National Forest Research Articles

Towards data-driven tropical forest restoration: Uncovering spatial variation, interactions and historical management effects on nutrients along soil depth gradients

Data scarcity hinders global conservation initiatives, and there is a pressing demand for spatially detailed soil and species data to restore human-altered tropical forests. We, therefore, aimed to generate foundational soil environment and habitat suitability data and high-resolution soil maps to aid restoration efforts in a critical ecosystem of the threatened Indo-Burma Biodiversity Hotspot region, i.e., Tarap Hill Reserve (THR) in Bangladesh. Using multiple soil depths and vegetation data, we answered three major questions. (QI) How do spatial distribution and the relationships between soil physicochemical properties (i.e., pH, sand, silt, and clay percentages, organic carbon, and nutrients – N, P, K, Ca, Mg, Fe, and Zn) vary from surface to deeper soils (top 1 m)? (QII) How do different forest management interventions, i.e., old-growth forests (OGF), mixed plantations (MXP), and mono-specific plantations (MOP), influence soil properties, nutrients, and carbon in different soil depths? (QIII) Which spatial interpolation methods are best suited for making more accurate soil property predictions at different depths? Our analyses reveal decreasing availability of critical nutrients like N, P, Mg, and Fe from surface to subsurface soils, while pH, soil organic carbon, and clay content increased with depth. Several soil properties showed significant interactions, although the strength of the interactions changed from surface to deeper soils. Besides, forest management interventions significantly influenced soil functionality by having higher nutrient availability and soil organic carbon in OGF than MXP and MOP. Predictive performances of the deterministic and geostatistical interpolation methods varied for different soil properties in different soil depths, and soil maps revealed substantial heterogeneity in the distribution of soil properties across space and along depths. This study represents a pioneering step in data-driven tropical forest restoration, and our novel findings and high-resolution soil maps could guide future studies focusing on species habitat preferences, restoration ecology, and spatial conservation planning in the Indo-Burma Biodiversity Hotspot region and elsewhere in the tropics.

Assessing Land-Cover Changes in the Natural Park ‘Fragas do Eume’ over the Last 25 Years: Insights from Remote Sensing and Machine Learning

The ‘Fragas do Eume’ Natural Park includes one of the best-preserved Atlantic forests in Europe. These forests are part of the Natura 2000 Network. This scientific study focuses on analysing land-cover changes in the ‘Fragas do Eume’ Natural Park (NW Spain) over a 25-year period, from 1997 to 2022, using machine learning techniques for the classification of satellite images. Several image processing operations were carried out to correct radiometry, followed by supervised classification techniques with previously defined training areas. Five multispectral indices were used to improve classification accuracy, and their correlation was evaluated. Land-cover changes were analysed, with special attention to the transitions between eucalyptus plantations and native deciduous forests. A significant increase in eucalyptus plantations (48.2%) (Eucalyptus globulus Labill.) was observed, while native deciduous forests experienced a decrease in their extent (17.6%). This transformation of the landscape affected not only these two habitats, but also cropland and scrubland areas, both of which increased. Our results suggest that the lack of effective conservation policies and the economic interest of fast-growing tree plantations could explain the loss of native deciduous forests. The results highlight the need to implement pro-active and sustainable management measures to protect these natural forest ecosystems in the ‘Fragas do Eume’ Natural Park.

Combining multiple feature selection methods and structural equation modelling for exploring factors affecting stand biomass of natural coniferous-broad leaved mixed forests

