Abstract. A mechanistic understanding of how tropical-tree mortality responds to climate variation is urgently needed to predict how tropical-forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure; temporal variation; and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or the collapse of standing dead trees. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though wind speeds were lower in the wet season. The strongest correlate of monthly variation in canopy disturbance rates was the frequency of extreme rainfall events. The size distribution of canopy disturbances was best fit by a Weibull function and was close to a power function for sizes above 25 m2. Treefalls accounted for 74 % of the total area and 52 % of the total number of canopy disturbances in treefalls and branchfalls combined. We hypothesize that extremely high rainfall is a good predictor because it is an indicator of storms having high wind speeds, as well as saturated soils that increase uprooting risk. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates at fine temporal and spatial resolutions over large areas, thereby enabling robust tests of how temporal variation in disturbance relates to climate drivers. Further insights could be gained by integrating these canopy observations with high-frequency measurements of wind speed and soil moisture in mechanistic models to better evaluate proximate drivers and with focal tree observations to quantify the links to tree mortality and woody turnover.

Tree growth and survival differ strongly between canopy trees (those directly exposed to overhead light), and understory trees. However, the structural complexity of many tropical forests makes it difficult to determine canopy positions. The integration of remote sensing and ground-based data enables this determination and measurements of how canopy and understory trees differ in structure and dynamics. Here we analyzed 2 cm resolution RGB imagery collected by a Remotely Piloted Aircraft System (RPAS), also known as drone, together with two decades of bi-annual tree censuses for 2 ha of old growth forest in the Central Amazon. We delineated all crowns visible in the imagery and linked each crown to a tagged stem through field work. Canopy trees constituted 40% of the 1244 inventoried trees with diameter at breast height (DBH) > 10 cm, and accounted for ~70% of aboveground carbon stocks and wood productivity. The probability of being in the canopy increased logistically with tree diameter, passing through 50% at 23.5 cm DBH. Diameter growth was on average twice as large in canopy trees as in understory trees. Growth rates were unrelated to diameter in canopy trees and positively related to diameter in understory trees, consistent with the idea that light availability increases with diameter in the understory but not the canopy. The whole stand size distribution was best fit by a Weibull distribution, whereas the separate size distributions of understory trees or canopy trees > 25 cm DBH were equally well fit by exponential and Weibull distributions, consistent with mechanistic forest models. The identification and field mapping of crowns seen in a high resolution orthomosaic revealed new patterns in the structure and dynamics of trees of canopy vs. understory at this site, demonstrating the value of traditional tree censuses with drone remote sensing.

In mid‐January 2005 a convective squall line traversed 4.5 × 106 km2 of Amazonia from southwest to northeast. As seen in Landsat images, this atypical convective storm left blowdown imprints with diffuse geometry, unlike the fan‐shaped wind disturbance of much more frequent east‐to‐west propagating squall lines. Previous work reported 0.2% of the forest area damaged by this one relatively rare event within one Landsat image and assumed similar disturbance across the entire traverse. We mapped convective wind damage impact to the region in 2005 by identifying large‐scale (>4 ha) blowdown imprints in 30 Landsat images. The diffuse‐type imprints associated with this single squall line contributed up to 60–72% of total 2005 wind‐disturbed area detected across the region, but damage was highly concentrated in central Amazonia. Consequently, the distribution of large wind damage patches in 2005 across Amazonia was very different from long‐term average. Regional distribution of wind‐driven tree mortality for smaller patch sizes remains unknown.

Abstract. A mechanistic understanding of how tropical tree mortality responds to climate variation is urgently needed to predict how tropical forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used five years of approximately monthly drone-acquired RGB imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure, temporal variation, and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or collapse of standing dead trees. Treefalls accounted for 77 % of the total area and 60 % of the total number of canopy disturbances in treefalls and branchfalls combined. The size distribution of canopy disturbances was close to a power function for sizes above 25 m2, and best fit by a Weibull function overall. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though windspeeds were lower in the wet season.  The strongest correlate of temporal variation in canopy disturbance rates was the frequency of 1-hour rainfall events above the 99.4th percentile (here 35.7 mm hour−1, r = 0.67). We hypothesize that extreme high rainfall is associated with both saturated soils, increasing risk of uprooting, and with gusts having high horizontal and vertical windspeeds that increase stresses on tree crowns. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates over large spatial scales at fine temporal and spatial resolution, thereby enabling strong tests of linkages to drivers. Future studies should include high frequency measurements of vertical and horizontal windspeeds and soil moisture to better capture proximate drivers, and incorporate additional image analyses to quantify standing dead trees in addition to treefalls.

Uma das principais ferramentas para quantificar e qualificar o potencial de uma floresta é o inventário florestal. Durante a sua fase de planejamento, é necessário definir a intensidade de amostragem e o tamanho e forma de unidades de amostra para minimizar os custos de coleta de dados, aumentando a precisão do inventário florestal. Este estudo teve como objetivo testar diferentes tamanhos e formas de unidades de amostra para diferentes categorias de diâmetros a altura do peito (DAP). O estudo foi realizado na região de Manaus, incluindo INPA e áreas como a estação experimental da Embrapa em torno da BR-174, no estado do Amazonas, Brasil. Cinco categorias de DAP foram consideradas, como a seguir: 5 centímetros, 10 cm, 20 cm, 25 cm e 45 cm. Para todas as categorias de DAP, vinte e três diferentes tamanhos e duas formas foram testados, de 100 m² a 10.000 m². O número de amostras foi definido como n = 30 para todas as simulações de tamanho, para se confirmar a utilização dos pressupostos do teorema do limite central. A área basal foi utilizada para estimar a incerteza em relação ao verdadeiro valor da média para a comparação entre os diferentes tamanhos para cada categoria de DAP. Quase todos os tamanhos de parcela, em todas as categorias de DAP, obtiveram incertezas inferiores a 10%. Os que obtiveram melhores resultados foram os de 1000 m², 800 m², 1200 m², 2000 m² e 10.000 m² respectivamente, para os DAP mínimos de 5, 10, 20, 25 e 45 centímetros. A maioria dos inventários florestais exploratórios no estado do Amazonas tem sido feita para árvores com DAP maior que 10 centímetros, e os tamanhos variando de 1000 a 2000 m². Os resultados deste trabalho demonstram que o tamanho para o inventário exploratório é adequado, porém, tamanhos diferentes devem ser usados para DAP maior ou igual a 45 centímetros, que é normalmente o DAP mínimo para os planos de exploração madeireira. Palavras-chave: levantamentos florestais; suficiência amostral; unidade amostral.