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Mapping of selective logging activities and estimation of forest degradation in each compartment. Maps in (a), (b,c) represent the unplanned conventional logging (CL). Figures from (d–g) are representative of the planned managed logging 1 (ML1). Finally, (h,i) reflects the second planned logging approach (ML2). Codes for logging compartments: RP I: Research plot I; RP II: Research plot II; EDP: Experimental Development Plot; C1: Compartment 1; C2: compartment 2; C3: Compartment 3; C4: Compartment 4; STM I: Santa Maria I; and STM II: Santa Maria II.
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Selective logging in the tropics is a major driver of forest degradation by altering forest structure and function, including significant losses of aboveground carbon. In this study, we used a 30-year Landsat time series (1985–2015) to analyze forest degradation and carbon emissions due to selective logging in a Forest Reserve of the Venezuelan Ama...
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... En el nuevo Plan de Manejo se anunció la ejecución de técnicas de aprovechamiento de impacto reducido para disminuir "…un 70 % el impacto sobre el bosque con relación a las técnicas de extracción aplicadas tradicionalmente…" Pero Ussher (2014) realizó una evaluación en el primer compartimiento que aprovecharon (STM1) e indicó que en la empresa "...no se encontraron evidencias de aplicación de la tala dirigida… deberá suministrar un mapa detallado con los árboles a ser cosechados… deberá mapear las vías de arrastre, suministrarle a las cuadrillas de arrastre dichos mapas y a su vez los mapas de los árboles cosechados…" Esto significa que esos mapas tal vez existían, pero no estaban disponibles en el campo para los operadores. De igual forma, los resultados reportados por Pacheco et al. (2021) demuestran que el aprovechamiento ejecutado en dos compartimientos de la ENAFOR tiene igual o mayor impacto de aprovechamiento que lo generado, en la misma Unidad de Manejo, por la empresa Intecmaca en compartimientos anteriores (Cuadro 3.2). Al considerar los daños por árbol aprovechado, el impacto generado por ENAFOR (en 2012) supera a los valores de todos los años anteriores. ...
... Existen algunas experiencias en este sentido, pero han sido muy incipientes y no han logrado los objetivos de reducir el impacto. En el Capítulo 2 se detalló que el Plan de Manejo de ENAFOR (2012) indicaba la intención de aplicar técnicas de AIR; pero Ussher (2014) señaló que una medida fundamental (cartografía de los árboles a aprovechar) realmente no llegó al terreno y Pacheco at al. (2021) demostraron que en varios aspectos el aprovechamiento ejecutado por la ENAFOR tuvo igual o mayor impacto a lo que se hizo con la iniciativa privada en años anteriores. Lozada et al. (2016bLozada et al. ( , 2022a indican que un aprovechamiento desordenado puede generar una alteración importante en la dinámica del ecosistema y ocurre una transformación a un bosque de lianas. ...
Revista Forestal Venezolana, vol 66, Num Esp 2024: 7-154.
Con la visión de que el sector forestal venezolano debe convertirse en un sistema que promueva un aprovechamiento sostenible de los recursos forestales del país, a la vez de conservar o mejorar los valores intrínsecos de los ecosistemas boscosos y otros territorios del medio rural donde ejecuta sus actividades y con la misión de aportar elementos de diagnóstico y de diseño de alternativas de programas forestales que coincidan con los intereses ambientales de la nación y la satisfacción de necesidades de diversos productos forestales y servicios ambientales, la presente propuesta plantea como objetivos: eliminar la deforestación en Venezuela; mejorar el conocimiento de los ecosistemas y las plantaciones forestales y agroforestales de Venezuela, con la finalidad de lograr su manejo sostenible; favorecer la conservación de los ecosistemas dentro de las áreas destinadas al aprovechamiento forestal sostenible; lograr el autoabastecimiento sostenible de productos forestales en Venezuela, prescindiendo de las importaciones y generando excedentes para exportación; reducir la producción de madera generada por permisos anuales; aumentar la cobertura forestal de Venezuela mediante plantaciones forestales; incrementar el uso integral de la tierra, la rentabilidad y la resiliencia económica de las poblaciones rurales, mediante los sistemas agroforestales.
Esta propuesta es una iniciativa técnica basada en la larga experiencia forestal de Venezuela, proponiendo realizar mejoras sustanciales para el diseño y las operaciones futuras de la gestión forestal, contenidas en los siguientes programas forestales: 1. Programa de Deforestación Neta Cero (PDNC). 2. Programa de Manejo Sostenible del Patrimonio Forestal Natural (PMSPFN). 3. Programa Nacional de Plantaciones Forestales y Agroforestales (PNPFA).