Recognition of biotic and abiotic factors affecting biomass of natural mixed forests is of great importance for forest carbon estimation and management. When estimating stand biomass using models, different variable selection methods often yield inconsistent results, and there is lack of systematic analysis. This study aimed to combine multiple feature selection methods with structural equation modelling (SEM) to identify a set of variables affecting stand biomass more reasonably. Eight methods were applied for feature selection based on data from 286 permanent sample plots in natural coniferous-broad leaved mixed forests in northeast China. These methods included Pearson correlation analysis, two methods derived from principal component analysis (PCA), stepwise regression, redundancy analysis (RDA), generalized additive model (GAM), random forest (RF), and boosted regression tree (BRT). A total of 56 candidate variables were considered, covering stand, biodiversity, climate and soil features. Significant variability was observed in the variables selected, however, there were 6 variables consistently identified across all methods, including tree species diversity (N_Sp_Div), stand structural diversity (N_ Size_ Div), nearest taxon index (NRI), community weighted mean based on dry matter mass of leaves (CWM.LDMC), soil pH, and degree-days above 18 °C (DD18). Then, these variables were included in the SEM with stand average age and additive stand density index (aSDI) to explore the direction and magnitude of their impacts on stand biomass. The SEM results showed that aSDI and average age had the greatest positive effects on stand biomass, and structural diversity also had a significant positive effect. DD18 affected stand biomass both directly and indirectly, with the total negative effect. Soil pH indirectly affected stand biomass via aSDI. Our findings demonstrated that combining multiple feature selection methods with SEM was an effective approach for understanding multiple factors affecting stand biomass, and provided valuable insights for forest biomass estimation and carbon management.

Evaluation of nature-based climate solutions for agricultural landscapes in the Galápagos Islands

The Galápagos Islands are highly vulnerable to climate and environmental change, and nature-based solutions can help local communities adapt local agricultural systems. Through a comparative analysis, we evaluated the effects of three land management strategies on soil temperature, soil water availability and storage, and carbon stocks in Santa Cruz Island (Galápagos Archipelago). We installed six monitoring sites that consisted of two replicates per pathway: (i) the avoided loss of tropical forest, (ii) the conservation of scattered trees and living fences in at-risk agroforestry system, and (iii) the increase in biomass after a reduction of the grazing intensity. The monitoring sites were equipped with a dense network of rain gauges, air temperature and relative humidity sensors, and capacitance/frequency probes that registered volumetric water content and soil temperature. After pedological characterization of the soil profiles, the soil physico-chemical and hydrophysical properties were determined in laboratory. Over a period of 30 months (July 2019 to December 2021), hydrometeorological and soil environmental data were collected.We assessed differences in soil temperature, moisture availability and soil organic carbon content between native forests, sites under traditional agroforestry and under passive restoration. Forest soils were 12 % cooler;, and soil moisture under forest was 20 % higher than in parcels with silvopastural management. Forest soils had a lower dry bulk density, lower saturated hydraulic conductivity and higher water retention capacity in comparison with the other two management types. In silvopastural systems, a decrease of grazing intensity had a positive effect on soil carbon stocks, that were about 50 % higher than in soils under traditional management. This study shows that avoided loss of tropical forest within an agricultural landscape is a promising strategy to mitigate increasing soil temperatures, agricultural drought, and decline in soil organic carbon content. Continued monitoring of the experimental sites is necessary to corroborate the findings of this investigation at longer temporal scales.

Globally Distributed Arbuscular Mycorrhizal Fungi Associated With Invasive Cinchona pubescens on Santa Cruz Island, Galápagos.

The presence of arbuscular mycorrhizal fungi (AMF) is essential for the survival and establishment of most plant species in nature. The reproductive success of invasive plant species in a particular habitat could also depend on these AM fungi. Cinchona pubescens, commonly known as quinine, is highly invasive on Santa Cruz Island, Galápagos, but at the same time severely endangered in its native range on mainland Ecuador due to overexploitation in the past. In this study, we aim at determining the AMF communities associated with C. pubescens at both locations to investigate whether the successful invasion of C. pubescens on Santa Cruz is related to its association with a particular community of AMF. For this, roots of C. pubescens trees were sampled at three sites, one site on Santa Cruz and two sites in the province of Loja, on mainland Ecuador. Communities of AM fungi were determined through the molecular cloning and sequencing of the 18S nrDNA gene and through the delimitation of Operational Taxonomic Units (OTUs), associated with the plant roots. We found 36 AMF OTUs associated with C. pubescens, most of them belonging to the genus Glomus. The highest richness of AMF OTUs was detected in samples from sites located on mainland Ecuador. The AMF communities between Santa Cruz and mainland Ecuador were significantly different, and only five OTUs were shared between both locations. Two dominant OTUs in C. pubescens from Santa Cruz were detected but no dominant OTUs from mainland Ecuador. Almost two thirds of the OTUs associated with C. pubescens had a wide global distribution. Our results suggest that the successful invasion of C. pubescens on Santa Cruz could have been facilitated by local generalist AMF and not by particular AMF. The observed generalist AMF from both locations could be important for conservation plans of restoring the endangered C. pubescens in the native forests on mainland Ecuador.

