Abstract: Ants are omnipresent in tropical forests, especially territorially dominant arboreal ants whose territories are spatially segregated forming ‘ant mosaics’. These ecologically important species are rarely used in conservation monitoring because of the difficulty in collecting them. We developed a standardised baitline protocol to study the distribution of dominant ants on canopy trees and also a procedure to objectively define species dominance, even in unknown ant assemblages.
Besides eliminating the need to climb trees, this protocol allows live arboreal ant specimens to be sampled at different heights. Behavioural aggressiveness assays between the collected workers provide data on the three-dimensional distribution of colonies and on interactions between species. We compared the results of the behavioural tests to those from null models.
In the New Guinean lowland forest studied, we show that the canopy was either shared by multiple territorial species or inhabited by a single species with a large territory. The baitline protocol collected up to half of the arboreal ant species found in a felling census. However, the proportion of species collected at baits decreased with the increasing spatial dominance of single territorial species.
Behavioural observations used in the protocol allowed a more efficient detection of ant mosaics than null models. Territorially dominant ants were active on both understorey and canopy trees.
The protocol is fast and easy to replicate. It is a potential tool for understanding and monitoring the spatiotemporal dynamics of arboreal ant assemblages and can detect populous colonies, including those of invasive species

Abstract: Selective logging in tropical forests is often perceived as a source of forest degradation and carbon emissions. Improved practices, such as reduced-impact logging (RIL), and alternative timber production strategies (e.g. plantations) can drastically change the overall carbon impact of the wood production sector. Assessing the carbon balance of timber production is crucial but highly dependent on methodological approaches, especially regarding system boundaries and temporality. We developed a temporally-explicit and territory scale model of carbon balance calibrated with long-term local data using Bayesian inference. The model accounts for carbon fluxes from selective logging in natural forest, timber plantation, first transformation and avoided emissions through energy substitution. We used it to compare prospective scenarios of development for the wood sector in French Guiana. Results show that intensification of practices, through increased logging intensity conducted with RIL and establishment of timber plantations, are promising development strategies to reduce the carbon emissions of the French-Guianese wood sector, as well as the area needed for wood production and hence the pressure on natural forests. By reducing logging damage by nearly 50%, RIL allows increasing logging intensity in natural forest from 20 m3 ha−1 to 30 m3 ha−1 without affecting the carbon balance. The use of logging byproducts as fuelwood also improved the carbon balance of selective logging, when substituted to fossil fuel. Allocating less than 30 000 ha to plantation would allow producing 200 000 m3 of timber annually, while the same production in natural forest would imply logging more than 400 000 ha over 60 years. Timber plantation should be preferentially established on non-forested lands, as converting natural forests to plantation leads to high carbon emission peak over the first three decades. We recommend a mixed-strategy combining selective logging in natural forests and plantations as a way to improve long-term carbon balance while reducing short-term emissions. This strategy can reduce the pressure on natural forests while mitigating the risks of changing practices and allowing a diversified source of timber for a diversity of uses. It requires adaptation of the wood sector and development of technical guidelines. Research and monitoring efforts are also needed to assess the impacts of changing practices on other ecosystem services, especially biodiversity conservation.

Abstract: Automatic tree crown segmentation from remote sensing data is especially challenging in dense, diverse, and multilayered tropical forest canopies, and tracking mortality by this approach is even more difficult. Here, we examine the potential for combining airborne laser scanning (ALS) with multispectral and hyperspectral data to improve the accuracy of tree crown segmentation at a study site in French Guiana. We combined an ALS point cloud clustering method with a spectral deep learning model to achieve 83% accuracy at recognizing manually segmented reference crowns (with congruence >0.5). This method outperformed a two-step process that involved clustering the ALS point cloud and then using the logistic regression of hyperspectral distances to correct oversegmentation. We used this approach to map tree mortality from repeat surveys and show that the number of crowns identified in the first that intersected with height loss clusters was a good estimator of the number of dead trees in these areas. Our results demonstrate that multisensor data fusion improves the automatic segmentation of individual tree crowns and presents a promising avenue to study forest demography with repeated remote sensing acquisitions.

Abstract: Tropical forests disappear rapidly because of deforestation, yet they have the potential to regrow naturally on abandoned lands. We analyze how 12 forest attributes recover during secondary succession and how their recovery is interrelated using 77 sites across the tropics. Tropical forests are highly resilient to low-intensity land use; after 20 years, forest attributes attain 78% (33 to 100%) of their old-growth values. Recovery to 90% of old-growth values is fastest for soil (<1 decade) and plant functioning (<2.5 decades), intermediate for structure and species diversity (2.5 to 6 decades), and slowest for biomass and species composition (>12 decades). Network analysis shows three independent clusters of attribute recovery, related to structure, species diversity, and species composition. Secondary forests should be embraced as a low-cost, natural solution for ecosystem restoration, climate change mitigation, and biodiversity conservation.

Abstract: Fostered by the upcoming BIOMASS mission, this article explores long-term trends of P-band temporal decorrelation over a tropical forest due to a time series of 617 days acquired during the TropiScat-2 experiment. The interest in this unique time series is twofold. First, it provides consistent statistics to monitor the yearly evolution of temporal coherences according to specific time scales of the BIOMASS tomographic and interferometric phases. Second, it provides key insights to explore new processing approaches with the combination of data from different orbit directions (ascending/descending) and different mission cycles separated by about seven months according to the current acquisition plan. For the first time, this study shows that 18-day coherences (corresponding to the time interval between the first and last acquisitions of the BIOMASS tomographic processing) can vary significantly according to rainy and dry seasons (medians from 0.3 to 0.9). The extension to time intervals of up to 90 days within both seasons and over two consecutive years puts forward the key role of the typical sporadic rainfalls occurring during dry periods in tropical rainforests, with a stronger impact on temporal coherence evolution compared to the more reproducible rainy seasons. Furthermore, outstanding values significantly above zero have been obtained for the 7- and 14-month coherences (medians of 0.35 and 0.2, respectively), opening the way to new methods of change detection. Overall, this study highlights the role of P-band temporal decorrelation not only as a disturbance factor for coherent applications but also as a relevant indicator of forest changes.