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Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan‐tropical model to predict plot‐level forest structure properties and biomass from only the largest trees. Location: Pan‐tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot‐ and site‐level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium‐sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate‐diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change. [ABSTRACT FROM AUTHOR]

In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun-scene-sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun-scene-sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R² = 0.85; P < 0.001) across a wide range of AGB levels from 26 Mg/ha to 460 Mg/ha, and was confirmed by cross validation. A high-resolution biomass map (100-m pixels) was produced for a 400-km² area, and predictions obtained from both imagery sources were consistent with each other (r -- 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. in particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies. [ABSTRACT FROM AUTHOR]

In the early 2000s, beech forests in Western Europe suffered from a so far unexplained burst of mortality. Necroses, ambrosia-beetle and fungal attacks were observed on the trunks. The symptoms were similar to previous events reported throughout the 20th Century., One current hypothesis is that these phenomena were related to early frost events for which the trees were physiologically unprepared and which made them vulnerable to biotic attacks. In the present study, we aimed to test this hypothesis further, by retrospective meteorological analyses and also by an experimental approach., Our meteorological analyses highlighted the occurrence of cold waves a year before the beech declines were reported in 1929, 1942 and 1998., In our experimental approach, frost injuries were inflicted to mature trees in a beech stand using dry ice. The treated trees were more attractive to insects than untreated controls. Insect attacks were observed in the treated zones on the trees but colonization was not very successful. The galleries had aborted most of the time with only a few larval chambers. Very few insects were caught in emergence traps., The results of these two approaches support and strengthen the hypothesis that frost induced beech dieback. Frost injuries increased tree attraction to ambrosia beetles to the point of inducing attacks. However, the overall success of these attacks was much lower than that observed in the 2000s. These differences might reflect limitations in our experimental approach, where frost wounding was applied locally to the trees. [ABSTRACT FROM AUTHOR]

Understanding entry pathways resulting from global trade is critical to assess the risks of introduction of invasive alien species (IAS). From 1996 onward, the import of timber from Russia and the Baltic States to Belgium dramatically increased, with more than one million cubic metres of coniferous round wood imported until 2004. Such a high volume could have served as entry pathway for exotic bark beetles from the East that have the potential to become forest insect pests upon establishment. We collected and cross-checked different data sources (FAOSTAT, Eurostat, National Bank of Belgium, Belgian Customs, the Belgian sawmills industry) regarding the import of timber in an attempt to trace back the spatial and temporal patterns of this trade, and to assess the expected validity of a pest risk analysis based on those data. We found that the timber trade between 1996 and 2004 is particularly dynamic in space and time, and may have allowed several opportunities for exotic bark-beetle introductions. In addition, the patterns of trade change so quickly from year to year that the existing data sources are essentially not adequate for IAS risk assessment in a near real-time fashion. The data are either comprehensive, but then aggregated at a too coarse level (space, time, or category) to be of real use in risk assessment, or available with adequate levels of details, in which case they are mostly partial or incomplete. Better accessibility to data and data exchanges between organizations in charge of trade data collection and plant protection would help better targeting of phytosanitary controls. [ABSTRACT FROM AUTHOR]