🎤 ref drop

index.qmd

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 At the heart of modern biodiversity science are a set of concepts and theories about biodiversity, stability, and function [@loreauBiodiversityEcosystemStability2013]. These relate to the abundance, distribution, and services that biodiversity provides, and how biodiversity – as an interconnected set of species – responds to multiple stressors. Documenting interactions between and among species is thus one of the fundamental building blocks of community ecology, providing a powerful abstraction and platform for mathematical and statistical modelling of biodiversity in order to make predictions, mitigate threats, and manage services [@windsorUsingEcologicalNetworks2023]. Such network representations of biodiversity are increasingly argued to be an asset to understanding and predicting the abundance, distribution, dynamics, and services provided by multiple species facing multiple stressors. However, there is a growing discourse around limitations to the interpretation and applied use of networks [@dormannRisePossibleFall2023; @bluthgenWhyNetworkAnalysis2010], primarily as the result of shortcomings regarding their conceptualisation [@bluthgenCriticalEvaluationNetwork2024].
 
-Because an 'interaction network' can be defined and conceptualised in many ways, each method will be embed different assumptions about the determinants of interactions, and characterise patterns and process at different scales, which will ultimately influence the nature and scope of inference [@proulxNetworkThinkingEcology2005]. The different ways in which a network can be represented is the result of *how* the network is constructed, which represents an intersection of the data used to construct the network and the underlying theory as to what drives the occurrence of interactions between species. Although there have been extensive discussions as to the the challenges relating to the scale and nature of data collection/observation [*e.g.,* @bluthgenCriticalEvaluationNetwork2024; @brimacombeShortcomingsReusingSpecies2023; @moulatletScalingTrophicSpecialization2024; @pringleResolvingFoodWebStructure2020; @polisComplexTrophicInteractions1991; @saberskiImpactDataResolution2024] we still lack a clear framework as to how different data sources result in networks that are fundamentally different [@sec-representation].
+Because an 'interaction network' can be defined and conceptualised in many ways, each method will be embed different assumptions about the determinants of interactions, and characterise patterns and process at different scales, which will ultimately influence the nature and scope of inference [@proulxNetworkThinkingEcology2005]. The different ways in which a network can be represented is the result of *how* the network is constructed, which represents an intersection of the data used to construct the network and the underlying theory as to what drives the occurrence of interactions between species. Although there have been extensive discussions as to the the challenges relating to the scale and nature of data collection/observation [*e.g.,* @bluthgenCriticalEvaluationNetwork2024; @brimacombeShortcomingsReusingSpecies2023; @brimacombePublicationdrivenConsistencyFood2024; @moulatletScalingTrophicSpecialization2024; @pringleResolvingFoodWebStructure2020; @polisComplexTrophicInteractions1991; @saberskiImpactDataResolution2024] we still lack a clear framework as to how different data sources result in networks that are fundamentally different [@sec-representation].
 
 In this perspective we aim to provide an overview of the different **food web** representations, particularly how these relate to the terminology used to define a food web, and how this is influenced by both the processes that determine interactions [@sec-process], as well as how this relates to the way in which we construct the resulting networks [@sec-construct]. This allows us to deliver an overview of fundamental questions in ecology that we think can benefit from network thinking and a proposal that such thinking can accelerate our capacity to predict the impact of multiple stressors on biodiverse communities. Specifically, we finish this perspective with an overview of fundamental questions in ecology that we think can benefit from network thinking and a proposal that such thinking can accelerate our capacity to predict the impact of change on biodiverse communities.
 

references.bib

@@ -491,6 +491,25 @@ @article{brimacombeInferredSeasonalInteraction2021
   file = {/Users/tanyastrydom/Zotero/storage/JXBQV7IY/Brimacombe et al. - 2021 - Inferred seasonal interaction rewiring of a freshw.pdf}
 }
 
+@article{brimacombePublicationdrivenConsistencyFood2024,
+  title = {Publication-Driven Consistency in Food Web Structures: {{Implications}} for Comparative Ecology},
+  shorttitle = {Publication-Driven Consistency in Food Web Structures},
+  author = {Brimacombe, Chris and Bodner, Korryn and Gravel, Dominique and Leroux, Shawn J. and Poisot, Timoth{\'e}e and Fortin, Marie-Jos{\'e}e},
+  year = {2024},
+  journal = {Ecology},
+  volume = {n/a},
+  number = {n/a},
+  pages = {e4467},
+  issn = {1939-9170},
+  doi = {10.1002/ecy.4467},
+  urldate = {2024-11-25},
+  abstract = {Large collections of freely available food webs are commonly reused by researchers to infer how biological or environmental factors influence the structure of ecological communities. Although reusing food webs expands sample sizes for community analysis, this practice also has significant drawbacks. As food webs are meticulously crafted by researchers for their own specific research endeavors and resulting publications (i.e., books and scientific articles), the structure of these webs inherently reflects the unique methodologies and protocols of their source publications. Consequently, combining food webs sourced from different publications without accounting for discrepancies that influence network structure may be problematic. Here, we investigate the determinants of structure in freely available food webs sourced from different publications, examining potential disparities that could hinder their effective comparison. Specifically, we quantify structural similarity across 274 commonly reused webs sourced from 105 publications using a subgraph technique. Surprisingly, we found no increased structural similarity between webs from the same ecosystem nor webs built using similar network construction methodologies. Yet, webs sourced from the same publication were very structurally similar with this degree of similarity increasing over time. As webs sourced from the same publication are typically sampled, constructed, and/or exposed to similar biological and environmental factors, publications likely holistically drive their own webs' structure to be similar. Our findings demonstrate the large effect that publications have on the structure of their own webs, which stymies inference when comparing the structure of webs sourced from different publications. We conclude by proposing different approaches that may be useful for reducing these publication-related structural issues.},
+  copyright = {{\copyright} 2024 The Author(s). Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.},
+  langid = {english},
+  keywords = {communities,methodology,networks,sampling,species interactions,subgraphs,trophic relationships},
+  file = {/Users/tanyastrydom/Zotero/storage/U2RBHXSU/Brimacombe et al. - Publication-driven consistency in food web structu.pdf;/Users/tanyastrydom/Zotero/storage/AMWU6P7I/ecy.html}
+}
+
 @article{brimacombeShortcomingsReusingSpecies2023,
   title = {Shortcomings of Reusing Species Interaction Networks Created by Different Sets of Researchers},
   author = {Brimacombe, Chris and Bodner, Korryn and {Michalska-Smith}, Matthew and Poisot, Timoth{\'e}e and Fortin, Marie-Jos{\'e}e},