Forest Products Research Articles

PENDAMPINGAN KELOMPOK TANI HUTAN DAN PENGELOLAAN HUTAN DESA SECARA PARTISIPATIF DI DESA MASIHULAN KECAMATAN SERAM UTARA

The community engagement program with forest farmer groups and forest managers in Masihulan Village aimed to enhance the community's capacity to sustainably manage forest resources and strengthen the local economy through the diversification of non-timber forest products. A participatory approach was employed in this assistance process, actively involving the community in every stage of the program. The results show a significant improvement in the farmer groups' understanding of agroforestry practices and sustainable forest management. Additionally, the institutional strengthening of the forest farmer groups positively impacted their ability to access government assistance programs and financial institutions.

PENGENALAN STRUKTUR DAN SIFAT FISIK BAHAN PRODUK TANAMAN BAMBU PADA KELOMPOK TANI DESA URENG, KABUPATEN MALUKU TENGAH

Bamboo is a non-timber forest product that is abundant in tropical and subtropical regions of Asia, thriving in areas with high rainfall. In Indonesia, bamboo can be found in lowland to mountainous areas, typically growing in open spaces. In Ureng Village, bamboo has yet to significantly contribute to improving the local community’s welfare. One of the main factors limiting the optimal utilization of bamboo is the lack of knowledge regarding the physical properties and characteristics of bamboo wood, which could be processed into various economically valuable products. This activity aimed to provide education on the structure and properties of bamboo wood to enhance the economic value for the Ureng Village community. The results show that participants were highly enthusiastic about learning the properties and structure of bamboo wood, which can enable them to utilize bamboo as a substitute for timber.

Climate-smart forestry: an AI-enabled sustainable forest management solution for climate change adaptation and mitigation

AbstractClimate change is the most severe ecological challenge faced by the world today. Forests, the dominant component of terrestrial ecosystems, play a critical role in mitigating climate change due to their powerful carbon sequestration capabilities. Meanwhile, climate change has also become a major factor affecting the sustainable management of forest ecosystems. Climate-Smart Forestry (CSF) is an emerging concept in sustainable forest management. By utilizing advanced technologies, such as information technology and artificial intelligence, CSF aims to develop innovative and proactive forest management methods and decision-making systems to address the challenges of climate change. CSF aims to enhance forest ecosystem resilience (i.e., maintain a condition where, even when the state of the ecosystem changes, the ecosystem functions do not deteriorate) through climate change adaptation, improve the mitigation capabilities of forest ecosystems to climate change, maintain high, stable, and sustainable forest productivity and ecosystem services, and ultimately achieve harmonious development between humans and nature. This concept paper: (1) discusses the emergence and development of CSF, which integrates Ecological Forestry, Carbon Forestry, and Smart Forestry, and proposes the concept of CSF; (2) analyzes the goals of CSF in improving forest ecosystem stability, enhancing forest ecosystem carbon sequestration capacity, and advocating the application and development of new technologies in CSF, including artificial intelligence, robotics, Light Detection and Ranging, and forest digital twin; (3) presents the latest practices of CSF based on prior research on forest structure and function using new generation information technologies at Qingyuan Forest, China. From these practices and reflections, we suggested the development direction of CSF, including the key research topics and technological advancement.

Can indigenous peasants of Central Kalimantan live viably while conserving their forest lands?

Purpose This study aims to investigate the feasibility of a community-based non-timber forest products (NTFP) enterprise, or CBNE, within the indigenous peasant communities in Manuhing Raya, Central Kalimantan, Indonesia. This includes assessing the potential for generating featured agricultural products from the region. Design/methodology/approach This is a descriptive qualitative study that integrates ethnographic methods into the SLA analysis, to investigate the feasibility of a CBNE approach within an indigenous peasant community. A number of 13 peasant groups, which comprise 251 members, from the seven villages in Manuhing Raya participated in the study. Findings The CBNE approach, when combined with One Village One Product method, is considered appropriate for the determination of featured agricultural products in a local community. In addition, the SLA analysis in this study contributes to identifying vulnerable aspects of CBNE development in the local communities, including weaknesses in social cohesion, leadership and entrepreneurial orientation. Research limitations/implications Efforts to preserve the rainforest lands in Central Kalimantan cannot be excluded from the involvement of the local peasant communities. The best livelihood strategy in this case is to adopt a CBNE approach. This shall be made possible by empowering the peasant communities to revive their local wisdom of Upun Pambelum, which means forest lands are their primary resources for life. Practical implications This study highlights the importance of using ethnographic investigation prior to the implementation of a CBNE development. Originality/value The implementation of the CBNE approach should take into account socioeconomic aspects of the local community, especially the presence of social cohesion, leadership roles and entrepreneurial orientations. In addition, the study demonstrates the potential of integrating traditional ecological knowledge with modern business models in CBNEs.

