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Pulp feedstock components (including extractives, lignin and holocellulose) are major products of the pulp and paper industry, and their proportion in production feedstock (e.g., wood) greatly impact pulp yield and pulp production costs. Near-infrared (NIR) spectroscopy offers a potential solution for rapid characterizing physical and chemical properties of woody biomass. However, NIR models are highly specific to the physical form and species of the samples used in the production process. Traditional calibration transfer (CT) methods usually fail to adapt NIR models to significant differences between spectra. Adversarial transfer learning (ATL) strategies, an emerging algorithm in computer imaging, align source and target distributions by introducing adversarial mechanisms. For the first time, deep ATL architecture, coupled with NIR spectroscopy (collected from ASD LabSpecPro spectrometer), was applied to quantitatively predict the pulpwood feedstock component content for adapting models of different physical forms (wood blocks, wood meals) and tree species to each other without the need for constructing a new model. It was discovered that ATL methods, including domain adversarial neural networks (DANN), domain separation networks (DSN), and dynamic adversarial adaptation networks (DAAN) not only remove the differences between wood block and wood meal spectral data sources (i.e., domains), but also make desired predictions for cross-species domain adaptation. The robustness and stability of the transferred models exceed those of traditional CT and transfer learning methods. Our results suggest that ATL models could be effectively adapted to polymorphic, multi-species pulp feedstock data, and can be extended to the detection and inversion of other feedstock properties.

Aim This study reports on the contribution of the Australian Tree Seed Centre (ATSC) to the international dissemination of Australian acacias. It also describes the current uses and the scale of economic benefits derived from planting Australian acacias, and speculates about possible future trends in usage. This information is crucial for the evaluation of overall human-mediated transfers of Australian acacias as a global experiment in biogeography. Location Australia and Global. Methods ATSC databases were used to determine which taxa were sent to which regions of the world and in what numbers. Location, scale and value of uses of the most important species were described from a review of published and grey literature, and we drew on our collective experience to speculate about future trends. Results The ATSC despatched samples of 322 taxa (or roughly a third oí Acacia species native to Australia) between 1980 and 2010 to 149 countries. Plantations in SE Asia and South Africa supplying the pulp and paper industry cover an area of over 2 M ha and produce pulp worth around $US4.3B p.a. In SE Asia, pulpwood species also provide logs for an expanding industry based on solid wood product. Tannin is produced from Acacia mearnsii in South Africa and Brazil. A suite of multi-purpose species helps meeting the demand for food, fodder, iuelwood, poles and site amelioration in dry zone regions of Africa and elsewhere and are widely incorporated into agro-forestry systems. Acacia saligna is the most widely planted non-timber species with around 600,000 ha established worldwide. Many acacia species also have horticultural uses particularly in Europe. Main conclusions The ATSC has been the major agent for systematic exploration and worldwide dissemination of Australian acacias over the past 30 years, but seed from local and regional sources of exploited species will dominate future movements. The scale of production from currently planted species will expand to meet the demands of population growth, using improved varieties. Plantations for energy and carbon sequestration might become increasingly widespread.

The links between plantation expansion and deforestation in Borneo are debated. We used satellite imagery to map annual loss of old‐growth forests, expansion of industrial plantations (oil palm and pulpwood), and their overlap in Borneo from 2001 to 2017. In 17 years, forest area declined by 14% (6.04 Mha), including 3.06 Mha of forest ultimately converted into industrial plantations. Plantations expanded by 170% (6.20 Mha: 88% oil palm; 12% pulpwood). Most forests converted to plantations were cleared and planted in the same year (92%; 2.83 Mha). Annual forest loss generally increased before peaking in 2016 (0.61 Mha) and declining sharply in 2017 (0.25 Mha). After peaks in 2009 and 2012, plantation expansion and associated forest conversion have been declining in Indonesia and Malaysia. Annual plantation expansion is positively correlated with annual forest loss in both countries. The correlation vanishes when we consider plantation expansion versus forests that are cleared but not converted to plantations. The price of crude palm oil is positively correlated with plantation expansion in the following year in Indonesian (not Malaysian) Borneo. Low palm oil prices, wet conditions, and improved fire prevention all likely contributed to reduced 2017 deforestation. Oversight of company conduct requires transparent concession ownership.

