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Relative growth rate and its components

Hendrik Poorter
Contributors : John_Richard_Evans1578 points 


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Author Affliations

This article is modified from Perez-Harguindeguy et al (2013). The "New handbook for standardised measurement of plant functional traits worldwide" is a product of and is hosted by Nucleo Diversus (with additional Spanish translation). For more on this trait and on its context as part of the entire trait handbook visit its primary site Nucleo DiverSus at http://www.nucleodiversus.org/?lang=en

Overview

Relative growth rate (RGR) is a prominent indicator of plant strategy with respect to productivity as related to environmental stress and disturbance regimes. RGR is the (exponential) increase in size relative to the size of the plant present at the start of a given time interval. Expressed in this way, growth rates can be compared among species and individuals that differ widely in size. By separate measurement of leaf, stem and root mass as well as leaf area (LA), good insight into the components underlying growth variation can be obtained in a relatively simple way. These underlying parameters are related to allocation (leaf-mass fraction, the fraction of plant biomass allocated to leaf), leaf morphology (see SLA), and physiology (unit leaf rate, the rate of increase in plant biomass per unit LA, a variable closely related to the daily rate of photosynthesis per unit LA; also known as net assimilation rate).

 

Background

Ideally, RGR is measured on a dry-mass basis for the whole plant, including roots. Growth analysis requires the destructive harvest of two or more groups of plant individuals, grown either under controlled laboratory conditions or in the field. Individuals should be acclimated to the current growth conditions. At least one initial and one final harvest should be carried out. The actual number of plants to be harvested for a reliable estimate increases with the variability in the population. Size variability can be reduced by growing a larger number of plants and selecting a priori similarly-sized individuals for the experiment, discarding the small and large individuals. Alternatively, plants can be grouped by eye in even-sized categories, with the number of plants per category equal to the number of harvests. By harvesting one plant from each category at each harvest, each harvest should include a representative sample of the total population studied. The harvest intervals may vary from less than 1 week in the case of fast-growing herbaceous species, to more than 2 months or longer in the case of juvenile individuals of slow-growing woody species. As a rule of thumb, harvest intervals should be chosen such that plants have less than doubled mass during that interval.

At harvest, the whole root system is excavated and subsequently cleaned, gently washing away the soil (see details on procedure under Specific root length). Plants are divided into three functional parts, including leaves (light interception and carbon (C) uptake), stem (support and transport) and roots (water and nutrient uptake, as well as storage). The petioles can either be included in the stem fraction (reflecting support; this is the preferred option), or combined with the leaf fraction (to which they belong morphologically), or they can be measured separately. LA is measured (for details, see SLA) before the different plant parts are oven-dried for at least 48 h at 70°C and weighed.

Destructive harvests provide a wealth of information, but are extremely labour-intensive and, by their nature, destroy at least a subset of the materials being studied. Alternatively or additionally, growth can be followed non-destructively for several individuals (~10–15 per treatment), by non-destructively measuring an aspect of plant size at two or more moments in time. By repeatedly measuring the same individuals, a more accurate impression of RGR can be obtained. However, RGR cannot be factorised into its components then, and repeated handling may cause growth retardation. Ideally, the whole volume of stems (and branches) is determined in woody species (Stem-specific density), or the total area of leaves, in the case of herbaceous plants. In the latter case, leaf length and width are measured, along with the number of leaves. To estimate LA, a separate sample of leaves (~20) has to be used to determine the linear-regression slope of leaf length × width.

 

Materials/Equipment

 

Units, terms, definitions

LA - leaf area (units: mm2 ; range of values: 1 – >206 )

LMF - leaf mass fraction

SLA - specific leaf area : the one-sided area of a fresh leaf, divided by its oven-dry mass (units: mm2 mg-1 also can be expressed as  m2 kg-1; range of values: <1–300)

ULR - unit leaf rate

Procedure

From two consecutive harvests at times t1 and t2, yielding plant masses M1 and M2, the average RGR is calculated as: 

RGR = (lnM2 – lnM1) / (t2t1)

In the case of a well balanced design where plants are paired, it is probably simplest to calculate RGR and its growth parameters for each pair of plants, and then use the RGR values for each pair to average over the population. Otherwise, the average RGR over the whole group of plants is calculated from the same equation. In doing so, make sure to first ln-transform the total mass of each plant before the averaging. In the case of more than two harvests, average RGR can be derived from the linear-regression slope of ln(mass) over time. The average unit leaf rate (ULR) over a given period is:

ULR = [(M2M1) / (A2A1)] × [(lnA2 – lnA1) / (t2t1)],

where A1 and A2 represent the LA at t1 and t2, respectively.

Again, the simplest option would be to calculate ULR from each pair of plants. Average leaf mass fraction (LMF) during that period is the average of the values from the 1st and 2nd harvest, as follows:

LMF = [(ML1 / M1) + (ML2 / M2)] /2,

where ML1 and ML2 indicate the leaf mass at t1 and t2, respectively.

