Forest Research Research Articles

Constraining light dependency in modeled emissions through comparison to observed biogenic volatile organic compound (BVOC) concentrations in a southeastern US forest

Abstract. Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated biogenic volatile organic compound (BVOC) measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA, for the year 2020 with emissions estimated by the Model of Emissions of Gases and Aerosols from Nature version 3.2 (MEGANv3.2). The emissions were subjected to oxidation in a 0-D box model (F0AM v4.3) to generate time series of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability in regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDFα-pinene=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using an LDF =0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions–chemistry model constrained by regional concentrations of NOX and O3.

Mango forest Soil Nutritional Components Analysis and Research in Dong District of Panzhihua City

Purpose: the pH value of soil determines soil properties and determines whether the activities of plants and microbes in the soil are active or not. A large number of elements such as nitrogen, phosphorous and potassium in soil can reflect a basic characteristic of soil and play a guiding role in further fertilization and soil improvement. Organic matter can reflect the amount of humus in the soil, whether the soil is fertile, the fertility of the soil, and the activities of microbes in the soil. So, this study will focus on exploring the soil pH value, N, P, K factors such as organic matter, because the subjects as the mango trees, and Panzhihua is a large amount of planting mango region, therefore, to appeal the influence of factors on the mango is very direct, hope that the result of the experiment can provide some basic data on mango cultivation, to help farmers to further understanding of the nature of soil and fertilization. Methods: chemical measuring methods were applied to determine the soil pH, organic matter and N, P, K values or concentrations. Results: the average available phosphorus in the whole experimental area is only 5.24, which belongs to a slightly lower level. Conclusions: The content of phosphorus in the soil of mango forest is very low, and the phosphorus element is very deficient. It is suggested to apply phosphorus fertilizer, irrigate mango trees and reduce the pH value to improve the situation of low phosphorus

Education researchers as negotiators: Leveraging expertise across teachers and scientists to implement authentic data investigations in grade 7–12 classrooms

AbstractIncorporating authentic research skills and practices into K‐12 science, technology, engineering, and mathematics (STEM) instruction is a challenging yet crucial approach for introducing students to authentic science inquiry. While recommendations for emphasizing data literacy and quantitative reasoning in science classroom contexts are well‐established, implementation remains challenging. Over the span of 4 years (2019–2023), a multi‐institution team of teachers, education researchers, and forest scientists established a partnership with the overarching goal of integrating authentic forest research and data into middle and high school classrooms. The education researchers played a critical role in facilitating effective scientist and teacher interactions while addressing classroom implementation challenges. Importantly, the effectiveness and mutual benefits of the research partnership were greatly influenced by specific practices implemented by the education research team, and the assumption of different collaborative roles by all stakeholders involved. In this study, we examine these roles, relationships, and interactions of all stakeholders in the partnership, with “stakeholder” referring to participating teachers, education researchers, and collaborating forest scientists.

Taxonomic studies on the lichenized fungi inhabiting bamboos and rattans of KFRI Peechi campus

A total of 17 lichen taxa inhabiting the bamboos and rattans of the Kerala Forest Research Institute, Peechi campus were enumerated. Out of these, sterile specimens of Cryptothecia, Pyxine, Tricharia, and some species of Porina and Strigula were identified up to generic level based on thallus morphology, anatomical and chemical characters. The study added eight species viz., Diorygma soozanum (Zahlbr.) M. Nakan. & Kashiw., Fellhanera bouteillei (Desm.) Vězda, Graphis pyrrhocheiloidesZahlbr., Gyalectidium cf. filicinum Müll. Arg., Herpothallon cinereum G. Thor, Porina tetramera (Malme) R. Sant., Puiggariella nemathora (Mont.) S.H. Jiang, Lücking & J.C. Wei, and Tricharia sp. as new distributional records to Kerala. The genera Fellhanera, Gyalectidium, Puiggariella, and Tricharia are reported for the first time in Kerala. Brief descriptions of the species new to Kerala are provided.

Volatile-mediated plant–plant communication in natural beech forests

ABSTRACT Natural forests present complex environments due to abiotic and biotic heterogeneity. While studies on volatile organic compounds (VOCs) mediated plant–plant communication have been conducted in controlled environments such as laboratories, research in natural forests remains scarce. To determine whether beech (Fagus crenata) exhibits plant–plant communication in natural forests, we investigated plant hormones and leaf damage as defense responses considering wind direction, forest stand structure and genetic relatedness. Our findings indicated that trees closer to the VOCs source accumulated more salicylic acid than those farther away downwind, resulting in less damage from pathogens and herbivores. Conversely, there was no distance-dependent change in hormone levels or leaf damage upwind. Additionally, genetic relatedness between the VOC source tree and surrounding trees did not influence the levels of plant hormones or leaf damage. Thus, our results suggested that beech exhibits plant–plant communication in natural forests influenced by abiotic and biotic heterogeneity of forest ecosystems.