Seed dispersal by bats (Chiroptera: Phyllostomidae) and mutualistic networks in a landscape dominated by cocoa in the Brazilian amazon

Bats play essential roles in neotropical ecosystems, performing crucial ecological functions such as insect pest control, pollination of plants with significant economic, social, and ecological value, and seed dispersal, including that of pioneer plant species. These animals are directly linked to human well-being, and declines in their populations can even have adverse effects, such as increasing the need for pesticides in regions where natural insect control is reduced. The seed dispersal conducted by bats is fundamental for maintaining neotropical biodiversity, as it supports habitat regeneration and the propagation of various plant species. Moreover, the role of these dispersers is enhanced due to their ability to inhabit a variety of environments, from natural forests to anthropized areas. However, the conversion of natural forests into agricultural production areas, as well as urbanization, has affected the structure of mutualistic networks between bats and plants. In this context, the objective of this study was to identify the pattern of seed dispersal by bats of the Phyllostomidae family in an anthropized landscape of the Brazilian Amazon. Data collection was conducted in different areas of natural forest, cocoa cultivation, and urban areas in the municipalities of the States of Pará. Regarding the results, the most representative subfamilies of bats were Carollinae (72.15%) and Stenodermatinae (21.8%). The botanical families Piperaceae (35.52%) and Solanaceae (19.71%) were the ones most preferred by the bats. Regarding species richness, the general bat-plant interaction network included 15 botanical families and 26 species of bats. The general interaction network was nested (WNODF= 29.8), with low Specialization (H2=0.27), Connectance (0.17), and Modularity corresponding to M=0.21. Thus, we highlight the importance of these species for the restoration of degraded environments. Therefore, through the execution of projects that demonstrate the importance of chiropterochory in the restoration of degraded ecosystems in the Amazon, it will be possible to create measures and subsidies focused on the conservation of bat and plant species that play a role in maintaining the planet's biodiversity.

External and internal driving forces of community and functional group stability in the forest mammal community

Conserving mammal community stability in forest ecosystems is an urgent challenge in the face of global biodiversity threats and complex trophic interaction. However, understanding of the stability of mammal communities and targeted functional groups is still limited, hindering adaptive strategy development. We collected 210 120 camera trap photos across 5897 km 2 within the Amur tiger ( Panthera tigris altaica ) range in China’s natural forests. We decomposed stability into compensatory effects, statistical-averaging effects and population stability. Using structural equation modelling, we explored the impact of external factors, species diversity and vertical effects on the stability of the community and of four functional groups. As external factors, primary productivity increased the stability of top predators, while precipitation had inconsistent effects. Horizontal diversity (richness and evenness) positively impacted community stability. However, the vertical structure of the community, including trophic-level richness and functional groups’ compensatory dynamics, were the largest drivers for maintaining community stability. Horizontal diversity within functional groups and the diversity or biomass of their food resources/consumers both influenced the stability of functional groups. Our results recognize the importance of conserving and even re-establishing vertical trophic structures in forest communities. Acknowledging multiple levels of stability, from functional groups to communities, is an indispensable step for effective conservation strategies.

How large felids of South America are influenced by environmental and anthropogenic variables in the most degraded portion of the Amazon

AbstractWe evaluated the most relevant natural and anthropogenic factors for the occurrence and co‐occurrence of jaguars (Panthera onca) and pumas (Puma concolor) in the eastern Amazon, the most degraded portion of this tropical rainforest in Brazil. We found that in a context of high human pressure, a more significant amount of primary forest and more significant annual rainfall most positively influence the occurrence of jaguars. In contrast, pumas are negatively influenced by proximity to roads and positively by slope. Additionally, the presence of primary forest areas and high annual rainfall also favour the co‐occurrence of jaguars and pumas in the same areas. In contrast, open areas more related to anthropogenic zones disfavour the co‐occurrence of these two species in this degraded portion of the Amazon. Our results support landscape management for conserving big cat species in the Amazon and reinforce the importance of forest conservation for maintaining big cats in altered landscapes. Although these animals occur in open habitats, in the Amazon, these species are dependent on primary forests, as they are better‐structured habitats that maintain the capacity to support prey and shelter.

