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Abstract: Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Tropical rainforests of Latin America (LATAM) are one of the world's largest carbon sinks, with substantial future carbon sequestration potential and contributing a major proportion of the global supply of forest carbon credits. LATAM is poised to contribute predominantly towards high-quality forest carbon offset projects designed to reduce emissions from deforestation and forest degradation, halt biodiversity loss, and provide equitable conservation benefits to people. Thus, carbon markets, including compliance carbon markets and voluntary carbon markets continue to expand in LATAM. However, the extent of the growth and status of forest carbon markets, pricing initiatives, stakeholders, amongst others, are yet to be explored and extensively reviewed for the entire LATAM region. Against this backdrop, we reviewed a total of 299 articles, including peer-reviewed and non-scientific gray literature sources, from January 2010 to March 2023. Herein, based on the extensive literature review, we present the results and provide perspectives classified into five categories: (i) the status and recent trends of forest carbon markets (ii) the interested parties and their role in the forest carbon markets, (iii) the measurement, reporting and verification (MRV) approaches and role of remote sensing, (iv) the challenges, and (v) the benefits, opportunities, future directions and recommendations to enhance forest carbon markets in LATAM. Despite the substantial challenges, better governance structures for forest carbon markets can increase the number, quality and integrity of projects and support the carbon sequestration capacity of the rainforests of LATAM. Due to the complex and extensive nature of forest carbon projects in LATAM, emerging technologies like remote sensing can enable scale and reduce technical barriers to MRV, if properly benchmarked. The future directions and recommendations provided are intended to improve upon the existing infrastructure and governance mechanisms, and encourage further participation from the public and private sectors in forest carbon markets in LATAM.

Societal Impact Statement Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net‐zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi‐automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net‐zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well‐documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi‐automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground‐based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground‐based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories. [ABSTRACT FROM AUTHOR]

Given that terrestrial ecosystems globally are facing the loss of biodiversity from land use conversion, invasive species, and climate change, effective management requires a better understanding of the drivers and correlates of biodiversity. Increasingly, biodiversity is co‐managed with aboveground carbon storage because high biodiversity in animal species is observed to correlate with high aboveground carbon storage. Most previous investigations into the relationship of biodiversity and carbon co‐management do not focus on the biodiversity of the species rich plant kingdom, which may have tradeoffs with carbon storage. To examine the relationships of plant species richness with aboveground tree biomass carbon storage, we used a series of generalized linear models with understory plant species richness and diversity data from the USDA Forest Service Forest Inventory and Analysis dataset and high‐resolution modeled carbon maps for the Tongass National Forest. Functional trait data from the TRY database was used to understand the potential mechanisms that drive the response of understory plants. Understory species richness and community weighted mean leaf dry matter content decreased along an increasing gradient of tree biomass carbon storage, but understory diversity, community weighted mean specific leaf area, and plant height at maturity did not. Leaf dry matter content had little variance at the community level. The decline of understory plant species richness but not diversity to increases in aboveground biomass carbon storage suggests that rare species are excluded in aboveground biomass carbon dense areas. These decreases in understory species richness reflect a tradeoff between the understory plant community and aboveground carbon storage. The mechanisms that are associated with observed plant communities along a gradient of biomass carbon storage in this forest suggest that slower‐growing plant strategies are less effective in the presence of high biomass carbon dense trees in the overstory. [ABSTRACT FROM AUTHOR]

Defoliation by eastern spruce budworm is one of the most important natural disturbances in Canadian boreal and hemi‐boreal forests with annual area affected surpassing that of fire and harvest combined, and its impacts are projected to increase in frequency, severity, and range under future climate scenarios. Deciding on an active management strategy to control outbreaks and minimize broader economic, ecological, and social impacts is becoming increasingly important. These strategies differ in the degree to which defoliation is suppressed, but little is known about the downstream consequences of defoliation and, thus, the implications of management. Given the disproportionate role of headwater streams and their microbiomes on net riverine productivity across forested landscapes, we investigated the effects of defoliation by spruce budworm on headwater stream habitat and microbiome structure and function to inform management decisions. We experimentally manipulated a gradient of defoliation among 12 watersheds during a spruce budworm outbreak in the Gaspésie Peninsula, Québec, Canada. From May through October of 2019–2021, stream habitat (flow rates, dissolved organic matter [DOM], water chemistry, and nutrients), algal biomass, and water temperatures were assessed. Bacterial and fungal biofilm communities were examined by incubating six leaf packs for five weeks (mid‐August to late September) in one stream reach per watershed. Microbiome community structure was determined using metabarcoding of 16S and ITS rRNA genes, and community functions were examined using extracellular enzyme assays, leaf litter decomposition rates, and taxonomic functional assignments. We found that cumulative defoliation was correlated with increased streamflow rates and temperatures, and more aromatic DOM (measured as specific ultraviolet absorbance at 254 nm), but was not correlated to nutrient concentrations. Cumulative defoliation was also associated with altered microbial community composition, an increase in carbohydrate biosynthesis, and a reduction in aromatic compound degradation, suggesting that microbes are shifting to the preferential use of simple carbohydrates rather than more complex aromatic compounds. These results demonstrate that high levels of defoliation can affect headwater stream microbiomes to the point of altering stream ecosystem productivity and carbon cycling potential, highlighting the importance of incorporating broader ecological processes into spruce budworm management decisions. [ABSTRACT FROM AUTHOR]

Spatially explicit global estimates of forest carbon storage are typically coarsely scaled. While useful, these estimates do not account for the variability and distribution of carbon at management scales. We asked how climate, topography, and disturbance regimes interact across and within geopolitical boundaries to influence tree biomass carbon, using the perhumid region of the Pacific Coastal Temperate Rainforest, an infrequently disturbed carbon dense landscape, as a test case. We leveraged permanent sample plots in southeast Alaska and coastal British Columbia and used multiple quantile regression forests and generalized linear models to estimate tree biomass carbon stocks and the effects of topography, climate, and disturbance regimes. We estimate tree biomass carbon stocks are either 211 (SD = 163) Mg C ha−1 or 218 (SD = 169) Mg C ha−1. Natural disturbance regimes had no correlation with tree biomass but logging decreased tree biomass carbon and the effect diminished with increasing time since logging. Despite accounting for 0.3% of global forest area, this forest stores between 0.63% and 1.07% of global aboveground forest carbon as aboveground live tree biomass. The disparate impact of logging and natural disturbance regimes on tree biomass carbon suggests a mismatch between current forest management and disturbance history. [ABSTRACT FROM AUTHOR]

Forests and woodlands are critical terrestrial carbon stores. Tree aboveground biomass (AGB) can be estimated using allometric models and terrestrial laser scanning (TLS). However, internal tree stem damage from biotic decay is an unresolved source of error for both TLS and allometries, with implications for accurate carbon assessment.We destructively harvested 63 TLS‐scanned trees in an Australian savanna, quantified internal damage in each tree by sampling cross sections at multiple heights, and modelled the effect of damage on AGB estimation for individual trees and total estimated biomass. We tested the performance of TLS AGB modelling against five allometries, applying both database and field‐measured wood specific gravity. For TLS‐modelled and allometric AGB estimates, we tested if tree size and level of internal stem damage contributed to AGB deviations.Approximately half of the trees in the study sustained 1–10% damage by volume, which was most extensive in the base and main trunk, decreasing into the crown. On average, damaged trees had 5% internal stem damage (by volume, SD = 6.65%), with some as high as 30%. We found TLS‐derived quantitative structural models (TLS‐QSMs) using field‐measured wood specific gravity to be most accurate in estimating total biomass (R2 = 0.99, +0.59% bias). TLS‐QSMs tended to overpredict AGB of large, damaged trees, and AGB estimates from allometric models were largely unaffected by internal damage. For individual trees, all methods were effective for predicting field‐measured AGB (R2 > 0.84) and several ASMs performed well (± ~10% bias). In the absence of local wood specific gravity calibration, a pantropical ASM was most accurate.For systems where internal stem damage is low (<10% of tree volume), TLS can be used to estimate AGB with low levels of error, however more damaged wooded ecosystems (>10%) are likely to produce inflated biomass estimates if TLS is used without calibration for damage. Internal stem damage should be quantified in ASMs and incorporated into TLS‐modelled AGB calibration to avoid biomass overestimation and maintain high standards of precision in forest carbon accounting. [ABSTRACT FROM AUTHOR]

