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

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.

Functional diversity and redundancy of freshwater fish communities across biogeographic and environmental gradients

“…Differences in functional rarity metrics across thermal preferences could indicate whether warming temperatures, expected to favor warm-water adapted species and lead to declines in cool and cold-water adapted species (Chu et al, 2005;Poesch, Chavarie, Chu, Pandit, & Tonn, 2016), will increase or decrease functional diversity. Furthermore, fish body size is related to many aspects of fish ecology including reproduction (Blueweiss et al, 1978) and dispersal (Radinger & Wolter, 2014), among others (Woodward et al, 2005;Alofs, 2016), and has also been used to predict vulnerability to predation (Alofs & Jackson, 2015) and shifts in species distributions under changing climate (Alofs, Jackson, & Lester, 2014). Finally,…”

Partitioning fish communities into guilds for ecological analyses: an overview of current approaches and future directions

“…Investigators often turn to available databases for data on species traits, such as FishBase (Froese and Pauly 2020), FishTraits (Frimpong and Angermeier 2020), and FishLife (Thorson et al 2017), to meet these data demands. Collectively, Cordlandwehr et al (2013) and Alofs (2016) suggest that the accuracy of specieslevel traits retrieved from such databases depends on the level of aggregation (or scale of data collection), the plasticity of the traits, the habitat the traits were retrieved from, and sampling bias. For example, Alofs (2016) found that the maximum size of small prey fishes recorded during field sampling was often larger than the maximum size recorded by other sources.…”

TOFF, a database of traits of fish to promote advances in fish aquaculture

“…Furthermore, the lack of important contextual information about measurement environmental context or levels of variation and replication for trait data limits such compilations. Yet, functional traits are environment-dependent 20 and display variability at the interpopulational level 21 . Therefore, a database hosting detailed information about functional traits and their environmental measurement context, which are required for aquaculture purpose, is still lacking.…”