Header

UZH-Logo

Maintenance Infos

Individual-Based Food Webs: Species Identity, Body Size and Sampling Effects


Woodward, Guy; Blanchard, Julia; Lauridsen, Rasmus B; Edwards, Francois K; Jones, J Iwan; Figueroa, David; Warren, Philip H; Petchey, Owen L (2010). Individual-Based Food Webs: Species Identity, Body Size and Sampling Effects. Advances in Ecological Research, 43:211-266.

Abstract

The study of food webs has been a central theme within ecology for decades, and their structure and dynamics have been used to assess a range of key properties of communities (e.g. complexity–stability relationships) and ecosystems (e.g. fluxes of energy and nutrients). However, many food web parameters are sensitive to sampling effort, which is rarely considered, and further, most studies have used either species- or size-averaged data for both nodes and links, rather than individual-based data, which is the level of organisation at which trophic interactions occur. This practice of aggregating data hides a considerable amount of biologically meaningful variation and could, together with potential sampling effects, create methodological artefacts. New individual-based approaches could improve our understanding of, and ability to predict, food web structure and dynamics, particularly if they are derived from simple metabolic and foraging constraints. We explored the effect of species-averaging in four highly-resolved individual-based aquatic food webs (Broadstone Stream, the Afon Hirnant, Tadnoll Brook and the Celtic Sea) and found that it obscured structural regularities resulting from intraspecific size variation. The individual-based approach provided clearer insights into seasonal and ontogenetic shifts, highlighting the importance of the temporal component of size-structuring in ecological networks. An extension of the Allometric Diet Breadth Model predicted the structure of the empirical food webs almost twice as accurately as the equivalent species-based webs, with the best-fitting model predicting 83% of the links correctly in the Broadstone Stream size-based web, and the few mismatches between the model and data were explained largely by sampling effects. Our results highlight the need for theoretical explanations to correspond closely with methods of data collection and aggregation, which is the exception rather than the rule at present. We suggest how this situation can be improved by including individual-level data and more explicit information on sampling effort when constructing food webs in future studies.

Abstract

The study of food webs has been a central theme within ecology for decades, and their structure and dynamics have been used to assess a range of key properties of communities (e.g. complexity–stability relationships) and ecosystems (e.g. fluxes of energy and nutrients). However, many food web parameters are sensitive to sampling effort, which is rarely considered, and further, most studies have used either species- or size-averaged data for both nodes and links, rather than individual-based data, which is the level of organisation at which trophic interactions occur. This practice of aggregating data hides a considerable amount of biologically meaningful variation and could, together with potential sampling effects, create methodological artefacts. New individual-based approaches could improve our understanding of, and ability to predict, food web structure and dynamics, particularly if they are derived from simple metabolic and foraging constraints. We explored the effect of species-averaging in four highly-resolved individual-based aquatic food webs (Broadstone Stream, the Afon Hirnant, Tadnoll Brook and the Celtic Sea) and found that it obscured structural regularities resulting from intraspecific size variation. The individual-based approach provided clearer insights into seasonal and ontogenetic shifts, highlighting the importance of the temporal component of size-structuring in ecological networks. An extension of the Allometric Diet Breadth Model predicted the structure of the empirical food webs almost twice as accurately as the equivalent species-based webs, with the best-fitting model predicting 83% of the links correctly in the Broadstone Stream size-based web, and the few mismatches between the model and data were explained largely by sampling effects. Our results highlight the need for theoretical explanations to correspond closely with methods of data collection and aggregation, which is the exception rather than the rule at present. We suggest how this situation can be improved by including individual-level data and more explicit information on sampling effort when constructing food webs in future studies.

Statistics

Citations

51 citations in Web of Science®
57 citations in Scopus®
Google Scholar™

Altmetrics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Language:English
Date:2010
Deposited On:11 Jul 2012 15:05
Last Modified:05 Apr 2016 15:46
Publisher:Elsevier
ISSN:0065-2504
Publisher DOI:https://doi.org/10.1016/B978-0-12-385005-8.00006-X
Other Identification Number:Accession Number: WOS:000286800200007

Download

Full text not available from this repository.
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations