Search

Abstract Nowadays, the load monitoring system is an important element in smart buildings to reduce energy consumption. Nonintrusive load monitoring (NILM) is utilized to determine the power consumption of each appliance in smart homes. The main problem of NILM is how to separate each appliance's power from the signal of aggregated consumption. In this regard, this paper presents a combination between particle swarm optimization (PSO) and artificial neural networks (ANNs) to identify electrical appliances for demand‐side management. ANN is applied in NILM as a load identification task, and PSO is used to train the ANN algorithm. This combination enhances the NILM technique's accuracy, which is further verified by experiments on different datasets like Reference Energy Disaggregation Dataset, UK Domestic Appliance‐Level ElectricityUK‐DALE, and Indian data for Ambient Water and electricity Sensing. The high accuracy of the proposed algorithm is verified by comparisons with state of the art methods. Compared with other approaches, the total mean absolute error has decreased from 39.3566 to 18.607. Also, the normalized root mean square error (NRMSE) method has been used to compare the measured and predicted results. The NRMSE is in the range of 1.719%–16.514%, which means perfect consistency. This demonstrates the effectiveness of the proposed approach for home energy management. Furthermore, customer behavior has been studied, considering energy costs during day hours.

AbstractForests can play an important role in climate change mitigation. However, limited information is available worldwide regarding forest carbon and biomass stocks. Financial mechanisms such as ‘reducing emissions from deforestation and forest degradation and the role of conservation of forest carbon, sustainable management of forests and enhancement of forest carbon stocks’ (REDD+) also emphasize the quantification of forest biomass and carbon. This study aimed to estimate the forest biomass in two forests of Margalla Hills National Park (MHNP): Sub-tropical Chir Pine Forest (SCPF) and Sub-tropical Broadleaved Evergreen Forest (SBEF). For this, circular sampling plots of a 20 m radius were used for the collection of the variables, “diameter at breast height (DBH) and height”. Statistical analysis was done for exploring regression relationships between the variables. We found a mean Aboveground Carbon (AGC) of 73.36 ± 32.55 Mg C ha−1 in SCPF and a mean AGC of 16.88 ± 25.81 Mg C ha−1 in SBEF. The mean Aboveground Biomass (AGB) for SCPF was recorded as 146.73 ± 65.11 Mg ha−1, while for SBEF it was 33.77 ± 51.63 Mg ha−1. It was therefore concluded that the SCPF had higher mean AGB and mean AGC than the SBEF. Similar differences were also noticed in the structural characteristics of the two forests. These could be valuable information while designing sustainable management plans and afforestation programmes for the future and also for accessing nature-based funding such as REDD+.

The Amazon Fund is a Brazilian creation with the aim of raising funds to implement national strategies for the reduction of deforestation and sustainable development in the Legal Amazon. This article explains the governing structure of the Amazon Fund and argues that it is an example of an innovative instrument for sustainable development which to a large extent secures national ownership. The innovative elements include pay-for-performance funding, participatory governance and independent monitoring. The fund differentiates itself from traditional development aid by avoiding economic and political conditionalities, emphasizing recipient ownership and responsibility, yet it involves donations from the North to the South. The article further investigates the donors’ scope of influence, focussing on the largest donor, Norway. Notwithstanding the institutional safeguards from donor influence, the article shows that donors remain in power to withhold disbursements if breaches occur, which is illustrated by the example of the 2019 donor freeze of donations and funds use to new projects, and that donors use their partnership with Brazil to discuss how sustainable forest management contributes to the climate and to income generation for local peoples.

Nowadays, the load monitoring system is an important element in smart buildings to reduce energy consumption. Nonintrusive load monitoring (NILM) is utilized to determine the power consumption of each appliance in smart homes. The main problem of NILM is how to separate each appliance's power from the signal of aggregated consumption. In this regard, this paper presents a combination between particle swarm optimization (PSO) and artificial neural networks (ANNs) to identify electrical appliances for demand‐side management. ANN is applied in NILM as a load identification task, and PSO is used to train the ANN algorithm. This combination enhances the NILM technique's accuracy, which is further verified by experiments on different datasets like Reference Energy Disaggregation Dataset, UK Domestic Appliance‐Level ElectricityUK‐DALE, and Indian data for Ambient Water and electricity Sensing. The high accuracy of the proposed algorithm is verified by comparisons with state of the art methods. Compared with other approaches, the total mean absolute error has decreased from 39.3566 to 18.607. Also, the normalized root mean square error (NRMSE) method has been used to compare the measured and predicted results. The NRMSE is in the range of 1.719%–16.514%, which means perfect consistency. This demonstrates the effectiveness of the proposed approach for home energy management. Furthermore, customer behavior has been studied, considering energy costs during day hours. [ABSTRACT FROM AUTHOR]

Background: Deforestation and forest degradation are recognized as some of the primary causes of global warming, contributing to approximately 15% of global greenhouse gas emissions and thereby posing a significant challenge for climate change in East Africa. Kibale Forest National Park (KFNP) has experienced deforestation and degradation for numerous decades due to population pressure from neighboring communities whose livelihoods depend on crop production and livestock rearing adjacent to the forest. Despite its significance, documentation of community conservation practices surrounding KFNP has been inadequate. Therefore, the objective of this study was to establish the contribution of the local community to the conservation of and expansion of KFNP located in South Western Uganda. Methodology: A cross-sectional research design was employed, and a sample of 200 respondents from three parishes, namely Bigodi, Busiriba, and Kikoni, which border with KNP and lie along Kamwenge-Fort Portal Road, were selected. Data were collected using questionnaires and focus group discussions and analyzed through SPSS version 20. Results: The results indicate that community-based initiatives play a pivotal role in forest conservation, and the practices of local people aimed at enhancing their livelihoods and reducing illegal activities in the protected area, thereby promoting biodiversity conservation. Conclusion and recommendations: The study recommends that local communities should be actively involved in the policy formulation, planning, and management of KFNP. To reduce illegal activities and human-wildlife conflicts and enhance biodiversity conservation in KFNP, training in alternative sources of livelihood, strengthening law enforcement, and the provision of soft loans are recommended.

