DOI: 10.5061/dryad.8931zcs4q
title: Data from: Trait-based species selection for restoration: A case study from tropical landscapes dominated by bracken

description: Deforestation leads to non-forested areas that often need active
 ecological restoration to promote forest succession. Here, we developed a
 trait-based approach to guide the design of restoration projects and
 tested our approach in tropical areas deforested by fires and dominated by
 bracken. Deforestation caused by human-induced fires creates complex
 conservation problems in tropical areas. After fire, montane tropical
 deforested areas are often dominated by bracken fern (Pteridium spp.),
 which prevents the establishment of many species of trees. This means that
 effective ecological restoration strategies are needed for forest
 recovery. We explored whether a trait-based approach could be used to
 guide the selection of tree species in active restoration projects in
 deforested areas. We first tested whether traits could be used to predict
 which species can overcome bracken-associated filters. We then tested the
 relationship between the trait-based predictions for each species and
 their abundance in a reference old-growth forest. To identify key traits,
 we conducted a seed addition experiment in bracken-dominated areas that
 had developed 5-15 years after a fire, using 23 tree species common in the
 Bolivian montane forests, and monitored seedling establishment, survival,
 and growth for 36 months. We then related seedling performance to the
 functional traits of adults and seedlings. We found that six functional
 traits improved tree seedling performance in bracken-dominated areas, and
 that only one-third of the species evaluated exceeded a 25% probability of
 recruitment. Most of the favored traits correspond to conservative
 strategies. The species dispersed by birds and with large seeds were the
 most likely to overcome the filters created by bracken. Based on the trait
 predictions, we found that the species predicted to overcome bracken are
 not common in old-growth forests. Our results can be used by stakeholders
 to select the species best suited for active restoration projects in
 bracken-dominated areas throughout the tropical region. Furthermore, our
 trait-based approach, which considers seedling performance in disturbed
 areas, can serve as a guide for species selection in restoration programs
 in other disturbed systems.
description: # Data from: Trait-based species selection for restoration: A case study
 from tropical landscapes dominated by bracken Dataset DOI:
 [10.5061/dryad.8931zcs4q](https://doi.org/10.5061/dryad.8931zcs4q) ##
 Description of the data and file structure The dataset contains all data
 required to replicate analyses in Gallegos et al. 2025. We established a
 seed addition experiment at eight sites in the vicinity of Chulumani
 village, Sud Yungas province, La Paz, Bolivia. The experiment was
 established in burned areas from the tropical montane forest dominated by
 the bracken fern *Pteridium esculentum,* at 100 m from the forest edge. In
 each site, we planted 23 tree species in different quantities according to
 their seed size. Seeds were collected from at least ten individuals per
 species. We monitored seedling establishment, survival, and growth after
 6, 12, 24, and 36 months. We measured the following functional traits in
 five adult individuals of each species: maximum tree height (HM, in m),
 leaf area (LA, in cm^2^), specific leaf area (SLA, in cm^2^/g), leaf dry
 matter content (LDMC, in mg/g), stem specific density (SSDc, in mg/mm^3^,
 corrected for secondary branches multiplying by 1.411), seed size (i.e.,
 seed length in mm), seed mass (in g) and dispersal vector (birds, bats or
 wind). The same traits were obtained for the species from the community
 from a database taken in the same study area (Missouri Botanical Garden –
 Bolivia Program, 2024). We related the functional traits to seedling
 performance of the planted species using GLMMs, and selected the best
 models for seedling establishment, survival, and relative growth rate
 (RGR), respectively. With these models, we predicted seedling performance
 of the species from the community by calculating their active restoration
 value (ARV). Finally, we related the ARV of each species to its abundance
 in old-growth forests from the study area (Lippok et al., 2014). **Time of
 data collection:** Seed addition: November 2019 Last monitoring: December
 2022 **Geographic location of data collection:** The study was carried out
 on the eastern slope of the Andes, in the vicinity of Chulumani village,
 Sud Yungas, La Paz, Bolivia (16°24’ S, 67°31’ W). The study area is
 located in the tropical montane humid forest between 1,850 and 2,450 m
 a.s.l. ### Files and variables #### File: Gallegos_dataset.csv
 **Description:** Seedling performance of the planted species and
 functional traits of the planted species and of the species from the
 community. ##### Variables * SITE: (= PLOT): Acronym of eight study sites
 or plots where we established the seed addition experiment. * DATABASE:
 planted (species that were planted); community (species from the
 community, non-planted). * SPECIES: Acronym from the species. *
 SPECIES_NAME: Full species name. * PLANTEDseeds: Number of sown seeds per
 site. * ESTABLtot: Number of seedlings established within the first 12
 months out of the number of seeds sown per site. * NONESTABL: Number of
 seeds that did not establish within the first 12 months out of the number
 of seeds sown per site. * SURFtot: number of seedlings that survived until
 the end of the experiment (36 months) relative to the number of
 established seedlings. * NONSURF: number of seedlings that did not survive
 until the end of the experiment (36 months) relative to the number of
 established seedlings. * RGR: Relative growth rate (RGR) using the formula
 (ln(*h~t+1~*) - ln(*h~t~*))/*t*, where *h* is the individual height in cm
 at time *t* and *t+1*, and *t* is the time elapsed in days between
 measurements. * Dispersal: Dispersal vector (birds, bats, wind). *
 HM: maximum tree height (m). * LA: leaf area (cm^2^). * SLA: specific leaf
 area (cm^2^/g). * LDMC: leaf dry matter content (mg/g). * BarkT: bark
 thickness (mm). * SSDc: stem specific density (mg/mm^3^, corrected for
 secondary branches multiplying by 1.411). * SS: seed length (mm). * SM:
 seed mass (g). #### File: Gallegos_abundance.csv **Description:** Active
 restoration value of each species from the community and its abundance in
 old-growth forests from the study area. ##### Variables *
 SPECIES_NAME: Full species name. * ARV: Active restoration value. We
 predicted the establishment, survival, and RGR for each species in the
 community from our models, using the coefficients from the best models
 (Table S3 in Supplementary Information). We then multiplied the predicted
 values to obtain the 'active restoration value' (i.e.,
 recruitment probability) for each species. * ARVP: Active restoration
 value in percentage. We assigned 100% of the active restoration value to
 the first species and calculated a relative active restoration value (%)
 for all other species. * ABUNDANCE: Abundance of each species in
 old-growth forests from our study area, based on the number of individuals
 per species found in 12 plots of 400 m^2^ each (extracted from Lippok et
 al., 2014). ##### References * Lippok, D., Beck, S. G., Renison, D.,
 Hensen, I., Apaza, A. E., & Schleuning, M. (2014b). Topography and
 edge effects are more important than elevation as drivers of vegetation
 patterns in a neotropical montane forest. *Journal of Vegetation Science*,
 *25*(3), 724–733.
 [https://doi.org/10.1111/jvs.12132](https://doi.org/10.1111/jvs.12132) *
 Missouri Botanical Garden – Bolivia Program. (2024). *Chulumani Plots and
 Checklist Project*. Tropicos.Org. Missouri Botanical Garden.
 [http://legacy.tropicos.org/PlotSearch.aspx?projectid=93](http://legacy.tropicos.org/PlotSearch.aspx?projectid=93)