Ecosystem functioning and functional approaches on marine macrobenthic fauna: A research synthesis towards a global consensus

Lam-Gordillo, Orlando; Baring, Ryan; Dittmann, Sabine

doi:10.1016/j.ecolind.2020.106379

Cited by 59 publications

(35 citation statements)

References 86 publications

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“…Functional approaches have become a requisite for studying ecosystem functioning (e.g., Bolam et al, 2016;Bremner et al, 2003Bremner et al, , 2006Degen et al, 2018), yet, functional assessments remain hindered by a lack of taxa-specific trait data (Lam-Gordillo et al, 2020). The SAMT database is available for easy downloading, sharing, and using.…”

Section: Discussionmentioning

confidence: 99%

“…Selection of traits was based on the most commonly used traits for assessing macrobenthic fauna (Lam-Gordillo et al, 2020), ensuring that the selected biological traits could be compared across studies (Degen et al, 2018), geographical areas (Bremner et al, 2006), and are applicable to most benthic taxa (Costello et al, 2015). The selected traits capture the four subject areas "Biology," "Habitat," "Lifehistory," and "Larval" introduced by Costello et al (2015) to structure trait categories.…”

Section: Selection Of Traitsmentioning

confidence: 99%

“…Trait‐based approaches have become topical in ecological research for understanding the relationship between species (biodiversity) and ecosystem functioning, ecosystem processes, ecosystem services, or responses to anthropogenic disturbances (Bolam et al., 2016; Bremner et al., 2003, 2006; Cano‐Barbcil et al., 2019; Weiss & Ray, 2019). Trait‐based approaches are also used to measure several functional indices (e.g., functional diversity: functional divergence, functional redundancy, and functional richness) and can be used to perform analyses across species pools from distinct geographical areas (Degen & Faulwetter, 2019; Lam‐Gordillo et al., 2020; Mason et al., 2005; Mouchet et al., 2010). Functional approaches are based on different subsets of traits (i.e., species characteristics) as a proxy of ecosystem functioning (Bremner, 2008; Bremner et al., 2006).…”

Section: Introductionmentioning

confidence: 99%

“…Traits can be defined as properties of organisms that can be measured, usually at the organism level and used comparatively across species. Examples of traits are the life history, morphology, physiology, and behavior characteristics that species can exhibit (Bremner et al., 2006; Degen et al., 2018; Lam‐Gordillo et al., 2020; Petchey & Gaston, 2006; Reiss et al., 2009). Selection of traits is flexible and should include an appropriate range of traits relevant to the specific research question, that is, capture the characteristics of organism for the ecosystem processes under investigation (Beauchard et al., 2017; Costello et al., 2015; Lam‐Gordillo et al., 2020; Petchey & Gaston, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…Throughout the literature, several traits have been proposed to assess the relationship between macrobenthic fauna and ecosystem functioning; however, there are no standardized definitions for traits. In addition, the deficiency on species trait information, data accessibility, and different levels of taxonomic resolution make the selection and use of traits even harder (Lam-Gordillo et al, 2020).…”

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confidence: 99%

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Establishing the South Australian Macrobenthic Traits (SAMT) database: A trait classification for functional assessments

Lam-Gordillo

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Dittmann

2020

Ecology and Evolution

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Section: Discussionmentioning

confidence: 99%

Section: Selection Of Traitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

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Establishing the South Australian Macrobenthic Traits (SAMT) database: A trait classification for functional assessments

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Dittmann

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Ecology and Evolution

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Collaboration and term usage dynamics in agricultural buffer strip research: Research weaving

Young,

Lagisz,

Callaghan

et al. 2024

Ecol Sol and Evidence

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Systematic maps are used to comprehensively gather and describe the literature on a topic, which is often defined by policy and practice relevance and stakeholder input, identifying trends and gaps in research. Bibliometric methods elucidate the connections between publications, for example, providing information about collaboration in research communities. Research weaving combines these approaches to produce a comprehensive view of research activity on a well‐defined research area. In this paper, we conduct and describe a bibliometric analysis on a previously published systematic map on the functional roles of buffer strips in agricultural fields. Among other findings, the original systematic map found a paucity of studies addressing multiple functional roles and a huge variation in terminology related to buffer strips. We used research weaving to deepen our understanding of these findings and shed light on collaboration within and among the research communities contributing knowledge to this field. Of the 1019 papers originally included in the systematic map, 930 were identified in Lens.org and used for subsequent analyses. Co‐authorship and bibliographic coupling networks identified distinct research communities, defined by geography, subdiscipline and characteristic usage of buffer strip terminology. Topic modelling provided further information about these subcommunities and aligned with manually extracted information about the studies' focus on functional roles, indicating potential utility for screening of records in large systematic maps. Practical Implication: We demonstrate that research weaving methods add insights in support of and in addition to the original systematic map. We provide a methodological approach and discuss limitations related to applying bibliometric analyses to a previously published systematic map. We demonstrate the feasibility of this approach and its ability to enhance and enrich the findings gained from conventional systematic mapping techniques.

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

Juan

Bremner

Hewitt

et al. 2022

Ecology and Evolution

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Biological traits analysis (BTA) links community structure to both ecological functions and response to environmental drivers through species’ attributes. In consequence, it has become a popular approach in marine benthic studies. However, BTA will reach a dead end if the scientific community does not acknowledge its current shortcomings and limitations: (a) uncertainties related to data origins and a lack of standardized reporting of trait information; (b) knowledge gaps on the role of multiple interacting traits on driving the organisms’ responses to environmental variability; (c) knowledge gaps regarding the mechanistic links between traits and functions; (d) a weak focus on the spatial and temporal variability that is inherent to the trait expression of species; and, last but not least, (e) the large reliance on expert knowledge due to an enormous knowledge gap on the basic ecology of many benthic species. BTA will only reach its full potential if the scientific community is able to standardize and unify the reporting and storage of traits data and reconsider the importance of baseline observational and experimental studies to fill knowledge gaps on the mechanistic links between biological traits, functions, and environmental variability. This challenge could be assisted by embracing new technological advances in marine monitoring, such as underwater camera technology and artificial intelligence, and making use of advanced statistical approaches that consider the interactive nature and spatio‐temporal variability of biological systems. The scientific community has to abandon some dead ends and explore new paths that will improve our understanding of individual species, traits, and the functioning of benthic ecosystems.

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Ecosystem functioning and functional approaches on marine macrobenthic fauna: A research synthesis towards a global consensus

Cited by 59 publications

References 86 publications

Establishing the South Australian Macrobenthic Traits (SAMT) database: A trait classification for functional assessments

Establishing the South Australian Macrobenthic Traits (SAMT) database: A trait classification for functional assessments

Collaboration and term usage dynamics in agricultural buffer strip research: Research weaving

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

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