Abstract Forests and woodlands are critical terrestrial carbon stores. Tree aboveground biomass (AGB) can be estimated using allometric models and terrestrial laser scanning (TLS). However, internal tree stem damage from biotic decay is an unresolved source of error for both TLS and allometries, with implications for accurate carbon assessment. We destructively harvested 63 TLS‐scanned trees in an Australian savanna, quantified internal damage in each tree by sampling cross sections at multiple heights, and modelled the effect of damage on AGB estimation for individual trees and total estimated biomass. We tested the performance of TLS AGB modelling against five allometries, applying both database and field‐measured wood specific gravity. For TLS‐modelled and allometric AGB estimates, we tested if tree size and level of internal stem damage contributed to AGB deviations. Approximately half of the trees in the study sustained 1–10% damage by volume, which was most extensive in the base and main trunk, decreasing into the crown. On average, damaged trees had 5% internal stem damage (by volume, SD = 6.65%), with some as high as 30%. We found TLS‐derived quantitative structural models (TLS‐QSMs) using field‐measured wood specific gravity to be most accurate in estimating total biomass (R2 = 0.99, +0.59% bias). TLS‐QSMs tended to overpredict AGB of large, damaged trees, and AGB estimates from allometric models were largely unaffected by internal damage. For individual trees, all methods were effective for predicting field‐measured AGB (R2 > 0.84) and several ASMs performed well (± ~10% bias). In the absence of local wood specific gravity calibration, a pantropical ASM was most accurate. For systems where internal stem damage is low (10%) are likely to produce inflated biomass estimates if TLS is used without calibration for damage. Internal stem damage should be quantified in ASMs and incorporated into TLS‐modelled AGB calibration to avoid biomass overestimation and maintain high standards of precision in forest carbon accounting.

Abstract Background Wood carbon fractions (CFs)—the proportion of dry woody biomass comprised of elemental carbon (C)—are a key component of forest C estimation protocols and studies. Traditionally, a wood CF of 50% has been assumed in forest C estimation protocols, but recent studies have specifically quantified differences in wood CFs across several different forest biomes and taxonomic divisions, negating the need for generic wood CF assumptions. The Intergovernmental Panel on Climate Change (IPCC), in its 2006 “Guidelines for National Greenhouse Gas Inventories”, published its own multitiered system of protocols for estimating forest C stocks, which included wood CFs that (1) were based on the best available literature (at the time) and (2) represented a significant improvement over the generic 50% wood CF assumption. However, a considerable number of new studies on wood CFs have been published since 2006, providing more accurate, robust, and spatially- and taxonomically- specific wood CFs for use in forest C estimation. Main text We argue that the IPCC’s recommended wood CFs and those in many other forest C estimation models and protocols (1) differ substantially from, and are less robust than, wood CFs derived from recently published data-rich studies; and (2) may lead to nontrivial errors in forest C estimates, particularly for countries that rely heavily on Tier 1 forest C methods and protocols (e.g., countries of the Global South with large expanses of tropical forests). Based on previous studies on this topic, we propose an alternative set of refined wood CFs for use in multiscale forest C estimation, and propose a novel decision-making framework for integrating species- and location-specific wood CFs into forest C estimation models. Conclusion The refined wood CFs that we present in this commentary may be used by the IPCC to update its recommended wood CFs for use in forest C estimation. Additionally, we propose a novel decision-making framework for integrating data-driven wood CFs into a wider suite of multitiered forest C estimation protocols, models, and studies.

Abstract Background Reducing Emissions from Deforestation and forest Degradation (REDD+) is a program established under the United Nations Framework Convention on Climate Change (UNFCCC) to reduce carbon emissions from forests in developing countries. REDD+ uses an incentive-based approach whereby participating countries are paid to reduce forest carbon loss and increase carbon storage. Country-level carbon accounting is challenging, and estimates of uncertainty in emission reductions are increasingly required in REDD+ reports. This requirement is hard to meet if countries lack the necessary resources, tools, and capabilities. Some REDD+ programs adjust their payments for the uncertainty reported, which presents a perverse incentive because uncertainties are larger if more sources of uncertainty are reported. We surveyed people involved in REDD+ reporting to assess current capacities and barriers to improving estimates of uncertainty. Results Representatives from 27 countries (44% of REDD+ countries at the time of survey implementation) responded to the survey. Nearly all respondents thought it important to include uncertainty in REDD+ reports, but most felt that the uncertainty reporting by their countries was inadequate. Our independent assessment of reports by these countries to the UNFCCC supported this opinion: Most countries reported uncertainty in activity data (91%) but not in emission factors (4–14%). Few countries use more advanced approaches to estimate uncertainty, such as Monte Carlo and Bayesian techniques, and many respondents indicated that they lack expertise, knowledge, or technical assistance. Other barriers include lack of financial resources and appropriate data. Despite these limitations, nearly all respondents indicated a strong desire to improve estimates of uncertainty in REDD+ reports. Conclusions The survey indicated that people involved in REDD+ reporting think it highly important to improve estimates of uncertainty in forest carbon accounting. To meet this challenge, it is essential to understand the obstacles countries face in quantifying uncertainty so we can identify where best to allocate efforts and funds. Investments in training and resources are clearly needed to better quantify uncertainty and would likely have successful outcomes given the strong desire for improvement. Tracking the efficacy of programs implemented to improve estimates of uncertainty would be useful for making further refinements.

Background: Wood carbon fractions (CFs)—the proportion of dry woody biomass comprised of elemental carbon (C)—are a key component of forest C estimation protocols and studies. Traditionally, a wood CF of 50% has been assumed in forest C estimation protocols, but recent studies have specifically quantified differences in wood CFs across several different forest biomes and taxonomic divisions, negating the need for generic wood CF assumptions. The Intergovernmental Panel on Climate Change (IPCC), in its 2006 "Guidelines for National Greenhouse Gas Inventories", published its own multitiered system of protocols for estimating forest C stocks, which included wood CFs that (1) were based on the best available literature (at the time) and (2) represented a significant improvement over the generic 50% wood CF assumption. However, a considerable number of new studies on wood CFs have been published since 2006, providing more accurate, robust, and spatially- and taxonomically- specific wood CFs for use in forest C estimation. Main text: We argue that the IPCC's recommended wood CFs and those in many other forest C estimation models and protocols (1) differ substantially from, and are less robust than, wood CFs derived from recently published data-rich studies; and (2) may lead to nontrivial errors in forest C estimates, particularly for countries that rely heavily on Tier 1 forest C methods and protocols (e.g., countries of the Global South with large expanses of tropical forests). Based on previous studies on this topic, we propose an alternative set of refined wood CFs for use in multiscale forest C estimation, and propose a novel decision-making framework for integrating species- and location-specific wood CFs into forest C estimation models. Conclusion: The refined wood CFs that we present in this commentary may be used by the IPCC to update its recommended wood CFs for use in forest C estimation. Additionally, we propose a novel decision-making framework for integrating data-driven wood CFs into a wider suite of multitiered forest C estimation protocols, models, and studies. [ABSTRACT FROM AUTHOR]

