Aquatic ecologists face challenges in identifying the general rules of the functioning of ecosystems. A common framework, including freshwater, marine, benthic, and pelagic ecologists, is needed to bridge communication gaps and foster knowledge sharing. This framework should transcend local specificities and taxonomy in order to provide a common ground and shareable tools to address common scientific challenges. Here, we advocate the use of functional trait‐based approaches (FTBAs) for aquatic ecologists and propose concrete paths to go forward. Firstly, we propose to unify existing definitions in FTBAs to adopt a common language. Secondly, we list the numerous databases referencing functional traits for aquatic organisms. Thirdly, we present a synthesis on traditional as well as recent promising methods for the study of aquatic functional traits, including imaging and genomics. Finally, we conclude with a highlight on scientific challenges and promising venues for which FTBAs should foster opportunities for future research. By offering practical tools, our framework provides a clear path forward to the adoption of trait‐based approaches in aquatic ecology.
Dormancy (diapause) is a key life-history strategy of pelagic copepods that allows them to thrive in highly seasonal environments. Successful dormancy of copepodid stages requires the ability to store energy efficiently (for example as lipids) and to slow down the rate of mobilization of this capital during the dormant period. The physiology of lipids in copepods has been extensively reviewed; however, data about the energetics of dormancy are currently scattered throughout the literature. Thus, we conducted a meta-analysis comparing the metabolism of active and dormant copepods in 15 species that undergo dormancy as copepodids. Linear mixed-effects models showed that the metabolic rate of dormant copepods is about one-fourth of the values for actively growing copepods, a level that remains consistent across a large range of body size or environmental conditions. Based on these metabolic rates, we used a numerical modelling approach to predict dormancy duration as a function of body mass and ambient temperature, and to explain the observed range of body masses at the initiation of dormancy. Our numerical approach also provides explanations for inter-and intra-specific variability in life-history strategies, such as
Imaging techniques are increasingly used in ecology studies, producing vast quantities of data. Inferring functional traits from individual images can provide original insights on ecosystem processes. Morphological traits are, as other functional traits, individual characteristics influencing an organism's fitness. We measured them from in situ image data to study an Arctic zooplankton community during sea ice break-up. Morphological descriptors (e.g., area, lightness, complexity) were automatically measured on 28,000 individual copepod images from a high-resolution underwater camera deployed at more than 150 sampling sites across the ice-edge. A statisticallydefined morphological space allowed synthesizing morphological information into interpretable and continuous traits (size, opacity, and appendages visibility). This novel approach provides theoretical and methodological advantages because it gives access to both inter-and intra-specific variability by automatically analyzing a large dataset of individual images. The spatial distribution of morphological traits revealed that large copepods are associated with ice-covered waters, while open waters host smaller individuals. In those ice-free waters, copepods also seem to feed more actively, as suggested by the increased visibility of their appendages. These traits distributions are likely explained by bottom-up control: high phytoplankton concentrations in the well-lit open waters encourages individuals to actively feed and stimulates the development of small copepod stages. Furthermore, copepods located at the ice edge were opaquer, presumably because of full guts or an increase in red pigmentation. Our morphological trait-based approach revealed ecological patterns that would have been inaccessible otherwise, including color and posture variations of copepods associated with ice-edge environments in Arctic ecosystems. Functional traits are any features-morphological, physiological, etc-measurable at the individual-level and affecting the fitness of the organism (Violle et al. 2007). They can be classified according to the ecological function that they influence, such as feeding, growth, reproduction, and survival (Litchman et al. 2013). Trait-based approaches appeared in plant ecology in the 70s (Grime 1974) and stated being used by aquatic ecologists in the early 2000s (Willby et al. 2000; Usseglio-Polatera et al. 2000; Benedetti et al. 2016; Martini et al. (in press)). Trait-based analyses are relevant in community ecology because an individual's set of traits given environment determines its success (Violle et al. 2007). Ecological interactions (predation, mutualism, etc.) happen between individuals, not between taxonomic groups. Therefore, using trait composition can simplify the analysis of ecosystem complexity by focusing on a few characteristics transcending taxonomic distinctions and impacting ecological strategies (Litchman et al. 2013). By studying the composition and distribution of individual traits in an ecosystem, its structure and dominant proc...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.