Information on forest extent and tree cover is required to evaluate the status of natural resources, conservation practices, and environmental policies. The challenge is that different forest definitions, remote sensing-based (RSB) products, and data availability can lead to discrepancies in reporting total forest area. Consequently, errors in forest extent can be propagated into forest biomass and carbon estimates. Here, we present a simple approach to compare forest extent estimates from seven regional and global land or tree cover RSB products at 30 m resolution across Mexico. We found substantial differences in forest extent estimates for Mexico, ranging from 387 607 km ^2 to 675 239 km ^2 . These differences were dependent on the RSB product and forest definition used. Next, we compared these RSB products with two independent forest inventory datasets at national ( n = 26 220 plots) and local scales ( n = 754 plots). The greatest accuracy among RSB products and forest inventory data was within the tropical moist forest (range 82%–95%), and the smallest was within the subtropical desert (range

Despite sustained declines in Amazon deforestation, forest degradation from logging and fire continues to threaten carbon stocks, habitat, and biodiversity in frontier forests along the Amazon arc of deforestation. Limited data on the magnitude of carbon losses and rates of carbon recovery following forest degradation have hindered carbon accounting efforts and contributed to incomplete national reporting to reduce emissions from deforestation and forest degradation (REDD+). We combined annual time series of Landsat imagery and high-density airborne lidar data to characterize the variability, magnitude, and persistence of Amazon forest degradation impacts on aboveground carbon density (ACD) and canopy structure. On average, degraded forests contained 45.1% of the carbon stocks in intact forests, and differences persisted even after 15 years of regrowth. In comparison to logging, understory fires resulted in the largest and longest-lasting differences in ACD. Heterogeneity in burned forest structure varied by fire severity and frequency. Forests with a history of one, two, and three or more fires retained only 54.4%, 25.2%, and 7.6% of intact ACD, respectively, when measured after a year of regrowth. Unlike the additive impact of successive fires, selective logging before burning did not explain additional variability in modeled ACD loss and recovery of burned forests. Airborne lidar also provides quantitative measures of habitat structure that can aid the estimation of co-benefits of avoided degradation. Notably, forest carbon stocks recovered faster than attributes of canopy structure that are critical for biodiversity in tropical forests, including the abundance of tall trees. We provide the first comprehensive look-up table of emissions factors for specific degradation pathways at standard reporting intervals in the Amazon. Estimated carbon loss and recovery trajectories provide an important foundation for assessing the long-term contributions from forest degradation to regional carbon cycling and advance our understanding of the current state of frontier forests.

Binuang bini (Octomeles sumatrana Miq) is a fast-growing tree with numerous economic benefits, such as the provision of wood for carpentry purposes, building boards, water management, and absorption of carbon dioxide (CO2). Therefore, this tree species has great potential and needs to be included in Reducing Emission from Deforestation and Forest Degradation (REDD)+'s mitigation program to tackle climate change. In its development, REDD+ has made it possible to carry out carbon trading in the world. Therefore, countries capable of performing protective functions and carry out reforestation, afforestation, and restoration, have the opportunity to be involved in world carbon trading. This study aims to determine the moisture content and carbon absorption rate of Binuang bini trees as a first step to regulate the allometric equation using destructive and laboratory analysis. The results show that the water content in the roots, leaves, as well as the base, middle, and tip of the stem were: 73.69%, 68.39%, 65.59%, 61.22%, and 66.26%, respectively. Furthermore, the sample test results indicate a very close relationship between carbon concentration and absorbance in the O. sumatrana tree with a simple linear regression equation: Y = 0.002X + 0.0593 with R2 = 0.9896. Therefore, this regression equation can be used to calculate the carbon concentration sample for the O. sumatrana tree fraction. The carbon content in 3 tree samples with a breast height diameter of 9.24 cm, 10.08 cm, and 11.68 cm was 2,585 kg. 2,913 kg, and 4,654 kg, respectively. In addition, the carbon sequestration for each tree diameter per year is 1.581 kg year-1, 1,782 kg year-1and 2,847 kg year-1, respectively.

Evolutionary analyses of the ways humans manage natural resources have until recently focused on the costs and benefits of prudent resource use to the individual. In contrast, the fields of environmental resource management and sustainability focus on institutions whereby successful practices can be established and maintained, and the extent to which these fit specific environmental conditions. Furthermore, recent theoretical work explores how resource conservation practices and institutions can emerge through co-evolutionary processes if there are substantial group-level benefits. Here we examine the design of a prominent yet controversial institutional intervention for reducing deforestation and land degradation in the developing world (REDD+), and its ongoing implementation on Pemba Island (Zanzibar, Tanzania) to determine the extent to which the features of REDD+ might allow for the endogenous adoption of sustainable forest management institutions. Additionally, we consider factors that might impede such outcomes, such as leakage, elite capture, and marginal community participation. By focusing on prospective features of REDD+ design that could facilitate the spread of environmentally sustainable behavior within and between communities, we identify distinct dynamics whereby institutional practices might coevolve with resource conservation practices. These insights should contribute to the design of more effective forest management institution in the future.