Similarly, average specific leaf area (SLA) is calculated as follows:

SLA = [(A1 / ML1) + (A2 / ML2)] /2

Other resources

Notes and troubleshooting tips

  1. Confounding effect of seed size. Especially tree seedlings may draw on seed reserves for a long time after germination. Inclusion of the seed in the total plant mass underestimates the RGR of the new seedling, whereas exclusion of the seed mass will cause an overestimation of growth. For large, persistent seeds, the decrease in seed mass between t1 and t2 can therefore be added to M1 (excluding seed mass itself from M1 and M2).
  2. Ontogenetic drift. As plants change over time, they readjust allocation, morphology and leaf physiology. Consequently, LMF, SLA and ULR may change with plant size, and RGR generally decreases over time, the more so in fast-growing species. This does not devalue the use of the RGR, as plant growth does not necessarily have to be strictly exponential. As long as plant growth is somehow proportional to the plant size already present, RGR is an appropriate parameter that encapsulates the average RGR over a given time period. However, ontogenetic drift is an important characteristic of plant growth, and a higher frequency of harvests may provide better insight into this phenomenon. In comparing species or treatments, it may be an option to compare plants at a given size or size interval, rather than over a given period of time.
  3. Related to ontogenetic drift, shrubs and trees accumulate increasing amounts of xylem, of which large proportions may die depending on the species. This inert mass would greatly reduce RGR. Previous studies express RGR (‘relative production rate’) on the living parts of large woody plants by treating the biomass increment over Year 1 as M1 and the increment over Year 2 as M2 it could similarly be based on annual diameter (or volume) increments.
  4. Smooth curves. In the case of frequent (small) harvests, a special technique can be applied, in which polynomial curves are fitted through the data. This is an art in itself!
 

Links to resources and suppliers

 

Literature references

References on theory, significance and large datasets: 

Cornelissen JHC, Castro-Díez P, Hunt R (1996) Seedling growth, allocation and leaf attributes in a wide range of woody plant species and types. Journal of Ecology 84, 755–765 doi:102307/2261337

Evans GC (1972) The quantitative analysis of plant growth. Blackwell Scientific Publications: Oxford, UK

Grime JP, Hunt R (1975) Relative growth-rate: its range and adaptive significance in a local flora. Journal of Ecology 63, 393–422 doi:102307/2258728

Kitajima K (1994) Relative importance of photosynthetic traits and allocation patterns as correlates of seedling shade tolerance of 13 tropical trees. Oecologia 98, 419–428 doi:101007/BF00324232

Poorter H, Nagel O (2000) The role of biomass allocation in the growth response of plants to different levels of light, CO2, nutrients and water: a quantitative review [published erratum appears in Australian Journal of Plant Physiology27, 1191]. Australian Journal of Plant Physiology 27, 595–607 doi:101071/PP99173_CO

Poorter H, Garnier E (2007) The ecological significance of variation in relative growth rate and its components. In Functional plant ecology. Eds FI Pugnaire, F Valladares pp. 67–100. CRC press: Boca Raton, FL 

Rees M, Osborne CP, Woodward FI, Hulme SP, Turnbull LA, Taylor SH (2010) Partitioning the components of relative growth rate: how important is plant size variation? American Naturalist 176, E152–E161 doi:101086/657037

Walters MB, Reich PB (1999) Low-light carbon balance and shade tolerance in the seedlings of woody plants: do winter deciduous and broad-leaved evergreen species differ? New Phytologist 143, 143–154 doi:101046/j1469-8137199900425x

More on methods:

Causton DR, Venus JC (1981) The biometry of plant growth. Edward Arnold: London

Cornelissen JHC, Castro-Díez P, Hunt R (1996) Seedling growth, allocation and leaf attributes in a wide range of woody plant species and types. Journal of Ecology 84, 755–765 doi:102307/2261337

Evans GC (1972) The quantitative analysis of plant growth. Blackwell Scientific Publications: Oxford, UK

Hunt R (1982) Plant growth curves. The functional approach to plant growth analysis. Edward Arnold: London 

Poorter H, Lewis C (1986) Testing differences in relative growth rate: a method avoiding curve fitting and pairing. Physiologia Plantarum 67, 223–226 doi:101111/j1399-30541986tb02447x

Poorter H, Welschen RAM (1993). Analyzing variation in RGR in terms of the underlying carbon economy. In Methods in comparative plant ecology – a laboratory manual. Eds GAF Hendry, JP Grime, pp. 107–110. Chapman and Hall: London  

Rees M, Osborne CP, Woodward FI, Hulme SP, Turnbull LA, Taylor SH (2010) Partitioning the components of relative growth rate: how important is plant size variation? American Naturalist 176, E152–E161 doi:101086/657037

Health, safety & hazardous waste disposal considerations

 


Contributors to this page: Admin26202 points  and John_Richard_Evans1578 points  .
Page last modified on Saturday 27 of July, 2013 16:05:21 EST by Admin26202 points . (Version 14)