Biological traits approaches in benthic marine ecology: Dead ends and new paths

Juan, Sílvia de; Bremner, Julie; Hewitt, Judi E.; Törnroos, Anna; Mangano, Maria Cristina; Thrush, Simon F.; Hinz, Hilmar

doi:10.1002/ece3.9001

Cited by 18 publications

(30 citation statements)

References 88 publications

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“…Yet, most trait-environment relationships, and most species-environment relationships were flat suggesting that polychaete assemblages are driven by processes other than abiotic ones, including neutral processes (Boyé et al 2019). However, the lack of contribution of other trait-environment relationships in our model could also be related to a mismatch between trait data, environmental data, and the ecological processes at play (Juan et al 2022). For instance, the physical coastal environment is highly dynamic; a feature that is only partially characterised by our environmental variables that summarise average climatological conditions (but not extreme events or annual/seasonal variability).…”

Section: Discussionmentioning

confidence: 87%

“…Our results provide some insights on trait-environment relationships but these contributions of functional ecology in jSDMs are likely limited by trait data quality and availability (Tyler et al . 2012 ; Juan et al . 2022).…”

Section: Discussionmentioning

confidence: 99%

“…2019). However, the lack of contribution of other trait-environment relationships in our model could also be related to a mismatch between trait data, environmental data, and the ecological processes at play (Juan et al . 2022).…”

Section: Discussionmentioning

confidence: 99%

“…Likewise, the list of available fuzzy-coded traits only partially captures species capacity to adapt to frequent disturbances or environmental variability (Violle et al . 2012 ; Juan et al . 2022).…”

Section: Discussionmentioning

confidence: 99%

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A Multifaceted Framework To Assess tradeoffs in Interpretability, Explanatory and Predictive Performances Of Alternative Joint Species Distribution Models

Violet

Boyé

Chevalier

et al. 2022

Preprint

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Joint Species Distribution Models (jSDM) are increasingly used to explain and predict biodiversity patterns. jSDMs account for species co-occurrence patterns and can include phylogeny or functional traits to better capture the processes shaping communities. Yet, several factors may limit or affect the interpretability and predictive ability of jSDMs : missing abiotic predictors, omitting ecologically-important species, or increasing the number of model parameters by adding phylogeny and/or trait information. We assessed how interpretability, explanatory and predictive power of jSDM varied across four alternative models focusing on 99 coastal benthic marine polychaete species: (1) a baseline jSDM with no additional information sources other than abiotic predictors and residual co-occurrence patterns, (2) a jSDM including phylogeny alone or (3) in combination with traits data and (4) a jSDM including monitoring information related to additional species sampled alongside the target assemblage (i.e. non-target species that are not of direct interest but potentially interact with the target assemblage). The four models fitted on both presence/absence and abundance data from a regional monitoring programme were assessed using complementary metrics. We compared performance at both species- and community-level, considering multiple facets of species responses and assemblage diversity. For both presence/absence and abundance data, all models displayed good and similar explanatory power but varied in their interpretability and predictive power. Considering trait data provides insights on species response along environmental gradients, which is a decisive element for model interpretability. Relative to the baseline model, predictive power increased by 26% when including data on additional species, whereas only marginal changes were detected for the two other models. These patterns are explained by changes in the species-environment relationships and residual co-occurrence patterns inferred by these models. Overall, this study highlights that adequate strategy to fit jSDM depends on data at hand, modelling objective and research question. To understand observed community space-time variability, adding phylogenetic or trait information is most effective. Inclusion of non-target species is however a better strategy to predict how the target species assemblage responds to environmental changes. Importantly, we provide a comprehensive toolbox for the comparative assessment of jSDM performance.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

A Multifaceted Framework To Assess tradeoffs in Interpretability, Explanatory and Predictive Performances Of Alternative Joint Species Distribution Models

