DOI: 10.5061/dryad.m905qfvbk
title: Photosynthetic and functional traits of tree seedlings from dry dipterocarp forest

description: Seedlings frequently suffer the highest mortality rate, as they have
 different requirements for growth and survival from their mature life
 cycle stage. However, the links between functional traits and
 photosynthetic performance traits of tree seedlings, especially from dry
 evergreen forests, remain largely unexplored. Here, we measured eleven
 functional traits and six photosynthetic performance traits of thirty
 species of tree seedlings from the seasonally dry evergreen forest in
 Southeast Asia. We explored the relationship between traits and
 photosynthesis, compared them with their canopy layers when mature to
 their adult stature, and classified growth strategies. The results showed
 that photosynthetic measurements were highly correlated with seedling
 growth traits. The measured functional and photosynthetic traits did not
 correspond with the canopy layers of the mature trees. Through k-mean
 clustering analyses of the tree seedling trait data, two main groups of
 growth strategies emerged: (1) the “fast-growing” group, which mainly
 consists of shade-intolerant or -avoidance species; and (2) the
 “slow-growing” group, which consists of shade-tolerant species. This
 finding can be applied by future practitioners to select tree seedlings
 accurately based on their juvenile physiology, which is fundamental to the
 success of species selection for forest restoration in the face of global
 climate change.
description: In this study, we collected seeds of 30 plant species
 from the permanent plot in the seasonally dry evergreen forest of Huai Kha
 Khaeng Wildlife Sanctuary (HKK) (15˚40 ́ N, 99˚10 ́ E), Uthai Thani
 (Bunyavejchewin et al., 2003), from December 2016 until September 2018. At
 least five seeds per species were collected to investigate the variation
 within species. The collected seeds were cleaned and dried under natural
 sunlight for 14 days (Chamchumroon, 1997). The seeds were then planted in
 a greenhouse using a prepared mixture of silt, rice husk charcoal, and
 manure in a ratio of 6:3:1 (Table S1). The plants were grown in 4-inches
 plastic pots under regular watering, natural light (3,402.9-5,978.2
 lumen/m2), and a temperature range of 28.5-33.9˚C.  
 The studied species were chosen to cover the species
 from all three canopy layers, as identified in previous studies (e.g.,
 Bunyavejchewin et al., 2016; Flora of China; Flora of Thailand; Pooma et
 al., 2017). These three canopy layers were classified by the average
 height of mature plants, including nine species from the understory (lower
 than 10 m), fourteen species in the sub-canopy (11-30 m), and seven
 species in the canopy layers (31-45 m; Table 1). 
 Functional traits and photosyntheticsis performances traits were
 measured from six to ten seedlings for each species (Table 1). The
 seedlings were measured at 12-18 months after planting, which is a typical
 age for seedlings used in reforestation (Snorrason, 2020). Eleven
 functional traits were measured from three leaves per samples, including
 1) leaf area, 2) leaf fresh weight, 3) leaf dry weight, 4) specific leaf
 area, 5) seedling height, 6) root collar diameter, 7) leaf thickness, 8)
 chlorophyll content, 9) carbon content, 10) nitrogen content, and 11)
 carbon-to-nitrogen ratio (Table S2).   
 Leaf areas were measured by using the scanner and the Fiji
 software (Schindelin et al., 2012; Umaña et al., 2015). Dry weights were
 measured after drying in a 70˚C hot air oven for 48 hr (Cornelissen et
 al., 2003; Garnier et al., 2001; Pérez-Harguindeguy et al., 2016).
 Specific leaf area (SLA) was the fraction between leaf area and dried
 matter, one of the most frequently studied plant traits (Cornelissen et
 al., 2003; Wright et al., 2004). Seedling height (H) and root collar
 diameter (RCD) were measured as a proxy for performance to represent plant
 seedling growth rate for one 2 years old (Table S2). Leaf thickness was
 determined using the Thickness Gauge 547 (Mitutoyo, Japan) (Onoda et al.,
 2011).  The chlorophyll
 content was measured using the SPAD-502 Chlorophyll Meter at the leaf
 apex, middle, and base, avoiding major veins and margins (Coste et al.,
 2010). Carbon, nitrogen content, and the ratio of C and N were also
 determined to represent leaf chemistry. Three dried leaves for each
 species were used for estimating these values, using the Standard Test
 Methods for Determination of Carbon, Hydrogen, and Nitrogen in Analysis
 Samples of Coal and Carbon in Analysis Samples of Coal and Coke, CHNS-628
 (LECO, USA) at the Biomass and Bio-energy Technology Division, Kasetsart
 Agricultural and Agro-Industrial Product Improvement Institute (KAPI).
 Each trait was measured with three replications (Pérez-Harguindeguy et
 al., 2016).  