Se planifica eliminar la deforestación, conservar 6,75 millones de ha de ecosistemas boscosos dentro de las reservas forestales y áreas boscosas bajo protección, el manejo sostenible de 4,3 millones ha de bosques y el aprovechamiento de las plantaciones que actualmente existen, proponiendo el establecimiento de 68.800 ha/año de nuevas plantaciones forestales. Estas actividades generarían 21.500 empleos directos, reducción de 50,86 millones de tCO2/año (22,5 % de las emisiones de Venezuela) y a mediano y largo plazo un sumidero de 16,86 millones de tCO2/año (un 7,5 % del total de emisiones anuales del país).
... NDVI is commonly used in vegetation analysis, such as mangroves [31] and forests, and is widely used to predict Remote Sens. 2023, 15, 1016 7 of 21 carbon stock and carbon emissions [32,33]. NDVI can derive forest attributes in terms of their density and can be used as carbon emission variables for predicting carbon emissions from selective logging activities based on the value of the indices employed from multispectral bands in satellite imagery [34]. NDVI was calculated using red and near-infrared channels as in Equation (2), with NDVI values varying from −1 to 1. ...
Harvested timber and constructed infrastructure over the logging area leave massive damage that contributes to the emission of anthropogenic gases into the atmosphere. Carbon emissions from tropical deforestation and forest degradation are the second largest source of anthropogenic emissions of greenhouse gases. Even though the emissions vary from region to region, a significant amount of carbon emissions comes mostly from timber harvesting, which is tightly linked to the selective logging intensity. This study intended to utilize a remote sensing approach to quantify carbon emissions from selective logging activities in Ulu Jelai Forest Reserve, Pahang, Malaysia. To quantify the emissions, the relevant variables from the logging’s impact were identified as a predictor in the model development and were listed as stump height, stump diameter, cross-sectional area, timber volume, logging gaps, road, skid trails, and incidental damage resulting from the logging process. The predictive performance of linear regression and machine learning models, namely support vector machine (SVM), random forest, and K-nearest neighbor, were examined to assess the carbon emission from this degraded forest. To test the different methods, a combination of ground inventory plots, unmanned aerial vehicles (UAV), and satellite imagery were analyzed, and the performance in terms of root mean square error (RMSE), bias, and coefficient of correlation (R2) were calculated. Among the four models tested, the machine learning model SVM provided the best accuracy with an RMSE of 21.10% and a bias of 0.23% with an adjusted R2 of 0.80. Meanwhile, the linear model performed second with an RMSE of 22.14%, a bias of 0.72%, and an adjusted R2 of 0.75. This study demonstrates the efficacy of remotely sensed data to facilitate the conventional methods of quantifying carbon emissions from selective logging and promoting advanced assessments that are more effective, especially in massive logging areas and various forest conditions. Findings from this research will be useful in assisting the relevant authorities in optimizing logging practices to sustain forest carbon sequestration for climate change mitigation.
... For example, some studies found no difference in coarse woody debris and litter carbon pools in logged stands [57,78], whereas others did [42]. Nonetheless, generally speaking, post-logging above-ground carbon stocks were found to be lower [42,47,54,57]. The recovery of carbon stock or above-ground biomass was found to be a longer process in heavily logged forests [79,80]. ...
Every year, logging in the world’s largest tropical forest, located within the Amazon biome, continues unabated. Although it is a preferred alternative to deforestation, the residual stand and site are impacted by logging. The objective of this review was to determine and assess the current state of research throughout Amazonia on the subject of logging impacts. To achieve this goal, a systematic approach was utilized to gather, assess and categorize research articles conducted in the Amazon biome over the last decade. Eligibility for inclusion of articles required demonstration of a direct impact from logging operations. A total of 121 articles were determined to meet the eligibility requirements and were included in this review. Articles were subdivided into three environmental categories: forest (n = 85), wildlife (n = 24) and streams (n = 12). The results of this review demonstrated that impacts from logging activities to the forest site were a direct result of the logging cycle (e.g., how often logging occurs) or logging intensity (e.g., how many trees are felled). The impacts to wildlife varied dependent on species, whereas impacts to streams were affected more by the logging system. Overall, research suggested that to attain sustainability and diminish the impacts from logging, a lower logging intensity of 10–15 m3 ha−1 and a longer logging cycle of 40–60 years would be essential for the long-term viability of forest management in Amazonia.