Post-fire vegetation dynamic patterns and drivers in Greater Hinggan Mountains: Insights from long-term remote sensing data analysis

Fire has become a major disturbing factor in boreal forests, and giant forest disturbances play a vital role in regulating the climate under global warming. Therefore, it is essential to investigate the spatiotemporal patterns and main drivers of post-fire vegetation recovery for forest ecological research and post-fire recovery management. However, previous studies have focused on the post-fire forest change within the entire fire perimeter, lacking separate analysis and comparison of the burned zone (BZ) and unburned zone (UNBZ). Here, we propose the utilization of Moderate Resolution Imaging Spectroradiometer land cover type and vegetation index data to monitor vegetation dynamics and explore its drivers after the most serious forest fire in the history of P.R. China in the Greater Hinggan Mountains (GHM). The temporal and spatial patterns of vegetation recovery in the BZ/UNBZ in the GHM were analyzed using the Sen & Mann-Kendall method, Hurst index and coefficient of variation, and their driving mechanisms were explored using GeoDetector and geographically weighted regression. The results showed that there were significant differences in the spatial distribution and fluctuation of vegetation between the BZ and UNBZ, and that the BZ exhibited higher productivity and vigor. Vegetation recovery was influenced by different dominant factors and changed over time, in which land surface temperature and precipitation dominated all the time, whereas topographic relief and elevation had a more significant contribution to vegetation recovery in the BZ and UNBZ, respectively. This study provides a scientific basis for the protection and management of vegetation in disturbed forested areas, particularly after fires.

Seasonal Climatic Variation and Flowering Intensity of Garcinia kola (Heckel) in a Humid Forest Plantation

Aim of study: The study designed to assess seasonal climatic variation and flowering intensity in G. kola in a humid forest plantation. Area of study: The study was conducted in the mono-plantation of Garcinia kola in the Swamp Forest Research station of the Forestry Research Institute of Nigeria, Onne, Rivers state, Nigeria. The plantation consists of 103 trees at 5×5m spacing. Material and methods: Climatic data were sourced from meteoblue.com. Flowering intensity was determined by the estimation of the total flower production per tree: total number of flower buds per inflorescence was determined by visual counting and then extrapolated for the total number of inflorescences per twig, total number of twigs per branch and total number of branches per tree to determine the average flowering intensity per tree. A total of 9 trees and twenty-five inflorescences per tree, were sampled. Data was analysed using covariance and analysis of variance. Main results: Rainfall, wind speed, and flowering intensity varied significantly (p ≤ 0.05) between seasons; seasonal rainfall variation influence on flowering intensity varied with tree gender. Research highlights: Rainfall is the flowering cue of the plantation; we recommend that farmers target low to moderate rainfall seasons for high fruit and seed yields.

Anthropogenic effects and ecosystem services of tropical highland forests in Ethiopia

Despite the significant direct and indirect benefits that forests, particularly tropical highland forests, provide to local communities, they are facing severe degradation primarily due to population growth and rapid land-use changes. This has made it difficult for policymakers to effectively manage these forests due to a lack of comprehensive current forest research data. Therefore, the primary objective of this study was to examine the anthropogenic impacts on forest ecosystems and the ecosystem services (11ecosystem services,ESs) they provide, as well as to understand local perspectives on management of natural forests. For collecting disturbance indicators and other environmental data, 12 transect lines by 150 meter interval between each of the two consecutive parallel transects and 40 quadrats (20 m x 20 m size each) by 100 m interval were laid out in 145 ha total forest land size of the five study sites of three districts. However, for questionnaire-based data, 266 respondents were participated. As revealed in the results, the majority of households (about 78 %) relied on mixed farming and had ≤ 1 ha of land with 5.6 average family size. Besides, 74.3 % of the households used forest products for cooking food and getting energy to their homes due to little or no electricity, or other energy sources in rural communities. Nearly 85 % of the households also obtained timber from natural forests. Tree cutting, grazing, cultivation, and fires were the major anthropogenic factors leading to deforestation and loss of ecosystem services and biodiversity of the studied forest ecosystems. Disturbance assessment indicated that almost all forest patches, excluding one in the eastern subregion of the study area, were severely impacted. This suggests a widespread degradation of Ethiopia's forests. However, various ESs, mainly regulating and habitat services, followed by provisioning ones, were delivered from these sites. Hence, soil erosion controlling, flood protecting, and soil fertility regulating services were some of the most services provided by the forests. Likewise, being shelter and nursery sites for biota were the other most important habitat service. The raw materials including grass for fodder, medicinal plants, timber, fuel wood, and water for livestock watering and domestic uses were the major provisioning services provided. Thus, more than 93 % of the households had a great interest for the protection and continuity of the present forest patches in the future. Briefly, despite being heavily degraded due to anthropogenic factors, these natural forests still provided various ecological, social, and economic services to the local people; thereby the people were interested in protecting and conserving them. Thus, for restoring degraded forest areas of the zone, community-based participatory conservation strategies were recommended.

