Land cover–land use (LCLU) classification tasks can take advantage of the fusion of radar and optical remote sensing data, leading generally to increase mapping accuracy. Here we propose a methodological approach to fuse information from the new European Space Agency Sentinel-1 and Sentinel-2 imagery for accurate land cover mapping of a portion of the Lower Magdalena region, Colombia. Data pre-processing was carried out using the European Space Agency’s Sentinel Application Platform and the SEN2COR toolboxes. LCLU classification was performed following an object-based and spectral classification approach, exploiting also vegetation indices. A comparison of classification performance using three commonly used classification algorithms was performed. The radar and visible-near infrared integrated dataset classified with a Support Vector Machine algorithm produce the most accurate LCLU map, showing an overall classification accuracy of 88.75%, and a Kappa coefficient of 0.86. The proposed mapping approach has the main advantages of combining the all-weather capability of the radar sensor, spectrally rich information in the visible-near infrared spectrum, with the short revisit period of both satellites. The mapping results represent an important step toward future tasks of aboveground biomass and carbon estimation in the region.

Theory for optimal allocation of foliar nitrogen (ONA) predicts that both nitrogen concentration and photosynthetic capacity will scale linearly with gradients of insolation within plant canopies. ONA is expected to allow plants to efficiently use both light and nitrogen. However, empirical data generally do not exhibit perfect ONA, and light-use optimization per se is little explored. The aim was to examine to what degree partitioning of nitrogen or light is optimized in the crowns of three tropical canopy tree species. Instantaneous photosynthetic photon flux density (PPFD) incident on the adaxial surface of individual leaves was measured along vertical PPFD gradients in tree canopies at a frequency of 0·5 Hz over 9–17 d, and summed to obtain the average daily integral of PPFD for each leaf to characterize its insolation regime. Also measured were leaf N per area (N_area), leaf mass per area (LMA), the cosine of leaf inclination and the parameters of the photosynthetic light response curve [photosynthetic capacity (A_max), dark respiration (R_d), apparent quantum yield (ϕ) and curvature (θ)]. The instantaneous PPFD measurements and light response curves were used to estimate leaf daily photosynthesis (A_daily) for each leaf. Leaf N_area and A_max changed as a hyperbolic asymptotic function of the PPFD regime, not the linear relationship predicted by ONA. Despite this suboptimal nitrogen partitioning among leaves, A_daily did increase linearly with PPFD regime through co-ordinated adjustments in both leaf angle and physiology along canopy gradients in insolation, exhibiting a strong convergence among the three species. The results suggest that canopy tree leaves in this tropical forest optimize photosynthetic use of PPFD rather than N per se. Tropical tree canopies then can be considered simple ‘big-leaves’ in which all constituent ‘small leaves’ use PPFD with the same photosynthetic efficiency.

Extreme drought events have negative effects on forest diversity and functioning. At the species level, however, these effects are still unclear, as species vary in their response to drought through specific functional trait combinations. We used long‐term demographic records of 21,821 trees and extensive databases of traits to understand the responses of 338 tropical dry forests tree species to ENSO₂₀₁₅, the driest event in decades in Northern South America. Functional differences between species were related to the hydraulic safety‐efficiency trade‐off, but unexpectedly, dominant species were characterised by high investment in leaf and wood tissues regardless of their leaf phenological habit. Despite broad functional trait combinations, tree mortality was more widespread in the functional space than tree growth, where less adapted species showed more negative net biomass balances. Our results suggest that if dry conditions increase in this ecosystem, ecological functionality and biomass gain would be reduced.