... The work by Pacheco-Angulo et al. [2] shows an overall precision of 94.3% when using a novel approach to efficiently map selective logging and forest degradation in the Venezuelan Amazon. Their analytical approach used Landsat-based linear spectral unmixing to map soil fraction and predict the location of log landings, logging roads and logging gaps, and then estimate the approximate area of forest degradation by selective logging within a buffer of 300 m. ...
For more than three decades, the remote sensing scientific community has successfully generated predictive models of tropical forest attributes and ecological processes at the leaf, canopy, patch and landscape scale by linking field-measured data to remotely sensed spectral values, as well as other variables derived from remotely sensed data. The main interest of these applications is to help describe ecological and functional patterns occurring at larger geographic scales with sufficient accuracy and precision and enable scientists to better understand ecological processes, such as the relationship between atmospheric fluxes, plant structural and ecophysiological traits, soil attributes, anthropogenic use, species occurrence and animal movement. However, as the earth’s environment suffers from ever-increasing human use and abuse, detecting spatiotemporal changes in these variables has become a necessary decision-making tool in conservation action and natural resources’ management. Moving from modeling into the study of soil, plants, wildlife and socioecological processes using remotely sensed data requires the extrapolation of single time-step models to its application on a time series of data with the same expected accuracy. The challenges in this matter are not trivial, since changes in soil moisture conditions, cloud contamination, canopy and leaf-level geometry and physiology can affect the strength of the proposed models. In this context, the term ‘Operationalization’ refers to migration from single time-step models to time series but also refers to the design and implementation of user-friendly tools to increase the efficacy of communicating spatiotemporal trends to the users. [...]
... UAV LiDAR highlighted the importance of detecting such events, as we found that, in an area of selectively logged forest, more than half of canopy gaps were smaller than 0.05 ha and 62% of disturbed area was caused by gaps below 0.1 ha: a degradation mapping tool that excluded these disturbances could severely underestimate degradation, and miss whole regions of degradation typified by multiple small clearances. For comparison, many previous attempts to detect selective logging from satellite data have worked at the 0.09 ha scale of Landsat pixels [64][65][66][67]. Although there is evidence that disturbances as small as 25% of a Landsat pixel can be detected [68], this relies on a cloud free image being available from the short period during which the disturbed area shows bare ground and therefore a strong optical difference to the canopy, which is likely to lead to high missed detection rates in cloudy tropical regions. ...
Selective logging is a major cause of forest degradation in the tropics, but its precise scale, location and timing are not known as wide-area, automated remote sensing methods are not yet available at this scale. This limits the abilities of governments to police illegal logging, or monitor (and thus receive payments for) reductions in degradation. Sentinel-1, a C-band Synthetic Aperture Radar satellite mission with a 12-day repeat time across the tropics, is a promising tool for this due to the known appearance of shadows in images where canopy trees are removed. However, previous work has relied on optical satellite data for calibration and validation, which has inherent uncertainties, leaving unanswered questions about the minimum magnitude and area of canopy loss this method can detect. Here, we use a novel bi-temporal LiDAR dataset in a forest degradation experiment in Gabon to show that canopy gaps as small as 0.02 ha (two 10 m × 10 m pixels) can be detected by Sentinel-1. The accuracy of our algorithm was highest when using a timeseries of 50 images over 20 months and no multilooking. With these parameters, canopy gaps in our study site were detected with a false alarm rate of 6.2%, a missed detection rate of 12.2%, and were assigned disturbance dates that were a good qualitative match to logging records. The presence of geolocation errors and false alarms makes this method unsuitable for confirming individual disturbances. However, we found a linear relationship (r2=0.74) between the area of detected Sentinel-1 shadow and LiDAR-based canopy loss at a scale of 1 hectare. By applying our method to three years’ worth of imagery over Gabon, we produce the first national scale map of small-magnitude canopy cover loss. We estimate a total gross canopy cover loss of 0.31 Mha, or 1.3% of Gabon’s forested area, which is a far larger area of change than shown in currently available forest loss alert systems using Landsat (0.022 Mha) and Sentinel-1 (0.019 Mha). Our results, which are made accessible through Google Earth Engine, suggest that this approach could be used to quantify the magnitude and timing of degradation more widely across tropical forests.