Background: Reducing Emissions from Deforestation and forest Degradation (REDD+) is a program established under the United Nations Framework Convention on Climate Change (UNFCCC) to reduce carbon emissions from forests in developing countries. REDD+ uses an incentive-based approach whereby participating countries are paid to reduce forest carbon loss and increase carbon storage. Country-level carbon accounting is challenging, and estimates of uncertainty in emission reductions are increasingly required in REDD+ reports. This requirement is hard to meet if countries lack the necessary resources, tools, and capabilities. Some REDD+ programs adjust their payments for the uncertainty reported, which presents a perverse incentive because uncertainties are larger if more sources of uncertainty are reported. We surveyed people involved in REDD+ reporting to assess current capacities and barriers to improving estimates of uncertainty. Results: Representatives from 27 countries (44% of REDD+ countries at the time of survey implementation) responded to the survey. Nearly all respondents thought it important to include uncertainty in REDD+ reports, but most felt that the uncertainty reporting by their countries was inadequate. Our independent assessment of reports by these countries to the UNFCCC supported this opinion: Most countries reported uncertainty in activity data (91%) but not in emission factors (4–14%). Few countries use more advanced approaches to estimate uncertainty, such as Monte Carlo and Bayesian techniques, and many respondents indicated that they lack expertise, knowledge, or technical assistance. Other barriers include lack of financial resources and appropriate data. Despite these limitations, nearly all respondents indicated a strong desire to improve estimates of uncertainty in REDD+ reports. Conclusions: The survey indicated that people involved in REDD+ reporting think it highly important to improve estimates of uncertainty in forest carbon accounting. To meet this challenge, it is essential to understand the obstacles countries face in quantifying uncertainty so we can identify where best to allocate efforts and funds. Investments in training and resources are clearly needed to better quantify uncertainty and would likely have successful outcomes given the strong desire for improvement. Tracking the efficacy of programs implemented to improve estimates of uncertainty would be useful for making further refinements. [ABSTRACT FROM AUTHOR]

Abstract Given that terrestrial ecosystems globally are facing the loss of biodiversity from land use conversion, invasive species, and climate change, effective management requires a better understanding of the drivers and correlates of biodiversity. Increasingly, biodiversity is co‐managed with aboveground carbon storage because high biodiversity in animal species is observed to correlate with high aboveground carbon storage. Most previous investigations into the relationship of biodiversity and carbon co‐management do not focus on the biodiversity of the species rich plant kingdom, which may have tradeoffs with carbon storage. To examine the relationships of plant species richness with aboveground tree biomass carbon storage, we used a series of generalized linear models with understory plant species richness and diversity data from the USDA Forest Service Forest Inventory and Analysis dataset and high‐resolution modeled carbon maps for the Tongass National Forest. Functional trait data from the TRY database was used to understand the potential mechanisms that drive the response of understory plants. Understory species richness and community weighted mean leaf dry matter content decreased along an increasing gradient of tree biomass carbon storage, but understory diversity, community weighted mean specific leaf area, and plant height at maturity did not. Leaf dry matter content had little variance at the community level. The decline of understory plant species richness but not diversity to increases in aboveground biomass carbon storage suggests that rare species are excluded in aboveground biomass carbon dense areas. These decreases in understory species richness reflect a tradeoff between the understory plant community and aboveground carbon storage. The mechanisms that are associated with observed plant communities along a gradient of biomass carbon storage in this forest suggest that slower‐growing plant strategies are less effective in the presence of high biomass carbon dense trees in the overstory.

Abstract Background Plantation forests are a nature-based solution to sequester atmospheric carbon and, therefore, mitigate anthropogenic climate change. The choice of tree species for afforestation is subject to debate within New Zealand. Two key issues are whether to use (1) exotic plantation species versus indigenous forest species and (2) fast growing short-rotation species versus slower growing species. In addition, there is a lack of scientific knowledge about the carbon sequestration capabilities of different plantation tree species, which hinders the choice of species for optimal carbon sequestration. We contribute to this discussion by simulating carbon sequestration of five plantation forest species, Pinus radiata, Pseudotsuga menziesii, Eucalyptus fastigata, Sequoia sempervirens and Podocarpus totara, across three sites and two silvicultural regimes by using the 3-PG an ecophysiological model. Results The model simulations showed that carbon sequestration potential varies among the species, sites and silvicultural regimes. Indigenous Podocarpus totara or exotic Sequoia sempervirens can provide plausible options for long-term carbon sequestration. In contrast, short term rapid carbon sequestration can be obtained by planting exotic Pinus radiata, Pseudotsuga menziesii and Eucalyptus fastigata. Conclusion No single species was universally better at sequestering carbon on all sites we tested. In general, the results of this study suggest a robust framework for ranking and testing candidate afforestation species with regard to carbon sequestration potential at a given site. Hence, this study could help towards more efficient decision-making for carbon forestry.

Several carbon offset programs allow West Virginia (WV) forest landowners to manage their forests to mitigate climate change and promote forest sustainability while providing an opportunity to earn extra income through carbon offset credits. While this market has grown rapidly, accessibility issues for small family forest owners remain. This study examines WV forest landowners’ insights and understanding of forest carbon offset programs and program preferences through an online survey of WV's Managed Timberland Program participants. Results showed that 97 % of respondents find it important to keep their land forested and 41 % think that carbon offset programs will help keep their land forested. However, the majority have no knowledge of carbon offset programs (55 %) nor an understanding the credit generation process (60 %). An econometric model was estimated to examine the influence of program attributes to landowners’ decision to enroll in a carbon offset program. Survey results suggest that landowners will more likely participate in carbon offset programs that require shorter time commitment (1–5 years), pay higher revenues, allow harvest or limited harvest restrictions, and do not charge an early withdrawal penalty. For example, a $1 increase in revenue payment raises the probability of enrolling in a carbon offset program by 1.2 %. However, extending the time commitment from 1 to 5 years to 40 years or 100 years decreases the probability of enrollment by 10.3 % and 17.4 %, respectively. Additionally, prohibiting harvest and imposing an early withdrawal penalty decrease the probability of enrollment by 18.1 % and 9.5 %, respectively. Landowners expressed greater willingness to enroll if they believe it is important to keep their land forested, they have familiarity and knowledge of the carbon offset market, and they believe carbon offset programs will help keep their land forested. Age, educational level, and length of ownership were also found to be significant factors in influencing landowner participation in forest carbon offset programs. Lastly, a welfare estimate, or landowners’ willingness-to-accept (WTA), was estimated for each of the program attributes. Surveyed landowners’ WTA payment for a carbon program was $22/ha/year or $37/ha/year greater if program duration increased from 1 to 5 years to 40 years or 100 years, respectively. In addition, landowners’ WTA payment was $39/ha/year greater if a “no harvest” requirement is implemented and $19/ha/year more if a penalty for early withdrawal is imposed. This study shows how factors like duration, payment, harvest restrictions, and withdrawal penalties influence landowner enrollment in carbon offset programs. By examining the preferences and decision-making processes of forest owners, this research fills a critical gap in the literature by providing insights into the drivers of program participation. The findings contribute to a better understanding of how to design more effective carbon programs that align with landowner motivations, ultimately supporting climate mitigation goals and sustainable forest management practices.

