Hi, I can give you some advice coming from my experience. Good sampling is very important; I assume the plant is herbaceous? It is crucial to collect individuals growing in the similar environmental condition and take leaves from the same part of the plant. In our studies we sample 10 leaves per individual and 30 individuals per population (so 25 should be OK). If you need inter-individual variation, you should analize at least 10 leaves - and if you expect differences between vegetative and flowering shoots, you would need 10 leaves od each type of shoots (5 should be enough if you have many samples). This is important to choose leaves from the same part of a shoot - the middle is the best usually, with fully developed leaves. One measurement of each trait from every leaf. You can find examples in the papers (you will see there statistical methods also):

Boratyńska K., Jasińska A.K., Ciepłuch E. 2008. Effect of tree age on needle morphology and anatomy of Pinus uliginosa and Pinus silvestris – species-specific character separation during ontogenesis. Flora - Morphology Distribution Functional Ecology of Plants 11/2008; 203(8-203):617-626. DOI:10.1016/j.flora.2007.10.004

Boratyńska K., Boratyński A. 2007. Taxonomic differences among closely related pines Pinus sylvestris, P. mugo, P. uncinata, P. rotundata and P. uliginosa as revealed in needle sclerenchyma cells. Flora - Morphology Distribution Functional Ecology of Plants 09/2007; 202(7):555-569. DOI:10.1016/j.flora.2006.11.004 ·

Marcysiak K. 2012. Variation of leaf shape of Salix herbacea in Europe. Plant Systematic and Evolution 298: 1597-1607.

See responses in

https://www.researchgate.net/post/How_can_I_calculate_power_for_multi-level_analysis

Hi, I can give you some advice coming from my experience. Good sampling is very important; I assume the plant is herbaceous? It is crucial to collect individuals growing in the similar environmental condition and take leaves from the same part of the plant. In our studies we sample 10 leaves per individual and 30 individuals per population (so 25 should be OK). If you need inter-individual variation, you should analize at least 10 leaves - and if you expect differences between vegetative and flowering shoots, you would need 10 leaves od each type of shoots (5 should be enough if you have many samples). This is important to choose leaves from the same part of a shoot - the middle is the best usually, with fully developed leaves. One measurement of each trait from every leaf. You can find examples in the papers (you will see there statistical methods also):

Boratyńska K., Jasińska A.K., Ciepłuch E. 2008. Effect of tree age on needle morphology and anatomy of Pinus uliginosa and Pinus silvestris – species-specific character separation during ontogenesis. Flora - Morphology Distribution Functional Ecology of Plants 11/2008; 203(8-203):617-626. DOI:10.1016/j.flora.2007.10.004

Boratyńska K., Boratyński A. 2007. Taxonomic differences among closely related pines Pinus sylvestris, P. mugo, P. uncinata, P. rotundata and P. uliginosa as revealed in needle sclerenchyma cells. Flora - Morphology Distribution Functional Ecology of Plants 09/2007; 202(7):555-569. DOI:10.1016/j.flora.2006.11.004 ·

Marcysiak K. 2012. Variation of leaf shape of Salix herbacea in Europe. Plant Systematic and Evolution 298: 1597-1607.

Lo ideal sería un n=30 pero con n=10 sería apropiado...good luck

You have gotten sound advise from the responses. We tried for 40 individuals in wild rice populations. We were doing DNA extraction and not all samples tend to work. By remaining at 30 you do have the power to resolve differences. Did you get the details you needed for amounts per plant? You appear to be looking at multivariate analysis if you want all the data analyzed together. You could look into DCA or detrended corespondance analysis. This is used in a species verses plots style of clustergram 

one leaf per individual; 10 individuals per population

Dear colleagues, thank you all for your valuable answers.

Dear Dr. Katarzyna Marcysiak, I think one measurement of a parameter per leaf seems not to be enough. Of course, leaf dimensions (length and width, etc.) will be naturally measured once for each leaf. But what about micro-characters, such as stomata, hairs, etc. (their linear dimensions and density)? As to me, there should be a number of their measurements (minimum 5, better 10) per leaf to allow for their within-leaf variation at least roughly. One measurement of the density can be done only if it covers the whole leaf at once, i.e., stomata/hairs are counted on the whole leaf.

You measure until the standard error (or any measure of variation) is equal to or less than 10 % of the mean. Unfortunately I don't have any literature to support this.

You may get the logic of a possible answer, not the recipe, from Section 5.8.2 in “Statistical Ecology”, downloadable from

https://www.researchgate.net/profile/Laszlo_Orloci

Good luck.

As with all studies, the sampling design depends on what you are trying to capture, and what can be reasonably measured with the resources at hand.

The first question is what population to sample, the individual, or the zone. If your main goal is to capture differences between two areas, or along an elevational transect, then within leaf variation is less important than capturing each population (lowland and montane). If this is the case, I would recommend sampling many individuals in each population. If time and resources allow, it would be nice to know if the within leaf variation is the same as the within population variation, but it is not necessary. However, if collecting many individuals is prohibitive, then sub-sampling each individual many times may be a useful proxy to reduce the number of individuals that must be sampled.

The second question is how much sampling is enough. I second Dimitri Veldkornet. The sample size must be large enough to provide reasonable standard errors.

Hi Eugene,

I think the paper by Perez-Harguindeguy et al. will provide some useful advice

Hi Eugene;

I propose this paper, I think it is really important for you.

Good luck.

Hi!! Thank you for sharing this excellent handbook for standardised measurement of plant functional traits.

Best regards

Marcela