Secondary Forest Research Articles

Hydraulic and structural traits of trees across light gradients in the Amazon secondary forest

Abstract Amazonian species are generally unable to adapt to long drought periods, indicating a low capacity to adjust their hydraulic traits. Secondary forests account for 20% of forest cover in the Amazon, making natural regeneration species crucial under climate change scenarios. In this study, we compared the hydraulic traits of five species, including non-pioneers (Bertholletia excelsa Bonpl., Carapa guianensis Aubl., Hymenaea courbaril L.) and pioneers (Cedrela fissilis Vell., Tabebuia rosea (Bertol.) Bertero ex A.DC.), across light conditions (understory, intermediate, gap) in a 22-year-old secondary forest in Central Amazon, Brazil. Twenty-five saplings were planted and monitored in 3 plots × 5 blocks. Five years after the plantation, we assessed growth, wood density, leaf water potential at predawn and midday, xylem embolism resistance (P50), and hydraulic safety margins (HSM). Leaf water potential ranged from −2.9 to 0 MPa. The non-pioneer species C. guianensis and H. courbaril exhibited the lowest P50 (−4.06 MPa), indicating higher embolism resistance, whereas the pioneer T. rosea had the highest P50 (−1.25 MPa), indicating lower resistance. HSM varied from −1.60 to 3.26 MPa, with lower values in gap conditions during the dry period (−1.60 MPa), especially affecting pioneer species. Wood density was influenced by both light and species type, with non-pioneers showing generally higher density, with H. courbaril reached 0.75 g cm−3 in the understory while the pioneer T. rosea showed the lowest density (0.27 g cm−3). These results highlight that light conditions affect hydraulic traits differently across species strategies, especially during early growth. Non-pioneer, slow-growing native species appear more resilient to light variation, making them suitable for future plantations aimed at climate adaptation in secondary forests.

CHEMICAL ATTRIBUTES AND SOIL CARBON AND NITROGEN STOCKS IN PASTURES IN THE MARANHÃO AMAZON

In the eastern Amazon region, converting forests into pastureland is a common practice that quickly leads to the degradation of these areas. This study aimed to evaluate the influence of different land uses in different evaluation periods on the chemical attributes, total contents, and carbon and nitrogen stocks of the soil in the Maranhão Amazon. The land use systems analyzed were: perennial pasture (PP), recovered pasture (RP), and secondary forest (SF). Trenches were opened in 2013 and 2019 in each use system in the 0.0-0.20 m and 0.20-0.40 m soil layers. The soil chemical attributes (pH, P, K, Ca, and Mg) and C and N contents and stocks were assessed. PP in the surface layer showed superior results compared to RP and SF, while the opposite behavior occurred in the subsurface. The chemical attributes of the soil decreased over the years evaluated, regardless of the layer and area. The chemical attributes of the soil, as well as the C and N contents and stocks, changed depending on the land use, layer, and year of sampling.

Agroforestry for Carbon Neutrality: An Effective Pathway to Net Zero

Agroforestry is a promising strategy to achieve carbon neutrality and net zero emission, aiming towards the balance between greenhouse gas emissions and equal amount of carbon removal through sequestration Among several methods of carbon sequestration, agroforestry stands out for its unique ability to simultaneously sequester carbon while reducing greenhouse gas emissions, particularly nitrous oxide (N2O) emissions associated with chemical fertilizer use in conventional agriculture. These systems store carbon through multiple pathways like, in above-ground biomass, below-ground root systems, and enhanced soil organic carbon accumulation while maintaining the agricultural productivity. Acknowledged under the afforestation and reforestation programs of the Kyoto Protocol, agroforestry has attracted interest for its several advantages from both industrialized and developing countries for its multifaceted benefits, including its potential to combat desertification and reduce anthropogenic emissions. Beyond carbon sequestration, it enhances soil fertility, supports biodiversity conservation, and provides economic diversification for farmers through multiple income streams. The role of REDD+ (Reducing Emissions from Deforestation and Forest Degradation) negotiations in extending the Kyoto Protocol's second commitment period has further strengthened agroforestry's position in global climate action, particularly through the development of REDD offset credits in compliance carbon markets. The World Agroforestry Centre defines agroforestry as a dynamic, ecologically based natural resources management system that integrates trees on farms and in the agricultural landscape, diversifying and sustaining production for increased social, economic, and environmental benefits. The Association for Temperate Agroforestry (AFTA) defines it as an intensive land management system that optimizes the benefits from biological interactions created when trees and/or shrubs are deliberately combined with crops and/or other natural resources. This review article critically examines agroforestry's crucial role as an effective pathway toward achieving carbon neutrality and net zero goals, synthesizing current knowledge and future prospects.