Deforestation—a call for consistent carbon accounting

Abstract Carbon accounting conventions treat emissions differently depending on their source. Fossil fuel carbon emissions are assessed as gross, whereas anthropogenic land carbon emissions are assessed as net. Despite calls for consistent gross accounting, accounting guidelines remain unchanged. Here we consolidate arguments for consistent accounting and explore implications for national inventories, sector contributions, carbon markets and forest protection programs. We find consistent gross accounting useful for programs supporting forest preservation, deforestation reduction and reforestation, as well as consistency with carbon markets.

Comparison between three different delivery technologies of virtual nature on psychological state related to general stress recovery: An experimental study

Visiting nature has been shown to have several benefits for psychological state related to general stress recovery. However, for many people, access to nature is limited. Technological development has made it possible to deliver nature environments virtually. The present study examines the benefits of a same virtual nature (forest) environment delivered through different technologies on psychological state related to general stress recovery, more precisely, on restoration, current stress, subjective vitality, and affective response. The main focus is on comparing three different delivery technologies of virtual nature: TV (75″), VR headset (Meta Quest 2), and virtual nature room (30m2). The study applies a three-condition randomized trial with pre-post assessments and a crossover design, where 62 participants visited once in each condition for a 15-minute exposure of virtual nature (360-degree video with congruent soundscape). The participants responded to psychological measures before and after each condition. Overall, participants’ restoration increased, while current stress and negative affect decreased during the exposure. In comparison to the TV (control) condition, both the VR headset condition and the virtual nature room condition had a better impact on psychological state related to general stress recovery, as restoration and subjective vitality increased more. There were no statistically significant differences between the VR headset and virtual nature room conditions in any of the measures.

Species mixtures enhance fine root biomass but inhibit root decay under throughfall manipulation in young natural boreal forests

Fine roots play crucial roles in terrestrial biogeochemical cycles. Although biodiversity loss and changes in precipitation are two major drivers of global change, our understanding of their effects on fine root biomass (FRB), root functional traits, and fine root decay (FRD) remains incomplete. We manipulated precipitation in young boreal forests dominated by Populus tremuloides, Pinus banksiana, and their relatively even mixtures using 25 % addition, ambient, and 25 % reduction in throughfall during the growing season. We collected root samples using soil core and trunk-traced methods to quantify FRB and root traits, and we simulated fine root decay using an in-situ experiment over 531 days. We found that compared to the average of single-species-dominated stands, species mixtures increased FRB by 41 % under ambient throughfall, by 89 % under throughfall reduction and by 71 % under throughfall addition. Root surface area, fine root volume, and root length density responded to species mixtures similarly to FRB. Meanwhile, species mixtures reduced FRD across all water treatments. There was a positive relationship between the effect of species mixtures on the FRD of absorptive roots and those on the FRB. Our results highlight that species mixtures could modify carbon cycling by enhancing fine root biomass accumulation and reducing its decomposition of young boreal forests under changing precipitation.