The paper focuses on the determination of fuel consumption (CO 2 emission) and exhaust emissions such as CO, HC, NO x , and PM in the process of timber extraction and transport. A complex assessment of fuel consumption and exhaust emissions was performed for the entire, fully mechanized supply chain including, tree felling, delimbing, and bucking with a harvester, timber extraction with a forwarder and transport with a truck. The performed investigations determined unit exhaust emissions (referred to 1 m 3 of timber) for the entire technological process and its individual stages. The investigations of the exhaust emissions and fuel consumption were performed under actual conditions of typical forest operations and transport. State-of-the-art portable emissions measurement system equipment was used for the measurements. The fuel consumption was determined through the carbon balance method. The investigations were performed for the process of extraction and transport of pulpwood. The measurements were performed on location in the town of Bębnikąt near Poznań, in a pinewood forest, typical of this part of Europe. The analysis includes the transport of timber to the lumberyard on a distance of 31.4 km. The total fuel consumption for the entire mechanized supply chain was 2.10 dm 3 /m 3 . The total exhaust emissions, however, amounted to: CO—8.91 g/m 3 , HC—1.19 g/m 3 , NO x —45.32 g/m 3 , PM—4.04 g/m 3 .

Worldwide many businesses have recently pledged to sourcing agricultural and timber products exclusively from deforestation and fire‐free supply chains. Geoinvestigations—monitoring the activities of plantation companies using satellites and concession maps—are now applied to identify which companies breach their commitments and regulations. We investigate the limitations of geoinvestigations by analyzing land‐use and fire in and around 163 Indonesian concessions of oil‐palm and pulpwood, where recurring forest and peatland fires are a national and international concern. We reveal a mismatch between de jure and de facto land occupancy inside and outside concessions. Independent farmers are present in concessions while some companies expand outside concessions. Thus, both actors may be responsible for deforestation and fire inside and outside concessions. On peatland, fire can start outside and spread into concessions, while draining in concessions may promote fire outside. These dynamics make attribution of fire and deforestation in Indonesian concessions impossible without detailed field investigations. This study highlights the need to combine very high‐resolution satellite data with extensive field investigations of de facto land ownership, claims and disputes inside and outside concessions. In Indonesia, such activities could fall under the One Map Policy, whose remit is to identify and resolve overlapping land claims.

The upcoming global mechanism for reducing emissions from deforestation and forest degradation in developing countries should include and prioritize tropical peatlands. Forested tropical peatlands in Southeast Asia are rapidly being converted into production systems by introducing perennial crops for lucrative agribusiness, such as oil-palm and pulpwood plantations, causing large greenhouse gas (GHG) emissions. The Intergovernmental Panel on Climate Change Guidelines for GHG Inventory on Agriculture, Forestry, and Other Land Uses provide an adequate framework for emissions inventories in these ecosystems; however, specific emission factors are needed for more accurate and cost-effective monitoring. The emissions are governed by complex biophysical processes, such as peat decomposition and compaction, nutrient availability, soil water content, and water table level, all of which are affected by management practices. We estimate that total carbon loss from converting peat swamp forests into oil palm is 59.4 ± 10.2 Mg of CO₂ per hectare per year during the first 25 y after land-use cover change, of which 61.6% arise from the peat. Of the total amount (1,486 ± 183 Mg of CO₂ per hectare over 25 y), 25% are released immediately from land-clearing fire. In order to maintain high palm-oil production, nitrogen inputs through fertilizer are needed and the magnitude of the resulting increased N₂O emissions compared to CO₂ losses remains unclear.

It is widely known that tropical peatlands, including peat swamp forests (PSFs), provide numerous ecosystem services in both spatial and temporal dimensions. These include their role as large stores for organic carbon, which when not managed well could be released as carbon dioxide and methane, accelerating climate warming. Massive destruction and conversion of peatlands occur at an alarming rate in some regions. We hope that the lessons learned from those regions currently under siege from conversion can inform other regions that are at the precipice of mass conversion to agriculture. Much has been learned about high latitude, northern hemisphere peatlands but less is known about tropical peatlands. We collate, analyze, and synthesize the evidence revealed from the set of articles in this special issue. This special issue is a step forward, presenting new information generated from a considerable amount of field data collected from peatlands across the tropics in Asia, Africa, and Latin America. The hard data collected using comparable scientific methodologies are analyzed and compared with existing published data to form a larger dataset as scientific evidence. The synthesis is then interpreted to generate new knowledge to inform the policy community on how to strategize the sustainable management of tropical peatlands. Carbon (C) stocks in tropical peatland ecosystems can be as large as 3000 Mg C ha−1, but the rate of loss is also phenomenal, causing substantial emissions of greenhouse gases of more than 20 Mg C ha−1 year−1. These losses have mainly taken place in Southeast Asia, particularly Indonesia, where peatland development for oil palm and pulpwood has accelerated over the past few decades. Although peatlands in the Amazon and Congo Basin are less developed, it is possible that the same unsustainable pathway would be followed in these regions, if lessons from the dire situation in Southeast Asia are not learned. Strong policies to halt further loss of tropical peatlands may be drawn up and combined with incentives that promote a global agenda under the United Nations Framework Convention on Climate Change 21st Conference of the Parties, Paris, France, Agreement. However, we also propose a framework to address national and local agendas that can be implemented under the nationally determined contributions (NDCs) by balancing conversion/development and conservation/restoration objectives.

