Local Forest Research Articles

Predicting corrosion current density in magnesium alloy battery anodes: machine learning approach using rapid miner

ABSTRACT Magnesium (Mg) alloys are increasingly recognised for their potential as anode materials in batteries due to their high specific capacity and cost-effectiveness. However, their susceptibility to corrosion poses a significant challenge to practical applications. This study explores the effectiveness of various machine learning models – local polynomial regression, Decision Trees, Random Forest, Gradient Boost, and Extreme Gradient Boost – in predicting the corrosion behaviour of Mg alloy battery anodes in a 3.5 wt.% NaCl electrolyte. Experimental data on the corrosion current density of Mg alloys are collected and analysed using the RapidMiner tool for model training and evaluation. The findings highlight that the Extreme Gradient Boost (XGBoost) model excels among other machine learning techniques in accurately forecasting the corrosion rates of Mg alloys. XGBoost achieves an exceptional R2 value of 0.9931 in Tafel plots, indicating a robust fit to the data as evidenced by scatter plots. Furthermore, the XGBoost model demonstrates strong positive monotonic and ordinal relationships between actual and predicted corrosion current densities, as indicated by a Spearman correlation coefficient of 1 and a Kendall tau coefficient of 0.99. These outcomes underscore XGBoost's potential as a powerful tool for enhancing the understanding and management of corrosion in Mg alloy battery applications.

Physicochemical Properties and Biochemical Profiling of Local Commercial Forest and Tualang Honeys

Physicochemical Properties and Biochemical Profiling of Local Commercial Forest and Tualang Honeys

A Spatially‐Distributed Machine Learning Approach for Fractional Snow Covered Area Estimation

AbstractSnowpack in mountainous areas often provides water storage for summer and fall, especially in the Western United States. In situ observations of snow properties in mountainous terrain are limited by cost and effort, impacting both temporal and spatial sampling, while remote sensing estimates provide more complete spacetime coverage. Spatial estimates of fractional snow covered area (fSCA) at 30m are available every 16 days from the series of multispectral scanning instruments on Landsat platforms. Daily estimates at 463m spatial resolution are also available from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite. Fusing Landsat and MODIS fSCA images creates high resolution daily spatial estimates of fSCA that are needed for various uses: to support scientists and managers interested in energy and water budgets for water resources and to understand the movement of animals in a changing climate. Here, we propose a new machine learning approach conditioned on MODIS fSCA, as well as a set of physiographic features, and fit to Landsat fSCA over a portion of the Sierra Nevada USA. The predictions are daily 30m fSCA. The approach relies on two stages of spatially‐varying models. The first classifies fSCA into three categories and the second yields estimates within (0, 100) percent fSCA. Separate models are applied and fitted within sub‐regions of the study domain. Compared with a recently‐published machine learning model (Rittger, Krock, et al., 2021), this approach uses spatially local (rather than global) random forests, and improves the classification error of fSCA by 16%, and fractionally‐covered pixel estimates by 18%.

Integrating Autoencoders with Local Outlier Factor and Isolation Forest for Effective Fraud Detection in Imbalanced Datasets

Integrating Autoencoders with Local Outlier Factor and Isolation Forest for Effective Fraud Detection in Imbalanced Datasets

Estimation of Forest Growing Stock Volume with Synthetic Aperture Radar: A Comparison of Model-Fitting Methods

Satellite-based estimation of forest variables including forest biomass relies on model-based approaches since forest biomass cannot be directly measured from space. Such models require ground reference data to adapt to the local forest structure and acquired satellite data. For wide-area mapping, such reference data are too sparse to train the biomass retrieval model and approaches for calibrating that are independent from training data are sought. In this study, we compare the performance of one such calibration approach with the traditional regression modelling using reference measurements. The performance was evaluated at four sites representative of the major forest biomes in Europe focusing on growing stock volume (GSV) prediction from time series of C-band Sentinel-1 and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS-2 PALSAR-2) backscatter measurements. The retrieval model was based on a Water Cloud Model (WCM) and integrated two forest structural functions. The WCM trained with plot inventory GSV values or calibrated with the aid of auxiliary data products correctly reproduced the trend between SAR backscatter and GSV measurements across all sites. The WCM-predicted backscatter was within the range of measurements for a given GSV level with average model residuals being smaller than the range of the observations. The accuracy of the GSV estimated with the calibrated WCM was close to the accuracy obtained with the trained WCM. The difference in terms of root mean square error (RMSE) was less than 5% units. This study demonstrates that it is possible to predict biomass without providing reference measurements for model training provided that the modelling scheme is physically based and the calibration is well set and understood.