Abstract Background The homestead forests of Bangladesh occupy 0.27 million hectares (10% of the total forested area) and have potential to store carbon (C) and conserve biodiversity. Small scale forestry practices, however, are lacking reliable estimation of C stocks and tree species diversity. This may hinder successful implementation of REDD + and similar mechanisms as they concentrate on large-scale forests. This study aimed to estimate the above- and below-ground carbon stocks in homestead forests of Maheshkhali Island in Bangladesh and how tree species diversity and stand structural variation affect these C stocks. We randomly surveyed a total of 239 homestead forests in the hillside, beachside, and inland in 2019. Results Tree biomass C stocks were 48–67% greater in the inland and hillside forests than in the beachside due to significantly greater stand density, basal area, tree diameter. In total we found 52 tree species, but most abundant species in the inland and hillside forests, Mangifera indica, Samanea saman, and Artocarpus heterophyllus stored the most C in tree biomass. Greater tree species richness and diversity index in the inland and hillside forests indicated greater above- and below-ground tree biomass C stocks. An increase in tree species richness and diversity index by one unit was found to increase the tree biomass C stock by 22 and 30 Mg C ha−1, respectively. The total soil C stock was also affected by tree species diversity, stand density, and their interaction with soil properties. Total soil C stocks were greatest (51 Mg ha−1) in the inland forests, having also the greatest stand density and tree species richness. C stock in soil surface was greatest in the hillside forests due to the greatest litterfall, but the average share of litterfall from the total biomass C was only 0.1%. Conclusions Homestead forest ecosystems could store 96 Mg C ha−1 in total, which can contribute to climate change mitigation by generating C credits for small-scale homestead forests owners. Above- and below-ground tree biomass C stocks were found to correlate with tree species diversity, which may also contribute to biodiversity conservation in the REDD + in Bangladesh and countries alike.

To benefit from reducing deforestation under the Paris Agreement, developing countries need to establish a forest reference emission level (FREL) but no FREL study exists in Afghanistan yet. This study is aim at determining the FREL for Afghanistan between 2020 and 2030 using the retrospective and prospective approaches. Data of forest area in 1993 and 2010 and a Tier-2 emission factor were used to obtain the baseline emissions in closed forest, open forest, undifferentiated open forest, and high shrubs. Carbon stocks in four carbon pools were considered. Loss of closed forest emitted approximately 7.2 TgCO2 year−1, while increase in areas of other forest categories resulted in carbon sequestration of approximately 2.6 TgCO2 year−1 between 1993 and 2010. Depending on the chosen approaches, FRELs in Afghanistan can range from 1.3 TgCO2 year−1 for retrospective approach to as high as 2.3 TgCO2 year−1 for prospective approach between 2020 and 2030. Enhancement of carbon stocks and reducing deforestation could achieve emission reductions amounting up to 36.4% of the total emissions in Afghanistan. This study was the first attempt to determine the national FREL in Afghanistan, paving the way for understanding the impacts of future development on deforestation and carbon emissions in this country.

Carbon stock quantification holds vital significance in evaluating the climate change mitigation potential and carbon management of forest ecosystems. The current study was designed to quantify the biomass carbon stocks in the lesser Himalayan subtropical broadleaf forests of the Kashmir region. Primary data about the structural attributes and species composition of the local forests was collected through quadrat-based sampling followed by the application of allometric equations for the estimation of forest biomass. The biomass carbon stocks were calculated as 135.2 Mg ha-1 ranging from a maximum of 226.64 Mg ha-1 to a minimum of 11.83 Mg ha-1. The tree layer contributed a biomass carbon content of 134.67 Mg ha-1 making up to 99% share in the total forest biomass as compared to the shrub and herb layers with a very low biomass carbon value of 0.37 Mg ha-1 and 0.17 Mg ha-1 respectively. Dalbergia sissoo was recorded as the most dominant tree species with a biomass carbon stock value of 40.70 Mg ha-1 followed by Mallotus philippensis (30.09 Mg ha-1) and Ficus palmata (20.11 Mg ha-1). Principal Component Analysis revealed that the variations in the local carbon stocks were significantly correlated with the distribution pattern of the dominant tree species. Generalized Linear models showed a strong affinity of biomass carbon reserves with the structural attributes of the forest stands. This study generated a standard scientific dataset of the local biomass carbon stocks in the subtropical broadleaf forests with dynamic implications in sustainable forestry and carbon pool management in the region. [ABSTRACT FROM AUTHOR]

La cuenca baja del río Ayuquila, Jalisco, a pesar de su importancia en términos de biodiversidad, presenta una compleja problemática ambiental, al menos 12% del territorio presenta algún proceso de cambio en su cobertura forestal a causa de actividades productivas no sustentables (Jardel-Peláez et al., 2016). En la actualidad los sistemas agropecuarios tienen una atención prioritaria debido a que se conciben como motores de procesos de degradación y deforestación de ecosistemas.

Inadequate funding from developed countries has hampered international efforts to conserve biodiversity in tropical forests. We present two complementary research approaches that reveal a significant increase in public demand for conservation within tropical developing countries as those countries reach upper-middle-income (UMI) status. We highlight UMI tropical countries because they contain nearly four-fifths of tropical primary forests, which are rich in biodiversity and stored carbon. The first approach is a set of statistical analyses of various cross-country conservation indicators, which suggests that protective government policies have lagged behind the increase in public demand in these countries. The second approach is a case study from Malaysia, which reveals in a more integrated fashion the linkages from rising household income to increased household willingness to pay for conservation, nongovernmental organization activity, and delayed government action. Our findings suggest that domestic funding in UMI tropical countries can play a larger role in (i) closing the funding gap for tropical forest conservation, and (ii) paying for supplementary conservation actions linked to international payments for reduced greenhouse gas emissions from deforestation and forest degradation in tropical countries.

