While attention on logging in the tropics has been increasing, studies on the long‐term effects of silviculture on forest dynamics and ecology remain scare and spatially limited. Indeed, most of our knowledge on tropical forests arises from studies carried out in undisturbed tropical forests. This bias is problematic given that logged and disturbed tropical forests are now covering a larger area than the so‐called primary forests. A new network of permanent sample plots in logged forests, the Tropical managed Forests Observatory (TmFO), aims to fill this gap by providing unprecedented opportunities to examine long‐term data on the resilience of logged tropical forests at regional and global scales. TmFO currently includes 24 experimental sites distributed across three tropical regions, with a total of 490 permanent plots and 921 ha of forest inventories.

In the Brazilian Amazon, multiple logging activities are undergoing, involving different actors and interests. They shape a disturbance gradient bound to the intensity and frequency of logging, and forest management techniques. However, until now, few studies have been carried out at the landscape scale taking into account these multiple types of logging and this disturbance gradient. Here we address this issue of how to account for the multiple logging activities shaping the current forest landscape. We developed an inexpensive and efficient remote sensing methodology based on Landsat imagery to detect and track logging activity based on the monitoring of canopy openings. Then, we implemented a set of remote sensing indicators to follow the different trajectories of forest disturbance through time. Using these indicators, we emphasized five major spatial and temporal disturbance patterns occurring in the municipality of Paragominas (State of Pará, Brazilian Amazon), from well-managed forests to highly over-logged forests. Our disturbance indicators provide observable evidence for the difference between legal and illegal patterns, with some illegal areas having suffered more than three explorations in fifteen years. They also clearly underlined the efficiency of Reduced Impact Logging (RIL) techniques applied under Forest Stewardship Council (FSC) guidelines to reduce the logging impacts in terms of canopy openings. For these reasons, we argue the need to promote legal certified logging to conserve forests, as without them, many actors mine the forest resources without any concerns for future stocks. Finally, our remote tracking methodology, which produces easy to interpret disturbance indicators, could be a real boon to forest managers, including for conservationists working in protected areas and stakeholders dealing with international trade rules such as RBUE (Wood regulation of European Union) or FLEGT (Forest Law for Enforcement, Governance and Trade).

A procura intensa por essências madeireiras nativas consolidadas, que apresentam elevado uso, pode ocasionar a superexploração de espécies e diminuição do seu estoque na floresta. Uma alternativa para essa situação é a substituição dessas espécies por outras com propriedades da madeira semelhantes e com suficiente estoque de crescimento na floresta. O objetivo deste trabalho foi agrupar as espécies da Amazônia através das propriedades físico-mecânicas da madeira e realizar a análise discriminante para identificar quais características tecnológicas são mais importantes para o agrupamento. As espécies estudadas foram provenientes de oito localidades distintas da região amazônica. As propriedades físico-mecânicas utilizadas obtidas da literatura especializada nacional foram: densidade básica, contração (tangencial, radial e volumétrica), flexão estática, compressão paralela e perpendicular às fibras, dureza Janka paralela e transversal, tração perpendicular às fibras, fendilhamento e cisalhamento. Foi utilizada a técnica de análise multivariada de Cluster (distância euclidiana simples e o método de Ward) e a análise discriminante para avaliar o agrupamento. A análise de Cluster foi eficiente para agrupar as espécies, que foram separadas em três grupos distintos. As espécies que se destacaram foram a Helicostylis pedunculata Benoist. e Tachigali chrysophylla (Poepp.) Zarucchi & Herend., por se agruparem com as espécies mais comercializadas. Os menores valores de Wilks’Lambda foram da densidade da madeira (0,759053), cisalhamento (0,802960) e compressão paralela às fibras (0,825594). Essas características foram as mais determinantes para discriminar os grupos. A análise de agrupamento é eficiente para indicar a substituição de espécies consolidadas na Amazônia.

Managed forests are a major component of tropical landscapes. Production forests as designated by national forest services cover up to 400 million ha, i.e. half of the forested area in the humid tropics. Forest management thus plays a major role in the global carbon budget, but with a lack of unified method to estimate carbon fluxes from tropical managed forests. In this study we propose a new time- and spatially-explicit methodology to estimate the above-ground carbon budget of selective logging at regional scale. The yearly balance of a logging unit, i.e. the elementary management unit of a forest estate, is modelled by aggregating three sub-models encompassing (i) emissions from extracted wood, (ii) emissions from logging damage and deforested areas and (iii) carbon storage from post-logging recovery. Models are parametrised and uncertainties are propagated through a MCMC algorithm. As a case study, we used 38 years of National Forest Inventories in French Guiana, northeastern Amazonia, to estimate the above-ground carbon balance (i.e. the net carbon exchange with the atmosphere) of selectively logged forests. Over this period, the net carbon balance of selective logging in the French Guianan Permanent Forest Estate is estimated to be comprised between 0.12 and 1.33 Tg C, with a median value of 0.64 Tg C. Uncertainties over the model could be diminished by improving the accuracy of both logging damage and large woody necromass decay submodels. We propose an innovating carbon accounting framework relying upon basic logging statistics. This flexible tool allows carbon budget of tropical managed forests to be estimated in a wide range of tropical regions.

Several studies have assessed forest disturbance in tropical forests using Landsat imagery. However, the spatial resolution (30 m) of Landsat images has often been considered too coarse to accurately detect the extent and impacts of selective logging. The Sentinel-2 satellite launched in 2015 has been providing images at spatial resolutions of 10 to 20 m and those images have shown an improved potential for detecting forest disturbances in tropical regions. We compared Landsat-8 and Sentinel-2 imagery for detecting selective logging in a rain forest site in the Brazilian Amazon. The aerosol-free modified soil adjusted vegetation index (MSAVI_af) was retrieved from the satellite images acquired in August 2020 immediately following logging. A robust reference dataset of very-high-resolution imagery (0.5 m) acquired using a complementary metal oxide semiconductor sensor (visible bands) onboard of an unmanned aerial vehicle was used to image the area of interest and a map derived from it was used to assess the classification accuracies made using satellite-derived data. The overall accuracy of the classified Sentinel-2 and Landsat-8 images varied between 54% and 83%, depending on the applied classification parameters for distinguishing undisturbed from disturbed forest canopy. Images acquired using the UAV allowed us to detect subtle impacts of canopy openings by selective logging activities. Images acquired using the UAV allowed the detection of small canopy openings, but not Sentinel-2 or Landsat-8. Sentinel-2 provided more details of canopy disturbances than Landsat image. Our classification approach is fully implementable on the Google Earth Engine platform and is a promising technique to monitor selective logging impacts in tropical forests.