Photosynthetic and functional traits of tree seedlings from dry dipterocarp forest
Data files
Oct 16, 2024 version files 8.26 KB
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README.md
4 KB
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species_level_dataset.csv
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Abstract
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.
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.
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).
Photosynthetic performance trait measurement
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).