Global forests are increasingly crucial for achieving net-zero carbon emissions, with a quarter of the mitigation efforts under the Paris Climate Agreement directed towards forests. In China, forests currently contribute to 13% of the global land's carbon sink, but their stability and persistence remain uncertain. We examined and identified that published studies suffered from oversimplifications of ecosystem succession and tree demographic dynamics, as well as poor constraints on land quality. Consequently, substantial estimations might have been suffered from underrepresented or ignored crucial factors, including tree demographic dynamics, and disturbances and habitat shifts caused by global climate change. We argue that these essential factors should be considered to enhance the reliability and accuracy of assessments of the potential for forest carbon sinks. [ABSTRACT FROM AUTHOR]

Background: Plantation forests are a nature-based solution to sequester atmospheric carbon and, therefore, mitigate anthropogenic climate change. The choice of tree species for afforestation is subject to debate within New Zealand. Two key issues are whether to use (1) exotic plantation species versus indigenous forest species and (2) fast growing short-rotation species versus slower growing species. In addition, there is a lack of scientific knowledge about the carbon sequestration capabilities of different plantation tree species, which hinders the choice of species for optimal carbon sequestration. We contribute to this discussion by simulating carbon sequestration of five plantation forest species, Pinus radiata, Pseudotsuga menziesii, Eucalyptus fastigata, Sequoia sempervirens and Podocarpus totara, across three sites and two silvicultural regimes by using the 3-PG an ecophysiological model. Results: The model simulations showed that carbon sequestration potential varies among the species, sites and silvicultural regimes. Indigenous Podocarpus totara or exotic Sequoia sempervirens can provide plausible options for long-term carbon sequestration. In contrast, short term rapid carbon sequestration can be obtained by planting exotic Pinus radiata, Pseudotsuga menziesii and Eucalyptus fastigata. Conclusion: No single species was universally better at sequestering carbon on all sites we tested. In general, the results of this study suggest a robust framework for ranking and testing candidate afforestation species with regard to carbon sequestration potential at a given site. Hence, this study could help towards more efficient decision-making for carbon forestry. [ABSTRACT FROM AUTHOR]

Nature‐based climate solutions (NCS) are championed as a primary tool to mitigate climate change, especially in forested regions capable of storing and sequestering vast amounts of carbon. New England is one of the most heavily forested regions in the United States (>75% forested by land area), and forest carbon is a significant component of climate mitigation policies. Large infrequent disturbances, such as hurricanes, are a major source of uncertainty and risk for policies relying on forest carbon for climate mitigation, especially as climate change is projected to alter the intensity and extent of hurricanes. To date, most research into disturbance impacts on forest carbon stocks has focused on fire. Here, we show that a single hurricane in the region can down between 121 and 250 MMTCO2e or 4.6%–9.4% of the total aboveground forest carbon, much greater than the carbon sequestered annually by New England's forests (16 MMTCO2e year−1). However, emissions from hurricanes are not instantaneous; it takes approximately 19 years for downed carbon to become a net emission and 100 years for 90% of the downed carbon to be emitted. Reconstructing hurricanes with the HURRECON and EXPOS models across a range of historical and projected wind speeds, we find that an 8% and 16% increase in hurricane wind speeds leads to a 10.7‐ and 24.8‐fold increase in the extent of high‐severity damaged areas (widespread tree mortality). Increased wind speed also leads to unprecedented geographical shifts in damage, both inland and northward, into heavily forested regions traditionally less affected by hurricanes. Given that a single hurricane can emit the equivalent of 10+ years of carbon sequestered by forests in New England, the status of these forests as a durable carbon sink is uncertain. Understanding the risks to forest carbon stocks from disturbances is necessary for decision‐makers relying on forests as a NCS. [ABSTRACT FROM AUTHOR]

The role of Perhutani and local farmers in developing agroforestry in Bogor Forest Management Unit (FMU) is important for carbon sequestration-based climate mitigation efforts. Different compositions of the plants in seven agroforestry systems in four part of Bogor FMU. Farmers adjust the multipurpose crops planted with Perhutani main plants, which are more dominant. The potential mean annual carbon increment based on aboveground carbon stock of agroforestry is between 2.26 to 66.65 tonnes per hectare, while in 2 monocultures land system is between 13.65 to 18.29 tonnes per hectare. The carbon increment in agroforestry systems is better than monoculture because of plant diversity and different ages. Then, carbon revenue using carbon pricing set by the World Bank-FCPF Program in East Kalimantan is in the range of IDR 1,547,325 to IDR 49,292,405 per hectare, using the Social Cost scheme in the range IDR 12,997,535 to IDR 414,056,204 per hectare and using domestic carbon tax is range IDR 635.017 to IDR 20,229,441 perhectare. Regarding carbon revenues, the wider the agroforestry land managed by farmers, the higher the carbon income received. Using the benefit transfer method over a 20-year mitigation period, an estimated 2.19 times increase in carbon revenues is obtained at an inflation rate of 4%. [ABSTRACT FROM AUTHOR]

Quantifying uncertainty is important to establishing the significance of comparisons, to making predictions with known confidence, and to identifying priorities for investment. However, uncertainty can be difficult to quantify correctly. While sampling error is commonly reported based on replicate measurements, the uncertainty in regression models used to estimate forest biomass from tree dimensions is commonly ignored and has sometimes been reported incorrectly, due either to lack of clarity in recommended procedures or to incentives to underestimate uncertainties. Even more rarely are the uncertainty in predicting individuals and the uncertainty in the mean both recognized for their contributions to overall uncertainty. In this paper, we demonstrate the effect of propagating these two sources of uncertainty using a simple example of calcium concentration of sugar maple foliage, which does not require regression, then the mass of foliage and calcium content of foliage, and finally an entire forest with multiple species and tissue types. The uncertainty due to predicting individuals is greater than the uncertainty in the mean for studies with few trees—up to 30 trees for foliar calcium concentration and 50 trees for foliar mass and calcium content in the data set we analyzed from the Hubbard Brook Experimental Forest. The most correct analysis will take both sources of uncertainty into account, but for practical purposes, country-level reports of uncertainty in carbon stocks can safely ignore the uncertainty in individuals, which becomes negligible with large enough numbers of trees. Ignoring the uncertainty in the mean will result in exaggerated confidence in estimates of forest biomass and carbon and nutrient contents. [ABSTRACT FROM AUTHOR]

The Indian Himalayan Region (IHR) has rich forest resources but is increasingly threatened by changes in land use. It is therefore imperative to understand forest carbon budgets and ecosystem productivity in this ecologically sensitive mountain landscape. The study assessed spatial distribution and changes in forest carbon stocks of Solan Forest Division over the period 1998–2010. Forest inventory data was gathered from the Divisional Working Plan and through field enumeration. The IRS 1D (LISS-III) satellite data were preprocessed through geometric and radiometric corrections. The Normalised Difference Vegetation Index (NDVI) was calculated from the reflectance of red and near-infrared radiation. Statistical relationships between inventory-based forest carbon stocks and NDVI were used as a basis for spatial extrapolation to the whole region. A significant relationship was observed between carbon stock and NDVI for both 1998 (R = 0.741) and 2010 (R = 0.663). The carbon density ranged from < 10.49 to 168.03 t ha−1 (1998) and from < 11.32 to 181.23 t ha−1 (2010). Over the period 1998–2010 although the forest area decreased, the carbon stock increased by < 0.71 to 11.49%. Imposition of felling bans, afforestation, natural ageing of secondary forests and profuse natural regeneration may be associated with the observed increase in carbon stock. The study suggested that NDVI derived from optical imageries can be utilised to assess vegetation carbon dynamics in subtropical forests of the region. Among a myriad of mitigation options, maintaining and enhancing carbon in forested landscapes remains an efficacious strategy. Similar studies in fragile ecosystems vulnerable to anthropogenic modification can facilitate robust monitoring of terrestrial carbon sequestration and its capacity in meeting emission reduction targets. [ABSTRACT FROM AUTHOR]

