Forest Contribution to Climate Change Mitigation: Management Oriented to Carbon Capture and Storage

Underlying plant trait strategies for understanding the carbon sequestration in Banj oak Forest of Himalaya

Plant functional attributes are subjected to environmental adjustments, which lead to modulations in forest processes under environmental changes. However, a comprehensive assessment of the relationships between plant traits and carbon stock remains subtle. The present study attempted to accomplish the gap of knowledge by examining the linkages between forest carbon with plant traits within the Banj Oak forest in the Garhwal Himalaya. Twelve individuals from three major species in the Banj Oak forest were randomly selected for trait measurements, and soil samples were collected randomly across the area for evaluation of soil nutrients and carbon. Forest biomass and soil carbon were estimated following standard protocols. A Structural Equation Model (SEM) was applied to establish the relationship between above ground carbon (AGC) and soil organic carbon (SOC) with leaf and stem traits, and soil nutrients. Stem traits were tree height and tree diameter; whereas leaf morphological traits were leaf area, specific leaf area, leaf dry matter content; leaf physiological traits were photosynthesis rate, stomatal conductance, and transpiration rate; and leaf biochemical traits were leaf carbon concentration, leaf nitrogen concentration, and leaf phosphorus concentration. Soil nutrients were available nitrogen, available phosphorus, and exchangeable potassium. Based on SEM results, AGC of the forest was positively correlated with stem traits and leaf physiological traits, while negatively correlated with leaf morphological traits. SOC was positively correlated with soil nutrients and leaf biochemical traits, whereas negatively correlated with stem traits. These findings may support for precise quantification of forest carbon and modeling of forest carbon stocks besides providing inputs to forest managers for devising effective forest management strategies.

Mycorrhizosphere bacteria inhibit greenhouse gas emissions from microplastics contaminated soil by regulating soil enzyme activities and microbial community structure

Microplastics (MPs) accumulation in terrestrial ecosystems can affect greenhouse gases (GHGs) production by altering microbial and soil structure. Presently, research on the MPs effect on plants is not consistent, and underlying molecular mechanisms associated with GHGs are yet unknown. For the first time, we conducted a microcosm study to explore the impact of MPs addition (Raw vs. aged) and Trichoderma longibrachiatum and Bacillus subtilis inoculation (Sole vs. combination) on GHGs emission, soil community structure, physiochemical properties, and enzyme activities. Our results indicated that the addition of aged MPs considerably enhanced the GHGs emissions (N2O (+16%) and CO2 (+21%), respectively), C and N cycling gene expression, microbial biomass carbon, and soil physiochemical properties than raw MPs. However, the soil microbial community structure and enzyme activities were enhanced in raw MPs added treatments, irrespective of the MPs type added to soil. However, microbial inoculation significantly reduced GHGs emission by altering the expression of C and N cycling genes in both types of MPs added treatments. The soil microbial community structure, enzymes activities, physiochemical properties and microbial biomass carbon were enhanced in the presence of microbial inoculation in both type of MPs. Among sole and combined inoculation of Trichoderma and Bacillus subtilis, the co-applied Trichoderma and Bacillus subtilis considerably reduced the GHGs emission (N2O (-64%) and CO2 (-61%), respectively) by altering the expression of C and N cycling genes regardless of MPs type used. The combined inoculation also enhanced soil enzyme activities, microbial community structure, physiochemical properties and microbial biomass carbon in both types of MPs treatment. Our findings provide evidence that polyethylene MPs likely pose a high risk of GHGs emission while combined application of Trichoderma and Bacillus subtilis significantly reduced GHGs emission by altering C and N cycling gene expression, soil microbial community structure, and enzyme activities under MPs pollution in a terrestrial ecosystem.