A Classification and Interpretation of Methodological Approaches to Pursue Natural Capital Valuation in Forest Research

This paper reviews natural capital (NC) valuation approaches in the context of woodland, forest, and riparian ecosystems, emphasising the need for participatory methods to take priority over neoclassical economics approaches. Focusing on research carried out in Scotland, the study analyses findings according to a classification of natural capital initiatives that we have developed, building on ideas proposed by the UK ENCA initiative, a guideline proposed to help researchers and practitioners understand NC and take it into account in valuation, decision-making and policy. We have found that landscape-scale initiatives that address the relationships between people and place to inform value and decision-making beyond the economic (monetary) benefits generated by ecosystem services (ES) are becoming popular. For instance, recent methods employed to capture stakeholders’ non-utilitarian preferences include the use of participatory GIS mapping, scenario planning, and other participatory methods to identify, explore and quantify less tangible cultural ecosystem services (CES). The review shows that many studies provide information relevant to the formulation of a place-based NC approach, working towards the integration of contextual and relational values into land management decisions to help formulate management strategies that maximise ES delivery. Conversely, we have not found evidence of the integration of shared values arising from an eco-centric perspective of nature valuation into the more classical, instrumental value lens. Such an approach would help inform broader, overarching aspects of woodland and forest management that may foster more effective conservation and help to manage conflicts.

Validation and Error Minimization of Global Ecosystem Dynamics Investigation (GEDI) Relative Height Metrics in the Amazon

Global Ecosystem Dynamics Investigation (GEDI) is a relatively new technology for global forest research, acquiring LiDAR measurements of vertical vegetation structure across Earth’s tropical, sub-tropical, and temperate forests. Previous GEDI validation efforts have largely focused on top of canopy accuracy, and findings vary by geographic region and forest type. Despite this, many applications utilize measurements of vertical vegetation distribution from the lower canopy, with a wide diversity of uses for GEDI data appearing in the literature. Given the variability in data requirements across research applications and ecosystems, and the regional variability in GEDI data quality, it is imperative to understand GEDI error to draw strong inferences. Here, we quantify the accuracy of GEDI relative height metrics through canopy layers for the Brazilian Amazon. To assess the accuracy of on-orbit GEDI L2A relative height metrics, we utilize the GEDI waveform simulator to compare detailed airborne laser scanning (ALS) data from the Sustainable Landscapes Brazil project to GEDI data collected by the International Space Station. We also assess the impacts of data filtering based on biophysical and GEDI sensor conditions and geolocation correction on GEDI error metrics (RMSE, MAE, and Bias) through canopy levels. GEDI data accuracy attenuates through the lower percentiles in the relative height (RH) curve. While top of canopy (RH98) measurements have relatively high accuracy (R2 = 0.76, RMSE = 5.33 m), the accuracy of data decreases lower in the canopy (RH50: R2 = 0.54, RMSE = 5.59 m). While simulated geolocation correction yielded marginal improvements, this decrease in accuracy remained constant despite all error reduction measures. Some error rates for the Amazon are double those reported in studies from other regions. These findings have broad implications for the application of GEDI data, especially in studies where forest understory measurements are particularly challenging to acquire (e.g., dense tropical forests) and where understory accuracy is highly important.

Principle, structure and application progress of the forest landscape model FireBGCv2.