Girrimarring wiirrilgal bulany ngayanbading (bat nest-type fur sun-like): blending traditional knowledge and western science to create roosting habitat for the threatened golden-tipped bat Phoniscus papuensis

Context Despite being widely distributed along eastern Australia, the golden-tipped bat (Phoniscus papuensis) is listed as Vulnerable in New South Wales (NSW). The 2019–2020 wildfires affected an estimated 40% of foraging and roosting habitat, causing further conservation concern. The species roosts in suspended birds’ nests located along watercourses in rainforest or wet sclerophyll forests. Habitat augmentation is a key recovery action for the species; however, effective techniques are unknown. Aims We integrated western scientific and Indigenous cultural knowledge and practice to deliver an artificial roosting structure for golden-tipped bats, and designed and implemented a collaborative model for habitat restoration, with genuine opportunity for cultural practice and two-way knowledge sharing. Methods In partnership, members of Indigenous groups, western scientific organisations and volunteers shared learnings about bats, culture and caring for Country. Weaving materials were collected from local forests, roosts were woven and hung in rainforest gullies and monitored using remote cameras and direct visual inspection. Key results Golden-tipped bats used woven roosts, suggesting that roosting-habitat augmentation could support recovery of the species. Strong partnerships were established between government conservation programs and local Indigenous communities, engaging younger generations in cultural practice and learning. Delivery models were demonstrated for further collaborative, two-way threatened species projects. Conclusions Golden-tipped bats will use woven structures for roosting. Integrating Indigenous knowledge into threatened species programs can deliver effective conservation outcomes for specialist and cryptic species. Implications Should further broadscale fire, or other impact causing loss of roosting structures occur, community, Indigenous groups or government agencies can utilise this model to implement effective conservation actions together.

Perceptions of preschoolers and parents on forest pollution

IntroductionAn examination of preschool children’s perceptions and attitudes towards the environment and forests has recently been conducted. However, little research has focused on preschool children’s and their parents’ perceptions of clean and dirty forests. Investigating these perceptions is essential to increase children’s interest in and sensitivity to the environment, thereby fostering their development as responsible individuals who protect the natural world.MethodsThis study aimed to address this knowledge gap by examining the perceptions of clean and dirty forests held by 40 5–6-year-old students and 40 parents, randomly selected from two preschools: one attended by children from high socioeconomic families and the other by children from low socioeconomic families, in a Mediterranean coastal city in southwestern Turkey. A semi-structured questionnaire was used to collect sociodemographic information and perceptions of clean and dirty forests. Additionally, drawing sheets were distributed to the students to illustrate their concepts of clean and dirty forests.ResultsThe results indicated that individuals with higher educational levels had more complex and conscious perceptions of clean forests. Children considered abstract concepts, such as supernatural forces and fossil fuels, while parents focused on awareness and conservation status. Conversely, parents and children with lower levels of education tended to concentrate on more concrete and everyday factors, such as litter and natural disasters. Individuals with higher socioeconomic status generally associated forest cleanliness with conscious behaviors and conservation, whereas those with lower socioeconomic status linked it more with polluting factors.DiscussionThis investigation provides valuable insights into the management and control of local forests by incorporating the perspectives of children and their parents, promoting responsible and sustainable tourism practices.

Modelling the Effects of Forest use Change on Brownification of Finnish Rivers under Atmospheric Pressure.