The Society of Information and the European Citizens' Perception of Climate Change: Natural or Anthropological Causes

The scientific community has reached a consensus on humans' important role as causative agents of climate change; however, branches of society are still sceptical about this. Climate change is a key issue for humanity and only the commitment to change human attitudes and lifestyles, at the global level, can be effective in its mitigation. With this purpose, it is important to convey the right message and prevent misinformation to manipulate people's minds. The present study aims to understand the factors shaping European citizens' thoughts on the causes of climate change. Using data from the European Social Survey 10 collected in 2022, we fitted statistical models using the people's thoughts on causes of climate change (natural, anthropogenic or both) as dependent variables. As independent variables, we used the impact of the media through time spent on news and time spent on the internet, level of education, level of trust in scientists, awareness of online or mobile misinformation and gender. We concluded that the typical European citizen who believes in anthropogenic causes of climate change is a female, is more literate, trusts more in scientists, is younger, spends more time reading the news and has more awareness of misinformation presence in online and mobile communications.

The impact of wind energy on plant biomass production in China

Global wind power expansion raises concerns about its potential impact on plant biomass production (PBP). Using a high-dimensional fixed effects model, this study reveals significant PBP reduction due to wind farm construction based on 2404 wind farms, 108,361 wind turbines, and 7,904,352 PBP observations during 2000-2022 in China. Within a 1-10 km buffer, the normalized differential vegetation and enhanced vegetation indices decrease from 0.0097 to 0.0045 and 0.0075 to 0.0028, respectively. Similarly, absorbed photosynthetically active radiation and gross primary productivity decline from 0.0094 to 0.0034% and 0.0003-0.0002 g*C/m2 within a 1-7 km buffer. Adverse effects last over three years, magnified in summer and autumn, and are more pronounced at lower altitudes and in plains. Forest carbon sinks decrease by 12,034 tons within a 0-20 km radius, causing an average economic loss of $1.81 million per wind farm. Our findings underscore the balanced mitigation strategies for renewable energy transition when transiting from fossil fuels.

The Carbon Sink Potential of Southern China After Two Decades of Afforestation

Afforestation and land use changes that sequester carbon from the atmosphere in the form of woody biomass have turned southern China into one of the largest carbon sinks globally, which contributes to mitigating climate change. However, forest growth saturation and available land that can be forested limit the longevity of this carbon sink, and while a plethora of studies have quantified vegetation changes over the last decades, the remaining carbon sink potential of this area is currently unknown. Here, we train a model with multiple predictors characterizing the heterogeneous landscapes of southern China and predict the biomass carbon carrying capacity of the region for 2002-2017. We compare observed and predicted biomass carbon density and find that during about two decades of afforestation, 2.34 PgC have been sequestered between 2002 and 2017, and a total of 5.32 Pg carbon can potentially still be sequestrated. This means that the region has reached 73% of its aboveground biomass carbon carrying capacity in 2017, which is 12% more than in 2002, equal to a decrease of 0.77% per year. We identify potential afforestation areas that can still sequester 2.39 PgC, while old and new forests have reached 87% of their potential with 1.85 PgC remaining. Our work locates areas where vegetation has not yet reached its full potential but also shows that afforestation is not a long-term solution for climate change mitigation.

Biodiversity Conservation of National Parks and Nature-Protected Areas in West Africa: The Case of Kainji National Park, Nigeria

Due to rising global warming and climate change, biodiversity protection has become a critical ecological concern. Rich biodiversity zones are under threat and are deteriorating, necessitating national, regional, and provincial efforts to safeguard these natural areas. The effective conservation of national parks and nature-protected areas help to improve biodiversity conservation, forest, and urban air quality. The continuous encroachment and abuse of these protected areas have degraded the ecosystem over time. While exploring the geophysical ecology and biodiversity conservation of these areas in West Africa, Kainji National Park was selected for this study because of its notable location, naturalness, rich habitat diversity, topographic uniqueness, and landmass. The conservation of national parks and nature-protected areas is a cornerstone of biodiversity conservation globally. This study is aimed at the target United Nations’ Sustainable Development Goal 13, 2030—Climate Action targeted at taking urgent action towards combating climate change and its impacts. The study captures both flora and fauna that are dominant in the study area. The 15 identified tree species were selected from over 30 species with 563,500,000 (an average of 3,700,000 in each sample frame) trees for every tree species/type with a total of 63% tree green canopy cover. The study areas divided into three zones were randomly sampled within a stratum of 25 × 25 km frames divided into 150 sample frames for proper analyses using the i-Tree Eco v6.0.25. It is a United States Department of Agriculture (USDA) Forest Service peer-reviewed application (software) designed which includes tools for urban and rural forestry study and benefits evaluations. The following microclimatic data were captured and analyzed photosynthetically active radiation, rain/precipitation, temperature, transpiration, evaporation, water intercepted by trees, runoff avoided by trees, potential evaporation by trees, and isoprene and monoterpene by trees. This study also further discusses the tree benefits of a green, low carbon, and sustainable environment within the context of biodiversity conservation, considering carbon storage, carbon sequestration, hydrology effects, pollution removal, oxygen production, and volatile organic compounds (VOCs). There is a quick need for remotely-sensed information about the national parks, protected areas and nature reserves at regular intervals, and government policies must be strict against illegal poaching, logging activities, and other hazardous human impacts.