Forest landscape model can quantitatively simulate the spatiotemporal variations in forest structure and function at the landscape scale based on traditional field survey data and mathematical models, providing a reference for the formulation of scientific forest management strategies. FireBGCv2 is one of the representative models currently used in the research area of forest landscape changes. It can simulate ecological processes at various scales, including trees scale (tree growth, establishment, and mortality), stand scale (carbon and nitrogen pools, fuel treatment, decomposition), site scale (resource competition and species phenology), and landscape scale (seed dispersal and wildfire disturbances), and the effects of those processes on forest landscape structure and function. The advantage of this model lies in its ability to simulate multiple ecological processes while considering the diversity and complexity of ecosystems. However, it also has drawbacks, such as high computational demands and complexity of use. We summarized the basic principles and structure of FireBGCv2 and introduced its application progress in forest landscape research and management. Currently, the application of the FireBGCv2 model, both domestically and internationally, mainly focused on exploring the interactions between fire, climate, and vegetation, quantifying the spatial and temporal dynamics of fires, and describing potential fire dynamics under future climate scenarios and land management strategies. With the in-depth development of forest landscape model theories and applications, the future prospects of FireBGCv2 include improving and updating the model's algorithms, adding new functional modules to explore fire management issues, and meeting the needs of different users.

Trends in forest livelihoods research – Taking stock in 2024

Forests are increasingly prominent in global policy discussions. Conservation, sustainable management, and restoration of forests are widely understood as necessary to reach climate and biodiversity goals. This attention to forests is vital. However, it risks overshadowing or, worse, undermining the livelihoods and well-being of the hundreds of millions of people worldwide who live in or near forests, especially Indigenous Peoples and marginalized groups. New international commitments to plant trees and halt and reverse deforestation and degradation are intensifying demands on forests and other lands. What are the implications of these shifts for the rights, livelihoods, and wellbeing of those living in forest and tree-based landscapes? What new thinking and evidence exists to help advance knowledge and policy on this topic? And what do current dynamics suggest for future research? The articles in this Special Issue on “Trends in Forest Livelihoods Research” respond to these questions. This introduction contextualizes current research at the forest-livelihoods nexus and provides an overview of the 18 articles compiled in this volume. We identify three key themes and two cross-cutting social sustainability concerns that emerge from this collected work. We conclude by highlighting implications for forest-related policy that better supports local livelihoods and broader sustainable development goals, and by identifying pressing research needs.

Spatial Variability in Soil Water-Physical Properties in Southern Subtropical Forests of China

Quantification of soil water-physical properties and their spatial variation is important to better predict soil structure and functioning, as well as associated spatial patterns in the vegetation. The provision of site-specific soil data further facilitates the implementation of enhanced land use and management practices. Using geostatistical methods, this study quantified the spatial distribution of soil bulk density (SBD), soil moisture (SM), capillary water-holding capacity (CWHC), capillary porosity (CP), non-capillary porosity (NCP), and total porosity (TP) in southern subtropical forests located at the Tropical Forest Research Center in Pingxiang City, China. A topographic map (scale = 1:10,000) was used to create a grid of l km squares across the study area. At the intersections of the grid squares, the described soil water-physical properties were measured. By calculating the coefficient of variation for each soil water-physical property, all measured soil water-physical properties were found to show moderate spatial heterogeneity. Exponential, gaussian, spherical, and linear models were used to fit the semivariograms of the measured soil water-physical properties. Across all soil water-physical properties, the range A0 variable (i.e., the separation distance between the semivariance and the sill value) measured between 3419 m and 14,156 m. The nugget-to-sill ratio ranged from 9 to 41%, indicating variations in the level of spatial autocorrelation among the soil water-physical properties. Many of the soil water-physical properties were strongly correlated (as assessed using Pearson correlation coefficients). Spatial distribution maps of the soil water-physical properties created via ordinary kriging (OK) showed that most water-physical properties had clumped (aggregated) distributions. SBD showed the opposite spatial pattern to SM and CWHC. Meanwhile, CP and TP showed similar distributions.

Considering temporality for SES analysis with reflections from urban food forests and orchards

ABSTRACT Social ecological systems research has noted various understandings and experiences of time, however, these engagements tend to be underdeveloped. In this paper, we consider how SES analyses can make diverse experiences of time more apparent and better support SES research, management, and policy making. To consider how diverse temporal experiences might be better integrated in SES, we sketch how time and temporality have been addressed in SES research and in the social sciences and humanities. We argue that insights from social science and humanities, as well as other adjacent disciplines, have paved the way for thinking critically, relationally, and intentionally about time and temporality. To illustrate how temporality can be considered and the usefulness of such consideration, we discuss conceptual insights in relation to a series of vignettes from ongoing research in urban food forests and orchards. Bringing together these insights and key concerns of SES research, we propose a series of questions for explicitly engaging with temporality, oriented around the concepts of relational change, space and place and bodies and practice. We suggest that a more explicit and critical temporal focus is vital for SES scholars’ recent calls and efforts to more meaningfully engage with diverse ontologies, world views, and experiences.

