Data Provider Contact Details *
* Name Stephan Kambach
* Email stephan.kambach@gmail.com
* Affiliation Institute of Biology / Geobotany, Martin Luther University Halle-Wittenberg, 06108 Halle (Saale).
* Country Germany
Role *
Data_creator true
Data_manager true
Data_owner
Primary_contact
Research Group *
* Research_group Other-specify
Other-specify Institute for Geobotany and Botanical Garden, MLU Halle-Wittenberg
Dataset *
* Project_or_workshop_or_thesis_title Supplentary data for Kambach et al. (2024 Ecology - accepted): Putting seedlings on the map. Trade-offs in demographic rates between ontogenetic size-classes in five tropical forests.
* Dataset_title Supplementary data on demographic rates and traits for woody plant species at the forest dynamics plots at Barro Colorado Island, Fushan, Pasoh and Yasuní
* Short_abstract All species must partition resources among the processes that underlie growth, survival, and reproduction. To analyse the demographic trade-offs that structure the diversity of life-history strategies in tropical forests, we compiled data on seed-to-seedling transition rates, species-level growth and survival rates of tree seedlings < 50 cm height, growth and survival rates of trees ≥ 1 cm diameter at breast height (dbh). Here, we provide the underlying data for those demographic rates that were not yet publicly available.
* Keywords ForestGeo, life-history strategies, trade-offs, growth, survival, recruitment, BCI, Fushan, Luquillo, Pasoh, Yasuní
* Data_access_policy Open (CC BY 4.0)
Extensive_description_of_the_dataset We assembled data on freestanding woody plant species from five tropical forest dynamics plots of 16–50 ha from the ForestGeo network (Anderson‐Teixeira et al. 2015, Davies et al. 2021). The five sites are Barro Colorado Island (BCI; Panama), Fushan (Taiwan), Luquillo (Puerto Rico), Pasoh (Malaysia), and Yasuní (Ecuador). In each forest, individuals < 1 cm dbh (hereafter seedlings) were mapped and measured in subplots of the ForestGeo plots, and all individuals > 1 cm dbh (hereafter trees) were mapped and measured following Condit (1998). All five ForestGeo plots have been re-censused approximately every five years (BCI: 1982-2015, Fushan: 2004-2013, Luquillo: 1992-2016, Pasoh: 1987-2010, and Yasuní: 1996-2008). Data on growth and survival of trees ≥ 1 cm dbh: In every census, each individual with at least one living stem ≥ 1 cm dbh was identified to species or morphospecies, determined as ‘alive’ and the stem with the largest dbh was measured with an accuracy of 1 mm following the protocol presented in Condit (1998). For each individual tree where the main stem survived a census interval, we calculated growth as the absolute annual increment in dbh (Δdbh)/t with t = time in years between two consecutive censuses. To account for the dependence of growth and survival on tree size and light availability, we assigned each tree to the overstory or the understory layer, based on the perfect plasticity approach as described in Kambach et al. (2022). The crown area of each individual tree was approximated with the allometric equation crown area (m²) = a * dbh (mm)^b with allometric coefficients a and b being either calculated from the Tallo global tree allometry and crown architecture database (for species with > 10 observations, Jucker et al. 2022) or assigned from site-specific allometries (as listed in Kambach et al. 2024). Each ForestGeo plot was divided into subplots of 31.5 x 31.5 m (following Bohlman and Pacala 2012), in which we ranked all individuals from the largest to the smallest diameter. We successively assigned the largest individuals to the overstory canopy layer, until their cumulative crown area exceeded twice the subplot area. The remaining smaller individuals were then assigned to the understory canopy layer. Palms (Arecaceae), hemi-epiphytic, and unidentified species were retained for assignment to the overstory or understory layer but were omitted from all other analyses. Data on growth and survival of seedlings < 50 cm height: At all five ForestGeo plots, growth, survival and recruitment rates of seedling individuals < 1 cm dbh were measured according to ForestGeo protocols (described in Davies et al. 2021). We calculated growth and survival in two seedling classes: individuals < 20 cm height and individuals of 20–50 cm height. Seedling datasets are described in detail in Kambach et al. (2024). For each individual seedling that survived a census interval, we calculated growth as the absolute annual increment in height (Δheight)/t with t = time in years between consecutive censuses. Data on seed production: Seed fall was recorded in seed traps according to ForestGeo protocols that are described in Davies et al. 2021. Seed trap datasets are described in detail in Kambach et al. (2024). Data on species traits: Species-level trait data were assembled from primary and published sources as