Recovery of Carbon and Vegetation Diversity 23 Years after Fire in a Tropical Dryland Forest of Indonesia

Understanding the recovery rate of forest carbon stocks and biodiversity after disturbance, including fire, is vital for developing effective climate-change-mitigation policies and actions. In this study, live and dead carbon stocks aboveground, belowground, and in the soil to a 30 cm depth, as well as tree and shrub species diversity, were measured in a tropical lowland dry forest, 23 years after a fire in 1998, for comparison with adjacent unburned reference forests. The results showed that 23 years since the fire was insufficient, in this case, to recover live forest carbon and plant species diversity, to the level of the reference forests. The total carbon stock, in the recovering 23-year-old forest, was 199 Mg C ha−1 or about 90% of the unburned forest (220 Mg C ha−1), mainly due to the contribution of coarse woody debris and an increase in the 5–10 cm soil horizon’s organic carbon, in the burned forest. The carbon held in the live biomass of the recovering forest (79 Mg C ha−1) was just over half the 146 Mg C ha−1 of the reference forest. Based on a biomass mean annual increment of 6.24 ± 1.59 Mg ha−1 yr−1, about 46 ± 17 years would be required for the aboveground live biomass to recover to equivalence with the reference forest. In total, 176 plant species were recorded in the 23-year post-fire forest, compared with 216 in the unburned reference forest. The pioneer species Macaranga gigantea dominated in the 23-year post-fire forest, which was yet to regain the similar stand structural and compositional elements as those found in the adjacent unburned reference forest.

Enabling Breeding Selection for Biomass in Slash Pine Using UAV-Based Imaging

Traditional methods used to monitor the aboveground biomass (AGB) and belowground biomass (BGB) of slash pine (Pinus elliottii) rely on on-ground measurements, which are time- and cost-consuming and suited only for small spatial scales. In this paper, we successfully applied unmanned aerial vehicle (UAV) integrated with structure from motion (UAV-SfM) data to estimate the tree height, crown area (CA), AGB, and BGB of slash pine for in slash pine breeding plantations sites. The CA of each tree was segmented by using marker-controlled watershed segmentation with a treetop and a set of minimum three meters heights. Moreover, the genetic variation of these traits has been analyzed and employed to estimate heritability (h 2). The results showed a promising correlation between UAV and ground truth data with a range of R 2 from 0.58 to 0.85 at 70 m flying heights and a moderate estimate of h 2 for all traits ranges from 0.13 to 0.47, where site influenced the h 2 value of slash pine trees, where h 2 in site 1 ranged from 0.13~0.25 lower than that in site 2 (range: 0.38~0.47). Similar genetic gains were obtained with both UAV and ground truth data; thus, breeding selection is still possible. The method described in this paper provides faster, more high-throughput, and more cost-effective UAV-SfM surveys to monitor a larger area of breeding plantations than traditional ground surveys while maintaining data accuracy.