Browning of surface waters due to increased terrestrial loading of dissolved organic matter (DOM) is observed across the Northern Hemisphere. The effects influence several ecosystem services from freshwater productivity to water purification. Brownification is often explained by changes in large-scale anthropogenic pressures and ecosystem functioning (acidification, climate change, and land cover changes). This study examined the effect of forest use changes on water browning in Finland, considering the effects of global pressures. Our goal was to find the ecosystems and geographic areas that are most sensitive to environmental pressures that increase the loading of DOM. We were also looking for land use strategies that decrease browning. We combined mathematical watershed modelling to scenarios of climate change, atmospheric deposition, and forest use change. Changes included scenarios of forest harvest and protection on forest, that were derived from European Union's regulation. The study area covered 20 watersheds from south to north of Finland. In northern Finland brownification continue. In southern Finland global influence (atmospheric deposition, climate change) seem to weaken, giving more space for local forest use change having an influence on brownification. Forest use change was more influential in river basins dominated by organic soils than in mineral soils. Extending forest protection decreased brownification especially in areas where the influence of atmospheric pressure is decreasing. When forest protection is planned to provide a carbon storage and sequestration potential and to favor biodiversity, it has favorable effect on surface water quality as well.

Copper concentration in the vineyard and forest topsoils. A comparative study with individual pollution indices

The study objectives were to evaluate the soil pollution with Copper (Cu) for different land uses, namely the cultivated and abandoned vineyards, the stripped soil from the abandoned vineyard, and the topsoil under forest vegetation, using individual pollution indices. Soil samples were systematically collected from the A horizon in both cultivated and abandoned vineyards, and from the local forest, and from three soil profiles. To assess the soil quality, the Enrichment Factor (EF), Geoaccumulation Index (Igeo), and Pollution Index (PI) were calculated based on values obtained from soil sample analysis and various thresholds or guideline values. The individual pollution indices reveal the following sequence for Cu concentration: stripped soil in the abandoned vineyard > soil in the abandoned vineyard > soil in the cultivated vineyard > soil in the forest. When using Romanian or Finnish standards, the PI shows more variability than EF and Igeo indices, leading to different soil contamination classifications. Indices based on conservative elements and local geochemical background provide more stable results, especially for cultivated soils. The volume of treatments applied can explain the higher concentration of Cu in the abandoned vineyard compared to the cultivated one (ampelographic collection). The Specific Pollution Index provides a two-dimensional assessment of pollution through the difference in Cu concentration in the upper part of the soil in two ecosystems (viticulture and forestry), adjusted to the content of the same element in the local geochemical background.

Effect of Trail Condition, Slope, and Direction of Extraction on Forwarding Performance: Insights from a Controlled Comparative Study

The performance of timber harvesting equipment is important for local operational planning and for making decisions on the way in which the forests should be opened up. However, there are many options used to extract timber, and there is a high variability in their performance. Forwarding is commonly used and became an attractive option for low-access forests. A controlled experiment was set up in this study to see how the configuration of the trails, characterized in terms of slope and surface condition, and the extraction direction (uphill or downhill) may affect the performance of forwarding operations. GNSS (Global Navigation Satellite System) data were collected at a rate of 5 s for five replications of moving empty downhill and uphill, respectively, on a dirt trail, measuring 250 m in length and having a slope of about 11%. The same experiment was run with the machine loaded at full capacity, then four replications with the machine loaded and unloaded moving downhill and uphill, respectively, were performed on a forest road resembling a rocky trail, which measured 390 in length and had a slope of about 4%. GNSS data were used to extract the moving speed for all the tested conditions with the aim to compute the cycle time, and the payload volume estimate was used to estimate efficiency, and productivity, depending on extraction distance in a range of 50 to 1000 m. For the first trail, statistical comparison tests indicated significant differences in the speed of uphill and downhill movement, for both empty and loaded conditions, whereas for the second trail, there were no significant differences in speed. In addition, on the second trail, the sustained speed was almost double. These were reflected sharply in the cycle time, efficiency, and productivity, depending on extraction distance and trail condition. These findings are important for decision making on local operational planning and forest opening up.

What animals live there? Exploring the factors influencing primary school children’s awareness of native and exotic fauna

ABSTRACT Education can help combat the current biodiversity crisis, particularly in Western societies where citizens often lack knowledge about biodiversity. This study investigates the factors affecting the low awareness of native species. Primary school students (ages 6–12; n = 960) from northern Spain were shown a photograph from a local temperate forest and another from an exotic African savannah, and were asked to mention what animals they thought might live there. Listings for the exotic biome were overall longer, included more animals correctly belonging to the biome in the picture, and displayed a finer taxonomic resolution level. Children mentioned TV, internet and books as the main sources of information regarding exotic fauna, whereas the most chosen source for local fauna was their families. Both interest in nature and in animals were positively related to greater knowledge about fauna, especially from the exotic biome, which was also linked to students’ educational level. It was also found that the smaller the student’s hometown, the greater their knowledge about local fauna. The implications of the results for the education community as well as for traditional and online media are discussed, and some educational strategies, adjusted to children’s current cultural context, are proposed.