Secondary forests comprise an increasing area of the tropics and play an important role in global carbon cycling. We compare above-ground biomass accumulation of both planted and naturally regenerating trees, as well as C in the top soil layer, in three restoration treatments replicated at 14, six to eight year old restoration sites in southern Costa Rica. Restoration strategies include: control (no planting), planting tree islands, and conventional, mixed-species tree plantations. We evaluate the importance of past land-use, soil nutrients, understory cover, and surrounding forest cover in explaining variation in above-ground biomass accumulation (ABA) rate across sites. Total ABA and planted tree ABA rate were highest in plantations, intermediate in islands, and lowest in control treatments, whereas ABA rate of naturally regenerating trees did not differ across treatments. Most ABA in plantations (89%) and islands (70%) was due to growth of planted trees. Soil carbon did not change significantly over the time period of the study in any treatment. The majority of across-site variation in both total and planted tree ABA rate was explained by duration of prior pasture use. Tree growth in the first two years after planting explained approximately two-thirds of the variation in ABA rate after 6-8. years. Soil nutrient concentrations explained relatively little of the variation in planted or naturally recruiting ABA rate. Our results show that planting trees substantially increases biomass accumulation during the first several years of forest recovery in former agricultural lands and that past-land use has a strong effect on the rate of biomass accumulation. Planting tree islands is a cost-effective strategy for increasing ABA and creating more heterogeneous habitat conditions than tree plantations. We recommend small scale planting trials to quickly assess potential biomass accumulation and prioritize sites for ecosystem service payments for carbon sequestration. © 2014 Elsevier B.V.

Secondary forests comprise an increasing area of the tropics and play an important role in global carbon cycling. We compare above-ground biomass accumulation of both planted and naturally regenerating trees, as well as C in the top soil layer, in three restoration treatments replicated at 14, six to eight year old restoration sites in southern Costa Rica. Restoration strategies include: control (no planting), planting tree islands, and conventional, mixed-species tree plantations. We evaluate the importance of past land-use, soil nutrients, understory cover, and surrounding forest cover in explaining variation in above-ground biomass accumulation (ABA) rate across sites. Total ABA and planted tree ABA rate were highest in plantations, intermediate in islands, and lowest in control treatments, whereas ABA rate of naturally regenerating trees did not differ across treatments. Most ABA in plantations (89%) and islands (70%) was due to growth of planted trees. Soil carbon did not change significantly over the time period of the study in any treatment. The majority of across-site variation in both total and planted tree ABA rate was explained by duration of prior pasture use. Tree growth in the first two years after planting explained approximately two-thirds of the variation in ABA rate after 6-8. years. Soil nutrient concentrations explained relatively little of the variation in planted or naturally recruiting ABA rate. Our results show that planting trees substantially increases biomass accumulation during the first several years of forest recovery in former agricultural lands and that past-land use has a strong effect on the rate of biomass accumulation. Planting tree islands is a cost-effective strategy for increasing ABA and creating more heterogeneous habitat conditions than tree plantations. We recommend small scale planting trials to quickly assess potential biomass accumulation and prioritize sites for ecosystem service payments for carbon sequestration. © 2014 Elsevier B.V.

Forest ecosystems provide a wide range of multiple ecosystem services (ESs) that are important for sustaining life on earth and maintaining the integrity of the ecosystems. One of the most important forest ESs is climate regulation. On one hand, carbon accumulates through growth of trees into the forest resources and on the other hand, land use/land cover (LULC) change activities impact on carbon reserves. Due to the ongoing Hyrcanian deforestation, in this study, we focused on how different LU change affect greenhouse gases (GHGs) emissions in Golestan province based on REDD (Reducing Emissions from Deforestation and Forest Degradation) project. Four carbon pools include above-ground, below-ground, litter and soil organic carbon provided based on the results of reviewing 31 internal studies and IPCC reports. For predict the rate of deforestation by 2047 year under the baseline scenario, the Markov Chain was used. With the implementation of the base scenario, the CO2emission was estimated at 43655472 tons by 2047. The conversion of forests to other LULC types because of the fire is an important source of other GHGs emissions such as CH4 and N2O. Forest fire information of Golestan province indicates that since the year 2011 to 2018, 1511 fires have occurred. The results showed that fire would emit 16083.51 tCO2e of GHGs (CH4 and N2O) by the year 2047. So that the highest emission rates of CO2 was 17 million tons occurred in Marave-Tappeh township. The results of this study showed that Hyrcanian forests have an important role in reducing GHGs emissions. [ABSTRACT FROM AUTHOR]

This article proposes a model-free lossless data compression method for time series in smart grids (SGs), namely, Lossless Coding considering Precision (LCP) method. The LCP method encodes the current datapoint only using the immediate previous datapoint by differential coding, XOR coding, and variable length coding and transmits the encoded data once generated. It does not use the dynamics (e.g., many previous datapoints) or prior knowledge (e.g., mathematical models) of the time series. It considers the patterns, potential applications, and associated precision to preprocess the time series and especially suits high-resolution time series with long steady periods. The LCP method features low-latency and generalizability which enables real-time data communication for different time-critical tasks. Sub-metered load profiles in REDD dataset, high-resolution LIFTED dataset, AMPds dataset and PMU dataset are used to evaluate the performance of the LCP method. The results show that the LCP method demonstrates high compression ratio, low latency, and low complexity compared to state-of-the-art Resumable Data Compression (RDC) method, DEFLATE based on LZ77 & Huffman coding, and Lempel-Ziv-Markov Chain Algorithm (LZMA). [ABSTRACT FROM AUTHOR]