The role of highland bamboo species (Oldeania alpina) non-timber forest products in household income and house construction in Masha district, Southern Ethiopia

The role of highland bamboo species (Oldeania alpina) non-timber forest products in household income and house construction in Masha district, Southern Ethiopia

“Can you ban the bees from the honey?”: exploring an integrated labour law and geographical indications approach for protecting the rights of forest-dwelling communities over non-timber forest produce

ABSTRACT In this article, we study the fragmented approach of two Indian statutes, namely, the Scheduled Tribes and Other Traditional Forest Dwellers (Recognition of Forest Rights) Act 2006 (“FRA 2006”) and the Geographical Indications of Goods (Registration and Protection) Act 1999 (“GIA 1999”). The article critically examines the labour law approach under the FRA 2006 and intellectual property ownership under the GIA 1999 with a specific focus on the production and commercialization of non-timber forest produce. The analysis leads to an argument for an integrated approach that starts with recognizing the agency of the communities, followed by guaranteeing protections under the labour rights approach and integrated protection through GIs. The integrated approach would facilitate cooperative experiments that go beyond strict private and public law distinctions. This can offer sustainable livelihood opportunities for forest-dwelling communities.

Performance evaluation of UKESM1 for surface ozone across the pan-tropics

Abstract. Surface ozone monitoring sites in the tropics are limited, despite the risk that surface ozone poses to human health, tropical forest and crop productivity. Atmospheric chemistry models allow us to assess ozone exposure in unmonitored locations and evaluate the potential influence of changing policies and climate on air quality, human health and ecosystem integrity. Here, we utilise in situ ozone measurements from ground-based stations in the pan-tropics to evaluate ozone from the UK Earth system model, UKESM1, with a focus on remote sites. The study includes ozone data from areas with limited previous data, notably tropical South America, central Africa and tropical northern Australia. Evaluating UKESM1 against observations beginning in 1987 onwards, we show that UKESM1 is able to capture changes in surface ozone concentration at different temporal resolutions, albeit with a systematic high bias of 18.1 nmol mol−1 on average. We use the diurnal ozone range (DOR) as a metric for evaluation and find that UKESM1 captures the observed DOR (mean bias of 2.7 nmol mol−1 and RMSE of 7.1 nmol mol−1) and the trend in DOR with location and season. Results from this study reveal that hourly ozone concentrations from UKESM1 require bias correction before use for impact assessments based on human and ecosystem health. Indeed, hourly surface ozone data have been crucial to this study, and we encourage other modelling groups to include hourly surface ozone output as a default.

Methodology For Extracting Poplar Planted Fields From Very High-Resolution Imagery Using Object-Based Image Analysis and Feature Selection Strategy

Abstract. Poplars (Populus sp.), a tree that grows rapidly species, are significant as industrial forest products. The delineation and monitoring of poplar cultivated areas are invaluable for decision-making processes. With the remote sensing technology, accurate detection of poplar planted areas could be determined much faster, more economically, and with minimum labor requirements. The objective of this research is to create a map of poplar plantations in the Sakarya region of Turkey utilizing Worldview-3 satellite imagery. Object-based image analysis (OBIA) through the application of the multi-resolution segmentation method (MRS) was employed to generate image segments, and then three prevailing machine learning algorithms, namely Support Vector Machine (SVM), Random Forest (RF) and Rotation Forest (RotFor) were implemented to produce LULC maps of the study area including 11 landscape features. The most effective and contributing object features that assure high separability between landscape features were determined using a filter-based Chi-square algorithm for the prediction models constructed with SVM, RF, and RotFor classifiers. Results revealed that the SVM classifier achieved the highest overall accuracy (91.73%) with 38 features out of 88 features, about 3% improvement compared to the other algorithms. According to the SHAP analysis, the IHS feature was the most effective one in the constructed RF model, followed by the CI (red edge), NDVI-1 and NDVI-2 vegetation indices.