The Controversy of Social Forestry Policy: Public Reaction on the Ministry of Environment and Forestry Decree No. 287/2022/KHDPK in Java, Indonesia

Social forestry in Java, Indonesia, refers to policies and practices aimed at involving local communities in management and protection of forest areas. The study focuses on the controversy surrounding Decree No. 287/2022/KHDPK of the social forest policy which was rejected by local forest communities and public. The primary contribution of this research is to investigate the reasons behind the rejection on the Ministry of Environment and Forestry regarding Forest Areas with Special Management (KHDPK) policy, particularly the reduction in the forest area it entails. The main stakeholder involved in this controversy include Perum Perhutani, which has a vested interest in maintaining control of 2.4-million-hectare of forest land in Java. A qualitative research method was employed, using a case study approach applied for content analysis. Data were gathered from online newspapers and social media reports published between April 2022 and October 2022. The results indicates that the ongoing controversy reflects a disharmonious relationship between regulators and operators in implementing Agrarian Reform and Social Forestry policies on Java Island. The data suggest that the failure to manage the dialogue between stakeholders can create a challenging environment for the sustainability of both people and forests. Furthermore, involvement of stakeholders in the formulation and implementation of new environmental policies can foster better relationships. This study also highlights the critical role of dialogue and collaboration among regulators, operators, local communities, Non-Governmental Organizations (NGOs), and other stakeholders.

Contrasting foliar nitrogen nutrition of coexisting temperate and boreal trees across a modest temperature cline

The temperate-boreal forest ecotone represents a transition zone from temperate to boreal forest where nitrogen (N) is frequently limiting tree growth, which is highly sensitive to climate change. However, the spatial patterns and potential drivers of plant N nutrition and soil N availability remain poorly understood. To address this, we conducted a field investigation along a temperate-boreal forest ecotone in northeastern China, characterized by a modest mean annual temperature gradient (∼1°C) within the range of current climate warming. Our goal was to evaluate the spatial variation in foliar N nutrition and soil N availability, and the potential driving factors for Mongolian oak (Quercus mongolica) and Dahurian larch (Larix gmelinii), the dominant trees of the local temperate and adjacent boreal forests, respectively. Our results revealed no significant spatial trend in topsoil N availability across the sampling transect. Overall, foliar N concentration was significantly higher, but foliar δ15N was lower, for Mongolian oak than Dahurian larch. More important, foliar N concentration for Mongolian oak increased significantly toward the boreal forest, driven by lower mean annual temperatures and mean annual precipitation, with no significant trend observed for Dahurian larch. Additionally, foliar Δδ15N (foliar δ15N−soil δ15N) decreased significantly for Mongolian oak as it approached the boreal forest, while it increased significantly for Dahurian larch toward the temperate forest. Furthermore, the foliar N concentration, δ15N, and Δδ15N for Dahurian larch were all higher with an increasing basal area proportion of Mongolian oak. Our findings reveal contrasting patterns of foliar N nutrition between co-occurring temperate and boreal trees across a temperate-boreal forest ecotone which experiences a modest climatic gradient. These results underscore the importance of incorporating interspecific interactions to enhance our understanding of future N cycling in southern boreal forests in the context of climate warming.

Assessment of forest disturbance and soil erosion in wind farm project using satellite observations

The construction of wind farms, involving road construction and wind turbine installation, severely disrupts natural landscapes. Wind energy expansion in global forested areas has unclear impacts on local forests and ecosystem services. Due to a lack of information on internal road distribution and deployment dates, few studies have assessed forest disturbances caused by wind farms. Environmental issues like vegetation destruction and soil erosion may be overlooked. To address this, we integrated multi-source spaceborne observations to identify deployment dates and road distributions of forest wind farms and mapped related forest disturbances and soil erosion changes. Six global locations were tested, showing over 80 % accuracy. Disturbance intensity ranged from 1.5 to 6.5 ha/MW, with NDVI decreasing by 0.03 to 0.33 in disturbed forest regions. The average soil erosion increase per unit area due to road construction ranged from 24.74 to 274.33 t/hm−1a−1, while wind turbine construction caused an average soil erosion increase ranging from 26.52 to 26.52 to 263.46 t/hm−1a−1. Road construction is the primary cause of forest disturbance, with greater soil erosion increases in mountainous than in plain forests. This method enhances monitoring and understanding of wind farms' environmental impacts.