Violet

Boyé

Chevalier

et al. 2022

Preprint

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show abstract

“…The resilience of a community, population, or species to external drivers depends to a large extend on the biological traits exhibited by the species and their mediating role on the survival of the species, populations, or communities under changing environmental conditions (Bremner et al 2006). A biological-traits approach to the assessment of species' vulnerability or resilience to external pressures has thus become popular in marine ecology over the past decades (Hinz et al 2021;de Juan et al 2022), and it is widely applied to understand species' distributions in relation with environmental variability and to develop ecological indicators as part of monitoring programs (Beauchard et al 2017;de Juan et al 2020).…”

Section: Introductionmentioning

confidence: 99%

A reproductive resilience index for pelagic fish in the southern Humboldt Current Large Marine Ecosystem

Ospina-Álvarez

Vásquez

Catalán

et al. 2022

Can. J. Fish. Aquat. Sci.

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Efforts to manage small and medium-sized pelagic fishes (SMPF) using traditional stock assessment methods are hampered by the elusive relationship between spawning stock biomass and recruitment. We propose to compute a Reproductive Resilience Index in three steps: 1) we selected 16 biological traits related to distinct aspects of SMPF reproductive biology and characterized by a continuous (e.g., growth rate) or ordinal variable (e.g., spawning site fidelity) scored from 1 to 5 (1 representing a low contribution of the trait to reproductive resilience); 2) an expert panel assigned the trait’s scores to five exploited species in the Southern Humboldt Current Large Marine Ecosystem; 3) a Bayesian Belief Network model (BBN) was used to estimate an RRI based on the combination of the traits’ scores. The BBN was used to explore environmental effects on the species’ RRI, as some reproductive traits can show intraspecies variability under external forces (e.g., fishing pressure). Through proving the RRI application to detect variability in species’ resilience at local time-series, we show how the resulting RRI can be interpreted by fishery managers to improve the current management of SMPF.

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Towards time and cost‐efficient habitat assessment: Challenges and opportunities for benthic ecology and management

Schenone,

Azhar,

Delmas

et al. 2023

Aquatic Conservation

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To the untrained eye, soft‐sediment habitats are often viewed as vast expanses of featureless sand and mud. With new technology, it is finally possible to begin to map the ecological heterogeneity of these ecosystems to reveal their importance for ecosystem service provision and open up new opportunities to manage their use and protect them. When compared with terrestrial or marine vegetated habitats, the characterization of unvegetated soft sediments still lacks rapid and cost‐effective practices that allow the direct collection of ecological data at multiple spatial and temporal scales facilitating direct relevance to conservation and management. New technologies that allow for the building of maps that incorporate multiple scales of heterogeneity also provide new ways of upscaling necessarily detailed and small‐scale process studies. The study of the relationship between benthic structure, biodiversity and ecosystem functioning can benefit from a range of established and novel techniques and creates new opportunities to empirically test generalities and predictions based on theory or small‐scale experimental studies. The capacity to map ecological changes rapidly and at scale and to link small‐scale experiments to landscapes uncovers new insights for seafloor conservation including rapid response to disturbance events, broad‐scale ecologically meaningful mapping and assessments of biodiversity–ecosystem function and biodiversity–ecosystem services relationships. As technology advances and becomes more accessible to all, it offers promising new avenues of research to expand our current capabilities, and the adoption of nested approaches, with a synergy of different samplings simultaneously covering several scales and resolutions, is likely to have the most benefit, supporting decision‐making with ecologically insightful data, as well as the timely assessment of the outcomes of conservation actions.

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Biological traits approaches in benthic marine ecology: Dead ends and new paths

Cited by 18 publications

References 88 publications

A Multifaceted Framework To Assess tradeoffs in Interpretability, Explanatory and Predictive Performances Of Alternative Joint Species Distribution Models

A Multifaceted Framework To Assess tradeoffs in Interpretability, Explanatory and Predictive Performances Of Alternative Joint Species Distribution Models

A reproductive resilience index for pelagic fish in the southern Humboldt Current Large Marine Ecosystem

Towards time and cost‐efficient habitat assessment: Challenges and opportunities for benthic ecology and management

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