Vegetation changes of Lushan, China between 1959 and 2020 based on pollen data

Both climatic change and human activity are currently driving the dynamic of vegetation, which may vary from region to region. On Lushan, located in the eastern China, the subtropical secondary forests during the natural succession endure the pressure from ongoing climate warming on the one hand. They are influenced by anthropogenic disturbance on the other hand for recent decades. Previously, palynological research has discovered that the pollen assemblages from surface soil sample on Lushan can basically reflect the characteristics of local vegetation. Here, we did a comparative study by using the pollen analysis to investigate the vegetation changes of Lushan from 1959 to 2020. We compared the composition of pollen assemblages obtained in 1959 with that in 2020 along different altitudes. Further, the biomisation method was employed to discover the changes of different vegetation types, which were reflected by the pollen-based reconstructed biomes. Meanwhile, the temporal beta diversity analysis was used to extract the sites experienced the significant vegetation shift and the most important taxa change. Results showed that the pollen composition over the past 60 years on Lushan had altered remarkably. The vegetation shifted at all altitudes. The current vegetation pattern of Lushan: evergreen broadleaved forest in low elevation, temperate deciduous broadleaved forest in middle elevation and cool mixed forest in high elevation, is the successional consequence of the past 60 years. The forces driving the vegetation dynamics might be from multiple sources. However, the human disturbance seems to play quite an important role during forest succession. Our study is potentially useful both for paleoecological reconstructions and wider understanding of current climate change that are relevant to subtropical forests of Asia.

Assessing the effectiveness of vegetation indices in detecting forest disturbances in the southeast Amazon

Amazon forests are becoming increasingly vulnerable to disturbances such as droughts, fires, windstorms, logging, and forest fragmentation, all of which lead to forest degradation. Nevertheless, quantifying the extent and severity of disturbances and their cumulative impact on forest degradation remains a significant challenge. In this study, we combined multispectral data from Landsat sensors with hyperspectral data from the Earth Observing-One (Hyperion/EO-1) sensor to evaluate the efficacy of multiple vegetation indices in detecting forest responses to disturbances in an experimentally burned forest in southeastern Amazonia. Our experimental area was adjacent to an agricultural field and consisted of three 50-ha treatments – an unburned Control, a plot burned every three years, and a plot burned annually from 2004 to 2010. All plots were monitored to assess vegetation recovery after fire disturbance. These areas were also affected by three drought events (2007, 2010, and 2016) over the study period. We evaluated a total of 18 Vegetation Indices (VI), one unique to Landsat, 12 unique to Hyperion/EO-1, and five commons to both satellites (i.e., 6 total from Landsat and 17 from Hyperion). We used linear models (LM) to evaluate how changes in ground observations of forest structure (biomass, leaf area index [LAI], and litter production) associated with fire were captured by the two VIs most sensitive to forest degradation. Our results indicate that the Plant Senescence Reflectance Index (PSRI) derived from Hyperion/EO-1 was the most sensitive to vegetation changes associated with forest fires, increasing by 94% in burned vs. unburned forests. Of the Landsat-derived VIs, we found that the Green-Red Normalized Difference (GRND) were the most sensitive to forest degradation by fire, showing a marked decline (87%) in the burned plots compared with the unburned Control. However, compared to PSRI, the GRND was a better predictor of changes associated with fire, both in the forest interior or forest edge, for the three ground variables: biomass stocks (r2 = 0.5–0.8), LAI (r2 = 0.8–0.9), and litter production (r2 = 0.4–0.7). This study demonstrate that VIs can detect forest responses to fire and other disturbances over time, highlighting the relative strengths of each VI. In doing so, it shows how the integration of multispectral and hyperspectral data can be useful for monitoring tropical forest degradation and recovery. Moreover, it provides valuable insights into the limitations of existing approaches, which can inform the design of next-generation sensors for global forest monitoring.