Preface

The International Conference on Natural Resources and Environmental Conservation (ICNREC) is an annual event dedicated to discussing various topics and issues regarding the conservation of natural resources and the environment. The 4th ICNREC was held on October 26, 2023, at the IPB International Convention Center (Botani Square) in Bogor, Indonesia. This year, the conference raised the theme: “Origin of Land Status, History of Land Use, and Development of Plantation Land Cover.” Over the past 25 years, driven by its high economic value, the area of oil palm plantations in Indonesia has nearly tripled. Since 2008, Indonesia has been the largest palm oil producer in the world, contributing 48% of the total global palm oil production. With an area of no less than 16.32 million hectares, palm oil plantations have brought various positive impacts, including generating foreign exchange, alleviating rural poverty, and creating jobs for approximately 21.49 million people. However, this success has also drawn accusations that oil palm plantations originate from primary or secondary forests, leading to deforestation, biodiversity loss, and a decline in plant diversity. Although these accusations are still debatable and not scientifically valid, they have significantly harmed Indonesia’s position in global trade. On May 16, 2023, the European Union officially implemented the European Union Deforestation-free Regulation (EUDR), which aims to ensure that products entering the EU market come from legal sources and do not cause deforestation. This regulation requires companies to trace these commodities back to the land where they were produced. In response, there is an urgent need to develop a scientifically valid and internationally recognized Deforestation Verification or Certification System for every oil palm plantation and palm oil mill. Research collaborations have shown that data and information about the “Origin of Land Status, History of Land Use, and Development of Plantation Land Cover” in various provinces are relatively easy to obtain and scientifically valid. To achieve both national and international legitimacy, it is necessary to discuss these findings with experts from various parts of the world with relevant disciplines. Therefore, the 4th ICNREC is themed “Origin of Land Status, History of Land Use, and Development of Plantation Land Cover.” Given the strategic position of palm oil as Indonesia’s main foreign exchange source and to avoid systemic negative impacts on the future progress of Indonesia’s palm oil industry, developing a deforestation verification/certification system based on data and information about the origin of land status, land cover development, and land use history is crucial. The 4th ICNREC was organized in partnership with the Center for Study, Advocacy, and Nature Conservation (PUSAKA KALAM), the Faculty of Forestry and Environment of IPB University, and the French Agricultural Research for International Development (CIRAD). It also received support from various sponsors, including the Indonesia Oil Palm Plantation Fund Management Agency (BPDPKS), Sampoerna Agri, the Indonesian Palm Oil Association (GAPKI), Asian Agri, the French Embassy in Indonesia, and the Indonesian Oil Palm Farmers Association (APKASINDO), along with many others who contributed to the event’s success. The conference resulted in a proceeding featuring 23 papers on various aspects of biodiversity. We appreciate all the support received in organizing the conference and preparing the proceedings and hope that these proceedings will benefit many people. Best Regards, Prof, Dr. Ir. Yanto Santosa, DEA Chairman of Committee of The 4th ICNREC List of Committee is available in this Pdf.

Timber and carbon sequestration potential of Chinese forests under different forest management scenarios

Developing forestry action plans with the goal of carbon neutrality is a critical task to identify carbon sink potential and balance the pathways of China's forests. Current research that predicts forest biomass carbon stock and sink potential has shortcomings, such as an incomplete assessment of China's forest carbon sink range, assumptions based on unchanged forest area in the base year and insufficient consideration of natural and human disturbance factors. This study utilised the national forest inventory (NFI) data to construct a model of forest growth and consumption using a machine learning algorithm (i.e. random forest), identified suitable areas for future forest expansion by integrating multi-source data, and set up three future forest management scenarios: business as usual (BAU), enhanced policy scenario (EPS) and maximum potential scenario (MPS). In addition, changes in the area, volume stock and biomass carbon stock in China's forests between 2020 and 2060 were predicted under three forestry activities (i.e. existing forest, afforested/reforested (AR) forest and forest conversion) and three climate scenarios (i.e. SSP126, SSP370 and SSP585) based on the 9th NFI (2014–2018). According to China's relevant planning goals and suitable forest space, the area of AR forests is predicted to be 55.55 × 106 hm2 by 2060, and the forest coverage rate is predicted to increase from 23% in 2018 to 28% by 2060. Biomass carbon sequestration (BCS) between 2020 and 2060 in AR forests is predicted to be 36.00 TgC per year. By 2060, the average BCS is predicted to be approximately 140.00–287.56 TgC per year in China's forests, which is mainly owing to arbor forest management. Under the BAU and EPS scenarios, BCS in China's forests is expected to decline from 2020 to 2060. However, under the MPS, BCS in China's forests is projected to increase and be maintained at 322 TgC per year or above by 2060, with wood production reaching 4.71 × 108 m3 per year. China's forests are predicted to experience an increase in biomass carbon stock in the future and play a role as a carbon sink. By taking measures to achieve the maximum growth potential of all forest types, China's forests will achieve a win‒win situation between carbon sinks and timber production.

