Table 1.

Recommendations for quantifying ITV, which will facilitate a deeper understanding of its causes and its ecological significance across levels of organization. We focus on experimental design and analysis and data collection techniques; detailed research questions are outlined in the main text

Question	Solutions
What are the mechanisms, drivers, and sources of ITV?	Design and analysis
	• Use mixed linear models to account for hierarchical relationships (e.g. species/individual/branch)
	• Apply variance partitioning analysis to determine sources of trait variation, e.g. site, across species, within species, climate, soil. Report total variation alongside these analyses
	• Use common garden experiments to separate plasticity from genetic differentiation, and incorporate with field studies whenever possible
	• Quantify spatiotemporal patterns in ITV alongside BTV. Search for parallels or discrepancies
	• Use multivariate environmental variables, e.g. integrate aridity and soil texture, in regressions
	• Use phylogenetic analyses if traits are suspected to be highly conserved among closely related species
	• Test for patterns of covariance and for underlying biophysical or developmental constraints on ITV, e.g. hydraulic constraints on tree height
	Data collection
	• Apply nested sampling designs, e.g. region/site/plot
	• When collecting trait data, track the identity of the individual plant but also the individual branch or stem
	• Measure biotic forces, e.g. competition and herbivory, but also interactions between abiotic and biotic variables, e.g. herbivore intensity over soil gradients
How does ITV influence individual higher-order processes?	Design and analysis
	• Measure traits that are likely to be under selection, rather than always using commonly measured traits such as SLA, and use integrative traits that capture multiple functions. Consider using ‘effect’ traits, i.e. traits that directly influence ecosystem processes
	• Analyse trait–performance relationships across a range of ages/sizes, genotypes, environmental conditions and levels of organization and test for interactions, e.g. genotype × environment to understand phenotypic variation but also trait × environment × size, to understand consequences for performance
	• Incorporate ITV within demographic models, and calculate demographic rates for co-occurring species
	• Simulate ITV when data are lacking, using published datasets to explore sensitivities of population growth or community dynamics to ITV
	Data collection
	• Measure traits across a range of plant ages or sizes, and environments
	• Measure at least one metric of plant performance, i.e. growth, survival, reproduction, but ideally more than one as there may be trade-offs among them
	• Measure ITV in traits of interacting species, e.g. plant and its pollinator
What is the extent of ITV and are there key generalities?	Design and analysis
	• Quantify extent of intraspecific trait variation (e.g. CV, SD) and distributions of data
	• Investigate changes in CV across environmental gradients
	• Report population means or individual level (replicate) data rather than species means in published trait databases
	• Report underlying genetic structure/variation
	• Investigate ITV in underrepresented traits or functions: biomass allocation, anatomy, defence, chemistry, hydraulics, architecture
	• Investigate ITV in underrepresented plant functional groups, biomes, across latitudinal gradients, and at global scale
	Data collection
	• Randomly sample individuals or organs
	• Repeatedly sample over time to assess temporal variation
	• Sample more extensively within species (ideally 20 if reporting CV but at least 5). Measure more extensively if environmental conditions are particularly heterogeneous (e.g. sites spanning topographic gradients)
	• Expand the breadth of traits measured to include roots, stems and reproductive organs
	• Use a combination of individual traits and multifunctional (integrative traits) and consider whether focal traits are likely to be under strong selection, e.g. wood density may be more meaningful along aridity gradients than chlorophyll content