Canopy structure and forest understory conditions in a wet Amazonian forest – no change over the last 20 years
Nabe-Nielsen, Jacob; Valencia, Renato (2020), Canopy structure and forest understory conditions in a wet Amazonian forest – no change over the last 20 years, Dryad, Dataset, https://doi.org/10.5061/dryad.612jm641x
Climate change is altering forest dynamics in the tropics, with large potential impacts on forest structure and understory conditions. However, we found that canopy height distribution and openness remained stable over two decades in the western Amazon, and that gap creation rates would need to increase 300% before affecting equilibrium.
Data were collected in the western part of the Amazon basin in Yasuní National Park in Ecuador (0°40’29” S, 76°23’51” W). Canopy height, canopy openness and understory density data were recorded in six 10 x 250m plots (1.5 ha in total) in 1998 and again in 2019 (labeled census 1 and 2 in the dataset, respectively). One of the plots was located in a seasonally inundated floodplain forest, and the five others covered ridge tops, slopes and bottomland areas. Each plot was divided into a 5 x 5m grid. For each grid square we measured maximum canopy height and average height to the centre of the tree crowns using a clinometer and measuring tape. Heights were assigned to the following classes: 0–5m, 5–10m, 10–20m and >20m. In the centre of each square we recorded canopy openness 1 m above the ground using crown illumination ellipses (CIE; see main text), where values >1.0 indicated areas with visible gaps in the canopy and elevated light conditions. Understory vegetation density was classified as either dense, herbaceous, liana-tangle, or sparse. Here ‘herbaceous’ was used for areas covered with herbs (e.g. Marantaceae spp.), but with very few woody plants, and ‘liana-tangle’ was used for areas where the ground was densely covered with lianas, but with only a few tree saplings.
We constructed two different transition matrices A to study the projected effects of changes in canopy dynamics, one for maximum and one for average canopy height. The matrices were based on observed probabilities of transitions between height classes for all 600 grid squares between 1998 and 2019. To assess how increased creation of gaps would influence the asymptotic height class distribution, we used matrix modelling to conduct a perturbation experiment by gradually altering the number of squares with average height 10–20m that were converted to gaps with 0–5m tall canopy over a 20-y period.
There are no missing values in the data, but additional data are available for some of the plots (measurements of canopy height outside the plot squares used in this study, and for additional censuses). These can be provided upon request.
The baselines of the plots are marked with grey plastic tubes in the field.