Abstract Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

The current study emphasizes the inherent shortcomings of laws and policy approaches that are based on the premise that by increasing wood production, much more emission credits can be achieved by using wood in alternative uses. The article aims to exploit the financing of emission reductions, discuss how carbon sinks held in forest resources can be activated, traded, and financed, and explain how Turkiye's forest carbon potential can be exploited. To make a comparative analysis of the situation of Turkiye at global level, Russian’s potential for carbon sequestration and its trade have been dealt with as a comparison by following quantitative research methodology. In this research, the calculation method has been used to determine the number of houses that are likely to be built in rural areas using wood materials, e.g., the construction of 100,000 houses with a construction area of 100 m2 per year. Consequently, the forest carbon generated by alternative scenarios contributes positively to the emission balance sheet, as well as climate change mitigation through carbon emission trade despite all legal and technical constraints. Although both countries have similar shortcomings of obtaining carbon credits and its trade, of course Russia has a promising situation in comparison with Turkiye with respect to the amount of carbon sequestered and the likelihood of its trade potential at global level.

Recent research has shown forest-related emissions reported in national greenhouse gas inventories are much lower than global estimates from models summarized in Intergovernmental Panel on Climate Change reports. A substantial part of this discrepancy could be explained by conceptual differences in what is counted as part of the anthropogenic forest carbon sink and the way countries report on their forest harvesting sectors. With Canada as a case study, we used published National Inventory Report and Common Reporting Format tables to isolate emissions and removals directly associated with forestry from those associated with forests more broadly. Forestry-related factors that affect CO2 emissions and removals include tree harvesting, post-harvest forest regeneration and growth, and carbon storage in long-lived harvested wood products. We found that between 2005 and 2021, forestry in Canada represented a net source of carbon (annual mean = 90.8 Mt. CO2e), and that total area logged was a significant predictor of net forestry emissions. In contrast, Canada’s NIR reported a small net carbon sink during the same time period (annual mean = −4.7 Mt. CO2e). We show this discrepancy can be explained by Canada’s GHG reporting approach that claims GHG emissions from wildfires are natural, but GHG removals from forests at the age of commercial maturity, despite being primarily natural disturbance origin, are anthropogenic. This reporting approach may lead to climate mitigation policies that are ineffectual or detrimental to reducing net carbon in the global atmosphere.

Abstract The interdependent crises of climate change and biodiversity losses require strategic policies to protect, manage, and restore essential ecosystems. Here, we evaluate the relative importance of US national forests (NFs) for protection and conservation as natural climate and biodiversity solutions. We compared landscape integrity (degree of modification by humans), habitat for three keystone species, forest carbon density, accumulation, and total biomass carbon stocks across 154 NFs in the United States. Southern Alaska's Tongass and Chugach NFs hold disproportionally large amounts of high landscape integrity area among all NFs with 25.3% and 5.6% (total 30.9%) of all high (≥9.6) landscape integrity found on NF lands. The Tongass and Chugach store approximately 33% and 3% of all biomass carbon stocks that occur in NFs with high landscape integrity. These two NFs together account for about 49%, 37%, and 18% of all bald eagle, brown bear, and gray wolf habitat found on NF lands. Gray wolf habitat extent was 4% of the total or less on remaining NFs. The Tongass and Chugach were historically wetter and cooler among NFs, and are projected to experience much larger increases in precipitation and much lower increases in maximum temperatures over the coming century. Combined with relatively low recent occurrence of wildfire, this makes permanence more likely. The Tongass and Chugach forests, along with the Pacific Northwest's high carbon density forests should be a high priority for protection and conservation to meet climate and biodiversity goals given their landscape‐scale scarcity and high value.

Management of boreal forests can increase terrestrial carbon sinks and reduce greenhouse gas (GHG) emissions to the atmosphere. A case study was conducted in the boreal balsam fir forests of Quebec (Canada), a commercially important region for forestry, to identify optimal management and wood production solutions that contribute to reducing GHG emissions to the atmosphere. Scenarios were based on a steady level of harvest and silvicultural activities over time and a stable flow of wood products to markets. Scenarios included: increases and decreases in the volume of harvested timber; the transition of harvesting activities from clearcuts (the most common practice in the region) to partial cuts; and changes in the rate of natural regeneration (the usual mode of regeneration) vs. plantations. All scenarios provided a carbon sink regardless of the time frame. Compared with other scenarios, reducing harvest levels increased the forest carbon sink in the short (10 to 20 years) and medium (20 to 50 years) terms. Also, for a similar harvest level, the increased use of partial cutting and planting increased the forest carbon sink. In the long term (over 50 years), strategies with low harvesting levels resulted in lower ecosystem carbon sequestration, even though they still had the lowest cumulative emissions. Nevertheless, higher harvesting levels could not be justified because the long-term increase in the forest ecosystem carbon sink could not offset higher emissions from wood products, particularly from short-lived paper products. Sensitivity analyses showed that improving sawmill efficiency and thus increasing the proportion of long-lived products was an important factor that can greatly reduce emissions. On the other hand, transportation distances between forest stands and sawmills had a relatively marginal impact on the overall carbon balance of forest management and wood production scenarios.

Managing disturbed forests for climate mitigation and biodiversity requires monitoring the carbon (C) cycle consequences of replacing established exotic vegetation with native seedlings. Standard approaches rely on allometric growth equations with unexplored limitations for measuring C changes during restoration. Most plants lack species-specific allometric growth equations. Additionally, these equations may perform poorly for different growth forms, especially when applied to both mature trees and seedlings. To address these limitations, we generated and compared allometric growth equations for four woody species with different biogeographic origins and growth forms, including two high impact invasive species, Cupaniopisis anacardioides and Schinus terebinthifolia. By borrowing strength from sampling across species to reduce estimation error within species, Bayesian multilevel models generated more accurate estimates than either independent species-level models or generic equations, although improvements over independent species-level models were modest. Because errors systematically changed with plant size, especially for species with unusual growth forms, allometric growth equations from custom multilevel models generated higher baseline aboveground biomass estimates and lower post-restoration estimates, which has important implications for monitoring C consequences of invasive tree management.