Elevated atmospheric CO2 alters the multi-element stoichiometry of pollen-bearing oak flowers, with possible negative effects on bees

Increasing atmospheric CO2 levels change the elemental composition in plants, altering their nutritional quality and affecting consumers and ecosystems. Ecological stoichiometry provides a framework for investigating how CO2-driven nutrient dilution in pollen affects bees by linking changes in pollen chemical element proportions to the nutritional needs of bees. We investigated the consequences of five years of Free Air CO2 Enrichment (FACE) in a mature oak-dominated temperate forest on the elemental composition of English oak (Quercus robur) pollen. We measured the concentrations and proportions of 12 elements (C, N, P, S, K, Na, Ca, Mg, Cu, Zn, Fe, and Mn) in Q. robur pollen-bearing flowers collected from the Birmingham Institute for Forest Research (BIFoR) FACE facility. An elevated CO2 (eCO2) level of 150 ppm above ambient significantly reduced the S, K, and Fe levels and altered the multi-element ratio, with different elements behaving differently. This shift in pollen multi-element composition may have subsequent cascading effects on higher trophic levels. To assess the impact on bees, we calculated the stoichiometric mismatch (a measure of the discrepancy between consumer needs and food quality) for two bee species, Osmia bicornis (red mason bee) and Apis mellifera (honey bee), that consume oak pollen in nature. We observed stoichiometric mismatches for P and S, in pollen under eCO2, which could negatively affect bees. We highlight the need for a comprehensive understanding of the changes in pollen multi-element stoichiometry under eCO2, which leads to nutrient limitations under climate change with consequences for bees.

Do Experimental Forests and Ranges of the Southeastern United States Represent the Climate, Ecosystem Structure, and Ecosystem Functions of the Region?

Abstract There are twenty experimental forest and range sites (EFRs) across the southeastern United States that are currently maintained by the USDA Forest Service (Forest Service) to conduct forest ecosystem research for addressing ecosystem management challenges. The overall objective of this study was to use multiple gridded datasets to assess the extent to which the twenty EFRs represent the climate, ecosystem structure, and ecosystem functions of southeastern forests. The EFRs represent the large variability of climate conditions across the region relatively well, but we identified small representation gaps. The representativeness of ecosystem structure by these EFRs can be improved by establishing EFRs in forests with relatively low tree cover, leaf area index, or tree canopy height. The current EFRs also represent the forest ecosystem functions of the region relatively well, although areas with intermediate and low aboveground biomass and water yield are not well represented. The trends in climate, ecosystem structure, and ecosystem functions were generally consistent between the region and the EFRs. Our study indicates that the current EFRs represent the region relatively well, but establishing additional EFRs in specific areas within the region could help more completely assess how southeastern forests respond to climate change, disturbance, and management practices. Study Implications This study across the experimental forests and ranges (EFRs) and the southeastern forest region fills the knowledge gap regarding climate, ecosystem structure, and ecosystem functions of EFRs in the context of the broader southeastern forest region. Understanding ecosystem functions and structures across the EFR network can help the Southern Research Station to address new research questions. Our study indicates that the current EFRs represent the climate, ecosystem structure, and ecosystem functions of southeastern forests well. However, establishing additional EFRs in certain regions could help more completely assess how southeastern forests respond to climate change, disturbance, and management practices.

FC-StackGNB: A novel machine learning modeling framework for forest fire risk prediction combining feature crosses and model fusion algorithm

