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The influence of variability in species trait data on community ‐ level ecological prediction and inference

View Article: PubMed Central - PubMed

ABSTRACT

Species trait data have been used to predict and infer ecological processes and the responses of biological communities to environmental changes. It has also been suggested that, in lieu of trait, data niche differences can be inferred from phylogenetic distance. It remains unclear how variation in trait data may influence the strength and character of ecological inference. Using species‐level trait data in community ecology assumes intraspecific variation is small in comparison with interspecific variation. Intraspecific variation across species ranges or within populations may lead to variability in trait data derived from different scales (i.e., local or regional) and methods (i.e., mean or maximum values). Variation in trait data across species can affect community‐level relationships. I examined variability in body size, a key trait often measured across taxa. I collected 12 metrics of fish species length (including common and maximum values) for 40 species from literature, online databases, museum collections, and field data. I then tested whether different metrics of fish length could consistently predict observed species range boundary shifts and the impacts of an introduced predator on inland lake fish communities across Ontario, Canada. I also investigated whether phylogenetic signal, an indicator of niche‐conservativism, changed among measures. I found strong correlations between length metrics and limited variation across metrics. Accordingly, length was a consistently significant predictor of the response of fish communities to environmental change. Additionally, I found significant evidence of phylogenetic signal in fish length across metrics. Limited variation in length across metrics (within species), in comparison with variation within metrics (across species), made fish species length a reliable predictor at a community‐level. When considering species‐level trait data from different sources, researchers should examine the potential influence of intraspecific trait variation on data derived by different metrics and at different scales.

No MeSH data available.


Correlation matrix for 12 metrics of fish species length for 40 species.
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ece32385-fig-0002: Correlation matrix for 12 metrics of fish species length for 40 species.

Mentions: Length data were highly correlated between the 12 metrics and across the 40 fish species I considered (Fig. 2). Correlations ranged from r = 0.9089 between the common length reported on FishBase and median length recorded in BsM field data to r = 0.9998 between the maximum length reported on FishBase and the world record reported in the Freshwater Fishes of Ontario. Variation among metrics was greater for larger species (higher CV across metrics; Supporting Information Appendix S1). The mean CV of length among metrics within species (range 0.15–0.52, mean = 0.33, SD = 0.09) was less than half the variation in length among species within metrics (range 0.80–0.93, mean = 0.86, SD = 0.05).


The influence of variability in species trait data on community ‐ level ecological prediction and inference
Correlation matrix for 12 metrics of fish species length for 40 species.
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5016654&req=5

ece32385-fig-0002: Correlation matrix for 12 metrics of fish species length for 40 species.
Mentions: Length data were highly correlated between the 12 metrics and across the 40 fish species I considered (Fig. 2). Correlations ranged from r = 0.9089 between the common length reported on FishBase and median length recorded in BsM field data to r = 0.9998 between the maximum length reported on FishBase and the world record reported in the Freshwater Fishes of Ontario. Variation among metrics was greater for larger species (higher CV across metrics; Supporting Information Appendix S1). The mean CV of length among metrics within species (range 0.15–0.52, mean = 0.33, SD = 0.09) was less than half the variation in length among species within metrics (range 0.80–0.93, mean = 0.86, SD = 0.05).

View Article: PubMed Central - PubMed

ABSTRACT

Species trait data have been used to predict and infer ecological processes and the responses of biological communities to environmental changes. It has also been suggested that, in lieu of trait, data niche differences can be inferred from phylogenetic distance. It remains unclear how variation in trait data may influence the strength and character of ecological inference. Using species‐level trait data in community ecology assumes intraspecific variation is small in comparison with interspecific variation. Intraspecific variation across species ranges or within populations may lead to variability in trait data derived from different scales (i.e., local or regional) and methods (i.e., mean or maximum values). Variation in trait data across species can affect community‐level relationships. I examined variability in body size, a key trait often measured across taxa. I collected 12 metrics of fish species length (including common and maximum values) for 40 species from literature, online databases, museum collections, and field data. I then tested whether different metrics of fish length could consistently predict observed species range boundary shifts and the impacts of an introduced predator on inland lake fish communities across Ontario, Canada. I also investigated whether phylogenetic signal, an indicator of niche‐conservativism, changed among measures. I found strong correlations between length metrics and limited variation across metrics. Accordingly, length was a consistently significant predictor of the response of fish communities to environmental change. Additionally, I found significant evidence of phylogenetic signal in fish length across metrics. Limited variation in length across metrics (within species), in comparison with variation within metrics (across species), made fish species length a reliable predictor at a community‐level. When considering species‐level trait data from different sources, researchers should examine the potential influence of intraspecific trait variation on data derived by different metrics and at different scales.

No MeSH data available.