Non-invasive biomarkers for investigating urban metal exposure in neotropical bats

In urban centers, sewage treatment plants (STPs) serve as foraging and shelter areas for bats; however, they are sources of persistent pollutants that affect the health of these animals. This study aimed to investigate the impact of pollutants from an STP on the health of different species of neotropical bats from different guilds using non-invasive biomarkers. A conservation unit, the Silvania National Forest (SNF), was used as a reference area for comparison purposes. Blood, buccal mucosa, and fur samples were obtained for comet assay, micronucleus test, leukocyte profile, and metal concentration analysis in fur. Our results demonstrated that bats collected at the STP show a higher frequency of genotoxic damage, nuclear abnormalities, and an inflammatory response linked to infection than bats from the SNF. Regarding guilds, frugivores and nectarivores showed more pronounced responses to damage, but insectivores bats also showed relevant responses. While STPs are considered a source of pollutants, other urban sources of contamination likely contributed to these results. Still we encourage further studies using other non-invasive biomarkers, detection analysis of different pollutants in biological matrices, and the use of other wildlife species inserted in urban centers.

Testing source elevation versus genotype as predictors of sugar pine performance in a post‐fire restoration planting

AbstractClimate change is motivating a reassessment of how seeds are selected for reforestation, as rapid environmental change can lead to local maladaptation in trees. Genetic association studies and past seed source climate both have the potential to help identify appropriate planting stock, but these techniques have not been compared and tested as part of an operational planting program. In this study, we combined an analysis of single nucleotide polymorphisms (SNPs) associated with environmental gradients in sugar pine (Pinus lambertiana) with an analysis of post‐fire seedling survival and growth in a restoration experiment. Our genotype–environment association (GEA) tests of 92 individuals from varying climates within CA revealed 829 SNPs (out of 300,604) with significant association with climate gradients, especially April snowpack. Of these, 323 either had annotations that suggested potential functional importance or were identified by two different methods. We then built Bayesian models of survival and growth for all seedlings in a separate post‐fire planting experiment, to test the relative predictive ability of source elevation (a common proxy for source climate) versus the proportion of seedling alleles expected to be locally advantageous based on GEA. Across three sites within the King Fire scar in Eldorado National Forest in 2017, 2018, and 2019, 1774 seedlings were planted. Of these, 206 had enough green needles in 2020 to allow sample collection, and 161 were successfully genotyped. We found that source elevation was generally better at predicting seedling performance than genotype indices, perhaps because of the limited scope of the association analysis. Seed sources from 500 to 1800 ft (152.4–548.6 m) lower in elevation, and one seed zone further south generally performed as well or better than local seed sources. This result, and those of similar previous studies, suggest that “climate matching” using past climate information for existing seed sourcing units is a reasonable starting point for finding seedlings suited to already‐altered planting site climate conditions. However, further tests with more extensive genomic and performance data may improve the utility of genotype information for seed selection.

Mapping forest tree species and its biodiversity using EnMAP hyperspectral data along with Sentinel-2 temporal data: An approach of tree species classification and diversity indices

Forests play a crucial role in maintaining ecological balance and biodiversity, making the accurate mapping of tree species and assessment of biodiversity indices essential for informed management decisions. This study introduces an innovative methodology that integrates EnMAP (Environmental Mapping and Analysis Program) hyperspectral data with Sentinel-2 multitemporal data to classify tree species in the biodiverse landscapes of Kampinos National Park and its surrounding regions in Poland.We extract essential vegetation indices such as NDVI, NDMI, SAVI, and EVI from Sentinel-2 data to assess forest health and dynamics. The Sentinel-2 data is upscaled from 10 m to 30 m to align with EnMAP’s spatial resolution, followed by precise co-registration of the images using QGIS. Utilizing a rich dataset from the National Forest Inventory, we extract spectral signatures of nine distinct tree species from both data sources. We employ five machine learning algorithms—Support Vector Machines (SVM), Random Forest (RF), CatBoost (CAT), Gradient Boosting Classifier (GBC), and XGBoost (XGB)—to enhance classification accuracy.Through iterative experimentation with data reduction techniques and algorithm tuning, we achieve optimal performance across needle-leaved and broad-leaved species. The resulting tree species maps are validated through quantitative accuracy assessments against mixed-species polygons from the National Forest Inventory and ground truthing in the Kampinos National Park. Achieving an overall accuracy of 85% to 93%, our study demonstrates the efficacy of this integrated approach in tree species mapping. Furthermore, the tree species maps serve as a foundation for deriving key biodiversity indices—species richness, Shannon-Wiener Diversity Index, Simpson’s Diversity Index, and a composite Biodiversity Index—providing insights into spatial biodiversity patterns and informing targeted conservation strategies. This study exemplifies the potential of combining advanced remote sensing techniques with field validation to enhance our understanding of forest ecosystems and guide sustainable management practices.