Currently, significant attention is paid to environmental issues at all levels of management. Over the long history of human civilization, significant environmental damage has been accumulated, because not only large-scale industrial production, but also ordinary human life leads to the formation of a significant amount of harmful products that pollute the atmosphere, soil, and water spaces. The huge scale of the accumulated damage makes it necessary to resolve environmental issues at the highest level - the level of international organizations and the leadership of individual states. At the same time, interest in the environmental agenda is connected both with the health of the population and with economic aspects, because in the near future in Europe, and then, possibly, in Russia, much more significant taxes and fines for nonenvironmentally friendly production and products will be introduced. Among a significant number of important environmental issues of our time, one of the most acute is the issue related to emissions of the so-called greenhouse gases (primarily carbon dioxide CO2 and methane, but also other gases) and the environmental damage resulting from this phenomenon. [ABSTRACT FROM AUTHOR]

Forestry offsets, recognized for their diverse environmental and social co-benefits, are gaining a growing interest as nature-based solutions to combat climate change. Despite Canada's extensive forest resources, its potential for carbon credit remains largely untapped. This study aims to unveil the prevailing challenges in developing forestry offsets in Canada and propose potential solutions, drawing on insights from in-depth semi-structured interviews (SSIs) with 23 experts in the field. A qualitative thematic analysis highlighted 14 challenges under four major frequently discussed themes: methodological (37%), social (29%), economic (22%), and implementation challenges (12%). Our findings highlighted the urgency of addressing key obstacles, including the impermanent nature of forestry carbon offsets, substantial public knowledge gaps, uncertainties in the cost-effectiveness impacting financial viability, and the need for enhanced capacity for project implementation. Building on the discussions on the identified challenges, this study further presented a comprehensive analysis of the future directions for Canada, emphasizing the importance of addressing key methodological issues, enhancing public and Indigenous education and engagement, and leveraging advanced technologies and innovative approaches like ton-year accounting for economic viability. This paper delivers pivotal insights that have the potential to shape the direction and integrity of the forestry offset markets in both Canada and globally. [ABSTRACT FROM AUTHOR]

The current study emphasizes the inherent shortcomings of laws and policy approaches that are based on the premise that by increasing wood production, much more emission credits can be achieved by using wood in alternative uses. The article aims to exploit the financing of emission reductions, discuss how carbon sinks held in forest resources can be activated, traded, and financed, and explain how Turkiye's forest carbon potential can be exploited. To make a comparative analysis of the situation of Turkiye at global level, Russian's potential for carbon sequestration and its trade have been dealt with as a comparison by following quantitative research methodology. In this research, the calculation method has been used to determine the number of houses that are likely to be built in rural areas using wood materials, e.g., the construction of 100,000 houses with a construction area of 100 m² per year. Consequently, the forest carbon generated by alternative scenarios contributes positively to the emission balance sheet, as well as climate change mitigation through carbon emission trade despite all legal and technical constraints. Although both countries have similar shortcomings of obtaining carbon credits and its trade, of course Russia has a promising situation in comparison with Turkiye with respect to the amount of carbon sequestered and the likelihood of its trade potential at global level. [ABSTRACT FROM AUTHOR]

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Bamboo, a rapidly growing woody grass prevalent in pan-tropical zones, holds promising potential as a nature-based solution (NbS) for climate change mitigation. In this systematic review of 91 research articles, we critically assess the scope and constraints of bamboo's role in mitigating climate change across three dimensions: as a carbon sink in biomass form, as carbon storage in bamboo products, and as a contributor to carbon project credits. Our analysis reveals that existing studies disproportionately focus on 36 limited species, such as Phyllostachys pubescens and Bambusa vulgaris, with geographic concentration in Asia (91%) and limited studies from Africa (7%) and South America (1%). While many studies emphasize the carbon-saving benefits of bamboo products compared with traditional goods, there is a noticeable gap in comprehensive evaluations of carbon pools from individual bamboo forests encompassing all product varieties. While bamboo forests offer significant carbon trading potential, their global role is restricted by the absence of internationally accepted methodologies and the presence of debates about classifying bamboo as a tree species. This extensive review highlights the multifaceted value of bamboo in climate change mitigation, thereby highlighting its significance as a critical component for informed policymaking and the development of sustainable practices in future climate strategies worldwide. [ABSTRACT FROM AUTHOR]

State and local governments are increasingly interested in understanding the role forests and harvested wood products play in regional carbon sinks and storage, their potential contributions to state-level greenhouse gas (GHG) reductions, and the interactions between GHG reduction goals and potential economic opportunities. We used empirically driven process-based forest carbon dynamics and harvested wood product models in a systems-based approach to project the carbon impacts of various forest management and wood utilization activities in Maryland and Pennsylvania from 2007 to 2100. To quantify state-wide forest carbon dynamics, we integrated forest inventory data, harvest and management activity data, and remotely-sensed metrics of land-use change and natural forest disturbances within a participatory modeling approach. We accounted for net GHG emissions across (1) forest ecosystems (2) harvested wood products, (3) substitution benefits from wood product utilization, and (4) leakage associated with reduced in-state harvesting activities. Based on state agency partner input, a total of 15 management scenarios were modeled for Maryland and 13 for Pennsylvania, along with two climate change impact scenarios and two bioenergy scenarios for each state. Our findings show that both strategic forest management and wood utilization can provide substantial climate change mitigation potential relative to business-as-usual practices, increasing the forest C sink by 29% in Maryland and 38% in Pennsylvania by 2030 without disrupting timber supplies. Key climate-smart forest management activities include maintaining and increasing forest extent, fostering forest resiliency and natural regeneration, encouraging sustainable harvest practices, balancing timber supply and wood utilization with tree growth, and preparing for future climate impacts. This study adds to a growing body of work that quantifies the relationships between forest growth, forest disturbance, and harvested wood product utilization, along with their collective influence on carbon stocks and fluxes, to identify pathways to enhance forest carbon sinks in support of state-level net-zero emission targets.

Visual data on the geographic distribution of carbon storage help policy makers to formulate countermeasures for global warming. However, Taiwan, as an island showing diversity in climate and topography, had lacked valid visual data on the distribution of forest carbon storage between the last two forest surveys (1993–2015). This study established a model to estimate and illustrate the distribution of forest carbon storage. This model uses land use, stand morphology, and carbon conversion coefficient databases accordingly for 51 types of major forests in Taiwan. An estimation in 2006 was conducted and shows an overall carbon storage of 165.65 Mt C, with forest carbon storage per unit area of 71.56 t C ha−1, where natural forests and plantations respectively contributed 114.15 Mt C (68.9%) and 51.50 Mt C (31.1%). By assuming no change in land use type, the carbon sequestration from 2006 to 2007 by the 51 forest types was estimated to be 5.21 Mt C yr−1 using historical tree growth and mortality rates. The result reflects the reality of the land use status and the events of coverage shifting with time by combining the two forest surveys in Taiwan. [ABSTRACT FROM AUTHOR]

We present the results of a study on the climate forcing effects of replacing coal for power generation in the United Kingdom (UK) with wood pellets produced in northern Ontario, Canada. Continuous wood pellet production from two biomass sources were considered: fiber from increased harvesting of standing live trees (stemwood scenario) and from harvest residue provided by ongoing harvesting operations (residue scenario). In both scenarios, biomass was collected from harvesting operations in two forest management units (FMUs) with contrasting harvest residue treatments: natural decay of slash piles in the Hearst FMU and slash pile burning in the Kenora FMU. Life cycle emissions associated with wood pellets were assessed for production, transportation, and combustion to replace coal at a hypothetical power generating station in the UK. Greenhouse gas (GHG) emissions and removals in wood pellet and coal scenarios were assessed using two methods: global warming potential (GWP)-based mass balance and dynamic life cycle assessment (LCA) approaches. In the stemwood scenario, climate change mitigation from replacing coal with wood pellets was not achieved within the study timeline (2020–2100). In the residue scenario, immediate climate change mitigation was achieved with fiber sourced from the Kenora FMU where the current practice is to burn slash piles; for the Hearst FMU, where slash is allowed to decompose in the forest, climate change mitigation occurred 11.6 and 3.1 years after biomass collection began, as assessed by the mass balance and dynamic LCA methods, respectively. Factors affecting mitigation potential in the studied scenarios are discussed. [ABSTRACT FROM AUTHOR]