This paper develops an integrated framework for modeling payment for ecosystem services (PES) mechanisms that deliver multiple environmental services. Specifically, under a community‐led PES, forest conservation is promoted to deliver carbon and stream water benefits. The upstream community is paid for avoided fuelwood harvesting through a United Nations programme on reducing emissions from deforestation and forest degradation (REDD) program, whereas additional income is generated from water sales to the downstream communities. A bio‐economic model derives optimal level of fuelwood harvesting, which in conjunction with the changing species composition of forests, streamflow hydrology and fire risks, impacts on the carbon and water generation potential of the PES project. Results indicate that forest conservation outcomes are better when water and carbon services are combined, however overall cost to the program is lower under a carbon‐based PES. Changing species composition of forests creates tradeoffs between water and carbon benefits. Forest fires further challenge the viability of PES schemes through reducing streamflow and carbon sequestration potential. Recommendations for Resource Managers: Linking two or more environmental services under a single payment for ecosystem services (PES) scheme could improve forest conservation through making it more attractive to the participating communities.PES programs that combine multiple environmental services become economically attractive to participating communities through increasing their incomes. For instance, water and carbon driven services complement each other due to the overlapping benefits from improving forest biomass.However, fire risks can lower the benefits from PES and dissuade community participation.Similarly, the ecological and hydrological dimensions of PES projects that offer carbon and water benefits need to be understood and incorporated within PES framework design to enhance their durability.Conservation of mixed forests is more responsive to water‐based PES payments, in comparison to monoculture oak forests, however, mixed forests are also more vulnerable to degradation in absence of cooking fuel subsidies. [ABSTRACT FROM AUTHOR]

Tropical deforestation has reduced the extent of natural forests, which conserve biodiversity, provide essential resources to people, and reduce climate change by storing carbon. Forest conservation projects need tree species data to effectively manage biodiversity while greenhouse gas reduction programs require robust methods to estimate forest carbon. Here, we use field measurements, remote sensing, and Monte Carlo analyses to quantify tree biodiversity and aboveground carbon changes and uncertainties in 5200km2 of Amazonian and Yungas rainforest and other land around the Parque Nacional Yanachaga-Chemillén and two other protected areas in the Selva Central, Peru. Field inventories of 17ha found 438 tree species in 156 families. Field measurements of 10,838 trees and Monte Carlo analyses of uncertainties in measurements, allometric equations, wood density, and the carbon fraction of biomass showed that aboveground live carbon densities were 93±39Mgha−1 (mean ±95% confidence interval [CI]) in old-growth forest and 40±10Mgha−1 in secondary forest. Carbon density was significantly correlated to tree species richness (P

Background: The homestead forests of Bangladesh occupy 0.27 million hectares (10% of the total forested area) and have potential to store carbon (C) and conserve biodiversity. Small scale forestry practices, however, are lacking reliable estimation of C stocks and tree species diversity. This may hinder successful implementation of REDD + and similar mechanisms as they concentrate on large-scale forests. This study aimed to estimate the above- and below-ground carbon stocks in homestead forests of Maheshkhali Island in Bangladesh and how tree species diversity and stand structural variation affect these C stocks. We randomly surveyed a total of 239 homestead forests in the hillside, beachside, and inland in 2019. Results: Tree biomass C stocks were 48–67% greater in the inland and hillside forests than in the beachside due to significantly greater stand density, basal area, tree diameter. In total we found 52 tree species, but most abundant species in the inland and hillside forests, Mangifera indica, Samanea saman, and Artocarpus heterophyllus stored the most C in tree biomass. Greater tree species richness and diversity index in the inland and hillside forests indicated greater above- and below-ground tree biomass C stocks. An increase in tree species richness and diversity index by one unit was found to increase the tree biomass C stock by 22 and 30 Mg C ha−1, respectively. The total soil C stock was also affected by tree species diversity, stand density, and their interaction with soil properties. Total soil C stocks were greatest (51 Mg ha−1) in the inland forests, having also the greatest stand density and tree species richness. C stock in soil surface was greatest in the hillside forests due to the greatest litterfall, but the average share of litterfall from the total biomass C was only 0.1%. Conclusions: Homestead forest ecosystems could store 96 Mg C ha−1 in total, which can contribute to climate change mitigation by generating C credits for small-scale homestead forests owners. Above- and below-ground tree biomass C stocks were found to correlate with tree species diversity, which may also contribute to biodiversity conservation in the REDD + in Bangladesh and countries alike. [ABSTRACT FROM AUTHOR]