Extracting above-ground biomass in areas corresponding to FAO’s definition of “Forest” using open geospatial data: Results for ASEAN

Abstract. In this study, we extracted above-ground biomass (AGB) information for forests in different ecological zones of ASEAN (Association of Southeast Asian Nations) by integrating freely-available global AGB, forest, and ecological zone map products. Our objective was to assess the suitability of the data and proposed approach for national reporting of forest carbon stocks. We compared the satellite-derived AGB values of forests in ASEAN countries with the corresponding AGB values provided by the Intergovernmental Panel for Climate Change (IPCC) in their Guidelines for National Greenhouse Gas Inventories (which are derived from ground-based measurements of forest AGB). For this, we used a map integration approach that ensures that AGB data is extracted from areas corresponding to the Food and Agricultural Association (FAO) of the UN’s definitions of “forest” and “ecological zones”, as recommended by the relevant IPCC Guidelines. We found that the average satellite-derived AGB values extracted for each ecological zone were generally lower than the values for natural forests (but higher than the values for plantation forests) provided in the IPCC Guidelines. Further investigation showed that this was partly due to the presence of many erroneously low AGB values for forests in the extracted results, caused by errors in the data masks applied to the original global AGB map, including masks of cropland, urban areas, bare soil, and water bodies. Our findings suggest that further processing is necessary before using satellite-derived data for national reporting of forest carbon stocks in ASEAN countries, and we give a few possible options for this.

Exploring the Relationship Between Time Series of Sentinel-1 Interferometric Coherence Data and Wild Edible Mushroom Yields in Mediterranean Forests

Edible wild mushrooms constitute a valuable marketable non-wood forest product with high relevance worldwide. There is growing interest in developing tools for estimation of mushroom yields and to evaluate the effects that global change may have on them. Remote sensing is a powerful technology for characterization of forest structure and condition, both essential factors in triggering mushroom production, together with meteo-climatic factors. In this work, we explore options to apply synthetic aperture radar (SAR) data from C-band Sentinel-1 to characterize, at the plot level, wild mushroom productive forests in the Mediterranean region, which provide saprotroph and ectomycorrhizal mushrooms. Seventeen permanent plots with mushroom yield data collected weekly during the productive season are characterized with dense time series of Sentinel-1 backscatter intensity (VV and VH polarizations) and 6-day interval interferometric VV coherence during the 2018–2021 period. Weekly-regularized series of SAR data are decomposed with a LOESS approach into trend, seasonality, and remainder. Trends are explored with the Theil-Sen test, and periodicity is characterized by the Discrete Fast Fourier transform. Seasonal patterns of SAR time-series are described and related to mycorrhizal and saprotroph guilds separately. Our results indicate that time series of interferometric coherence show cyclic patterns which might be related with annual mushroom yields and may constitute an indicator of triggering factors in mushroom production, whereas backscatter intensity is strongly correlated with precipitation, making noisy signals without a clear interpretable pattern. Exploring the potential of remotely sensed data for prediction and quantification of mushroom yields contributes to improve our understanding of fungal biological cycles and opens new ways to develop tools that improve its sustainable, efficient, and effective management.

A Status of Different Non Wood Forest Products in Chhattisgarh, India

A Status of Different Non Wood Forest Products in Chhattisgarh, India

Why models underestimate West African tropical forest primary productivity

Tropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical Americas. A recent field study indicated that West African forests have among the highest forests gross primary productivity (GPP) yet observed, contradicting models that rank them lower than Amazonian forests. Here, we show possible reasons for this data-model mismatch. We found that biometric GPP measurements are on average 56.3% higher than multiple global GPP products at the study sites. The underestimation of GPP largely disappears when a standard photosynthesis model is informed by local field-measured values of (a) fractional absorbed photosynthetic radiation (fAPAR), and (b) photosynthetic traits. Remote sensing products systematically underestimate fAPAR (33.9% on average at study sites) due to cloud contamination issues. The study highlights the potential widespread underestimation of tropical forests GPP and carbon cycling and hints at the ways forward for model and input data improvement.