... Additionally, the forest had 27,800 m 3 of green biomass and 13,066 t of carbon (Mihut et al. 2019). Another study on forest degradation as a result of logging was conducted in Venezuela's Amazon (Pacheco-Angulo et al. 2021). The findings indicated that forest degradation directly impacted 24,480 ha of the Imataca forest reserve. ...
The increasing global industrialization and over-exploitation of fossil fuels has induced the release of greenhouse gases, leading to an increase in global temperature and causing environmental issues. There is therefore an urgent necessity to reach net-zero carbon emissions. Only 4.5% of countries have achieved carbon neutrality, and most countries are still planning to do so by 2050–2070. Moreover, synergies between different countries have hampered synergies between adaptation and mitigation policies, as well as their co-benefits. Here, we present a strategy to reach a carbon neutral economy by examining the outcome goals of the 26th summit of the United Nations Climate Change Conference of the Parties (COP 26). Methods have been designed for mapping carbon emissions, such as input–output models, spatial systems, geographic information system maps, light detection and ranging techniques, and logarithmic mean divisia. We present decarbonization technologies and initiatives, and negative emissions technologies, and we discuss carbon trading and carbon tax. We propose plans for carbon neutrality such as shifting away from fossil fuels toward renewable energy, and the development of low-carbon technologies, low-carbon agriculture, changing dietary habits and increasing the value of food and agricultural waste. Developing resilient buildings and cities, introducing decentralized energy systems, and the electrification of the transportation sector is also necessary. We also review the life cycle analysis of carbon neutral systems.
... Souza and Barreto (2000) [102] and Matricardi et al. (2005) [103] both concluded that by applying a buffer of ca. 160m to 180m around larger logging features (which can be detected by remote sensing analysis), most smaller-sized logging infrastructure and residual damaged vegetation due to the logging operations should be included [104], [105]. Using a similar approach, Beuchle et al. (2019) [61] estimated that the forest area 'affected by selective logging' in the Southern Brazilian Amazon is up to 5 times larger compared to a strict pixel-based mapping approach, once a buffer of 150 m is applied around the pixels mapped as selective logging. ...
This report aims to communicate the statistics of deforestation and forest degradation 2002-2020 for the rainforest in the South American countries of the Amazon region, based on the new JRC Tropical Moist Forest (JRC-TMF) dataset. In addition, the report describes the dynamics of deforestation and forest degradation in the region, while putting an emphasis on various types of forest degradation and the effects of forest cover change related to road building, protected areas and the spread of zoonotic diseases.
Forest degradation and hunting are two major drivers of species declines in tropical forests, often associated with forest production activities and infrastructure. To assess how the medium‐to‐large bodied terrestrial vertebrate community varied across these two main gradients of anthropogenic impact, we conducted a camera‐trap survey across three production forest reserves in central Sabah, Malaysian Borneo, each with different past and current logging regimes. We analyzed data from a 32‐species community using a Bayesian community occupancy model, investigating the response of occurrence, diversity, and composition to forest degradation and accessibility (a proxy for hunting pressure). We found forest degradation to be a strong driver of occurrence of individual species. Such responses led to declines in diversity and shifts in community composition, where forest‐dependent species decreased while disturbance‐tolerant species increased in occupancy probability with increasing forest degradation. Accessibility had a weaker effect on community diversity and species occupancy, and low‐level hunting pressure and management of access to our study sites likely played an important role in mitigating accessibility effects. Nonetheless, our results showed accessibility had compounding effects on a wildlife community already affected negatively by forest degradation. Despite the impacts of forest degradation and accessibility on the terrestrial vertebrate community, our results highlight how the application of more sustainable practices—reducing forest disturbance and managing unauthorized access to logging roads—resulted in more intact wildlife communities. Understanding how both disturbances combined affect the terrestrial vertebrate community is essential for evaluating and developing effective sustainability guidelines.
Abstract in malay is available with online material.
Este relatório comunica as estatísticas de desmatamento e degradação florestal 2002-2020 para a floresta tropical nos países sul-americanos da região amazônica, com base no novo conjunto de dados JRC Tropical Moist Forest (JRC-TMF). Além disso, o relatório descreve a dinâmica do desmatamento e degradação florestal na região, enfatizando vários tipos de degradação florestal e os efeitos da mudança da cobertura florestal relacionados à construção de estradas, áreas protegidas e disseminação de doenças zoonóticas.