En México, la deforestación de los bosques y selvas han colocado a una gran variedad de especies de flora y fauna en peligro de extinción. Este impacto genera grandes emisiones de gases de efecto invernadero a la atmosfera. Este trabajo analizó la dinámica de cambio en la cobertura y uso de suelo en la región centro de la Sierra Madre Oriental, particularmente en la región Huasteca. Se interpretaron y clasificaron tres imágenes de satélite Landsat (1986, 1990 y 2000) y una imagen de satélite Spot 2015. Se calcularon las tasas de deforestación a través del método propuesto por la FAO. Se elaboraron los escenarios a futuro con el Software DINAMICA EGO, para conocer las tendencias de cambio de las coberturas y usos del suelo al 2030 y 2050. Se estimó el potencial de carbono en dos fragmentos de bosque mesófilo en los municipios de Tlanchinol y San Bartolo a través del método NDVI y con base al INFyS de la CONAFOR para la implementación de una estrategia futura de REDD+. Los resultados muestran que para la región Huasteca, las tasas de deforestación anual oscilan entre el 0.7% y 4.5% y para los fragmentos de bosque mesófilo entre el 1.3% y 1.5%, mismas que son transformadas para áreas agropecuarias. La cantidad de carbono estimada para ambos fragmentos de bosque fue de 13,539. 84 toneladas por hectárea para el municipio de Tlanchinol y 4,363.02 toneladas de carbono por hectárea para el municipio de San Bartolo. Por ello, REDD+ permitiría frenar el avance de la deforestación en la Huasteca y de los fragmentos de BMM en la región centro de la Sierra Madre Oriental. Sin embargo, es necesario involucrar estudios como el de éste trabajo para la construcción de una estrategia futura orientada a un manejo integral del territorio de manera sustentable.

Incentive from REDD mechanism is needed for developing countries in creating compensation to prevent forest from conversion to other uses. Incentive distribution mechanism regulates the proportional distribution of incentives and responsibilities between the parties which are the central government, local governments, communities, investors and other parties concerned. This mechanism is required in the implementation of REDDin the future. This paper aims to design a mechanism for distribution of REDDincentives through the rules of central-local budgets distribution that already exist. The research method used in this study was content analysis to see the possibility of designingREDDincentive distribution mechanism based on existing policy and the expectations of the parties involved in this activity. The research was conducted in Central Kalimantan and South Sumatera in 2009. The results showed that in the proposed REDD incentive distribution mechanisms, payments from the voluntary market can be received directly by the manager, whereas in the compliance market should be through the central government. The proportion of benefits distribution for central and local government is proposed to follow the rules in distribution of Revenue Sharing Funds from the Reforestation Fund in accordance with government regulations (PP) 55 / 2005 concerning the balance funds 60% for central government and 40% for local governments. This proportion is based on the implementation of REDD national approach with a broad range of technical and institutional cross-sectoral activities. The success of REDD implementation depend on the commitment of land owners to maintain the level of emission reductions from the previous land use practices. Thus, enforcement agreement with land owners is needed.

Special attention is needed to quantify emissions from human‐induced degradation in forest lands because these data are more uncertain and less comprehensive than deforestation data in target countries in the United Nations Reducing Emissions from Deforestation and Forest Degradation (REDD) programme. This study illustrates a Residual Trends (RESTREND) technique with a new baseline that isolates the human influence from natural climatic fluctuations to estimate emissions from forest degradation in countries across the tropics. Based on the recommended Intergovernmental Panel on Climate Change methodology and framework, we found a pattern of high carbon density of 183 t C/ha in degraded areas, which was on average 1.5 times that of deforestation areas. Further analysis revealed that the initial value of carbon stock in degraded areas was about 5.45 Pg C during 2002–2012. We found that 17% of countries displayed values more than 100% of those from deforestation under the low degradation emission scenario, whereas 23% of countries displayed values less than 10% under the high degradation emission scenario. Thus, at a national level, with such an approach REDD could be further optimized and REDD targets could be achieved in an effective way. [ABSTRACT FROM AUTHOR]

Protected areas (PAs) can mitigate climate change by reducing carbon emissions that result from forest loss. Carbon emissions from forest degradation are a large component of forest loss and are often driven by the extraction decisions of resource-dependent households. PA policies must reflect how villagers use forests to be effective. Here, a spatial Nash equilibrium of extractors' uncoordinated forest extraction pattern decisions establishes a baseline of forest-use patterns. Using that baseline, a manager chooses the location and enforcement level of PAs to maximize the avoided forest degradation in the landscape and in the PAs. Optimal PA locations depend on the labour market and the distance between forest patches. A combination of wage-improving projects and appropriately located PAs increases avoided forest degradation. [ABSTRACT FROM AUTHOR]

The formation of local carbon knowledge is central to the meaningful participation of communities in the land-based carbon projects which have become widespread in pursuit of global emissions reductions. Through a qualitative analysis of interviews with community sensitization practitioners, this paper considers how concepts of carbon are communicated to project communities. We find that fieldworkers use people's own experiences to make intangible carbon visible, but rely on scientific concepts to explain the transfer of carbon between states. However, interviews suggest that project communities' knowledge and understanding of carbon is partial. This highlights the challenges of meeting the safeguarding principles of respect for local knowledge and informed consent in carbon projects. We conclude that greater attention needs to be given by planners to the role of communication in carbon projects, including the potential to draw on indigenous knowledges to advance local understanding. [ABSTRACT FROM AUTHOR]