Habitat Associated with Ramps/Wild Leeks (Allium tricoccum Ait.) in Pennsylvania, USA: Guidance for Forest Farming Site Selection

Ramps or wild leeks (Allium tricoccum) are a popular foraged non-timber forest product in North America consumed for their edible bulbs and leaves. The agroforestry practice of forest farming is a possible solution to conservation challenges surrounding the wild exploitation of this species, but it requires proper site selection to be successful. In this study, maximum entropy (Maxent) modeling using 163 occurrence points and field data collected at 30 wild populations were combined to determine the characteristics of the ramp habitat in Pennsylvania. Both Maxent modeling and field measurements highlighted moist, lower slope positions with base-rich bedrock types as suitable for ramps. Sites shared 50% of their floristic associates on average, with 252 species documented in total. Forest communities associated with ramps included many species indicative of base-rich mesic soil conditions, but the relative abundance of some indicator species differed by region. The confirmation of model variables by field measurements and forest community types points to the usefulness of these characteristics in identifying suitable forest farming sites. When used in tandem, these results can help to guide site selection for forest farming and other conservation strategies.

Resource pulses drive spatio‐temporal dynamics of non‐native bark beetles and wood borers

Abstract Clear‐fell harvesting of non‐native plantation forests in the southern hemisphere creates large amounts of woody debris that is used for breeding by non‐native bark beetles and wood borers. Limited competition and a shortage of natural enemies allow some invasive pine bark beetles and wood borers to become highly abundant and cause phytosanitary issues. Replicated transects (550–750 m long) of funnel traps baited with alpha‐pinene and ethanol spanning even‐aged Pinus radiata stands were established in New Zealand's largest plantation forest and monitored from pre‐harvest until up to 5 years post‐harvesting to test the effects of harvesting residue resource pulses on the spatio‐temporal population dynamics of Hylurgus ligniperda, Hylastes ater and Arhopalus ferus. Generalised additive mixed model analyses of trap captures of >687,000 H. ligniperda, >7600 H. ater and >5000 A. ferus individuals showed greatly elevated populations for the first 2–3 years post‐harvest. Subsequently, populations returned to very low levels once the resource pulse was exhausted. Spatial patterns of captures reflecting beetle dispersal from breeding material showed a curvilinear decline along the breeding resource gradient by up to 95% from the interior of a recently harvested stand into an adjacent, previously harvested stand with exploited resources. Synthesis and applications. The results show that forest management characterised by ongoing harvesting of neighbouring stands facilitates the build‐up of large populations of bark beetles and wood borers of phytosanitary concern. This is due to recurrent resource pulses caused by the supply of substantial amounts of breeding material from tree felling. Our findings can inform forest planning aimed at avoiding such harvesting patterns, by assisting with the development and implementation of strategies for the management of beetle populations across the landscape. Most beetles dispersed <400 m beyond the source stand edge, although some beetles are likely to have dispersed further. Keeping a distance of 1–2 km between recently felled stands and those scheduled for felling would be expected to reduce rapid population growth. This knowledge can also be used to reduce seedling attack, minimise infestation of logs, and ultimately, mitigate pathway and biosecurity risks, with important implications for forest product exports and quarantine measures.

Applications of CRISPR Technologies in Forestry and Molecular Wood Biotechnology.

Forests worldwide are under increasing pressure from climate change and emerging diseases, threatening their vital ecological and economic roles. Traditional breeding approaches, while valuable, are inherently slow and limited by the long generation times and existing genetic variation of trees. CRISPR technologies offer a transformative solution, enabling precise and efficient genome editing to accelerate the development of climate-resilient and productive forests. This review provides a comprehensive overview of CRISPR applications in forestry, exploring its potential for enhancing disease resistance, improving abiotic stress tolerance, modifying wood properties, and accelerating growth. We discuss the mechanisms and applications of various CRISPR systems, including base editing, prime editing, and multiplexing strategies. Additionally, we highlight recent advances in overcoming key challenges such as reagent delivery and plant regeneration, which are crucial for successful implementation of CRISPR in trees. We also delve into the potential and ethical considerations of using CRISPR gene drive for population-level genetic alterations, as well as the importance of genetic containment strategies for mitigating risks. This review emphasizes the need for continued research, technological advancements, extensive long-term field trials, public engagement, and responsible innovation to fully harness the power of CRISPR for shaping a sustainable future for forests.

