and monitoring, the advantages, strengths, and limitations were discussed to achieve better accuracy and transparency towards the performance-based payment mechanism of the REDD+ program. Apart from technical limitations, we realized that very few studies talked about real-time monitoring of AGB or quantifying AGB change, a dimension that needs exploration. Full article
(This article belongs to the Special Issue Modelling and Managing the Dynamics of Forest and Agroforest Ecosystems Biomass and Carbon Pools)
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