AI-based Validation of Deforestation Using High-Resolution Satellite Imagery in the Brazilian Amazon

Abstract. Forests play an important role in the Earth systems for carbon sequestration and climate change mitigation, yet they have been increasingly disturbed by deforestation and forest degradation at an unprecedented pace. The Brazilian Amazon, for instance, experienced a 140% rise in deforestation from 2012 to 2020, with a record loss of 13,200 km2 between August 2020 and July 2021. Alarmingly, 87% of 2019 deforestation alerts occurred on private properties, with 61% in legally restricted areas. Existing deforestation monitoring systems, such as PRODES and the Global Forest Change dataset, use about 30m resolution satellite imagery, which is insufficient for operational validation at fine scales. The Deforestation Alert System by Imazon leverages high-resolution PlanetScope data (3-4m) but faces challenges due to fewer spectral bands and variations in reflectance values across different satellite sensors and dates. As a result, current validation is based mainly on manual inspection which is highly time-consuming. To address the challenges and automate the validation process, this work develops a system based on deep learning – known for its ability to capture complex texture patterns in high-resolution images – to inspect and confirm new deforestation sites. Specifically, the system takes inputs from potential deforestation sites suggested by coarse-resolution products and uses a pair of PlanetScope images before and after the change at each site to determine new deforestation (excluding existing deforestation). Our results demonstrate that the new system achieves robust and high-quality accuracy under various test conditions.

Impacts of Participatory Forest Management on Land Use/Land Cover of Adaba-Dodola Forest in South Eastern Ethiopia and its Implication to REDD+ Implementation.

Despite various interventions to protect forests, many developing countries, including Ethiopia, continue to face substantial forest conservation challenges, particularly where local communities heavily rely on forests for their livelihoods. Recognizing the urgency of this issue, the government of Ethiopia introduced Participatory Forest Management (PFM) and devolved forest management responsibilities to enhance forest conservation. Therefore, this assessment examines the impacts of PFM on forest cover based on an analysis of the Land Use/Land Cover Change (LULCC) over the last 23 years in Adaba-Dodola, and its implications for REDD+ implementation. The study involved determining the LULCC of the Adaba-Dodola forest after the introduction of PFM from 2000 to 2023. Landsat images of 2000, 2012, and 2023 were analyzed to detect LULCC. The study result showed that the Adaba-Dodola forest cover increased by 1.83% since the PFM was introduced. The decreased agricultural land by 0.87% was the main factor attributed to the increase in shrub cover, while shrubland attributed to the rise in forest cover. Net areas of about 148 ha/year of shrublands were converted into forest land owing to significant forest regeneration, while shrublands had a net gain of 110.5 ha/year from agriculture and grasslands between 2000 and 2023. The increase in forest cover is attributed to the effectiveness of PFM in halting deforestation and promoting forest conservation. Thus, the PFM approach is a tool for preserving forest ecosystems and mitigating the adverse effects of deforestation and forest degradation, therefore would be used as an umbrella for implementing REDD+.

A Study on the Growth Model of Natural Forests in Southern China Under Climate Change: Application of Transition Matrix Model

This study establishes a climate-sensitive transition matrix growth model and predicts forest growth under different carbon emission scenarios (representative concentration pathways RCP2.6, RCP4.5, and RCP8.5) over the next 40 years. Data from the Eighth (2013) and Ninth (2019) National Forest Resource Inventories in Chongqing and climate data from Climate AP are utilized. The model is used to predict forest growth and compare the number of trees, basal area, and stock volume under different climate scenarios. The results show that the climate-sensitive transition matrix growth model has high accuracy. The relationships between the variables and forest growth, mortality, and recruitment correspond to natural succession and growth. Although the number of trees, basal area, and stock volume do not differ significantly for different climate scenarios, the forest has sufficient seedling regeneration and large-diameter trees. The growth process aligns with succession, with pioneer species being replaced by climax species. The proposed climate-sensitive transition matrix growth model fills the gap in growth models for natural secondary forests in Chongqing and is an accurate method for predicting forest growth. The model can be used for long-term prediction of forest stands to understand future forest growth trends and provide reliable references for forest management. Forest growth can be predicted for different harvesting intensities to determine the optimal intensity to guide natural forest management in Chongqing City. The results of this study can help formulate targeted forest management policies to deal more effectively with climate change and promote sustainable forest health.

