Realizing the potential of trait‐based aquatic ecology: New tools and collaborative approaches

Kremer, Colin T.; Williams, Alicia K.; Finiguerra, Michael; Fong, Allison A.; Kellerman, Anne M.; Paver, Sara F.; Tolar, Bradley B.; Toscano, Benjamin J.

doi:10.1002/lno.10392

Cited by 42 publications

(52 citation statements)

References 169 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite the potential for a temperature-dependent resource competition theory to improve forecasting of community dynamics, experimental characterization of resource requirements for a large number of taxa is not practical (Kremer et al 2017b). However, the integration of nutrient-based competition models with metabolic-based theory (Brown et al 2004) may be a critical step towards understanding fundamental constraints governing community and ecosystem dynamics under changing climate (Allen and Gillooly 2009).…”

Section: Discussionmentioning

confidence: 99%

Temperature‐dependence of minimum resource requirements alters competitive hierarchies in phytoplankton

Lewington‐Pearce

Narwani

Thomas

et al. 2019

Oikos

Self Cite

View full text Add to dashboard Cite

Resource competition theory is a conceptual framework that provides mechanistic insights into competition and community assembly of species with different resource requirements. However, there has been little exploration of how resource requirements depend on other environmental factors, including temperature. Changes in resource requirements as influenced by environmental temperature would imply that climate warming can alter the outcomes of competition and community assembly. We experimentally demonstrate that environmental temperature alters the minimum light and nitrogen requirements – as well as other growth parameters – of six widespread phytoplankton species from distinct taxonomic groups. We found that species require the most nitrogen at the highest temperatures while light requirements tend to be lowest at intermediate temperatures, although there are substantial interspecific differences in the exact shape of this relationship. We also experimentally parameterize two competition models, which we use to illustrate how temperature, through its effects on species’ traits, alters competitive hierarchies in multispecies assemblages, determining community dynamics. Developing a mechanistic understanding of how temperature influences the ability to compete for limiting resources is a critical step towards improving forecasts of community dynamics under climate warming.

show abstract

Section: Discussionmentioning

confidence: 99%

Temperature‐dependence of minimum resource requirements alters competitive hierarchies in phytoplankton

Lewington‐Pearce

Narwani

Thomas

et al. 2019

Oikos

Self Cite

View full text Add to dashboard Cite

show abstract

“…The identification of reliable species associations in phytoplankton might be further enhanced by the future combination of different approaches, that is, using trait‐based approaches to identify characteristic response groups in natural phytoplankton communities (Kruk et al., ). In the future, trait‐based approaches in phytoplankton ecology may favour the identification of ecologically relevant traits (Kremer et al., ), the evaluation of continuous traits (Edwards, Klausmeier, & Litchman, ; Edwards, Thomas, Klausmeier, & Litchman, ) as well as the consideration of intraspecific variations in traits (Carmona, De Bello, Mason, & Lepš, ).…”

Section: Discussionmentioning

confidence: 99%

Functional richness outperforms taxonomic richness in predicting ecosystem functioning in natural phytoplankton communities

2017

View full text Add to dashboard Cite

Recent studies clearly support a positive biodiversity–ecosystem functioning (BEF) relationship in phytoplankton. As taxon richness does not quantify functional diversity, functional approaches have been developed to link community functioning to diversity. Compared to terrestrial plant communities, only a few studies have validated phytoplankton functional approaches in BEF relationships. Furthermore, the ability of functional and taxonomic richness measures in predicting ecosystem functioning of natural phytoplankton communities has not been compared yet. Here, we analysed the BEF relationship using taxonomic and functional (trait categories and response groups sensu Reynolds) approaches in a broad‐scale phytoplankton dataset from Fennoscandia. First, we analysed how taxonomic and functional compositions were related to local environmental predictors. We then compared how taxonomic and functional richness performed in predicting resource‐use efficiency (the yield in phytoplankton biomass standardised by total phosphorus) as an ecosystem functioning measure. Finally, we tested whether the relationship between ecosystem functioning and taxonomic richness is further enhanced once each of the functional richness measure is also considered. Among the approaches, phytoplankton functional trait categories as community matrix showed the best correspondence with the local environment. The richness of phytoplankton response groups predicted ecosystem functioning significantly better than the taxonomic and the functional trait category richness—both in the full dataset and in almost all Fennoscandian countries. On top of taxonomic richness, only the residual variation in response group richness predicted ecosystem functioning positively in the entire dataset and in all individual countries. Applying functional approaches, reduced complexity of data should come along with reduced ecological information. We showed, however, that both functional approaches represented some functional redundancy among taxa in a meaningful way, and enhanced our ability in predicting community composition from environmental predictors. Moreover, phytoplankton response group richness sensu Reynolds summarises information on ecosystem functioning contained in the taxonomic data in a way that represents functional diversity better than the richness of functional trait categories. Interestingly, the response group approach, which is exclusively derived from field observations rather than from quantified phytoplankton traits, outperforms taxonomic richness and trait category richness in predicting ecosystem functioning in our dataset. This may highlight that our ability to quantify phytoplankton traits is still limited. Existing phytoplankton functional approaches, however, can translate the taxonomic information into a reduced but reliable functional matrix already and predict ecosystem functioning better than taxonomic data.

show abstract

“…Although there are websites that compile a large amount of data on fish (e.g. FishBase.org), there is generally no single database covering all species and all relevant traits, even for small geographical areas (Kremer et al, ). In addition, these databases often include fishes that are not evenly studied and thus have different coverage and gaps regarding some specific trait information, presumably due to methodological reasons, e.g.…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis of fish traits reveals discrepancies among databases

2020

View full text Add to dashboard Cite

Trait‐based approaches are commonly used in ecology to understand the relationship between biodiversity and ecosystem functioning, environmental filtering or biotic responses to anthropogenic perturbations. However, little is known about the reliability of assigned traits and the consistency of trait information among different databases currently in use. Using 99 native and alien Iberian inland fish species, we investigated a total of 27 biological and ecological traits for their consistency among 19 different databases and identified less reliable traits, that is, traits with high disagreement among databases. Specifically, we used generalised linear models and inter‐rater reliability statistics (Krippendorff's α) to test for differences in trait values among databases. We also identified well‐studied versus data‐deficient traits and species. Our results show notable discrepancies and low reliability for several biological and ecological traits such as microhabitat preference, omnivory, invertivory, rheophily, and limnophily. Least reliable traits were mainly categorical (rather than continuous) and established by expert judgment and without a clear definition or a common methodology. Interestingly, categorical traits such as rheophily or limnophily, which showed significantly lower reliability, concurrently showed higher data availability and use than continuously scaled traits. Such uncertainties in trait assignments could affect bioassessment and other ecological analyses. Species with smaller distributional ranges and those that have been described more recently, presented lower coverage and data availability in trait databases. We encourage further standardisation of fish trait measurement protocols to help improve the robust application of bioassessment indices and trait‐based approaches.

show abstract

Realizing the potential of trait‐based aquatic ecology: New tools and collaborative approaches

Cited by 42 publications

References 169 publications

Temperature‐dependence of minimum resource requirements alters competitive hierarchies in phytoplankton

Temperature‐dependence of minimum resource requirements alters competitive hierarchies in phytoplankton

Functional richness outperforms taxonomic richness in predicting ecosystem functioning in natural phytoplankton communities

Reliability analysis of fish traits reveals discrepancies among databases

Contact Info

Product

Resources

About