Monitoring, Assessment and Management of Forest Resource

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 (25 February 2023) | Viewed by 7676

Special Issue Editor


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Guest Editor
Department of Research and Development in Forestry and Forest Management, Embrapa Amazônia Oriental, Belém 66095-100, PA, Brazil
Interests: forest monitoring; botany applied to forest management and conservation

Special Issue Information

Dear Colleagues,

A continuous monitoring process of the forest dynamics by permanent plot inventories is the most effective strategy for managers learning and understanding their forests. This knowledge refers to the floristic structure, the dynamics of new recruitments (inputs) mortalities (outputs), and the growth of each species by periodically returning to and measuring the same plots, consequently building an understanding and knowledge about the structure, dynamics, and floristic composition of these forests. In Brazil, the implementation of sustainable forest management plans (SFMP) in parallel with the monitoring of forest dynamics is a practice recommended using permanent plots installments by the regulatory environmental agencies. However, in the great majority of SFMPs carried out by private companies and/or concessionaries contracts, this practice results only as an obligatory activity, very often being inadequately performed and generating little information of little value due to inadequate species identification, imprecise measurements, abandonment of these plots after their installation, and the first measurement data recording. Additionally, these data are not currently used in connection with available forest management practices and knowledge. The SFMP adopted, as a rule, is somewhat out of date, according to research information available, but managers can implement innovations. Nevertheless, the main focus seems to be only an adequacy to the licensing rules required by the environmental agency responsible for these forests’ production activities. Knowledge of forest botany needs to be strongly stimulated, since the inventories are based mainly from the local knowledge of the people as tree's identifiers, called "mateiros". This gap between scientific and vernacular names can generate harmful inconsistencies (< 70%) in the correct identification of species.

The rules for the SMFP in the Brazilian legislation are very strict, but in general, due to the volume restriction of the harvest (maximum of 30 m³/ha), are distributed among the species of highest commercial value. There are exceptions for situations based on results and technical published references; however, the environmental licensing agency does not have its technical staff prepared for these situations. SFMPs main's premise/assumption is the conservation of species, however, with incorrect identification, a rare species with strict rules to be harvested continues to be widely exploited, compromising its conservation and, consequently, the forest quality as a whole. As an example, Hymenolobium excelsum Ducke is a rare species, included in the list of endangered species, the exploitation of which is prohibited. When applying the vernacular identification, this species is more commonly called "angelim-pedra", and this same denomination is used for at least four other distinct species, without rules for logging restriction.

It is recommended, therefore, that continuous botanical training of these "mateiros" be conducted and a direct connection be established between their local knowledge and the forest manager/ technicians’ knowledge as a way to considerably improve the quality of the forest information. A good strategy is to implement an exsiccate collection (small herbarium), and the companies should conduct their botanical collections of the managed species and adequately prepare them with identified exsiccates for consultation when necessary. This will provide a complete list of the species identified by vernacular and translated into the correct scientific name. This practice will allow for continuous learning and knowledge appropriation by the company and their staff, and will certainly be less affected by the rotations of “mateiros” and /or the forest managers.

Prof. Dr. Ademir Roberto Ruschel
Guest Editor

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Published Papers (3 papers)