Assessing the Potential of Biomass Power Generation for Renewable Energy Transition in South Papua Province, Indonesia

This study aims to explore the potential for biomass-based power plant to accelerate the development of renewable energy to replace the role of fossil energy in Merauke district, South Papua Province. The method used in this study is, first, to collect data and analyze the load on the grid system and the portion of the energy mix as well as the availability of woody biomass from forest areas by making a simulation of the development of a 2 x 12 MW Biomass Power Plant. Second, by conducting experiments to obtain woodchip conversion, as the fuel of the Biomass Power Plant, from the wood log and conversion from Biomass Power Plant capacity to the required biomass plantation area. The results provide an overview of the big potency for developing biomass-based power generation by utilizing biomass from the local industrial plantation forest and show the energy transition towards energy independence. This study can be useful for policy makers and opportunities for entrepreneurs or suppliers of wood biomass, as well. For the future, in terms of fuel efficiency, it is necessary to reduce the plantation area as a source of biomass for power plants by reducing the moisture content of the woodchip to increase the calorific value and utilizing the forest residue. Furthermore, the comparison cost study between fossil power plant and biomass power plant, as well as the strategy for preserving the plantation to ensure a steady biomass supply is conducted.

Contrasting Non-Timber Forest Products’ Case Studies in Underdeveloped Areas in China

Enhancing the sustainability of the non-timber forest products industry has dual significance for both the management of local forest resources and socio-economic development. This paper adopts a systems theory perspective to construct an analytical model for the sustainable development of non-timber forest products, based on a “social-economic-natural” framework. By analyzing case studies of non-timber forest products industry sustainability from four underdeveloped counties in China, the paper derives the following main conclusions and insights: The sustainability of non-timber forest products development models is influenced by factors such as resource endowments and institutional environments and includes both single and composite models. Underdeveloped regions can achieve considerable sustainability in the development of non-timber forest products, but this requires a rational allocation of six key elements—policy, model, stakeholders, natural resources, funding, and technology—to stimulate industry growth. To promote the sustainable development of this industry, optimization should be pursued across five aspects: “policy leadership and top-level design to guide industry development”, “selection of appropriate development models based on local natural endowments and socio-economic foundations”, “large enterprise-driven mechanisms to form multi-stakeholder interest connections”, “focus on product technology research and development, and establishment of technical training mechanisms”, and “market-driven funding to develop product sales markets”.

Riparian forests shape trophic interactions in detrital stream food webs

Abstract Freshwater and terrestrial biodiversity are linked through spatial resource flows. Key examples are detrital subsidies from the riparian vegetation that form the base of food webs in small streams. Despite the central role of detritivores in these food webs, the consequences of altered riparian vegetation type and resource availability on their trophic strategies are less known. Therefore, we experimentally tested direct and indirect effects of riparian vegetation type (i.e. riparian forests present vs. absent) on trophic interactions and dietary imbalances of aquatic detritivores. To characterise trophic strategies, we used stoichiometric and isotopic differences between consumers and resources as functional measures of trophic link strength in leaf litter bags naturally colonised by stream decomposers and detritivores. Our results show that an absence of riparian forests affected stoichiometric and isotopic properties in stream detrital food webs. Where local riparian forests were absent, leaf litter showed lower C:N ratios, which only trichopteran detritivores mirrored, whereas plecopteran and crustacean detritivores showed differences in their isotopic signatures. Diverging patterns between resources and consumers could lead to a rewiring of energy flow paths and weaken the coupling between aquatic detritivores and terrestrial detritus. Consequently, our findings demonstrate that riparian forests are essential for aquatic food webs by not only influencing organisms themselves but also their trophic interactions and energy flow paths. Aquatic detritivores depending on terrestrial subsidies can be highly sensitive to local changes in their resource environment. Therefore, functionally divergent patterns between resources and consumers in recipient systems highlight how habitat properties of the donor system can affect food webs connected across ecosystem boundaries. Read the free Plain Language Summary for this article on the Journal blog.