In the California compliance cap‐and‐trade carbon market, improved forest management (IFM) projects generate carbon credits in the initial reporting period if their initial carbon stocks are greater than a baseline. This baseline is informed by a "common practice" stocking value, which represents the average carbon stocks of surveyed privately owned forests that are classified into the same general forest type by the California Air Resources Board. Recent work has called attention to the need for more ecologically informed common practice carbon stocking values for IFM projects, particularly those in areas with sharp ecological gradients. Current methods for estimating common practice produce biases in baseline carbon values that lead to a clustering of IFM projects in geographical areas and ecosystem types that in fact support much greater forest carbon stocks than reflected in the common practice. This phenomenon compromises additionality, or the increases in carbon sequestration or decreases in carbon emissions that would not have occurred in the absence of carbon crediting. This study seeks to expand upon recent work on this topic and establish unbiased common practice estimates along sharp ecological gradients using methods that do not rely upon discrete forest classification. We generated common practice values for credited IFM projects in the Southern Cascades using a principal components analysis on species composition over an extensive forest inventory to determine the ecological similarity between inventoried forests and IFM project sites. Our findings strengthen the results of recent research suggesting common practice bias and adverse selection. At several sites, even after controlling for private ownership, 100% of the initial carbon stocks could be explained by ecological variables. This result means that improved management did not preserve or increase carbon stocks above what was typical, suggesting that no carbon offsets should have been issued for these sites. This result reveals greater bias than that been found at project sites in this region by research that has used discrete forest categorization. [ABSTRACT FROM AUTHOR]

Islands are hotspots of biological and cultural diversity that face growing threats from invasive species and climate change. Invasive mammal eradication on islands is a proven conservation intervention that prevents biodiversity loss and is a foundational activity for restoring degraded island-ocean ecosystems. However, these interventions are prioritized and evaluated primarily on biodiversity-based objectives despite growing evidence that invasive species removal may also serve as an effective nature-based solution to increase climate resilience of island-ocean ecosystems and contribute to climate change solution by protecting and restoring unique carbon stocks of native woody vegetation. To assess the effectiveness of interventions at the global scale, we developed a consistent and scalable framework for the long-term monitoring of tree cover, forest extent, forest carbon, and vegetation productivity in 1078 islands across 17 ecozones. Time-series of satellite-derived estimates of tree cover and the Normalized Difference Vegetation Index over 36 yr (1984–2020) were used to establish annual baselines and changes in forest extent, carbon stocks, and vegetation productivity. The analysis revealed significant and sustained positive trends in all the indices on islands with eradication. The magnitude and potential biological relevance of these effects was highly variable across ecozones, but the overall sustained effects provide strong evidence of a positive ecosystem response to invasive mammal removal. We also found that, collectively, these islands sustain more than 940 000 ha of forest and 53 million MgC of forest carbon. This novel framework enables measuring the climate co-benefits of island restoration interventions in relevant policy terms using a low cost and globally consistent methodology that is applicable across the range of spatial and temporal scales pertinent to ecosystem recovery dynamics on islands.

Climate change mitigation by increased paper recycling can alleviate the two-sided pressure on the Swedish forest sector: supplying growing demands for wood-based products and increasing the forest carbon sink. This study assesses two scenarios for making use of a reduced demand for primary pulp resulting from an increased paper recycling rate in Sweden, from the present 72% to 78%. A Conservation scenario uses the saved primary pulp to reduce pulplog harvests so as to increase the forest carbon sink concomitant with constant overall wood product supply. In contrast, a Substitution scenario uses the saved primary pulp to produce man-made cellulosic fibers (MMCF) from dissolving pulp replacing cotton fiber, implying increased overall wood product supply. Our results suggest that utilizing efficiency gains in paper recycling to reduce pulplog harvests is better from a climate change mitigation perspective than producing additional MMCF to substitute cotton fiber. This conclusion holds even when assuming the use of by-products from dissolving pulp making and an indirect increase in MMCF availability. Hence, unless joint improvements across the value chain materialize, the best climate change mitigation option from increased paper recycling in Sweden would seemingly be to reduce fellings rather than producing additional MMCF.

Abstract Fossil‐based emissions can be avoided by using wood in place of non‐renewable raw materials as energy and materials. However, wood harvest influences forest carbon stocks. Increased harvest may reduce the overall climate benefit of wood use significantly, but is widely overlooked. We reviewed selected simulation studies and compared differences in forest carbon and amount of wood harvested between harvest scenarios of different intensities for three different time perspectives: short‐ (1–30 years), mid‐ (31–70 years), and long‐term (71–100 years). Out of more than 450 reviewed studies 45 provided adequate data. Our results show that increased harvest reduces carbon stocks over 100 years in temperate and boreal forests by about 1.6 (stdev 0.9) tC per tC harvested (referred to as carbon balance indicator (CBI)). CBI proved to be robust when outliers explicitly influenced by factors other than changes in the harvest rate, such as fertilization or increase in forest area, were removed. The carbon impacts tend to be greatest in the mid‐term, but no significant difference in was found for average values between short and long time‐horizons. CBI can be interpreted as carbon opportunity costs of wood harvest in forests. Our results indicate that even after 100 years, CBI is significant compared to the typical GHG credits expected in the technosphere by avoiding fossil emissions in substitution and increasing carbon stocks in harvested wood products. Our estimates provide typical values that can directly be included in GHG balances of products or assessments of mitigation policies and measures related to wood use. However, more systematic scenarios with transparent information on influencing factors for forest carbon stocks are required to provide better constrained estimates for specific forest types.

Trees can invest up to one-third of the carbon (C) fixed by photosynthesis into belowground allocation, including fine root exudation into the rhizosphere. It is still unclear how climate and soil warming affect tree root C exudation, in particular quantifying longer-term warming effects remains a challenge. In this study, using a C-free cuvette incubation method, in situ C exudation rates from tree fine roots of a mature spruce dominated temperate forest were measured in regular intervals during the 14th and 15th year of experimental soil warming (+ 4°C). In addition, a short-term temperature sensitivity experiment (up to + 10°C warming within 4 days) was conducted to determine the inherent temperature sensitivity of root exudation. Root exudation rates in the long-term warmed soil (17.9 μg C g–1 root biomass h–1) did not differ from those in untreated soil (16.2 μg C g–1 root biomass h–1). However, a clear increase (Q10 ∼5.0) during the short-term temperature sensitivity experiment suggested that fine root exudation can be affected by short-term changes in soil temperature. The absence of response in long-term warmed soils suggests a downregulation of C exudation from the individual fine roots in the warmed soils. The lack of any relationship between exudation rates and the seasonal temperature course, further suggests that plant phenology and plant C allocation dynamics have more influence on seasonal changes in fine root C exudation. Although exudation rates per g dry mass of fine roots were only marginally higher in the warmed soil, total fine root C exudation per m2 soil surface area increased by ∼30% from 0.33 to 0.43 Mg C ha–1 yr–1 because long-term soil warming has led to an increase in total fine root biomass. Mineralization of additional fine root exudates could have added to the sustained increase in soil CO2 efflux from the warmed forest soil at the experimental site.