Suitable gravel availability is critical for the spawning success of lithophilous fishes, including redd builders. Redd construction during spawning can alter substrate characteristics, thereby influencing hydraulic conditions and sediment transport, highlighting the importance of spawning as a zoogeomorphic activity. Here, interactions between redd‐building fish and their spawning environment were investigated for European barbel Barbus barbus with a comparative approach across three English rivers: Teme (western), Great Ouse (eastern) and Idle (central). Sediment characteristics of spawning habitats were similar across the rivers, including subsurface fine sediment (<2 mm) content (≈20% dry weight), but elevated subsurface silt content and coarser surface sediments were found in the river Teme. Water velocities were similar at spawning sites despite differences in channel width and depth. Redds were characterized by a pit and tailspill, with no differences in surface grain‐size characteristics between these and the surrounding riverbed, but with topographic alteration (dimensions and tailspill amplitude) in line with those of salmonids. Estimates of the fraction of the bed that spawning barbel were capable of moving exceeded 97% in all rivers. Estimated reproductive potential varied significantly between the rivers Idle and Teme (3,098 to 9,715 eggs/m2), which was largely due to differences in barbel lengths affecting fecundity. Larger barbel, capable of producing and depositing more eggs, but in more spatially extensive redds, meaning fewer redds per given surface area of riverbed. Predictions of barbel egg mortality based on sand content were low across both rivers. The effects of silt on barbel egg and larvae development are unknown, but the levels detected here would significantly impact salmon egg mortality. Similarities in fish length to redd area and the size of moveable grains by spawning barbel and salmon suggest they have similar geomorphic effects on sediments, although fine sediment tolerance is highly divergent. [ABSTRACT FROM AUTHOR]

A changing climate is poised to inflict massive-scale damage through extreme weather events. Preserving Earth's forests stands out as a critical resource in our battle to mitigate climate change. One pivotal approach for this endeavour is the Reduction of Emissions from Deforestation and Forest Degradation (REDD), a climate change mitigation solution currently being enacted through locally-based projects certified by the Verified Carbon Standard (VCS) Association. Nevertheless, these REDD projects have recently faced severe scrutiny for potentially overemphasizing their effectiveness. To address these concerns, the VCS has put forth a new jurisdictional and nested REDD methodology. This study, therefore, aims to assess the impact of the new REDD methodology on the baseline measurements of existing REDD projects within the VCS registry. For this assessment, we selected four REDD projects, each spanning across four continents and encompassing two major forest types. An in-depth analysis of these four projects reveals a noteworthy trend: under the new methodology, three of them are projected to experience a substantial reduction in the number of issued credits compared to the previous methodologies. Consequently, it appears that the new REDD methodology holds promise in generating higher-quality credits by reducing the potential for an inflated baseline. • Application of the new methodology showed a huge reduction in baseline emission number in most of the REDD projects. • The selection of historical reference period affects the activity data estimation and deforestation risk map generation. • Use of jurisdiction in place of reference region area minimizes any chance of inflated baseline. • The new baseline emission numbers significantly reduces the chance of over crediting for the REDD projects. [ABSTRACT FROM AUTHOR]

Identifying forest ecosystems with significant ecological, social, and/or economic values is an important first-step in conserving landscape function. Here, we identify priority conservation areas in the municipalities of Chignahuapan and Zacatlan, Puebla (Mexico), based on: (i) their capacity to sequester atmospheric CO2; and (ii) risk of future deforestation. We also explore management strategies for priority-lands conservation in the Mexican context. Above-ground C sequestration was estimated using wood density and biomass expansion-factor data available from local forestry sources. Deforestation risk was estimated by a probabilistic model of land use change using socioeconomic and biophysical variables. Carbon sequestration estimates ranged from 14 to 531 Mg ha-1 for Chignahuapan and Zacatlan, respectively. An estimated 11 746 and 4 406 ha of forest was determined to be at risk of deforestation in each municipality. Of these at-risk lands, 2 421 and 1 798 ha were determined to be at high risk. In combination, we determined that 10 687 and 4 319 ha, respectively, are priority lands for carbon sequestration in Chignahuapan and Zacatlan, of which 628 and 310 ha were determined to have high conservation priority. Identifying priority conservation areas through the integrated assessment of carbon sequestration and deforestation risk can enhance efforts to target land management strategies to mitigate climate change impacts. This approach can serve as a model for other forested regions in Mexico and other countries.

Tropical forests play a key role in global carbon cycle. Reducing Emissions from Deforestation and forest Degradation (REDD+) program requires reliable mechanisms for Monitoring, Reporting and Verification (MRV). In this regard, new methods must be developed using updated technologies to assess carbon stocks. The combination of LiDAR technology and in situ forest networks allows the estimation of biomass with high resolution in low data environments, such as tropical countries. However, the evaluation of current LiDAR methods of biomass inventory, and the development of new methodologies to reduce uncertainty and increase accuracy, is still needed. Our aim is to evaluate new methodologies of spatially explicit LiDAR biomass inventories based on local and general plot-aggregate allometry. For this purpose, 25 field plots were inventoried, covering the structural and ecological variability of Poás Volcano National Park (Costa Rica). Important differences were detected in the estimation of aboveground biomass (92.74 t ha-1 considering the mean value of plot sample) depending on the chosen tree allometry. We validated the general aboveground biomass plot-aggregate allometry proposed by Asner & Mascaro (2014) in our study area, and we fitted two specific models for Poás forests. Both locals and general models depend on LiDAR top-of-canopy height (TCH), basal area (BA) and wood density. Small deviations in the wood density plot sample (0.60 ± 0.05) indicated that a single wood density constant value could be used throughout the study area. A BA-TCH origin forced linear model was fitted to estimate basal area, as suggested by the general methodology. Poás forest has a larger biomass density for the same THC compared to the rest of the forests previously studied, and shows that the BA-TCH relationship might have different trends in each life zone. Our results confirm that the general plot-aggregate methodology can be easily and reliably applied as aboveground biomass in a new area could be estimated by only measuring BA in field plots to obtain a local BA-TCH regression. For both local and general methods, the estimation of BA is critical. Therefore, the definition of precise basal area field measurement procedures is decisive to achieve reliable results in future studies.