Forest fire risk prediction is a crucial link in maintaining forest ecological security. Machine learning, due to its powerful non-linear modeling capabilities, has been widely applied in forest fire risk prediction research. However, existing studies often focus on the direct information provided by multiple environmental factor features when constructing the feature space, while overlooking the deeper information conveyed by feature cross-correlations. Additionally, fire risk prediction predominantly relies on single-model forecasting, exhibiting slightly insufficient generalization and stability in models. Model fusion algorithms (MFA) can combine the advantages of multiple models to compensate for this limitation. In this study, a machine learning framework, FC-StackGNB, combining feature crosses (FC) and model fusion, is proposed. This framework employs the FC method to analyze the temporal trends of various environmental factors influencing fire occurrence, constructing multiple seasonal cross features (SCFs) capable of effectively capturing the non-linear relationship between environmental factors and time. Moreover, the framework develops a Gaussian Naive Bayes (GNB) optimized stacking MFA to fully leverage the strengths of different ML algorithms. Results demonstrate that the introduction of SCFs effectively enhances the prediction performance of six machine learning models, with the mean values of five evaluation metrics (Accuracy, Precision, Recall, F1-score, and ROC_AUC) increasing by 1.58% to 6.30%. The fusion model constructed based on the StackGNB algorithm can effectively handle the multicollinearity issue of features, exhibiting significantly better prediction performance than single models, particularly in improving the Recall metric (increasing by around 3% and 5% compared to the top two ranked single models respectively), which signifies the model’s ability to predict positive samples (i.e., high-risk fire areas). The proposed modeling framework effectively enhances the robustness and prediction performance of the models, offering new modeling insights for subsequent research. This study holds significant importance for enhancing the level of forest fire risk warning.

Review of the Current Status and Development Trend of Global Forest Carbon Storage Research Based on Bibliometrics

Forests are one of the largest terrestrial ecosystems on Earth, absorbing carbon dioxide from the atmosphere through photosynthesis and storing it as organic carbon, thereby mitigating global warming. Conducting bibliometric analysis of forest carbon storage can identify current research trends and hot issues in this field, providing data support for researchers and policy makers. This review article provides a comprehensive bibliometric analysis of global forest carbon storage research, using databases from the Web of Science Core Collection. CiteSpace software (6.2.6 version) was employed to visualize and analyze the data, focusing on key researchers, institutions, and countries, as well as major research themes and emerging trends. The main findings are as follows: (1) Since the 21st century, the publication volume in this field has been increasing, with the United States and China being the top contributors. (2) There is active collaboration among key authors, institutions, and countries, with a notable close-knit network centered around French author Philippe Ciais. This group includes nearly half of the field’s authors and many of them are crucial for advancing research in this field. (3) Cluster and citation burst analyses suggest that future research will focus more on the impact of forest management policies on carbon stocks, with particular attention to the roles of northern temperate forests and mangroves in global carbon storage. These findings provide valuable insights into the current state and future directions of forest carbon storage research. This article is instrumental in elucidating the role of forest ecosystems within the global carbon cycle, evaluating the impacts of anthropogenic activities on forest carbon stocks, and informing the development of effective climate change mitigation strategies.

Understanding the physical properties of multipurpose trees: A comprehensive analysis

The study was conducted at the Forest College and Research Institute in Tamil Nadu, India, to characterize the physical properties of eight different tree species: Tectona grandis, Swietenia macrophylla, Acrocarpusfraxinifolius, Artocarpus heterophyllus, Casuarina junghuhniana, Neolamarkiacadamba, Pterocarpus marsupium, and Melia dubia. One-meter billets were collected from felled trees of each species, debarked, and cleaned for analysis. The samples were prepared according to the requirements for assessing various physical properties, including bulk and basic density, moisture content, specific gravity, and shrinkage and swelling. The results indicated that all eight species exhibited high moisture content and medium-range density. Understanding these physical properties is crucial for determining the suitability of these species for use in the timber and furniture industries.

Using a location-based game to collect preference information for urban and rural forest planning

Location-based games provide an opportunity to collect crowdsourced, spatially explicit data that can be used in decision-making processes in forest planning. While these games have been more widely used in collecting mapping and modelling data, there is limited research on their suitability for collecting location-based data on human preferences, opinions, and emotions in these contexts. Collecting human-centred data can be resource-intensive and costly, hence exploring the potential of location-based games is important. This study investigates the use of geocaching in gathering meaningful data in urban and rural settings. A methodology was developed wherein surveys were embedded in geocaches on trails located in urban and rural forests in Finland. These surveys collected quantitative, qualitative, and photographic data relating to human-forest relationships and landscape preferences. The findings indicate that trails closer to urban areas with higher population density showed increased cache log volume and survey response rates. Moreover, trails tended to collect most information in the first summer after establishment. It is recommended that future studies employing this methodology create shorter, easily accessible, circular trails and that survey questions should be clear and incorporate a method to verify that submitted responses reflect experiences at the chosen location. Furthermore, forest planning professionals and researchers seeking to utilise location-based games in data collection are advised to engage with the communities active in playing them to ensure success..