Trait‐based approach using in situ copepod images reveals contrasting ecological patterns across an Arctic ice melt zone

Abstract

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...

Marine snow morphology illuminates the evolution of phytoplankton blooms and determines their subsequent vertical export

“…Developing new algorithms calculating sinking speed by considering not only size but also image-derived porosity or density would be a considerable improvement in estimating flux from in situ images, which, for the moment, solely relies on size 24,30 ). Furthermore, we consider that similar to what was recognized for plankton 79,81,82 , the morphological trait-based approach should be informative and complementary to other approaches to assess and model a variety of ocean processes. Moreover, one important advantage of the classification we proposed is that it is based on deterministic morphological features, easily assessed and compared across systems.…”

“…With the increasing number of in situ imaging technologies, there is an urgent need for classification methods for marine particles and plankton. Plankton classification has been developed in numerous studies, both for the development of classification algorithms 29,[73][74][75] and for retrieving ecological dynamics from imaging datasets [76][77][78][79] . In contrast, marine snow classification has not been addressed quantitatively, although analysis of marine snow dynamics remains fundamental for building an understanding of trophic interactions and carbon sequestration.…”

Processes controlling aggregate formation and distribution during the Arctic phytoplankton spring bloom in Baffin Bay

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“…9(1) page 4 of 19 Toullec et al: Aggregates formation in the Baffin Bay during phytoplankton spring bloom by only a few copepod species such as Calanus glacialis and Calanus finmarchicus, Calanus hyperboreus, Metridia longa, and Pseudocalanus spp. adults (Vilgrain et al, 2021).…”

Modelling the biogeographic boundary shift of Calanus finmarchicus reveals drivers of Arctic Atlantification by subarctic zooplankton

“…Mechanistic approaches that estimate an organism's energetic budget at a fine temporal resolution and that incorporate the Arctic's extreme light environment, will have an important, complementary role in predicting the success of subarctic species at Arctic latitudes (Ljungstrom et al, 2021). Novel observation methods (Vilgrain et al, 2021) and increased sampling within sea-ice environments will also be important in overcoming data limitations in the Arctic and for parameterizing and validating model outputs.…”