A changing climate is altering ecosystem carbon dynamics with consequences for natural systems and human economies, but there are few tools available for land managers to meaningfully incorporate carbon trajectories into planning efforts. To address uncertainties wrought by rapidly changing conditions, many practitioners adopt resistance and resilience as ecosystem management goals, but these concepts have proven difficult to monitor across landscapes. Here, we address the growing need to understand and plan for ecosystem carbon with concepts of resistance and resilience. Using time series of carbon fixation (n = 103), we evaluate forest management treatments and their relative impacts on resistance and resilience in the context of an expansive and severe natural disturbance. Using subalpine spruce–fir forest with a known management history as a study system, we match metrics of ecosystem productivity (net primary production, g C m−2 year−1) with site‐level forest structural measurements to evaluate (1) whether past management efforts impacted forest resistance and resilience during a spruce beetle (Dendroctonus rufipennis) outbreak, and (2) how forest structure and physiography contribute to anomalies in carbon trajectories. Our analyses have several important implications. First, we show that the framework we applied was robust for detecting forest treatment impacts on carbon trajectories, closely tracked changes in site‐level biomass, and was supported by multiple evaluation methods converging on similar management effects on resistance and resilience. Second, we found that stand species composition, site productivity, and elevation predicted resistance, but resilience was only related to elevation and aspect. Our analyses demonstrate application of a practical approach for comparing forest treatments and isolating specific site and physiographic factors associated with resistance and resilience to biotic disturbance in a forest system, which can be used by managers to monitor and plan for both outcomes. More broadly, the approach we take here can be applied to many scenarios, which can facilitate integrated management and monitoring efforts. [ABSTRACT FROM AUTHOR]

This study examines the landscape distribution of aboveground biomass (AGB) in fragmented tropical rainforests in Sri Lanka. While most attribute AGB losses from fragmentation to abiotic edge effects (e.g., desiccation and wind), land tenure and human disturbance also play a significant role. In South Asia, forest fragments are essential food, medicine, and wood sources for large rural populations. Despite this, few studies have addressed AGB dynamics in smallholder landscapes with a long land clearance and cultivation history. This study explored three objectives: (a) assessing the accuracy of a common allometric height-diameter model, (b) comparing AGB stocks in forest fragments to primary forests, and (c) examining the influence of land tenure, abiotic edge effects, and human disturbance on AGB distribution. We estimated AGB using field-based measurements in 18 forest fragments and two primary forest sites and employed mixed effects models to explore the landscape distribution of AGB. The allometric height-diameter model overestimated fragment tree heights compared to measured heights, leading to an overestimation of AGB by 25 %. AGB stocks were significantly lower in fragmented forests (259.9 Mg ha−1) than in primary forests (434.5 Mg ha−1), and there was no significant correlation between plot AGB and variables associated with abiotic edge effects (i.e., distance-to-edge, fragment size, isolation). However, AGB positively correlated with factors related to decreased accessibility and local land ownership. These findings suggest that land tenure and human disturbance strongly influence the current AGB distribution in Sri Lankan rainforest fragments, emphasizing the need to understand human impacts for effective conservation and management. • Forest fragments store as much as 42 % less aboveground biomass than primary forests. • Fragments contain trees with lower wood densities. • Aboveground biomass in fragments is more associated with land tenure and human disturbance than abiotic edge effects. • Recommend including more community-based, local management in carbon projects. [ABSTRACT FROM AUTHOR]

Several recent studies point out that climate change is expected to influence boreal forest succession, disturbances, productivity, and mortality. However, the effect of climate change on those processes and their interactions is poorly understood. We used an ecophysiological-based mechanistic landscape model to study those processes and their interactions and predict the future productivity and composition under climate change scenarios (RCP) for 300 years (2010–2310). The effects of climate change and wildfires on forest composition, biomass carbon sequestration and storage, and mortality were assessed in three management units of Quebec boreal forest, distributed along a longitudinal gradient from west to east: North-of-Quebec (MU1), Saguenay–Lac-Saint-Jean (MU2), and Côte-Nord region (MU3). Coniferous mortality variation was explained by competitive exclusion and wildfires, which are related to climate change. In the studied MU, we found a decrease in coniferous pure occupancy at the landscape scale and an increase in mixed deciduous forests in MU1 and MU2, and an increase in mixed coniferous, mainly black spruce and balsam fir in MU3. On the other hand, for extreme scenarios (RCP4.5 and RCP8.5), in the absence of broadleaves dispersal, the open woodland occupancy could increase to more than 8, 22, and 10% in MU1, MU2, and MU3 respectively. Also, climate change might increase overall biomass carbon stock two times for RCP2.6 and RCP4.5 scenarios compared to the baseline this may be explained by the extension of the growing season and the reduction of potential cold-temperature injuries. Generally, western regions were more sensitive to climate changes than the eastern regions (MU3), in fact under RCP8.5 biomass carbon stock will be decreasing in the long-term for MU1 compared to the current climate. This study provides a good starting point to support future research on the multiple factors affecting forest C budget under global change.

A campaign is underway to clear established forests and expand early-successional habitats—also called young forest, pre-forest, early seral, or open habitats—with the intention of benefitting specific species. Coordinated by federal and state wildlife agencies, and funded with public money, public land managers work closely with hunting and forestry interests, conservation organizations, land trusts, and private landowners toward this goal. While forest-clearing has become a major focus in the Northeast and Upper Great Lakes regions of the U.S., far less attention is given to protecting and recovering old-forest ecosystems, the dominant land cover in these regions before European settlement. Herein we provide a discussion of early-successional habitat programs and policies in terms of their origins, in the context of historical baselines, with respect to species’ ranges and abundance, and as they relate to carbon accumulation and ecosystem integrity. Taken together, and in the face of urgent global crises in climate, biodiversity, and human health, we conclude that public land forest and wildlife management programs must be reevaluated to balance the prioritization and funding of early-successional habitat with strong and lasting protection for old-growth and mature forests, and, going forward, must ensure far more robust, unbiased, and ongoing monitoring and evaluation.

TreeSim is an open-source, user-extendable framework that offers new opportunities for users to model, simulate, visualize, and animate the dynamics of forest. It provides a general environment for modellers to implement and evaluate forest growth models. In this paper, we introduce the object-oriented architecture for our proposed simulator and examine its performance to model and simulate forest growth, management, and dynamics. The simulator uses various models to predict the dynamics and attributes of forest (e.g., regeneration, increment, mortality, biodiversity, biomass, carbon, dead wood). Finally, TreeSim can be integrated into a simulation–optimization framework for decision-making support.

Abstract Forest biomass estimation at large scale is challenging and generally entails large uncertainty in tropical regions. With their wall‐to‐wall coverage ability, passive remote sensing signals are frequently used to extrapolate field estimates of forest aboveground biomass (AGB). However, studies often use limited reference data and/or flawed validation schemes and thus report unreliable extrapolation error estimates. Here, we compared the ability of three medium‐ to high‐resolution passive satellite sensors, Landsat‐8 (L8), Sentinel‐2B (S2) and Worldview‐3 (WV3), to map AGB in a forest landscape of Thailand. We used a large airborne LiDAR‐derived AGB dataset as a reference to train and validate a random forest algorithm and conducted robust error assessments and variable selection using spatialized cross‐validations. Our results indicate that the selected predictors strongly varied among the three sensors and between analyses restricted to low (≤200 Mg ha−1) and high (>200 Mg ha−1) AGB areas. WV3 and S2 data outperformed L8 data to extrapolate AGB (RMSE of 68 and 72 against 84 Mg ha−1, respectively) due to the inclusion of the red‐edge band and, probably, to their higher spatial and spectral resolution. Sensitivity to large AGB values was higher for WV3 than for S2 and L8 with saturation point of 247 Mg ha−1 against 204 and 192 Mg ha−1. AGB values above these saturation points remained poorly predictable, especially for L8, indicating that several tropical forest AGB maps should be interpreted with extreme caution. However, predicted gradients of lower AGB values (≤200 Mg ha−1), i.e., in early forest successional stages, were fairly consistent among sensors (r > 0.70), even if the mean absolute difference between estimates was large when AGB predictions were extrapolated out of the calibration area at regional level (34%). We finally showed that calibrating the model only within the sensitivity AGB domain (e.g.,