Advancing ecosystem recovery with diverse species plantings in tropical forest restoration

This data release provides data on an active, multi-species planting restoration effort in the Premontane Wet Life Zone, Monteverde, Costa Rica. The study involves comparison of 13 actively restored forest stands planted three to 21 years prior on abandoned pastures to four nearby reference stands of altered primary/mature forests that were at least 70 years old (actual age unknown). All stands were located in the Premontane Wet Life zone on the Pacific side of the Tilarán mountain range in Costa Rica at elevations between 1200m to 1440m asl (10⁰ 18’ 55.3” N and 84⁰ 50’ 29.8” W). Soils were classified as Andisols, formed under wet (udic) conditions from volcanic parent material with moderate clay content. The 13 restored forest stands were located close to the reference forests with a distance between stands ranged from 75m to 7km. The restored stands were established on pasture previously grazed by cattle and horses; three stands had been converted to coffee. The four older reference forests ranged in size from 7.6 to 35+ ha and are natural compositions of nearly 100 tree species (the regional tree diversity throughout five life zones is 755 species). Human alterations within the reference forests were evident with some large tree removals. Natural blow downs and light gaps added to the natural diversity of species, and edge effects were apparent where higher solar irradiance and wind effects occur.

For each restoration and reference stand, we measured a suite tree species traits for species detected. The tree data and stand attribute measurements are provided in 3 CSV files: (1) tree_traits.csv provides a full listing of all tree taxa observed in plots, and associated life history characteristics as recorded in the scientific literature; (2) plot_trees.csv provides information about each tree measured within a plot within a given stand; (3) plot_cov.csv provides information about other plot level characteristics. See the Data Quality section for processing steps that outline methods for each CSV file.