follows that are described in Kambach et al. (2024).Maximum dbh was calculated as the mean dbh of the six largest trees of each species at the respective ForestGeo plot. Calculation of species-specific demographic rates: For each of the five forests, we estimated species-specific mean annual growth and survival rates in four size classes (seedlings < 20 cm height, seedlings 20–50 cm height, trees ≥ 1 cm dbh in the understory and in the overstory canopy) as well as species-specific mean seed-to-seedling transition rates. We only calculated growth and survival rates for species and size classes when there were > 10 observations. We transformed the observed annual growth rates to an approximate normal distribution using the Modulus transformation with λ = 0.4 (Eqn. 1) as described in John and Draper (1980) and Condit et al. (2017). To calculate species-specific growth rates within each size class, we randomly selected (without replacement) up to 200 growth observations across all census intervals per species and size class. We used hierarchical Bayesian models with flat priors to calculate the mean transformed growth rate of species j in size class k according to the likelihood described in Kambach et al. (2024). To calculate species-specific survival rates within each size class, we randomly selected (without replacement) up to 1,000 survival observations across all census intervals per species and size class. We used hierarchical Bayesian models with flat priors to calculate the mean annual survival rate of species j in size class k according to the likelihhod described in Kambach et al. (2024). To calculate comparable seed-to-seedling transition rates, we first calculated, for each forest and census interval, the annual number of newly emerging seedlings per ha (scaled from the summed area of seedling plots) and the annual number of seeds captured per ha (scaled from the summed area of seed traps). Seed-to-seedling transition rates were then calculated by dividing the number of newly emerged seedlings per ha and year by the number of seeds captured per ha and year, averaged across all census intervals. Mean seed-to-seedling transition rates > 1 were replaced with a value of one (as described in Kambach et al. 2024). List of flies: - readme.txt: metadata file with descriptions of variables in each file - bci_seedling_rates.csv: Barro Colorado's species-level mean growth and survival rates of seedlings < 20 cm tall - fushan_rates.csv: Fushan's species-level mean annual seed numbers, growth and survival rates of trees ≥ 1 cm diameter at breast height (dbh), and seedlings < 50 cm tall - pasoh_rates.csv: Pasoh's species-level growth and survival rates of seedlings < 50 cm tall - yasuni_growth_above_1cm_dbh.csv: Yasuní's growth observations per species and size class ≥ 1 cm dbh - yasuni_survival_above_1cm_dbh.csv: Yasuní's survival observations per species and size class ≥ 1 cm dbh The original data providers chose not to disclose the species’ full names. All files use UTF-8 character encoding and represent missing values as "NA". References: Anderson‐Teixeira, K. J., S. J. Davies, A. C. Bennett, E. B. Gonzalez‐Akre, H. C. Muller‐Landau, S. J. Wright, K. A. Salim, et. al. 2015. CTFS‐ForestGEO: a worldwide network monitoring forests in an era of global change. Global Change Biology 21 (2): 528–549. Bohlman, S., and S. Pacala. 2012. A forest structure model that determines crown layers and partitions growth and mortality rates for landscape‐scale applications of tropical forests. Journal of Ecology 100 (2): 508–518. Condit, R., R. Pérez, S. Lao, S. Aguilar, and S. P. Hubbell. 2017. Demographic trends and climate over 35 years in the Barro Colorado 50 ha plot. Forest Ecosystems 4 (1): 17. Condit, R. S. 1998. Tropical Forest Census Plots: Methods and Results from Barro Colorado Island, Panama, and a Comparison with Other Plots. Berlin, New York: Springer. Davies, S. J., I. Abiem, K. A. Salim, S. Aguilar, D. Allen, A. Alonso, K. Anderson-Teixeira, et al. 2021. ForestGEO: Understanding forest diversity and dynamics through a global observatory network. Biological Conservation 253: 108907. John, J. A., and N. R. Draper. 1980. An alternative family of transformations. Applied Statistics 29 (2): 190–197. Jucker, T., F. J. Fischer, J. Chave, D. A. Coomes, J. Caspersen, A. Ali, G. J. Loubota Panzou et al. 2022. Tallo: A global tree allometry and crown architecture database. Global Change Biology 28:5254–5268. Kambach, S., R. S. Condit, S. Aguilar, H. Bruelheide, S. Bunyavejchewin, C.‐H. Chang‐Yang, Y.‐Y. Chen, et al. 2022. Consistency of demographic trade‐offs across 13 (sub)tropical forests. Journal of Ecology 110 (7): 1485–1496. Kambach, S., H. Bruelheide, L. S. Comita, R. Condit, S. J. Wright, S. Aguilar et al. 2024. Putting seedlings on the map: Trade-offs in demographic rates between ontogenetic size-classes in five tropical forests. (Ecology accepted).