Decreased Irradiance and Nutrient Enrichment Mitigate the Negative Effect of Ocean Warming on Growth and Biochemical Compositions of a Canopy-Forming Marine Macroalga

Heatwaves under global warming have negative impacts on ecosystem primary producers. This warming effect may be synergized or antagonized by local environments such as light and nutrient availability. However, little is known about the interactive effects of warming, irradiance, and nutrients on physiology of marine macroalgae, which are dominant in coastal ecosystems. The present study examined the combined effects of warming (23 and 26 °C), irradiance (30 and 150 µmol photon m−2 s−1), and nutrients (enriched and non-enriched) on specific growth rate (SGR) and biochemical compositions of the canopy-forming marine macroalga Sargassum fusiforme. The negative effect of warming on SGR and ratio of chlorophyll (Chl) c to Chl a was antagonized by decreased irradiance. Moreover, the negative effect of temperature elevation on carbon content was antagonized by nutrient enrichment. These results suggest that the effect of warming on the growth and carbon accumulation of this species can be mitigated by decreased irradiance and nutrient enrichment.

Improving Forest Baseline Maps in Tropical Wetlands Using GEDI-Based Forest Height Information and Sentinel-1

Remote Sensing-based global Forest/Non-Forest (FNF) masks have shown large inaccuracies in tropical wetland areas. This limits their applications for deforestation monitoring and alerting in which they are used as a baseline for mapping new deforestation. In radar-based deforestation monitoring, for example, moisture dynamics in unmasked non-forest areas can lead to false detections. We combined a GEDI Forest Height product and Sentinel-1 radar data to improve FNF masks in wetland areas in Gabon using a Random Forest model. The GEDI Forest Height, together with texture metrics derived from Sentinel-1 mean backscatter values, were the most important contributors to the classification. Quantitatively, our mask outperformed existing global FNF masks by increasing the Producer’s Accuracy for the non-forest class by 14%. The GEDI Forest Height product by itself also showed high accuracies but contained Landsat artifacts. Qualitatively, our model was best able to cleanly uncover non-forest areas and mitigate the impact of Landsat artifacts in the GEDI Forest Height product. An advantage of the methodology presented here is that it can be adapted for different application needs by varying the probability threshold of the Random Forest output. This study stresses that, in any application of the suggested methodology, it is important to consider the UA/PA trade-off and the effect it has on the classification. The targeted improvements for wetland forest mapping presented in this paper can help raise the accuracy of tropical deforestation monitoring.

Assessment of optimal conditions for the performance of greenhouse gas removal methods

In this study, a comparative literature-based assessment of the impact of operational factors such as climatic condition, vegetation type, availability of land, water, energy and biomass, management practices, cost and soil characteristics was carried out on six greenhouse gas removal (GGR) methods. These methods which include forestation, enhanced weathering (EW), soil carbon sequestration (SCS), biochar, direct air capture with carbon storage (DACCS) and bioenergy with carbon capture and storage (BECCS) were accessed with the aim of identifying the conditions and requirements necessary for their optimum performance. The extent of influence of these factors on the performance of the various GGR methods was discussed and quantified on a scale of 0-5. The key conditions necessary for optimum performance were identified with forestation, EW, SCS and biochar found to be best deployed within the tropical and temperate climatic zones. The CCS technologies (BECCS and DACCS) which have been largely projected as major contributors to the attainment of the emission mitigation targets were found to have a larger locational flexibility. However, the need for cost optimal siting of the CCS plant is necessary and dependent on the presence of appropriate storage facilities, preferably geological. The need for global and regional cooperation as well as some current efforts at accelerating the development and deployment of these GGR methods were also highlighted.

Howland Forest, ME, USA: Multi-Gas Flux (CO2, CH4, N2O) Social Cost Product Underscores Limited Carbon Proxies

