Plant functional traits – fixed facts or variable depending on the season?
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Traits are widely used to detect and explain responses of ecosystem processes to environmental changes. Various studies use trait data from databases, often providing one value per trait and species, neglecting intraspecific trait variability along spatio-temporal gradients. Handbooks for standardized trait measurements claim that traits should be measured at an ‘optimal’ stage, which is typically defined to be reached when the plants are in full blossom. However, it is unclear whether this method is appropriate. The main aim of this study was to quantify the extent to which trait values vary with season and phenology, a type of variation that has been overlooked so far relative to other sources of intraspecific variation. Further, we aimed to investigate whether species rankings remain consistent throughout the year.
From April to November 2012, we monitored seven leaf traits [specific leaf area SLA, leaf dry matter content, chlorophyll fluorescence parameters (Fv/Fm, performance-index PI], stomatal density, stomatal size and the stomatal pore area index SPI) of 15 summer green woody species weekly under controlled conditions. In parallel, we recorded phenological stages.
The results showed that all traits varied significantly throughout the year in a species-specific manner. We detected trait relationships with vegetative but not with flowering phenology. Species rankings were inconsistent throughout the season in all traits.
We concluded that the seasonal timing of trait measurements is crucial. Most notably SLA, Fv/Fm and stomatal size were the most robust traits in terms of small intraspecific and large interspecific variation and showed largely consistent species rankings across seasons.
KeywordsFv/Fm intraspecific trait variability LDMC phenology SLA stomatal density
- Bernhardt-Römermann M, Gray A, Vanbergen AJ, Berges L, Bohner A, Brooker RW, De Bruyn L, De Cinti B, Dirnbock T, Grandin U, Hester AJ, Kanka R, Klotz S, Loucougaray G, Lundin L, Matteucci G, Meszaros I, Viktor O, Preda E, Prevosto B, Pykala J, Schmidt W, Taylor ME, Vadineanu A, Waldmann T, Stadler J (2011b) Functional traits and local environment predict vegetation responses to disturbance: a pan-European multi-site experiment. J Ecol 99:777–787CrossRefGoogle Scholar
- Crawley MJ (2007) The R Book. Ed. 1, John Wiley & SonsGoogle Scholar
- Dubey P, Raghubanshi AS, Singh JS (2011) Intra-seasonal variation and relationship among leaf traits of different forest herbs in a dry tropical environment. Curr Sci 100:69–76Google Scholar
- Grant, B. W. & Vatnick, I. (2004) Environmental Correlates of Leaf Stomata Density. Teaching issues and Experiments in Ecology, 1, 1–24Google Scholar
- Hulshof CM, Violle C, Spasojevic MJ, McGill B, Damschen E, Harrison S, Enquist BJ (2013) Intra-specific and inter-specific variation in specific leaf area reveal the importance of abiotic and biotic drivers of species diversity across elevation and latitude. J Veg Sci 24:921–931CrossRefGoogle Scholar
- Kattge J, Diaz S, Lavorel S, Prentice IC, Leadley P, Bönisch G, Garnier E, Westoby M, Reich PB, Wright IJ, Cornelissen JHC, Violle C, Harrison SP, Van Bodegom PM, Reichstein M, Enquist BJ, Soudzilovskaia NA, Ackerly DD, Anand M, Atkin O, Bahn M, Baker TR, Baldocchi D, Bekker R, Blanco CC, Blonder B, Bond WJ, Bradstock R, Bunker DE, Casanoves F, Cavender-Bares J, Chambers JQ, Chapin Iii FS, Chave J, Coomes D, Cornwell WK, Craine JM, Dobrin BH, Duarte L, Durka W, Elser J, Esser G, Estiarte M, Fagan WF, Fang J, Fernandez-Mendez F, Fidelis A, Finegan B, Flores O, Ford H, Frank D, Freschet GT, Fyllas NM, Gallagher RV, Green WA, Gutierrez