Data_origin Field Experiment
Other-specify
Status_of_the_data_collection Completed
Persons Associated With Dataset ( 1 )
Name Helge Bruelheide
Email
Affiliation Institute of Biology / Geobotany, Martin Luther University Halle-Wittenberg, 06108 Halle (Saale); German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig
Country Germany
Research Group
Research_group iDiv Member
Other-specify
Persons Associated With Dataset ( 2 )
Name Liza S. Comita
Email
Affiliation School of the Environment, Yale University, New Haven, CT, 06511
Country United States
Persons Associated With Dataset ( 3 )
Name Richard Condit
Email
Affiliation School of the Environment, Yale University, New Haven, CT, 06511
Country United States
Persons Associated With Dataset ( 4 )
Name S. Joseph Wright
Email
Affiliation Smithsonian Tropical Research Institute, Box 0843-03092 Balboa, Ancón
Country Panama
Persons Associated With Dataset ( 5 )
Name Salomón Aguilar
Email
Affiliation Smithsonian Tropical Research Institute, Box 0843-03092 Balboa, Ancón
Country Panama
Persons Associated With Dataset ( 6 )
Name Chia-Hao Chang-Yang
Email
Affiliation Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung
Country Taiwan
Persons Associated With Dataset ( 7 )
Name Yu-Yun Chen
Email
Affiliation Department of Natural Resources and Environmental Studies, National Dong Hwa University, Hualien
Country Taiwan
Persons Associated With Dataset ( 8 )
Name Nancy C. Garwood
Email
Affiliation School of Biological Sciences, Southern Illinois University Carbondale, Carbondale, IL 62901
Country United States
Persons Associated With Dataset ( 9 )
Name Stephen P. Hubbell
Email
Affiliation Smithsonian Tropical Research Institute, Box 0843-03092 Balboa, Ancón
Country Panama
Persons Associated With Dataset ( 10 )
Name Pei-Jen Luo
Email
Affiliation Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung
Country Taiwan
Persons Associated With Dataset ( 11 )
Name Margaret R. Metz
Email
Affiliation Department of Biology, Lewis & Clark College, Portland, OR
Country United States
Persons Associated With Dataset ( 12 )
Name Musalmah Bt. Nasardin
Email
Affiliation Forest Research Institute Malaysia (FRIM), Kepong, Selangor Darul Ehsan
Country Malaysia
Persons Associated With Dataset ( 13 )
Name Rolando Pérez
Email
Affiliation Smithsonian Tropical Research Institute, Box 0843-03092 Balboa, Ancón
Country Panama
Persons Associated With Dataset ( 14 )
Name Simon A. Queenborough
Email
Affiliation School of the Environment, Yale University, New Haven, CT, 06511
Country United States
Persons Associated With Dataset ( 15 )
Name I-Fang Sun
Email
Affiliation Center for Interdisciplinary Research on Ecology and Sustainability (CIRES), National Dong Hwa University, Hualien
Country Taiwan
Persons Associated With Dataset ( 16 )
Name Nathan G. Swenson
Email
Affiliation Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, 46556
Country United States
Persons Associated With Dataset ( 17 )
Name Jill Thompson
Email
Affiliation UK Centre for Ecology & Hydrology, Bush Estate, Penicuik Midlothian, EH26 0QB
Country United Kingdom
Persons Associated With Dataset ( 18 )
Name María Uriarte
Email
Affiliation Department of Ecology, Evolution & Environmental Biology, Columbia University, New York, 10027
Country United States
Persons Associated With Dataset ( 19 )
Name Renato Valencia
Email
Affiliation Escuela de Ciencias Biológicas, Pontificia Universidad Católica del Ecuador, Aptado. 1701-2184, Quito
Country Ecuador
Persons Associated With Dataset ( 20 )
Name Tze Leong Yao
Email
Affiliation Forest Research Institute Malaysia (FRIM), Kepong, Selangor Darul Ehsan
Country Malaysia
Persons Associated With Dataset ( 21 )
Name Jess K. Zimmerman
Email
Affiliation Department of Environmental Sciences, Universidad de Puerto Rico, San Juan
Country Puerto Rico
Persons Associated With Dataset ( 22 )
Name Nadja Rüger
Email
Affiliation German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig
Country Germany
Habitat
Terrestrial true
Freshwater
Marine
Taxonomic Scope
Animalia
Plantae true
Fungi
Bacteria
Virus
Microorganism
Spatial Cover
Coverage Global
Locality_names Barro Colorado Island
Locality_names 2 Fushan
Locality_names 3 Luquillo
Locality_names 4 Pasoh
Locality_names 5 Yasuní
Country Panama
Country 2 China
Country 3 Puerto Rico
Country 4 Malaysia
Country 5 Ecuador
Additional Information
How_to_cite_dataset Kambach, S., Bruelheide, H., Comita, L. S., Condit, R., Wright, S. J., Aguilar, S., Chang-Yang, C.-H., Chen, Y.-Y., Garwood, N. C., Hubbell, S. P., Luo, P.-J., Metz, M. R., Nasardin, M. B., Pérez, R., Queenborough, S. A., Sun, I.-F., Swenson, N. G., Thompson, J., Uriarte, M., … Rüger, N. (2024). Supplementary data on demographic rates and traits for woody plant species at the forest dynamics plots at Barro Colorado Island, Fushan, Pasoh and Yasuní (Version 1.0) [Dataset]. German Centre for Integrative Biodiversity Research. https://doi.org/10.25829/idiv.3565-ws9g97
Dataset_doi_or_url https://doi.org/10.25829/idiv.3565-ws9g97
Publications_based_on_this_dataset Kambach, S., H. Bruelheide, L. S. Comita, R. Condit, S. J. Wright, S. Aguilar et al. 2024. Putting seedlings on the map: Trade-offs in demographic rates between ontogenetic size-classes in five tropical forests. (Ecology, accepted).
Projects_that_are_related_to_this_dataset
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