Forest carbon sequestration is a widely accepted natural climate solution. However, methods to determine net carbon offsets are based on commercial carbon proxies or CO2 eddy covariance research with limited methodological comparisons. Non-CO2 greenhouse gases (GHG) (e.g., CH4, N2O) receive less attention in the context of forests, in part, due to carbon denominated proxies and to the cost for three-gas eddy covariance platforms. Here we describe and analyze results for direct measurement of CO2, CH4, and N2O by eddy covariance and forest carbon estimation protocols at the Howland Forest, ME, the only site where these methods overlap. Limitations of proxy-based protocols, including the exclusion of sink terms for non-CO2 GHGs, applied to the Howland project preclude multi-gas forest products. In contrast, commercial products based on direct measurement are established by applying molecule-specific social cost factors to emission reductions creating a new forest offset (GHG-SCF), integrating multiple gases into a single value of merit for forest management of global warming. Estimated annual revenue for GHG-SCF products, applicable to the realization of a Green New Deal, range from ~$120,000 USD covering the site area of ~557 acres in 2021 to ~$12,000,000 USD for extrapolation to 40,000 acres in 2040, assuming a 3% discount rate. In contrast, California Air Resources Board compliance carbon offsets determined by the Climate Action Reserve protocol show annual errors of up to 2256% relative to eddy covariance data from two adjacent towers across the project area. Incomplete carbon accounting, offset over-crediting and inadequate independent offset verification are consistent with error results. The GHG-SCF product contributes innovative science-to-commerce applications incentivizing restoration and conservation of forests worldwide to assist in the management of global warming.

Parent Material Effect on Soil Organic Carbon Concentration under Primeval European Beech Forests at a Regional Scale

The research presented herein explores soil organic carbon concentration (SOCC) under monodominant primeval forests of European beech trees and their association with parent material on a regional scale. Soil sampling to a maximum depth of 0.8 m was conducted in six localities in the West, East, and South Carpathians, Eastern Albanides, and Central Apennines, situated on different parent materials. Samples were analysed for SOCC by the dry combustion method. The average SOCC values representing individual localities ranged from 12.5 g kg−1 to 154.8 g kg−1 with a 99.7% coefficient of variation. SOCC association with climatic variables and forest stand volume data available from the literature were assessed by a Pearson correlation coefficient. Differences in SOCC among localities caused by site conditions were treated as a fixed factor in Welch’s ANOVA and found to be significant (p < 0.05) in the majority of cases. The associations between SOCC and climatic variables or stand volume were nonsignificant or perturbed. Since they validly explained less than 10% of the overall SOCC variance, the results of multiple comparison tests were assessed and interpreted in view of distinct parent materials.

Forest Resource Management and Its Climate-Change Mitigation Policies in Taiwan

Based on high carbon emissions in recent years (i.e., about 11 metric tons in 2018) per capita in terms of carbon dioxide equivalents, Taiwan has actively development greenhouse gas (GHG) reduction action plans. One of the action plans has been to promote afforestation and reforestation in non-forested lands for carbon sequestration. Thus, this paper aims to address the forest resources in Taiwan by using the latest national survey, reporting on an interactive analysis of forest carbon sequestration, GHG emissions, and climate-change mitigation policies. In this regard, the methodology is based on the official websites of forest resources, GHG emissions, and carbon sequestration from the yearbooks, national statistics, and regulations relevant to the mitigation policies in the forestry sector. It is found that Taiwan’s forest area is estimated to be 2.197 million hectares, which corresponds to a total forest stock volume of about 502.0 million cubic meters. During the period of 1990–2018, the change in total carbon sequestration did not vary much (with the exception of 2009), decreasing from 23.4 million metric tons in 1990 to 21.4 million metric tons in 2018. Compared to the total carbon dioxide emissions (i.e., 102.4 million metric tons in 1990 and 282.8 million metric tons in 2018), the contribution to GHG mitigation in the forestry sector shows a declining trend. However, biomass (i.e., wood) carbon sequestration indicates a slight increase from 20.4 million metric tons in 2010 to 20.7 million metric tons in 2018 due to the afforestation policy. Obviously, regulatory policies, based on the Forestry Act and the Greenhouse Gas Reduction & Management Act in 2015, play a vital role in mitigating GHG emissions in Taiwan. The discussion on the regulations is further addressed to highlight climate-change mitigation policies in Taiwan’s forestry sector.

