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Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

ABSTRACT: The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits' variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITVBI) and among populations (ITVPOP), relatively few studies have analyzed intraspecific variability within individuals (ITVWI). Here, we provide an analysis of ITVWI of two foliar traits, namely specific leaf area (SLA) and osmotic potential (?), in a population of Quercus ilex L. We assessed the baseline ITVWI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITVWI, comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while ? variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.

SUBMITTER: Petruzzellis F

PROVIDER: S-EPMC5743657 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

Petruzzellis Francesco F Palandrani Chiara C Savi Tadeja T Alberti Roberto R Nardini Andrea A Bacaro Giovanni G

Ecology and evolution 20171121 24

The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits' variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITV<sub>BI</sub>) and among populations ( ...[more]

PMID: 29299296

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Project description:Background and aimsUnderstanding impacts of altered disturbance regimes on community structure and function is a key goal for community ecology. Functional traits link species composition to ecosystem functioning. Changes in the distribution of functional traits at community scales in response to disturbance can be driven not only by shifts in species composition, but also by shifts in intraspecific trait values. Understanding the relative importance of these two processes has important implications for predicting community responses to altered disturbance regimes.MethodsWe experimentally manipulated fire return intervals in replicated blocks of a fire-adapted, longleaf pine (Pinus palustris) ecosystem in North Carolina, USA and measured specific leaf area (SLA), leaf dry matter content (LDMC) and compositional responses along a lowland to upland gradient over a 4 year period. Plots were burned between zero and four times. Using a trait-based approach, we simulate hypothetical scenarios which allow species presence, abundance or trait values to vary over time and compare these with observed traits to understand the relative contributions of each of these three processes to observed trait patterns at the study site. We addressed the following questions. (1) How do changes in the fire regime affect community composition, structure and community-level trait responses? (2) Are these effects consistent across a gradient of fire intensity? (3) What are the relative contributions of species turnover, changes in abundance and changes in intraspecific trait values to observed changes in community-weighted mean (CWM) traits in response to altered fire regime?Key resultsWe found strong evidence that altered fire return interval impacted understorey plant communities. The number of fires a plot experienced significantly affected the magnitude of its compositional change and shifted the ecotone boundary separating shrub-dominated lowland areas from grass-dominated upland areas, with suppression sites (0 burns) experiencing an upland shift and annual burn sites a lowland shift. We found significant effects of burn regimes on the CWM of SLA, and that observed shifts in both SLA and LDMC were driven primarily by intraspecific changes in trait values.ConclusionsIn a fire-adapted ecosystem, increased fire frequency altered community composition and structure of the ecosystem through changes in the position of the shrub line. We also found that plant traits responded directionally to increased fire frequency, with SLA decreasing in response to fire frequency across the environmental gradient. For both SLA and LDMC, nearly all of the observed changes in CWM traits were driven by intraspecific variation.

Project description:Background and aimsTrait-environment relationships are commonly interpreted as evidence for local adaptation in plants. However, even when selection analyses support this interpretation, the mechanisms underlying differential benefits are often unknown. This study addresses this gap in knowledge using the broadly distributed South African shrub Protea repens. Specifically, the study examines whether broad-scale patterns of trait variation are consistent with spatial differences in selection and ecophysiology in the wild.MethodsIn a common garden study of plants sourced from 19 populations, associations were measured between five morphological traits and three axes describing source climates. Trait-trait and trait-environment associations were analysed in a multi-response model. Within two focal populations in the wild, selection and path analyses were used to test associations between traits, fecundity and physiological performance.Key resultsAcross 19 populations in a common garden, stomatal density increased with the source population's mean annual temperature and decreased with its average amount of rainfall in midsummer. Concordantly, selection analysis in two natural populations revealed positive selection on stomatal density at the hotter, drier site, while failing to detect selection at the cooler, moister site. Dry-site plants with high stomatal density also had higher stomatal conductances, cooler leaf temperatures and higher light-saturated photosynthetic rates than those with low stomatal density, but no such relationships were present among wet-site plants. Leaf area, stomatal pore index and specific leaf area in the garden also co-varied with climate, but within-population differences were not associated with fitness in either wild population.ConclusionsThe parallel patterns of broad-scale variation, differences in selection and differences in trait-ecophysiology relationships suggest a mechanism for adaptive differentiation in stomatal density. Densely packed stomata may improve performance by increasing transpiration and cooling, but predominately in drier, hotter climates. This study uniquely shows context-dependent benefits of stomatal density--a trait rarely linked to local adaptation in plants.

Dataset Information

Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

Publications

Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

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