 <strong>Photosynthetic performance trait
 measurement </strong> To
 determine the performance traits of tree seedling photosynthesis, we
 measured five fully expanded leaves from each 1-year-old tree seedling
 before midday (Pérez-Harguindeguy et al., 2016) using the LI-6400 Portable
 Photosynthesis System (LICOR Inc., USA). The leaf chamber contained an LED
 light source at 25-30˚C air temperature and 400 ppm CO2. Intensities of
 light were set at 2000, 1600, 1200, 1000, 800, 600, 400, 200, 100, 50, 20,
 and 0 µmol · m-2 · s-1 to measure photosynthetic rate at each light
 intensity and generate a light response curve. The following
 photosynthesis parameters were estimated using the equation from Lobo et
 al. (2013): maximum capacity of photosynthesis (Pmax, µmol · m-2 · s-1),
 quantum yield (ɸ or Phi), dark respiration (Rd, µmol · m-2 · s-1),
 convexity index (θ or Theta), light compensation point (LCP, µmol · m-2 ·
 s-1), and light saturation point (Qsat75, µmol · m-2 · s-1).  
description: # Photosynthetic and functional traits of tree seedlings from dry
 dipterocarp forest
 [https://doi.org/10.5061/dryad.m905qfvbk](https://doi.org/10.5061/dryad.m905qfvbk) ## Description of the data and file structure Average value of functional traits and photosynthetic performance of the seedlings. ### Files and variables #### File: species\_level\_dataset.csv **Description:**  ##### Variables * Codes: Species code * LA: leaf area (cm2) * DW: leaf dry weight (g) * FW: leaf fresh weight (g) * H: height (cm) * SLA: specific leaf area (cm2 · g-1) * RCD: root collar diameter (mm) * T: leaf thickness (mm) * SPAD: SPAD index, chlorophyll content * N: nitrogen content (%) * C: carbon content (%) * C:N: carbon-to-nitrogen ratio * Pmax: maximum photosynthesis (µmol · m-2 · s-1) * ɸ (phi): quantum yield * Rd: dark respiration (µmol · m-2 · s-1) * θ (theta): convexity index * LCP: light compensation point (µmol · m-2 · s-1) * Qsat75: light saturation point (µmol · m-2 · s-1) Species code | Codes  | Scientific Names  | | :------ | :------------------------------------------------------------------ | | AFZEXY  | *Afzelia xylocarpa* (Kurz) Craib  | | ALANCH  | *Alangium chinense* (Lour,) Harms  | | ALCHRU  | *Alchornea rugosa* (Lour.) Muell. Arg.  | | ALPHVE  | *Alphonsea ventricosa* (Roxb.) Hook. f. & Thomson  | | ANTIAC  | *Antidesma acidum* Retz.  | | ANTIMO  | *Antidesma montanum* Blume  | | APHAPO  | *Aphanamixis polystachya* (Wall.) R. Parker  | | ARDIPO  | *Ardisia polycephala* Wall. ex A. DC.  | | CASEGR  | *Casearia grewiifolia* Vent.  | | CHUKTA  | *Chukrasia tabularis* A. Juss.  | | CLEIJA  | *Cleidion javanicum* Blume  | | CROTHU  | *Croton hutchinsonianus* Hosseus  | | DILLIN  | *Dillenia indica* L.  | | DIOSVE  | \*Diospyros vera \*(Lour.) A. Chev.  | | DIPTAL  | *Dipterocarpus alatus* Roxb.  | | DISCAB  | *Discospermum abnorme* (Korth.) S. J. Ali & Robbr.  | | GARCCE  | *Garcinia celebica* L.  | | GARUFL  | *Garuga floribunda* var. *gamblei* (King ex Smith) Kalkman  | | GARUPI  | *Garuga pinnata* Roxb.  | | HOPEOD  | *Hopea odorata* Roxb.  | | HYPTST  | *Hyptianthera stricta* (Roxb. ex Schult) Wight & Arn.  | | IRVIMA  | *Irvingia malayana* Oliv. ex A.W. Benn.  | | MALLNU  | *Mallotus nudiflorus* (L.) Kulju & Welzen  | | MITRTH  | *Mitrephora tomentosa* Hook. f. & Thomson  | | MONOVI  | *Monoon viride* (Craib) B. Xue & R. M. K. Saunders  | | PRISTE  | *Prismatomeris tetrandra* subsp. *malayana* (Ridl.) J. T. Johanss.  | | PSYCAS  | \*Psychotria asiatica \*L.  | | PTERMA  | *Pterocarpus macrocarpus* Kurz  | | SYZYME  | *Syzygium megacarpum* (Craib) Bathakr. & N. C. Nair  | | TOONCI  | *Toona ciliata* M. Roem  | ## Code/software The file can be read with any spreadsheet software and statistical programming software, such as R.  ## Access information Other publicly accessible locations of the data: * N/A Data was derived from the following sources: * The authors produced these data.