In order to reduce deforestation, the Government of Indonesia has introduced several initiativies, including a Hutan Desa (village forest) program to bring local communities to become actor in the forest management. The Reduced Emissions from Deforestation and Forest Degradation plus (REDD+) and Payment for Environmental Services (PES) scheme for the hutan desa is one of the alternative scheme to provide economic incentives for their effort to manage their forest sustainably. This study aims to evaluate the impact of the initiation of REDD+ and PES funds for hutan desa to deforestation and community wellbeing. The impact to deforestation is measured through quantitative approach by comparing quantitatively forest cover on 1070ha of village forest through satelite image analysis. The impact to community wellbeing is measured through participatory wellbeing assessment involving 30 informants during a focus group discussion. An attribution to the variables are conducted qualitatively by in-depth interviews to 25 key informants. The result shows eventhough the benefit provided by the initiation of REDD+ and PES (the money) is much less than the opportunity cost, the community is still accepting the scheme and succeeds reducing deforestation. However, the benefit is not sufficient enough yet to improve community wellbeing.

Every policy solution is embedded in a certain “problem representation” that is taken for granted and assumed by policymakers. This paper examines how emission reductions and forest management have been problematized for policymaking and solution implementation from multiple actors’ perspectives. Reducing Emissions from Deforestation and Forest Degradation (REDD+), particularly Forest Carbon Partnership Facility (FCPF) programs, in the Lao People’s Democratic Republic (Lao PDR) serves as a demonstrative example. By applying the ‘What is the Problem Represented to be’ (WPR) approach as a poststructuralist method, this study first comparatively analyzes the general problem as represented by multiple actors, including the government, media, academia and civil society. In particular, queries such as what and how the “problem” is represented and what is not problematized are reflected during the analyses. Next, this research further examines the corresponding problematization gap based on drivers of deforestation and forest degradation and discusses the noncarbon benefits of FCPF in the rhetoric. The objective of the study is to not to find the best policy choice but to reveal the heterogeneity in problem representations formulated by multiple actors to yield space for alternative and disruptive change for future problem solving in emission reductions and forest management

Los bosques tropicales almacenan gran parte del carbono terrestre en su biomasa e iniciativas como REDD+ (Reducción de Emisiones por Deforestación y Degradación del Bosque y más) buscan evitar la liberación de este carbono por medio de la protección de los bosques. Sin embargo, no todos los bosques ricos en carbono son ricos en biodiversidad. Aquí, sintetizo la información existente sobre la relación entre la cantidad de carbono almacenado y la biodiversidad de árboles en bosques tropicales, enfatizando la importancia de que REDD+ explícitamente maximice la conservación de la biodiversidad, no solo del carbono.

Compared to conventional abatement measures, Reducing Emissions from Deforestation and Forest Degradation (REDD) offers attractive cost savings while tackling the climate change problem. However, there exist challenges associated with the selection of the optimal level of REDD-based abatement given the risks and non-uniform costs of their implementation across countries. This paper develops an integrated assessment model of carbon mitigation, incorporating the REDD option. Using a dynamic optimization framework, it derives the optimal timing and level of REDD participation for key countries with REDD potential based on their opportunity costs and risks. Specifically, Brazil, Indonesia, the Democratic Republic of Congo, Cameroon and Papua New Guinea, are chosen for inclusion under the REDD-based abatement option. Together, these five countries account for roughly 20 percent of global forest area and 40 percent of current global deforestation. The relevance and contribution of REDD-based abatement is explored under the possibility of non-linear damages resulting from increasing concentrations of greenhouse gases. Results indicate that the REDD programme is an attractive option to consider despite the associated risks of impermanence. Including the REDD option, in fact, also increases conventional abatement efforts because low costs of REDD reduce the overall abatement costs, thereby making it optimal to abate more. Further, use of REDD option helps stabilise the atmospheric carbon stock in the long term. Without REDD, atmospheric carbon concentrations would be higher by 800 billion tonnes in the next 300 years. Whereas, optimal implementation of REDD in just five countries would help avoid the release of about 80 billion tonnes of carbon in the next 50 years. • This paper develops an IAM for carbon mitigation incorporating the REDD option. • Investigates the influence of REDD option on overall carbon abatement levels. • Explores optimal REDD involvement when damages evolve non-linearly. • Models individual opportunity costs and risks for countries with large REDD potential. • Derives optimal involvement level through REDD for Brazil and Indonesia. [ABSTRACT FROM AUTHOR]

Climate change is a complex and uncertain global problem because it is driven by human behavior, with long-term climate-related risks for natural and human systems. Changes in human behavior, financing flow, policy instruments, and multilevel governance are needed for mitigating and managing major climate risks. Understanding the social dimensions of climate change is, quite literally, a hot topic to be studied. Most of the scientific literature in the field is focused on the 'hard science'. Different methods of theory building are used in applied social sciences. However, the use of the grounded theory approach in sustainability research, specially on 'soft science' in the fi eld of climate change, is scarce. The intent of this paper is to discussion the use of the grounded theory method in an emergent research fi eld that combines governance and climate change. The article presents substantive results of an emerging theoretical framework that explain the governance process of REDD+ in Brazil, an United Nations Framework Convention on Climate Change (UNFCCC) climate fi nance mechanism focused on mitigating forest-related emissions in developing countries. Instead of discussing best procedures and techniques to build grounded theory, which are largely accessed through several peer-reviewed publications, our focus is to provide a practical guide and discuss lessons learned from the fi eld to integrate the 'REDD+ Governance Theoretical Framework'. Thus, scholars and graduate students are encourage to test and validate (or not) the emerging theoretical framework. [ABSTRACT FROM AUTHOR]