Nature vs. nurture: Drivers of site productivity in loblolly pine (Pinus taeda L.) forests in the southeastern US

Forest productivity is one of the most important aspects of forest management, landscape planning, and climate change assessment. However, although there are multiple elements known to affect productivity, most of them rely on the “nature” of the edaphic, climatic, and geographic conditions, and only some specific aspects can be modified through forest management or “nurture”. Through evaluation of site resource availability and an understanding of the main drivers of productivity, management can present solutions to overcome site resource limitations to productivity. Therefore, understanding the implications of a specific management regime requires understanding what drives productivity across large spatial extents and among different management regimes. In this study, we used data from over 1 million hectares of industrial forestland, covering over 6000 different soils and several management regimes of Pinus taeda L. plantations, as well as plot-based data from the Forest Inventory and Analysis (FIA) program, facilitating a comparison of planted and natural Pinus taeda stands. Combined with US Geological Survey LiDAR data, we computed site index and generated wall-to-wall productivity maps for planted Pinus taeda stands in the southeastern US, as well as point-based site index estimates for the FIA dataset. We modeled site index using a random forest algorithm considering edaphic, geologic, and physiographic province information based on the Forest Productivity Cooperative “SPOT” system, and also included climate and management history data. Our model predicted site index with an R2 of 0.701 and RMSE of 1.41 m on the industrial data and R2 of 0.417 and RMSE of 1.84 m for the FIA data. We found that year of establishment of the forest, physiographic province, and geology, were the most important drivers of site index. The soil classification modifier indicating root restrictions were the most important soil-specific variable. Additionally, we found an average increase in site index of 3.05 m since the 1950s for all FIA data, and an average increase of 4.73 m for all industrial data since the 1970s. For the latest period analyzed (2000–2012), average site index in planted FIA plots was 1.2 m higher than naturally regenerated FIA plots, and site index in all industrial forestland had a site index almost 3 m greater than planted FIA plots. Overall, we believe this work sets the foundation for better understanding of forest productivity and highlights the importance of intensive silviculture to improve productivity, and as an additional tool to achieve the economic, environmental, and social objectives.

Planting density effect on poplar growth traits and soil nutrient availability, and response of microbial community, assembly and function

BackgroundThe interaction between soil characteristics and microbial communities is crucial for poplar growth under different planting densities. Yet, little is understood about their relationships and how they respond to primary environmental drivers across varying planting densities.ResultsIn this study, we investigated poplar growth metrics, soil characteristics, and community assembly of soil bacterial and fungal communities in four poplar genotypes (M1316, BT17, S86, and B331) planted at low, medium, and high densities. Our findings reveal that planting density significantly influenced poplar growth, soil nutrients, and microbial communities (P < 0.05). Lower and medium planting densities supported superior poplar growth, higher soil nutrient levels, increased microbial diversity, and more stable microbial co-occurrence networks. The assembly of bacterial communities in plantation soils was predominantly deterministic (βNTI < -2), while fungal communities showed more stochastic assembly patterns (-2 < βNTI < 2). Soil available phosphorus (AP) and potassium (AK) emerged as pivotal factors shaping microbial communities and influencing bacterial and fungal community assembly. Elevated AP levels promoted the recruitment of beneficial bacteria such as Bacillus and Streptomyces, known for their phosphate-solubilizing abilities. This facilitated positive feedback regulation of soil AP, forming beneficial loops in soils with lower and medium planting densities.ConclusionsOur study underscores the critical role of planting density in shaping soil microbial communities and their interaction with poplar growth. This research carries significant implications for enhancing forest management practices by integrating microbiological factors to bolster forest resilience and productivity.