Modeling the Soil Response to Rainstorms after Wildfire and Prescribed Fire in Mediterranean Forests

The use of the Soil Conservation Service-curve number (SCS-CN) model for runoff predictions after rainstorms in fire-affected forests in the Mediterranean climate is quite scarce and limited to the watershed scale. To validate the applicability of this model in this environment, this study has evaluated the runoff prediction capacity of the SCS-CN model after storms at the plot scale in two pine forests of Central-Eastern Spain, affected by wildfire (with or without straw mulching) or prescribed fire and in unburned soils. The model performance has been compared to the predictions of linear regression equations between rainfall depth and runoff volume. The runoff volume was simulated with reliability by the linear regression only for the unburned soil (coefficient of Nash and Sutcliffe E = 0.73–0.89). Conversely, the SCS-CN model was more accurate for burned soils (E = 0.81–0.97), also when mulching was applied (E = 0.96). The performance of this model was very satisfactory in predicting the maximum runoff. Very low values of CNs and initial abstraction were required to predict the particular hydrology of the experimental areas. Moreover, the post-fire hydrological “window-of-disturbance” could be reproduced only by increasing the CN for the storms immediately after the wildfire. This study indicates that, in Mediterranean forests subject to the fire risk, the simple linear equations are feasible to predict runoff after low-intensity storms, while the SCS-CN model is advisable when runoff predictions are needed to control the flooding risk.

Continuous Forest Monitoring Using Cumulative Sums of Sentinel-1 Timeseries

Forest degradation is recognized as a major environmental threat on a global scale. The recent rise in natural and anthropogenic destruction of forested ecosystems highlights the need for developing new, rapid, and accurate remote sensing monitoring systems, which capture forested land transformations. In spite of the great technological advances made in airborne and spaceborne sensors over the past decades, current Earth observation (EO) change detection methods still need to overcome numerous limitations. Optical sensors have been commonly used for detecting land use and land cover changes (LULCC), however, the requirement of certain technical and environmental conditions (e.g., sunlight, not cloud-coverage) restrict their use. More recently, synthetic aperture radar (SAR)-based change detection approaches have been used to overcome these technical limitations, but they commonly rely on static detection approaches (e.g., pre and post disturbance scenario comparison) that are slow to monitor change. In this context, this paper presents a novel approach for mapping forest structural changes in a continuous and near-real-time manner using dense Sentinel-1 image time-series. Our cumulative sum–spatial mean corrected (CUSU-SMC) algorithm approach is based on cumulative sum statistical analysis, which allows the continuous monitoring of radar signal variations, derived from forest structural change. Taking advantage of the high data availability offered by the Sentinel-1 (S-1) C-band constellation, we used an S-1 ground range detected (GRD) dual (VV, VH) polarization timeseries, formed by a total of 84 images, to monitor clear-cutting operations carried out in a Scottish forest during 2019. The analysis showed a user’s accuracy of 82% for the (conservative) detection approach. The use of a post-processing neighbor filter increased the detection performance to a user’s accuracy of 86% with an overall accuracy of 77% for areas of a minimum extent of 0.4 ha. To further validate the detection performance of the method, the CUSU-SMC change detector was tested against commonly-used pairwise change detection approaches for the same period. These results emphasize the capabilities of dense SAR time-series for environmental monitoring and provide a useful tool for optimizing national forest inventories.

Control of Invasive Forest Species through the Creation of a Value Chain: Acacia dealbata Biomass Recovery

In Portugal, some species are now considered invasive by law and have proliferated in recent years. Among these, Acacia dealbata stands out. This work investigated the behavior of this species, in order to characterize and evaluate its potential as raw material for biomass pellets production, while controlling its proliferation. It was found that A. dealbata has a large capacity for raw material supply, as cutting 2 ha resulted in about 140 tons of biomass. Thus, the attribution of a market value for this material could result in a reduction in the area occupied by the invasive species, once the demand for it increases, causing a pressure over the resource. This pressure on the species must be duly followed by other control measures, such as reducing the population and mitigating its proliferation. Laboratory tests have shown that both the raw material and the finished product are similar to those obtained with other species normally used for biomass pellet production, such as Pinus pinaster and Eucalyptus globulus. Thus, it can be concluded that there is a high potential for this species in the production of biomass pellets for energy, and that this may be an important contribution to controlling the proliferation of this invasive species.