The Acoustic adaptation hypothesis does not support the occurrence of common songs in a neotropical urban bird species

ABSTRACT The Acoustic Adaptation Hypothesis indicates that vocalisations will have acoustic characteristics that maximise their transmission within the habitat where they are produced. Therefore, vocalisations of the same species are expected to vary between habitats if the habitats vary in structure. We conducted a sound transmission experiment to analyse if the common songs of the White-eared ground sparrow, Melozone leucotis, an urban bird species, differ between populations because they are adapted to the characteristics of each habitat to maximise their transmission. The experiment was conducted in four isolated populations within the urban areas of Costa Rica with different habitats: secondary forests, coffee plantations, gardens and thickets. In each population, we reproduced the three common songs of each population, and we compared four song degradation measures (excess attenuation, blur ratio, signal-to-noise ratio, and tail-to-signal ratio). Contrary to our expectations, our results contradicted the Acoustic Adaptation Hypothesis, since the common songs of each population did not transmit better in their own habitat, but the songs are adapted to transmit better in the original habitat. We suggest that common songs of this bird may be selected and maintained in each population by female selection.

Economic Valuation of Ecosystem Services of Coastal Area of Kinondoni District, Tanzania

This study investigates the often overlooked economic values of ecosystem services in the coastal area of Kinondoni District, Tanzania, in the context of spatial and temporal changes in land use and land cover (LULC). The primary objectives were to assess how ecosystem services and functions have been affected by LULC changes over a 30-year period, from 1993 to 2023. The study employs a benefit transfer method, integrating local and global estimations of ecosystem service value (ESV) with field survey, remote sensing and GIS techniques. The findings reveal that the annual changes in ESV during the study period are estimated at US$ 0.024 million and US$ 0.034 million using local and global coefficients, respectively. Over the three decades, there has been a significant annual loss of US$ 0.72 million locally and US$ 2.11 million globally, primarily due to the degradation of mangrove forests and bushland. The decline in ecosystem functions is largely driven by reductions in regulating services, which account for 54.1% of the total decrease in local valuations and 31.6% in global valuations. Supporting services also experienced substantial declines, with reductions of 39.7% in local valuations and 55.8% in global valuations. The study underscores the urgent need to review and enhance management and conservation strategies to ensure the sustainability of the coastal ecosystems in Kinondoni District, Tanzania.

How ambient temperature rise affects mercury dynamics and its pools in secondary forests

The forest ecosystem is a significant pool for capturing atmospheric mercury (Hg) deposition, with most Hg accumulating in forest soils. As secondary forests now dominate global forest cover, they are particularly sensitive to changes in ambient temperature. However, the impact of these changes on Hg dynamics in secondary forests remains poorly understood. Here, we quantified Hg inputs, outputs, and mass balances in two secondary forests in China, each with different ambient temperatures. We found that elevated ambient temperature (~1.0℃) advanced the germination of leaves by 2-3 days and extended the growing season by approximately one week, resulting in increased litterfall biomass by 1.18 Mg hm-2 yr-1 and a thicker litterfall layer by 0.22cm over 34 years. This temperature rise also facilitated Hg methylation within forest and enhanced methylmercury (MeHg) export, heightening the potential risk of MeHg exposure to surrounding ecosystems. Additionally, higher ambient temperature not only increased soil Hg emissions (2.75µgm-2 yr-1) but also led to significant Hg deposition via litterfall (9.26µgm-2 yr-1), resulting in a net annual Hg deposition of 6.88µgm-2 yr-1. This net Hg deposition accumulated in the topsoil, increasing the Hg pool by 0.51mgm-2 in organic and 0-10cm mineral soil horizons. Our findings suggest that even a ~1.0℃ temperature rise could enhance the role of secondary forests as atmospheric Hg sink by 45.10%. Therefore, the impact of ongoing climate warming on Hg cycling and pools in forests should receive increased attention and warrants further research.