AG, Hickler T, Higgins SI, Hodgson JG, Jalili A, Jansen S, Joly CA, Kerkhoff AJ, Kirkup D, Kitajima K, Kleyer M, Klotz S, Knops JMH, Kramer K, Kühn I, Kurokawa H, Laughlin D, Lee TD, Leishman M, Lens F, Lenz T, Lewis SL, Lloyd J, Llusia J, Louault F, Ma S, Mahecha MD, Manning P, Massad T, Medlyn BE, Messier J, Moles AT, Müller SC, Nadrowski K, Naeem S, Niinemets Ü, Nöllert S, Nüske A, Ogaya R, Oleksyn J, Onipchenko VG, Onoda Y, Ordonez J, Overbeck G, Ozinga WA, Patino S, Paula S, Pausas JG, Penuelas J, Phillips OL, Pillar V, Poorter H, Poorter L, Poschlod P, Prinzing A, Proulx R, Rammig A, Reinsch S, Reu B, Sack L, Salgado-Negret B, Sardans J, Shiodera S, Shipley B, Siefert A, Sosinski E, Soussana JF, Swaine E, Swenson N, Thompson K, Thornton P, Waldram M, Weiher E, White M, White S, Wright SJ, Yguel B, Zaehle S, Zanne AE, Wirth C (2011) TRY – a global database of plant traits. Global Change Biol 17:2905–2935CrossRefGoogle Scholar
- Kikuzawa K, Lechowicz MJ (2011) Ecology of Leaf Longevity. Ed. 1, Springer JapanGoogle Scholar
- Kleyer M, Bekker RM, Knevel IC, Bakker JP, Thompson K, Sonnenschein M, Poschlod P, Van Groenendal JM, Klimes L, Klimesova J, Klotz S, Rusch G, Hermy M, Adriaens D, Boedeltje G, Bossuyt B, Endels P, Götzenberger L, Hodgson JG, Jackel A-K, Dannemann,A, Kühn I, Kunzmann D, Ozinga W, Römermann C, Stadler M, Schlegelmilch J, Steendam H, Tackenberg O, Wilmann B, Cornelissen JHC, Eriksson O, Garnier E, Fitter A, Peco B (2008) The LEDA traitbase, A database of plant life-history traits of North West Europe. J Ecol 96:1266–1274Google Scholar
- Lauterbach D, Römermann C, Jeltsch F, Ristow M (2013) Factors driving plant rarity in dry grasslands on different spatial scales: a functional trait approach. Biodiv & Conservation 22:2337–2352Google Scholar
- Muggeo VMR (2008) segmented: an R Package to Fit Regression Models with Broken-Line Relationships. R News 8:20–25Google Scholar
- Perez-Harguindeguy N, Diaz S, Garnier E, Lavorel S, Poorter H, Jaureguiberry P, Bret-Harte M S, Cornwell W K, Craine J M, Gurvich D E, Urcelay C, Veneklaas E J, Reich P B, Poorter L, Wright I J, Ray P, Enrico L, Pausas J G, de Vos A C, Buchmann N, Funes G, Quetier F, Hodgson J G, Thompson K, Morgan H D, ter Steege H, van der Heijden M G A, Sack L, Blonder B, Poschlod P, Vaieretti M V, Conti G, Staver A C, Aquino S & Cornelissen J H C (2013) New handbook for standardised measurement of plant functional traits worldwide. Austral J Bot 61:167–234Google Scholar
- R Foundation for Statistical Computing (2014) R: A language and environment for statistical computing ViennaGoogle Scholar
- Schreiber U, Bilger W, Neubauer C (1995) Chlorophyll fluorescence as a nonintrusive indicator for rapid assessment of in vivo photosynthesis. In: Ecophysiology of photosynthesis. Springer, pp 49–70Google Scholar
- Steer BT (1971) Dynamics of leaf growth and photosynthetic capacity in Capsicum frutescens L.. Ann Bot 35:1003–1015Google Scholar
- Strasser RJ, Srivastava A, Tsimilli-Michael M (1999) Screening the vitality and photosynthetic activity of plants by fluorescence transient. In Behl RK, Punia MS, Lather BPS (eds) Crop improvement for food security, Hisar, SSARM, pp 79–126Google Scholar
- Strasser RJ, Srivastava A, Tsimilli-Michael M (2000) The fluorescence transient as a tool to characterize and screen photosynthetic samples. In Yunus M, Pathre U, Mohanty P (eds) Probing photosynthesis: mechanisms, regulation and adaptation. Taylor and Francis, London, pp 443–480Google Scholar
- Wisskirchen R, Haeupler H (1998) Standardliste der Farn- und Blütenpflanzen Deutschlands. (Ed. 1), Ulmer, Stuttgart (Hohenheim)Google Scholar
- Zeileis A, Hothorn T (2002) Diagnostic Checking in Regression Relationships. R News 2:7–10Google Scholar