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Trait dimensionality and population choice alter estimates of phenotypic dissimilarity

View Article: PubMed Central - PubMed

ABSTRACT

The ecological niche is a multi‐dimensional concept including aspects of resource use, environmental tolerance, and interspecific interactions, and the degree to which niches overlap is central to many ecological questions. Plant phenotypic traits are increasingly used as surrogates of species niches, but we lack an understanding of how key sampling decisions affect our ability to capture phenotypic differences among species. Using trait data of ecologically distinct monkeyflower (Mimulus) congeners, we employed linear discriminant analysis to determine how (1) dimensionality (the number and type of traits) and (2) variation within species influence how well measured traits reflect phenotypic differences among species. We conducted analyses using vegetative and floral traits in different combinations of up to 13 traits and compared the performance of commonly used functional traits such as specific leaf area against other morphological traits. We tested the importance of intraspecific variation by assessing how population choice changed our ability to discriminate species. Neither using key functional traits nor sampling across plant functions and organs maximized species discrimination. When using few traits, vegetative traits performed better than combinations of vegetative and floral traits or floral traits alone. Overall, including more traits increased our ability to detect phenotypic differences among species. Population choice and the number of traits used had comparable impacts on discriminating species. We addressed methodological challenges that have undermined cross‐study comparability of trait‐based approaches. Our results emphasize the importance of sampling among‐population trait variation and suggest that a high‐dimensional approach may best capture phenotypic variation among species with distinct niches.

No MeSH data available.


Correct assignment of individuals to species using single traits. No single trait performed best for all species, and “functional” traits such as SLA and height (white boxplots) were not noticeably better than morphological traits such as leaf aspect ratio. Only traits for which complete field data were available and which were variable within subsampled species were used in this analysis. Boxplots summarize data from all 100 runs
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ece32780-fig-0003: Correct assignment of individuals to species using single traits. No single trait performed best for all species, and “functional” traits such as SLA and height (white boxplots) were not noticeably better than morphological traits such as leaf aspect ratio. Only traits for which complete field data were available and which were variable within subsampled species were used in this analysis. Boxplots summarize data from all 100 runs

Mentions: No single trait performed best for all species (Figure 3). Single functional traits, such as SLA and height, did not capture any more among‐species variation than did other morphological traits. Instead, different species were better distinguished by different traits (Fig. S4). For example, correct assignment of individuals to species using only SLA averaged approximately 75% for M. moschatus but was below 25% for several other species including M. guttatus (Fig. S4). Although not distinctive in several leaf traits (e.g., SLA, circularity), M. guttatus was best distinguished using leaf aspect ratios. Generally, M. leptaleus individuals were well discriminated using corolla width but not plant height. These findings suggest that to capture interspecific phenotypic differences, we need to measure multiple traits. Further, the identity of these traits may vary among assemblages.


Trait dimensionality and population choice alter estimates of phenotypic dissimilarity
Correct assignment of individuals to species using single traits. No single trait performed best for all species, and “functional” traits such as SLA and height (white boxplots) were not noticeably better than morphological traits such as leaf aspect ratio. Only traits for which complete field data were available and which were variable within subsampled species were used in this analysis. Boxplots summarize data from all 100 runs
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383497&req=5

ece32780-fig-0003: Correct assignment of individuals to species using single traits. No single trait performed best for all species, and “functional” traits such as SLA and height (white boxplots) were not noticeably better than morphological traits such as leaf aspect ratio. Only traits for which complete field data were available and which were variable within subsampled species were used in this analysis. Boxplots summarize data from all 100 runs
Mentions: No single trait performed best for all species (Figure 3). Single functional traits, such as SLA and height, did not capture any more among‐species variation than did other morphological traits. Instead, different species were better distinguished by different traits (Fig. S4). For example, correct assignment of individuals to species using only SLA averaged approximately 75% for M. moschatus but was below 25% for several other species including M. guttatus (Fig. S4). Although not distinctive in several leaf traits (e.g., SLA, circularity), M. guttatus was best distinguished using leaf aspect ratios. Generally, M. leptaleus individuals were well discriminated using corolla width but not plant height. These findings suggest that to capture interspecific phenotypic differences, we need to measure multiple traits. Further, the identity of these traits may vary among assemblages.

View Article: PubMed Central - PubMed

ABSTRACT

The ecological niche is a multi‐dimensional concept including aspects of resource use, environmental tolerance, and interspecific interactions, and the degree to which niches overlap is central to many ecological questions. Plant phenotypic traits are increasingly used as surrogates of species niches, but we lack an understanding of how key sampling decisions affect our ability to capture phenotypic differences among species. Using trait data of ecologically distinct monkeyflower (Mimulus) congeners, we employed linear discriminant analysis to determine how (1) dimensionality (the number and type of traits) and (2) variation within species influence how well measured traits reflect phenotypic differences among species. We conducted analyses using vegetative and floral traits in different combinations of up to 13 traits and compared the performance of commonly used functional traits such as specific leaf area against other morphological traits. We tested the importance of intraspecific variation by assessing how population choice changed our ability to discriminate species. Neither using key functional traits nor sampling across plant functions and organs maximized species discrimination. When using few traits, vegetative traits performed better than combinations of vegetative and floral traits or floral traits alone. Overall, including more traits increased our ability to detect phenotypic differences among species. Population choice and the number of traits used had comparable impacts on discriminating species. We addressed methodological challenges that have undermined cross‐study comparability of trait‐based approaches. Our results emphasize the importance of sampling among‐population trait variation and suggest that a high‐dimensional approach may best capture phenotypic variation among species with distinct niches.

No MeSH data available.