Optimization of biodiesel production from Croton Macrostachyus seed oil with calcium oxide (CaO) catalyst and Characterization: Potential assessment of seed and kernel

This study investigates the use of Croton macrostachyus (CMS), a widely available, fast-growing, non-edible plant common in Ethiopia’s secondary forests and less productive lands, as a biodiesel feedstock. The research compared oil yields from the seed and kernel, assessed the oxidation stability of the resulting biodiesel, and conducted transesterification using a novel combination of a CaO catalyst with methanol, which had not been explored in previous studies. Oil yield was obtained 40.8 % from the seed and 50.3 % from the kernel. Calcium oxide (CaO) was derived from eggshells through a calcination process and characterized using BET, SEM-EDX, and FTIR techniques to assess its suitability as a heterogeneous catalyst for biodiesel production. The Box-Behnken design (BBD) based on the response surface methodology (RSM) was used to optimize the reaction parameters, including reaction time (60–120 min), methanol to oil molar ratio (4:1 – 12:1), and catalyst concentration (1 % – 5 %), while the reaction temperature (60 °C) and stirring speed (450 rpm) were kept constant. Analysis of variance (ANOVA) showed that the coefficients of determination (R2 and R2 adj) were 99.42 % and 98.38 %, respectively, indicating a strong correlation between experimental and predicted values. The optimum conditions identified for maximum yield of CMS biodiesel (98.314 %) were a methanol to oil molar ratio of 8.44:1, a catalyst concentration of 2.78 %, and a reaction time of 108 min. The oxidation stability of the CMS biodiesel was obtained an induction time of 2.3 h but was enhanced to 16.17 h due to the addition of TBHQ antioxidant. All physiochemical properties were compared with ASTM D6751 and EN 14214 biodiesel standards, demonstrating that the biodiesel produced is suitable for internal combustion engine applications.

Effectiveness, Efficiency, and Equity in Jurisdictional REDD+ Benefit Distribution Mechanisms: Insights from Jambi province, Indonesia

The jurisdictional REDD+ (JREDD+) mechanism, aimed at reducing emissions from deforestation and forest degradation, has been crucial in global climate change mitigation efforts. However, designing effective, efficient, and equitable benefit-distribution policy at the site level remains a challenge. This research assesses three benefit distribution mechanisms in Indonesia for JREDD+ initiatives, facilitated by the Indonesian Environment Fund (IEF). They include: (1) distribution through the provincial revenue and expenditure budget (APBD), (2) distribution through intermediary institutions (LEMTARA), and (3) direct distribution or transfer to beneficiaries. Each mechanism is evaluated on effectiveness, efficiency, and equity, considering bureaucratic processes and stakeholder capacities. The study utilizes public deliberation by involving relevant stakeholders at the national and Jambi province levels and expert judgment by purposively selecting based on certain criteria to help determine the optimal mechanism as the reference for achieving Indonesia's climate mitigation goals and the administrative intricacies involved. The findings suggest that direct distribution to beneficiaries is the most efficient and equitable, although using LEMTARA is deemed slightly more effective for targeted fund allocation. The study provides recommendations for policy makers on enhancing institutional capacities and integrating flexible inclusive mechanisms to optimize JREDD+ benefit distribution at the sub-national level.

Vegetation community recovery on restored bottomland hardwood forests in northeast Indiana, USA.

Vegetation communities in restored bottomland hardwood forests in northeast Indiana were studied 6-21 years after restoration to assess progress toward restoration objectives. The study focused on four sites that were restored to compensate for resource injuries after contaminant releases. The restored sites were compared with four reference-site conditions, including crops (prerestoration condition), old field communities representing a no-management alternative, locally sampled second-growth mature forests, and forest community types described by the US National Vegetation Classification (USNVC), which represent ideal or defining conditions of recognized vegetation communities. Fixed-area plots provided data on field-sampled environmental variables, vegetation, soil, and hydrological conditions for crops, old fields, restored areas, and mature forests. The USNVC database provided quantitative data for three historically and geographically relevant reference forest community types for comparison with the sampled communities. Results of nonmetric multidimensional scaling based on species cover revealed clear gradients relating to site age and canopy development. Along those gradients, restored areas demonstrated increasing similarity to mature forest reference communities in terms of floristic composition. Specifically, the floristic quality of restored areas was significantly greater than that of crops and old fields. Furthermore, soil health measurements of physical, chemical, and hydrological conditions indicated significant improvements in restored site soils compared with prerestoration conditions represented by cropland soils. Descriptions and data from the USNVC provided ecological context for restoration target conditions and facilitated the assessment of restoration recovery along a trajectory from starting conditions to those target conditions. Descriptions by USNVC also helped identify deviations from the intended restoration objectives (e.g., invasive species recruitment) and potential adaptive management actions to return sites to their intended trajectories. Integr Environ Assess Manag 2024;20:1917-1938. Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Analyzing the impact of phosphorous and nitrogen on Castanopsis sclerophylla early growth stages

