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Tree seedling trait optimization and growth in response to local-scale soil and light variability

Citation

Umaña, Maria Natalia; Arellano, Gabriel; Swenson, Nathan; Zambrano, Jenny (2021), Tree seedling trait optimization and growth in response to local-scale soil and light variability, Dryad, Dataset, https://doi.org/10.5061/dryad.sqv9s4n29

Abstract

At local scales, it has been suggested that high levels of resources lead to increased tree growth via trait optimization (highly peaked trait distribution). However, this contrasts with (i) theories that suggest that trait optimization and high growth occur in the most common resource level and (ii) empirical evidence showing that high trait optimization can be also found at low resource levels. This raises the question of how are traits and growth optimized in highly diverse plant communities? Here, we propose a series of hypotheses about how traits and growth are expected to be maximized under different resource levels (low, the most common, and high) in tree seedling communities from a subtropical forest in Puerto Rico. We studied the variation in the distribution of biomass allocation and leaf traits and seedlings growth rate along four resource gradients: light availability (canopy openness) and soil K, Mg, and N contents. Our analyses consisted of comparing community trait means, trait kurtosis (a measurement of trait optimization), and relative growth rates at three resource levels (low, common, and high). Trait optimization varied across the three resource levels depending on the type of resource and trait, with leaf traits being optimized under high N and in the most common K and Mg conditions, but not at any of the light levels. Also, seedling growth increased at high light conditions and high N and K but was not related to trait kurtosis. Our results indicate that local-scale variability of soil fertility and understory light conditions result in shifts in species ecological strategies that increase growth despite a weak trait optimization, suggesting the existence of alternative phenotypes that achieve similar high performance. Uncovering the links between abiotic factors, functional trait diversity and performance is necessary to better predict tree responses to future changes in abiotic conditions.

Usage Notes

File: Dryad_rgr.csv

row.names = individual seedlings

plot = seedling plot identity

rgr = regalive growth rate, measured the change in log-transformed total seedling height (cm) from 2013 to 2014

File: DRYAD_soil.light.csv

plot = seedling plot identity

Mg.mg.kg = magnesium content in the soil (mg/kg) extracted using the Mehlich-III solution

K.mg.kg = potasium content in the soil (mg/kg) extracted using the Mehlich-III solution

N% = Total soil N concentration (%) obtained using the total combustion method

canopy.open% = canopy openness (%) obtained by taken hemispherical photographs at 1m height in the center of each seedling plot at uniform light conditions at dawn with homogeneous light conditions

File: Dryad_trait.csv

row.names = individual seedlings

plot = seedling plot identity

leaf_area = leaf area (cm2)

sla = specific leaf area (cm2/g)

lar =  leaf area ratio calculated as leaf area/total plant dry mass cm2/g

lmf = leaf mass fraction calculated as leaf dry mass/total plant dry mass (g/g)

rmf = root mass fraction calculated as root dry mass/total plant dry mass (g/g)