2009
DOI: 10.1007/s10021-009-9297-6
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Quantifying Food Web Flows Using Linear Inverse Models

Abstract: The quantitative mapping of food web flows based on empirical data is a crucial yet difficult task in ecology. The difficulty arises from the under-sampling of food webs, because most data sets are incomplete and uncertain. In this article, we review methods to quantify food web flows based on empirical data using linear inverse models (LIM). The food web in a LIM is described as a linear function of its flows, which are estimated from empirical data by inverse modeling. The under-sampling of food webs implies… Show more

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Cited by 122 publications
(120 citation statements)
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“…Methods used for inverse modelling include Bayesian inference, often used with the Markov chain Monte Carlo technique (Press 2012;Gelman et al 2014) and Frequentist inference (Press 2012). Different software packages for implementation of these methods exist (Vézina and Platt 1988;Reichert 1994;Lunn et al 2000;Van Oevelen et al 2010;Doherty 2015).…”
Section: Introductionmentioning
confidence: 99%
“…Methods used for inverse modelling include Bayesian inference, often used with the Markov chain Monte Carlo technique (Press 2012;Gelman et al 2014) and Frequentist inference (Press 2012). Different software packages for implementation of these methods exist (Vézina and Platt 1988;Reichert 1994;Lunn et al 2000;Van Oevelen et al 2010;Doherty 2015).…”
Section: Introductionmentioning
confidence: 99%
“…The community changes of different organisms can indirectly cause changes in the pathways and magnitude of material flows in food webs. These flows have been considered to reveal important features and functions of natural food webs Van Oevelen et al, 2010).…”
Section: Introductionmentioning
confidence: 99%
“…To do this effectively, Network Ecology will need to continue to develop methods for model construction and overcome sampling and data limitations (Polis 1991). Linear inverse modeling is one tool to assist with this (Vézina and Pace, 1994;van Oevelen et al 2010). Network Ecology will also need to improve its ability to quantify statistical uncertainty in network models and related implications for analysis and conclusions (Borrett and Osidele, 2007;Kones et al, 2009;Kaufman and Borrett, 2010).…”
Section: Frontiers Of Network Ecologymentioning
confidence: 99%