Plant growth elements, particularly nitrogen (N) and phosphorus (P) are vital for their growth and development, particularly for understory vegetation and their excess limits the net productivity of terrestrial ecosystems. This study focuses on the understory vegetation responds and adaptation to key essential nutrients under changing climate scenarios in subtropical evergreen broad-leaved forests, still needs research attention. this, we set up an experiment taking four treatments in a 50-year-old Castanopsis sclerophylla secondary forest under (a) control (CK), (b) N, (c) P, and (d) combined N and P addition, applied to natural forest regeneration seedlings of C. sclerophylla attained similar growth parameters of diameter of 3 cm and 10 cm height. In addition, carbon, N, P, and non-structural carbohydrates (NSC) were determined through the anthrone colorimetric approach in different parts of seedlings. Results show that the combined N + P application enhanced the N and P by 14.48 %−140.55 % in the seedlings in both dry and wet seasons, respectively. However, during wet season, the content of NSC in the plant leaves significantly exceeded under P addition. Remarkably, CK showed increased P in the growing season but lower during the dry season. Furthermore, the root starch content of seedlings showed a significant increase under the application of N and P compared to combined N + P, ranging between 45.60 % and 58.70 %. Overall, the plant growth is attributed to N and P intake. The nutrient addition and seasonal variations have a coupled effect on seedling growth as proved in the in the natural open forest experiment. The study outcomes emphasize that the alterations in NSC allocation in the roots and leaves of C. sclerophylla seedlings under N + P addition could enhance their adaptation to future global climate changes, drought conditions, and high N concentrations.

Content of Humus Compounds in Soils of Secondary Forests and Sub-Mediterranean Steppes of the Northwestern Caucasus (by the Example of the Gruzinka Ridge)

Content of Humus Compounds in Soils of Secondary Forests and Sub-Mediterranean Steppes of the Northwestern Caucasus (by the Example of the Gruzinka Ridge)

The challenges associated with firewood supply and analysis of fuel quality parameters of the tree species used as firewood in Rwanda

Firewood serves as an essential cooking energy source for households in Rwanda. However, the supply of firewood is hindered by various challenges, such as escalating scarcity, long distances traveled to collect firewood, and reliance on low-quality biomass during shortages. This study aimed to assess the challenges associated with firewood supply and analyze the fuel quality of tree species used as firewood in Rwanda, using systematic sampling with 504 and 368 farmers, respectively, in Bugesera and Musanze Districts. The results indicated that women and children are predominantly involved in firewood collection, with households traveling over 9 kilometers for firewood collection and spending 5 to 8 hours per collection session. Additionally, 42% and 43% of households in Bugesera and Musanze Districts gather firewood twice weekly. The most preferred species for firewood were Eucalypts spp, Senna spectabilis, Grevillea robusta, and Alunus acuminata due to their rapid drying, low smoke production, and efficient fuel qualities. The fuel quality analysis indicated that Eucalyptus spp., Grevillea robusta, Croton megalocarpus, Alnus acuminata, and Senna spectabilis exhibit a substantial promising bioenergy characteristic that points to their potential for sustainable energy production. The study advocates for strategically incorporating high fuel qualities, rapid growth, and regeneration of tree species into trees-based systems in the agricultural landscape to ensure a sustainable firewood supply while mitigating forest degradation.