Knowledge and attitudes about genetically advanced loblolly pine seedlings among foresters and family forest landowners in Georgia, United States

This study aims to estimate the adoption rate of genetically advanced loblolly pine (Pinus taeda) seedlings and better understand the factors influencing seedling choice among family forest landowners and consulting foresters in Georgia, a major forestry state in the Southern United States. We conducted two online surveys, one for landowners and one for registered foresters in Georgia. Our findings reveal that the adoption rate, self-reported knowledge, and positive perceptions of genetically advanced loblolly pine seedlings were high among respondents of both surveys. The adoption rate was 13.5% of all managed forestlands by foresters (29.3% for managed loblolly pine stands) and 18.0% of all the forestlands (37.4% of managed loblolly pine stands) owned by family forest landowners. Reasons for adopting among both groups included fast growth and favorable financial outcomes. However, barriers to adoption include cost, beliefs that other factors are equally or more important than the genetics of seedlings, and the need for more evidence. Furthermore, a high proportion of each group expressed an interest in adopting genetically advanced seedlings for increasing carbon revenue over time. Our findings suggest that more research about the related benefits is needed to increase the adoption of genetically advanced loblolly pine seedlings. We also found that communicating these benefits using trusted sources is also necessary. Our study will feed into the growing movement for using better genetics to improve forest productivity and reduce forest health issues in Georgia and beyond, especially on family forestlands, as they supply the majority of roundwood and other forest-based ecosystem services.

Genomic Data Support the Revision of Provenance Regions Delimitation for Scots Pine

ABSTRACTScots pine is a crucial component of ecosystems in Europe and Asia and a major utility species that comprises more than 60% of total forest production in Poland. Despite its importance, the genetic relationships between key conservation and the commercial value of Scots pine ecotypes in Poland remain unclear. To address this problem, we analyzed 27 populations (841 trees) of the most valuable Polish Scots pine ecotypes, including the oldest natural stands in all 24 regions of provenance established for the species in the country. By examining maternally inherited mitochondrial markers, nuclear microsatellite loci, and thousands of SNP markers from a genotyping array, we evaluated the genetic structure between and within them. These multilevel genomic data revealed high genetic similarity and a homogeneous structure in most populations, suggesting a common historical origin and admixture of populations after the postglacial recolonization of Central Europe. This research presents novel data on existing genomic resources among local ecotypes defined within strictly managed Polish regions of provenance, challenging their validity. Formal tests of the progeny of seed stands are needed to check whether the diversity in adaptation and quantitative traits still supports the delineation of provenance regions. In parallel, the health status of selected populations and the viability of seeds from these regions should be monitored to detect early‐stage symptoms of their environmental stress. It seems reasonable that periodic shortages of forest reproductive material (FRM) in a given region of provenance could be supplemented with the one from other regions that match their climatic envelope. Together, our results have important implications for the management of native Scots pine stands, particularly elite breeding populations, as they contribute to the discussion of the boundaries of provenance regions and the transfers of FRM that face increasing climate change.

Size and vitality characteristics of bilberry (Vaccinium myrtillus L.) populations in the Central Bohemian region of the Czech Republic: a case study of non-timber forest products

Bilberry (Vaccinium myrtillus L.) is a key non-timber forest product that plays an important role in forest biodiversity and ecosystem function. This study evaluated the vitality levels of eight bilberry populations in the Central Bohemian region of the Czech Republic, examining whether their vitality depends on the habitat type. Morphometric analyses were conducted, measuring 13 static metric and 16 static allometric morphological parameters of bilberry shoots. Statistical methods, including correlation, factor analysis, and ANOVA, were employed to determine the vitality index and population vitality structure based on the algorithm developed by Y.A. Zlobin. The results indicated that bilberry plants exhibit significant morphological variability based on forest conditions, forming plants with specific habitus traits. High positive correlations were found between many morphological characteristics, which were grouped into five clusters, each comprising 2–4 parameters. Among these, phytomass, total leaf surface area, and plant height were identified as the key determinants of vitality levels. Bilberry populations in Central Bohemian forests were classified into three vitality categories: prosperous, balanced, and depressed. The study found that the most vigorous populations, with Q-index values between 0.3333 and 0.4375, were located in associations such as Pinetum (sylvestris) vaccinio (myrtilli)-oxalidosum (acetosellae), Pinetum (sylvestris) vaccinio (myrtilli), and Pineto (sylvestris)-Piceetum (abietis) vaccinio (myrtilli)-oxalidosum (acetosellae). These populations are also of high economic value due to their bioresource potential. The study underscores the importance of habitat type in influencing bilberry vitality and offers insights into future research on bilberry populations as a vital component of non-timber forest products.