Understory plant biodiversity is inversely related to carbon storage in a high carbon ecosystem.

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.

Mapping percent canopy cover using individual tree- and area-based procedures that are based on airborne LiDAR data: Case study from an oak-hickory-pine forest in the USA

Canopy cover (CC) is the proportion of a forest floor covered by the vertical projection of tree crowns. Recently, it has become common to utilize LiDAR (light detection and ranging) canopy metrics to estimate CC over large areas. However, these metrics are primarily related to canopy density rather than the specific definition of CC. Here, two processes that employed individual tree segmentation (ITS) and area-based procedures based on LiDAR data are presented to estimate CC across the Talladega Division of the Talladega National Forest (93,694 ha) at the plot, stand, and landscape levels. The two analytical procedures were assessed using the results of a plot/grid method as a reference dataset, which focused on CC estimates within 255 field measurement fixed-area sample plots. The accuracy of a third process, employing an imagery-based visual CC assessment, was also compared against the two procedures and the reference dataset. The LiDAR-based analytical procedures were able to provide estimates of CC with an RMSE of approximately 15 %, which is acceptable for landscape-level assessments. Based on the results of this study, we conclude that CC maps, when created using LiDAR data, may be suitable for various operational tasks such as assessing the impact of forest disturbances and helping to determine the habitat suitability for certain wildlife species.

One Health, One Forest: Harnessing Reclaimed Wood as a Sustainable Solution

Deforestation is a multifaceted and wicked problem characterized by its complexity and resistance to straightforward solutions. The issue is driven by human activities and has severe ecological, socio-economic, and climatic consequences. Between 1990 and 2015, approximately 129 million hectares of forest were lost globally, a trend contributing to biodiversity loss, increased carbon dioxide emissions, and climate change. In Canada, deforestation due to logging significantly impacts the boreal forests, with consequences such as habitat fragmentation affecting species like the threatened boreal caribou. The Canadian logging industry aims to provide essential raw materials while fostering economic growth and employment, supplying critical resources for sawmills, planing mills, shingle mills, and pulp and paper industries. Despite economic benefits, logging, particularly clearcutting, disrupts natural forest regeneration, soil composition, and water cycles, leading to long-term ecological consequences. The One Health approach, integrating human, non-human animal, and environmental health, is proposed to address this issue sustainably. Actions like those by Forests Ontario and Evergreen focus on reforestation and urban greening, while companies like Consolidated Pallet Co. promote wood recycling. This action plan showcases the potential for community-driven solutions to reduce environmental footprints, enhance sustainability, and foster economic and social well-being.

Repeated Tree Inventories of Pine Forests in South Florida's Big Cypress National Preserve.

The natural forest ecosystems of South Florida, USA, support a high biodiversity of plant and animal species and provide valuable ecosystem services. However, these ecosystems remain poorly represented in global studies, primarily due to a paucity of standardized data. Here, we present previously unpublished data from 332 censuses of 54 permanent 1-ha tree inventory plots in the Racoon Point area of Big Cypress National Preserve, Florida, USA, including a total of nearly 100,000 measurements (diameter or height) of > 17,000 individual living trees and palms (with additional measurements of nearly 6000 dead pine snags) collected sporadically over a 19-year period (1993-2012). These data, which were originally collected as part of a project to investigate tree responses to different experimental burning regimes, provide unique insight into the diversity, composition, structure, and dynamics of South Florida's unique and endangered pine forest ecosystems. Data files include the species identity, size (dbh = diameter at breast height), and location of all trees ≥ 5 cm dbh in 54 individual tree plots. Additional data are provided about heights of palm trees, and the location and burn history of each plot. These data are freely available for noncommercial scientific use under a Creative Commons license; users are encouraged to cite this paper when using the data.