Forest biomass recovery twenty-four years after conventional and reduced-impact logging in Eastern Amazon

Given the mounting global concerns about mitigating climate change and curbing greenhouse gas emissions, it becomes increasingly crucial to comprehend the effects of logging techniques on biomass dynamics in tropical forests. This understanding is essential for fostering greater carbon retention and sequestration, aligning with the objectives of initiatives like REDD+ (Reducing Emissions from Deforestation and forest Degradation plus sustainable forest management and the conservation and enhancement of forest carbon stocks) and other conservation goals. In this context, this study investigated the effects of two wood harvesting methods, reduced-impact logging (RIL) and conventional logging (CL), on above-ground biomass (AGB) recovery rates 24 years after harvesting. The experimental design was based on three treatments: RIL, CL, and an unlogged control plot, situated in the municipality of Paragominas, State of Pará, in the Eastern Amazon region of Brazil. All trees with diameter at breast height (DBH) ≥25 cm, as well as all trees of commercial species with a DBH ≥10 cm, were monitored in a 24.5 ha plot within each treatment. Additionally, a 5.25 ha subplot within each treatment was designated for the monitoring of all trees with DBH ≥10 cm. The biomass data were generated from 11 measurements carried out from 1993 to 2017 (24-year period). Pre-logging AGB stocks were estimated at 181 Mg ha-1 in the RIL plot, 187 Mg ha-1 in the CL plot, and 174 Mg ha-1 in the control plot. One year after logging, AGB decreased by 19 % under RIL and 30 % under CL, while the control forest remained unchanged. By 13 years after harvest, the RIL plot achieved 102 % AGB recovery, while the CL plot recovered 86 % of the original pre-harvest stock. Over the 24-year post-logging period, AGB stocks recovered to 128 % in the RIL plot compared to only 90 % in the CL plot, while the control forest maintained 93 % of its original stock. The average annual ABG increment rates were 3.56 Mg ha-1 year-1 after RIL and 2.33 Mg ha-1 year-1 after CL. Our findings demonstrate that implementing RIL is a more effective strategy for maintaining post-logging AGB stocks and accelerating AGB recovery rates, serving as a significant mitigation measure against climate change.

The Role of Ngos in Localizing UN-REDD+ In Sulawesi Tengah, Indonesia

This study explores the role of national and local non-governmental organizations (NGOs) in localizing the UNREDD+ (Reducing Emissions from Deforestation and Forest Degradation) norm in Sulawesi Tengah, Indonesia. UN-REDD+ aims to mitigate climate change by promoting sustainable forest management in developing countries. Sulawesi Tengah was selected as a pilot province due to its extensive forest cover and relatively undisturbed deforestation activities. However, despite international support, the initiative encountered resistance from local communities, influenced by national and local NGOs. This research examines the complex interactions among international, national, and local NGOs by applying Acharya's norm localization theory. While international NGOs provided technical expertise, local NGOs significantly shaped the community perspective. These local NGOs raised concerns about the potential exploitation of forests and disruption to indigenous cultural values, fuelling opposition to the program. Consequently, the localization failed, and UN-REDD+ was discontinued in Sulawesi Tengah in 2012. The findings highlight the importance of considering local actors and their concerns in global environmental governance. Local NGOs, closely connected to communities, played a decisive role in rejecting the program, underscoring it, and addressing local values and governance issues.

Analysis of Land Use and Occupation in a Neighborhood of the City of Manaus-AM Using Geotechnologies

Objective: The objective of this study is to analyze the land use and occupation that occurred between 1999 and 2021 in the Tarumã neighborhood located in the city of Manaus-AM, with the aim of carrying out, through remote sensing techniques, the investigation of the environmental impacts that occurred, considering the classes of soil, vegetation and hydrography. Theoretical Framework: The accelerated population expansion and the lack of environmental planning contribute to the increasing degradation of natural resources. The disorderly distribution of the territory represents one of the main problems in Manaus. Method: Land use and occupation mapping was obtained from the supervised classification of Landsat 7 and Landsat 8 satellite images, RGB bands, through the United States Geological Survey – USGS (Earth Explore). Data comparisons were made based on the temporal analysis of the images and shapefile. Results and Discussion: The results obtained identified the class transformations that occurred in the last 22 years, which corresponds to 41.71% of primary vegetation, 8.98% of secondary vegetation, 17.70% of exposed soil. In the urban area, there was interference of 30.16%, with a 1.74% decrease in the water class, including the Environmental Preservation Area Research Implications: The practical and theoretical implications of this study favor the understanding, measurement and prediction of environmental impacts caused by the ordered and disordered urban occupation of cities. Originality/Value: This study contributes to the monitoring of occupations in the Tarumâ neighborhood, contributing to decision-making in preservation areas.