The application of near-infrared spectroscopy (NIR) technology in analyzing the compositional content of wood from pulping raw materials suffers from the problem that the multivariate correction model cannot be shared among different NIR spectrometers. To address this problem, NIR spectra of 84 samples of common pulpwood species ( Cunninghamia lanceolata , Eucalyptus robusta Smith , Acacia , Pinus massoniana , Populus L) are analyzed by traditional laboratory methods for the content of their main components (holocellulose and lignin content). Screening wavelengths based on spectrum ratio analysis (SWSRA) combined with UVE algorithm is used to screen stable characteristic bands, clarify the characteristic absorption of holocellulose and lignin, and optimize the model transfer results. The results are compared with those of SWSRA, CARS, piecewise direct correction algorithm (PDS) and slope intercept algorithm ( S / B ). The results show that for holocellulose, the 653 wavelengths screened by the SWSRA-UVE method contain a large amount of overtone and group frequency absorption information of C–H and O–H of holocellulose. For lignin, the 639 wavelengths screened by the SWSRA-UVE method contain a large amount of overtone and group frequency absorption information of lignin C–H and C=O. The SWSRA-UVE algorithm is optimal in improving the transfer effect of the models. This method can effectively remove the unimportant wavelengths in the SWSRA method and significantly improve the transfer accuracy and efficiency of the master models. This study contributes to the promotion of near-infrared spectroscopy in the rapid analysis and determination of the main components of pulping raw wood.

Tropical peatlands in Southeast Asia have experienced widespread subsidence due to forest clearance and drainage for agriculture, oil palm and pulp wood production, causing concerns about their function as a long-term carbon store. Peatland drainage leads to subsidence (lowering of peatland surface), an indicator of degraded peatlands, while stability/uplift indicates peatland accumulation and ecosystem health. We used the Advanced Pixel System using the Intermittent SBAS (ASPIS-DInSAR) technique with biophysical and geographical data to investigate the impact of peatland drainage and agriculture on spatial patterns of subsidence in Selangor, Malaysia. Results showed pronounced subsidence in areas subjected to drainage for agricultural and oil palm plantations, while stable areas were associated with intact forests. The most powerful predictors of subsidence rates were the distance from the drainage canal or peat boundary; however, other drivers such as soil properties and water table levels were also important. The maximum subsidence rate detected was lower than that documented by ground-based methods. Therefore, whilst the APSIS-DInSAR technique may underestimate absolute subsidence rates, it gives valuable information on the direction of motion and spatial variability of subsidence. The study confirms widespread and severe peatland degradation in Selangor, highlighting the value of DInSAR for identifying priority zones for restoration and emphasising the need for conservation and restoration efforts to preserve Selangor peatlands and prevent further environmental impacts.

The South-Central United States, which includes the states of Louisiana, Mississippi, Texas, and Arkansas, represents an important segment of the softwood sawtimber market. By using the Seemingly Unrelated Regression (SUR) method to account for the linkage among the four contiguous timber markets, this study examines the dynamics of softwood sawtimber stumpage markets within the region. Based on quarterly data from 1981 to 2014, the findings reveal that both pulpwood and chip-and-saw (CNS) prices have a positive influence on the Texas and Arkansas sawtimber markets. Moreover, Granger-causality tests suggest that unidirectional causality runs from pulpwood and CNS markets to the respective sawtimber market. Compared to the pre-financial crisis period, sawtimber prices in these four states are 9%–17% lower in the recent years.