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Research

20 pages, 29400 KiB  
Article
A GIS-Based Study on the Layout of the Ecological Monitoring System of the Grain for Green Project in China
by Ke Guo, Xiang Niu and Bing Wang
Forests 2023, 14(1), 70; https://doi.org/10.3390/f14010070 - 30 Dec 2022
Cited by 3 | Viewed by 1788
Abstract
The Grain for Green Project (GGP) is an essential ecological system protection and restoration measure which can effectively improve the ecological environment. Constructing ecological monitoring system and obtaining ecological parameters can scientifically evaluate the ecological benefits of the GGP, consolidate the existing achievements, [...] Read more.
The Grain for Green Project (GGP) is an essential ecological system protection and restoration measure which can effectively improve the ecological environment. Constructing ecological monitoring system and obtaining ecological parameters can scientifically evaluate the ecological benefits of the GGP, consolidate the existing achievements, take the road of high-quality development, and promote the construction of a national ecological civilization. Firstly, an index system was constructed based on the factors driving forest ecosystem functions, involving climate (thermal and moisture conditions), vegetation types, and typical ecological zones. Then, GIS spatial analysis technology and the merging criteria index method were used to identify GGP ecological function monitoring zones. Finally, according to the scale of the project, the spatial distribution of existing stations, typical ecological zones, and the density of monitoring stations, the eco-efficiency monitoring stations, were arranged in an overall way, which constitutes the GGP ecological monitoring network. The results showed that the ecological function monitoring zones of GGP included 77 divisions, and 99 ecological monitoring stations (20 compatible level-1 stations, 31 compatible level-2 stations, 18 professional level-1 stations, and 30 professional level-2 stations) were arranged. Among them, 83 are located in national major ecosystem protection and restoration engineering areas (NMEPREA), 79 in national ecological fragile areas (NEFA), 41 in national ecological barrier areas (NEBA), and 58 in national key ecological function areas (NKEFA). The proportion of types of NMEPREA, NEFA, NEBA, and NKEFA covered by monitoring is 66.7%, 100%, 100%, and 76%, respectively. The ecological monitoring system of GGP can not only meet the monitoring needs of the GGP but also effectively monitor the effectiveness of protection and restoration of typical ecological zones. In addition, this study can provide a methodological basis for other countries or ecological projects to build a more scientific and reasonable ecological monitoring system. Full article
(This article belongs to the Special Issue Monitoring, Assessment and Management of Forest Resource)
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13 pages, 2953 KiB  
Article
Assessing the Fragmentation, Canopy Loss and Spatial Distribution of Forest Cover in Kakamega National Forest Reserve, Western Kenya
by Erick O. Osewe, Mihai Daniel Niţă and Ioan Vasile Abrudan
Forests 2022, 13(12), 2127; https://doi.org/10.3390/f13122127 - 11 Dec 2022
Cited by 5 | Viewed by 2245
Abstract
Kakamega National Forest Reserve is a tropical forest ecosystem at high risk of irreplaceable biodiversity loss due to persistent human-induced pressures. The aim of this paper is to assess the effect of fragmentation and forest cover loss on forest ecosystems in Kakamega National [...] Read more.
Kakamega National Forest Reserve is a tropical forest ecosystem at high risk of irreplaceable biodiversity loss due to persistent human-induced pressures. The aim of this paper is to assess the effect of fragmentation and forest cover loss on forest ecosystems in Kakamega National Forest Reserve, with the objectives: (1) to quantify the forest cover loss and analyse fragmentation in the Kakamega forest ecosystem and (2) to analyse the effect of forest cover loss on the spatial distribution of the Kakamega forest ecosystem at different timescales. Hansen global forest change data was used as an input training dataset on the Google Earth Engine platform (GEE) to estimate the area of forest cover loss by aggregating the sum of pixel values, and to provide a time series visualization of forest change by the extent of cover loss using Sentinel-2 and Landsat 7 false colour composites (RBG) in QGIS software. Fragmentation analysis was performed using reclassified forest loss and distribution data from the Hansen product as binary raster input in Guidos software. Total forest cover loss over 20 years was estimated at 826.60 ha. The first decade (2000–2010) accounted for 146.31 ha of forest cover loss, and the second decade (2010–2020) accounted for 680.29 ha of forest cover loss. Forest area density (FAD) analysis depicted an increase in the dominant layer by 8.5% and a 2.5% decrease in the interior layer. Morphological spatial pattern analysis (MSPA) illustrated a change in the core layer of 96% and a 14% increase in the openings class layer. Therefore, this study demonstrates that forest cover loss and landscape pattern alteration changed the dynamics of species interaction within ecological communities. Fragmented habitats adversely affected the ecosystem’s ability to recover the loss of endemic species, which are at risk of extinction in the backdrop of climate change. Anthropogenic drivers i.e., the clearing of natural forest and conversion of forest land for non-forest use, have contributed significantly to the loss of forest cover in the study area. Full article
(This article belongs to the Special Issue Monitoring, Assessment and Management of Forest Resource)
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10 pages, 4297 KiB  
Article
The Application of Sonic Tomography (PiCUS 3 Sonic Tomograph) to Detect and Quantify Hidden Wood Decay in Managed Norway Spruce Stands
by Toomas Tarmu, Andres Kiviste, Ain Näkk, Allan Sims and Diana Laarmann
Forests 2022, 13(8), 1260; https://doi.org/10.3390/f13081260 - 9 Aug 2022
Cited by 3 | Viewed by 2900
Abstract
Tree mortality plays a vital role in the accuracy of growth and yield calculations. Economic loss caused by Heterobasidion sp. and Armillaria sp. is a common issue in forestry. Estonian forests, which are mostly managed, are susceptible to fungal infection due to freshly [...] Read more.
Tree mortality plays a vital role in the accuracy of growth and yield calculations. Economic loss caused by Heterobasidion sp. and Armillaria sp. is a common issue in forestry. Estonian forests, which are mostly managed, are susceptible to fungal infection due to freshly exposed wood surfaces, such as stumps and mechanical wounds. External signs of infection are often scarce and may lead to incorrect stand vitality valuation. Modern devices, such as the PiCUS 3 Sonic Tomograph, can be used for non-destructive decay assessment. We assessed decay in two intensively managed Norway spruce (Picea abies L. Karst.) stands in order to identify the reliability of sonic tomography in tree vitality assessment. We hypothesize that the tomograph assessment is more accurate than the visual assessment for detecting the extent of decay damage in Norway spruce stems. The sample trees were first visually assessed without additional equipment. In the second phase, the same sample trees were measured with the PiCUS 3 Sonic Tomograph. In the last part of the study, the sample trees were assessed from the tree stumps following the clear-cut. We identified a relationship (p-value < 0.001) between the tomograph assessment and the stump assessment when major decay was present. We did not discover a relationship between the visual assessment and stump assessment, indicating that evaluating the decay from external signs is inaccurate according to our results. Our data also indicate that the tomograph is not able to detect the early stages of decay damage, since it has no substantial effect on the wood structure. Full article
(This article belongs to the Special Issue Monitoring, Assessment and Management of Forest Resource)
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