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Assessment of protocols and variance for specific leaf area (SLA) in 10 Eucalyptus species to inform functional trait sampling strategies for TERN Ausplots

dataset
posted on 11.03.2021, 05:48 by Rhys Morgan, Irene Martin Fores, Emrys Leitch, Greg Guerin
Introduction

Functional trait-based approaches to ecological questions are becoming more common. The ongoing development of large functional trait databases has further enabled these kinds of studies.

TERN is Australia's national land ecosystem observatory. Through monitoring more than 750 plots across major biomes and bioclimatic gradients, TERN Ecosystem Surveillance has collected over 40,000 voucher specimens with herbarium level taxonomic determinations. This collection represents an opportunity to generate high quality functional trait data for a large number of Australian flora.

This pilot study aimed to test the feasibility of using the TERN collection to measure a simple morphological trait. Specific leaf area (SLA) is the one-sided area of a fresh leaf divided by its dry mass. We restricted our study to the Eucalyptus genus as Eucalyptus species are common in TERN monitoring plots and are often the dominant tree species. The results of the study should inform the future sampling strategy for SLA.


Method

The first component of the study was the measurement of leaves from voucher specimens. We located 30 Eucalyptus vouchers exclusively from South Australian plots (figure 1) and took 5 leaves from each specimen. The leaves were mounted onto sheets of paper and scanned with a flatbed scanner. Leaf area was measured from the scans using ImageJ software. The mounted leaves were placed into a plant press and dried in an oven for 24 hours at 70C. Each leaf was individually weighed using a 0.1mg microbalance.

The second component was the collection and measurement of fresh leaf samples. We collected 5 leaves from 5 individuals for 3 species growing at Waite Conservation Reserve in Adelaide, South Australia. The leaves were mounted, scanned and measured as before. They were then dried in an oven for 72 hours at 70C and weighed with the same microbalance. The dried leaves were scanned and measured again so that leaf area shrinkage between fresh and dry leaves could be estimated.

Shrinkage percentage was obtained using the formula:
((fresh area - dry area) / fresh area) * 100

SLA was obtained for each leaf using the formula:
dry area / dry mass

We ran an Anova (type II) on our SLA data using the Car v3.0-10 package in R v4.0.3.


Results

The pilot dataset contained 225 leaves from 45 individuals encompassing 10 species.

The mean shrinkage in leaf area was 10.27% with a standard deviation of 1.75%. This estimate came from 75 leaves (25 each from E. microcarpa, E. leucoxylon and E. camaldulensis subsp. camaldulensis).

The Anova output (figure 2) revealed that variation between individuals of the same species contributed the most to the overall SLA variation (sumsq = 111.6, R^2 = 0.499). A substantial portion of the overall variation was also attributed to variation between species (sumsq = 88.5, R^2 = 0.396%). The residual variation (sumsq = 23.3, R^2 = 0.104) was attributed to the variation between leaves from the same individual. The boxplots of 'SLA by individual' and 'SLA by species' (figure 3) support these results.


Recommendations

The shrinkage results show that shrinkage due to water loss is consistent and predictable for Eucalyptus leaves. This means that leaf traits can be reliably measured from herbarium style collections and the data derived from such measurements can be compared and integrated with data from fresh leaves.

By analysing the variance in the SLA data we have shown that the variation between individuals of the same species is significant and deserves further attention. However, the variation between species is also significant and should be captured in future studies. As such, we recommend that any subsequent attempt to construct a larger dataset of SLA measurements from the TERN voucher collection should focus on Eucalyptus species which are well represented. This will ensure that both intraspecific and interspecific variation is captured. Currently there are 27 Eucalyptus species with 10 or more vouchers, 47 species with 5 or more vouchers and 130 species with 1 or more voucher.

The variation between individual leaves was found to be a small part of the overall variation. This means that in future it should not be necessary to measure 5 leaves from each individual. Measuring 1 leaf from an individual will likely give a reliable estimate of the individual's mean SLA.

Certain changes to the TERN survey methodology could help to facilitate the accumulation of trait data. It is important that plant material taken for vouchers is the youngest fully mature material available and that it is from the outermost part of the canopy (i.e. sun leaves). This will help to ensure consistency and accuracy of trait measurements. When fruit/seeds are present they should be placed into a bag and kept with the voucher specimen. Taking ample plant material from each individual will ensure that destructive trait analysis does not affect the quality of the voucher specimen. Where a species is abundant or dominant it will be beneficial to take vouchers from multiple individuals to further investigate intraspecific and within-site trait variation.

This study has served to highlight the potential for a trait database to be produced from the TERN voucher collection. It is evident that, for at least the Eucalyptus genus, there is valuable trait information contained in specimen vouchers which, if measured, could enable further research into important ecological questions (e.g. how does SLA vary intraspecifically and does it contribute to a species' environmental tolerance?).


References

Garnier, E, Shipley, B, Roumet, C & Laurent, G 2001, 'A standardized protocol for the determination of specific leaf area and leaf dry matter content', Functional Ecology, vol. 15, pp. 688-695.

Munroe, S, Guerin, GR, Saleeba, T, , Martin-Fores, M, Blanco-Martin, B, Sparrow, B & Tokmakoff, A 2020. 'ausplotsR: An R package for rapid extraction and analysis of vegetation and soil data collected by Australia’s Terrestrial Ecosystem Research Network'. EcoEvoRxiv, DOI 10.32942/osf.io/25phx

Nock, CA, Vogt, RJ & Beatrix, BE 2016, 'Functional Traits', eLS.

Pérez-Harguindeguy, N, Díaz, S, Garnier, E, Lavorel, S, Poorter, H, Jaureguiberry, P, Bret-Harte, MS, Cornwell, WK, Craine, JM, Gurvich, DE, Urcelay, C, Veneklaas, EJ, Reich, PB, Poorter, L, Wright, IJ, Ray, P, Enrico, L, Pausas, JG, de Vos, AC, Buchmann, N, Funes, G, Quétier, F, Hodgson, JG, Thompson, K, Morgan, HD, ter Steege, H, van der Heijden, MGA, Sack, L, Blonder, B, Poschlod, P, Vaieretti, MV, Conti, G, Staver, AC, Aquino, S & Cornelissen, JHC 2016, 'New handbook for standardised measurement of plant functional traits worldwide', Australian Joural of Botany, vol. 64, pp. 715-716.

Perez, TM, Rodriguez, J & Heberling, JM 2020, 'Herbarium-based measurements reliably estimate three functional traits', American Journal of Botany, vol. 107, no. 10, pp. 1457-1464.

Queenborough, S 2017, 'Collections-based Studies of Plant Functional Traits', Scientia Danica, Series B, no. 6, pp. 223-236.

Sparrow, B, Foulkes, J, Wardle, G. Leitch, E, Caddy-Retalic, S, van Leeuwen, S, Tokmakoff, A, Thurgate, N, Guerin, G & Lowe, A 2020. 'A Vegetation and soil survey method for surveillance monitoring of rangeland environments'. Frontiers in Ecology and Evolution, vol. 8, pp. 157.

Tavsanoglu, C & Pausas, JG 2018, 'A functional trait database for Mediterranean Basin plants', Scientific Data, vol. 5, pp. 1-18.

Torrez, V, Jorgensen, PM & Zanne, AE 2012, 'Specific leaf area: a predictive model using dried samples', Australian Journal of Botany, vol. 61, pp. 350-357.

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The University of Adelaide

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