A General Model for Food Web Structure

Allesina, Stefano; Alonso, David; Pascual, Mercedes

doi:10.1126/science.1156269

Cited by 248 publications

(334 citation statements)

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“…By developing a mathematical theory for a class of models that encompasses the one proposed by Rossberg et al (2010a), this paper adds to a growing suite of food-web models which are well-understood analytically, such as the cascade model (Cohen et al, 1990), the niche model (Camacho et al, 2002;Allesina et al, 2008), the speciation model (Rossberg et al, 2006b), or the matching model (Rossberg, 2008). With a large number of analytically tractable foodweb models to work with, we expect that the mechanisms behind the emergence of more aspects of food-web structure will be pinned down in the years to come.…”

Section: Food-web Intervality With Weakly Focused Consumersmentioning

confidence: 99%

Rigorous conditions for food-web intervality in high-dimensional trophic niche spaces

2010

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Food webs represent trophic (feeding) interactions in ecosystems. Since the late 1970s, it has been recognized that food-webs have a surprisingly close relationship to interval graphs. One interpretation of food-web intervality is that trophic niche space is low-dimensional, meaning that the trophic character of a species can be expressed by a single or at most a few quantitative traits. In a companion paper we demonstrated, by simulating a minimal food-web model, that food webs are also expected to be interval when niche-space is high-dimensional. Here we characterize the fundamental mechanisms underlying this phenomenon by proving a set of rigorous conditions for food-web intervality in high-dimensional niche spaces. Our results apply to a large class of food-web models, including the special case previously studied numerically.

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Section: Food-web Intervality With Weakly Focused Consumersmentioning

confidence: 99%

Rigorous conditions for food-web intervality in high-dimensional trophic niche spaces

2010

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“…Here we assume body size constraints lead to forbidden links [13,4,135]. To assess the role of these constraints in shaping empirical food-webs, we compared two probabilistic food-web models: one that does not include body size constraints (Model 1), and one that retains the same number and structure of forbidden links as the respective empirical food-web (Model 2).…”

Section: Body Size Constraints and Ecological Implicationsmentioning

confidence: 99%

Dedication. Acknowledgments

2011

The Acquisition of German

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xvii Dedication xixAcknowledgments xx . See panel C. for a scenario where one prey is preferred over another. C. A tri-trophic system, where a top-predator consumes a meso-predator, which in turn consumes two prey. The sizes of the nodes denote relative abundance, and the thickness of the arrows denote the magnitude of the biomass flow. The top-predator in the leftmost network is relatively abundant, depressing the meso-predator population, thereby limiting the meso-predator's e↵ect on the two prey populations. The two rightmost networks (boxed) have reduced top-predator populations. In both cases, the meso-predator has greater abundance due to decreased predation pressure. However, in one scenario, both prey are preferred equally, resulting in apparent competition dynamics. In the second scenario, one prey is preferred over another, resulting in an asymmetric cascade. Such preferences could result from specific anatomical constraints of the meso-predator, a scenario explored in Chapter 4. C 1 and C 2 , and 4 prey: r 1 r 4 ) is represented by both pairwise interaction distributions for each link, and a network-level interaction distribution for the system. Link thickness represents the median link-strength, shown with the vertical bar in each pairwise interaction distribution. B-C. Both model food-webs X and Y have link-strengths drawn from the NLID. In model food-web X, the weights are distributed similar to the median weights of the empirical web (i.e. equivalent structure), but they are distributed di↵erently among nodes (i.e. alternative interactions). In model Y , the weight structure is di↵erent than that of the empirical web (i.e. alternative structure), and necessarily, the distribution of weights among nodes di↵ers as well (i.e. alternative interactions). Dotted nodes indicate those with link-strengths that di↵er from the median link-strengths of the empirical food-web. D-F. Given a single niche axis based on a continuous resource trait (e.g. body size) where prey are ranked from r 1 to r 4 , distributions of resource use are shown for the two consumers. Representations of dietary overlap illustrate higher similarity in diet between predators of the empirical system and model X, whereas the consumers in model Y have little dietary overlap, despite sharing the same NLID. 5 A-C. Sensitivity analyses of the Saskatchewan, Amboseli, and Lake Naivasha food-web ensembles, respectively. Similarity values for each cuto↵ (s i ) for Model 2 are on the y-axis, and the x-axis ranges from a lower standard deviation (SD) than the empirical SD to a higher SD (such that the empirical SD is central to the range; stippled vertical line). The colored data points represent the median similarity indices for each cuto↵ value (legend), while the top and bottom whiskers denote the 25 th and 75 th percentiles, respectively. The underlined values mark the standard deviation corresponding to the highest average similarity across cuto↵ values. For all systems, the highest average similarity is close to or exactly matches ...

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“…The cascade model was one of the first topological explanations for food web structure (Lawton and Warren, 1988 (Allesina and Pascual, 2009;Allesina et al, 2008;Cattin et al, 2004;Cohen et al, 1990;Rohr et al, 2010;Stouffer et al, 2005;Warren, 1996;Williams and Martinez, 2000). Their capacity to predict a variety of food web patterns has been thoroughly explored.…”

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confidence: 99%

“…One major driver of this development and refinement has been the quantitative assessment of how well models reproduce the structure of real food webs (Allesina et al, 2008;Cattin et al, 2004;Stouffer et al, 2005;Williams and Martinez, 2000;Williams and Martinez, 2008). Such quantitative comparisons usually involved measuring how accurately a set of structural properties are predicted, for example proportions of basal, intermediate, and…”

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confidence: 99%