Impacts of forest cover change on local temperature in Yangtze River Delta and Pearl River Delta urban agglomerations of China

The continuous economic and ecological construction in the Yangtze River Delta (YRD) and Pearl River Delta (PRD) has caused frequent temporal and spatial changes in local forests, thus affecting the regional climate. Yet few studies have addressed the temperature feedback through biophysical mechanisms due to forest change in two urban agglomerations of China. We compared MODIS and Landsat-based land cover data to detect a more accurate forest cover change. We then used the moving window strategy and spatiotemporal pattern change analysis method to quantify and compare the actual impact of forest cover change on temperature and the differences in driving factors (e.g., evapotranspiration (ET), albedo, and precipitation) from 2010 to 2020. The results showed that Landsat-based land cover data performed well. The conversion from forest to cropland was dominated in YRD and PRD, followed by the conversion of cropland to forest, with a small proportion of forest converting to impervious surface. The afforested areas in the two regions showed a diurnal cooling effect (-0.18 ± 0.07 °C and -0.10 ± 0.13 °C, respectively), which was greater than the air temperature. Forest converting to impervious surfaces led to stronger warming (0.39 ± 0.37 °C in YRD) than that of cropland (0.05 ± 0.03 °C in YRD and 0.07 ± 0.06 °C in PRD). The daytime LST variations can be explained by ET and inconsistent albedo effects. Seasonally, the cooling effects induced by afforestation predominated during the growing season (spring and summer), accompanied by the relatively high ET. This study shows that rational afforestation and control of deforestation are helpful to achieve sustainable forest management in urban agglomerations and to regulate climate warming.

Determinants of Dependency Between Local Communities and Forest Resources Around a Protected Area in Cameroon

Determinants of Dependency Between Local Communities and Forest Resources Around a Protected Area in Cameroon

Effectiveness of LOF, iForest and OCSVM in detecting anomalies in stream sediment geochemical data

This paper compares three unsupervised machine-learning algorithms – local outlier factor (LOF), Isolation Forest (iForest) and one-class support vector machine (OCSVM) – for anomaly detection in a multivariate geochemical dataset in northeastern Iran. This area contains several Au, Cu and Pb–Zn mineral occurrences. The methodology incorporates single-element geochemistry, multivariate data analysis and application of the three unsupervised machine-learning algorithms. Principal component analysis unveiled diverse elemental associations for the first seven principal components (PCs): PC1 shows a Co–Cr–Ni–V–Sn association indicating a lithological influence; PC2 shows a Au–Bi–Cu–W association suggesting epithermal Au mineralization; PC3 shows variability in Zn–V–Co–Sb–Cu–Cr; PC4 shows a Au–Cu–Ba–Sr–Ag association indicating Au and polymetallic mineralization; PC5 reflects Zn–Ag–Ni–Pb related to hydrothermal mineralization; and PC6 and PC7 show element associations suggesting epithermal and intrusive-related polymetallic mineralization. It was found that OCSVM performed slightly better than LOF and iForest in detecting anomalies associated with known Cu occurrences, and it successfully delineated dispersion from all known Au occurrences. LOF outperformed iForest and OCSVM in identifying all four Pb–Zn occurrences, and the three methods substantially limited the areas of the anomaly class. The analysis showed that LOF produced a less cluttered anomaly map compared to the isolated patterns in the iForest map. LOF was accurate in identifying anomalies associated with Au–Pb mineralization, while iForest detected anomalies associated with Pb–Zn–Cu occurrences and neighbouring Pb–Zn occurrence. OCSVM performed similarly in the northern and western areas but displayed unique discrepancies in the SE and west by detecting anomalies associated with two Cu occurences and a Pb–Cu occurrence. This study examined the influence of contamination fraction on detection of geochemical anomalies, revealing a noteworthy rise in the count of mineral occurrences delineated by anomalies when the contamination fraction increases from 5 to 10%. However, even with a 35% contamination fraction, some Cu occurrences remained outside the anomaly category, indicating potentially overlooked geochemical signals from mineral occurrences due to sampling schemes.