A neutral-niche theory of nestedness in mutualistic networks

Krishna, Abhay; Guimarães, Paulo R.; Jordano, Pedro; Bascompte, Jordi

doi:10.1111/j.0030-1299.2008.16540.x

Cited by 94 publications

(176 citation statements)

References 43 publications

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“…Taken together, these results suggest the ecological and/or coevolutionary processes that shape interaction patterns might be similar for systems with similar levels of intimacy despite these systems representing antagonisms or mutualisms. Nestedness partially emerges due to differences in population abundances among potential partners [6], probably a key component shaping both mutualisms and antagonisms with low intimacy. In addition, it has been proposed that grazing and free-living mutualisms might be much alike in the evolutionary processes shaping specialization [11], whereas symbiotic mutualisms might be similar to symbiotic antagonisms in the evolutionary processes shaping their patterns of interaction [33].…”

Section: Discussionmentioning

confidence: 99%

“…We expected that highly intimate interactions would have higher modularity due to different factors associated with the phenotypic integration among partners, including strong phylogenetic constraints and coevolution favouring specialization [9,23]. In contrast, high nestedness and low modularity are expected for interactions with low intimacy, in which differences in abundance [6] and body size [14] are hypothesized to play a key role. Second, the approach based on food web models allowed us to investigate whether the assembly of two-mode antagonistic networks varies across distinct levels of interaction intimacy.…”

Section: Introductionmentioning

confidence: 99%

“…Through these efforts, studies focusing on the biological attributes shaping species interactions have distinguished the key role of a few species traits in shaping patterns of interaction within ecological networks. These traits include abundance [5,6], interaction type [7] and interaction intimacy, the degree of biological integration among interacting individuals of different species [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Interaction intimacy organizes networks of antagonistic interactions in different ways

Pires

Guimarães

2013

J. R. Soc. Interface.

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Interaction intimacy, the degree of biological integration between interacting individuals, shapes the ecology and evolution of species interactions. A major question in ecology is whether interaction intimacy also shapes the way interactions are organized within communities. We combined analyses of network structure and food web models to test the role of interaction intimacy in determining patterns of antagonistic interactions, such as hostparasite, predator -prey and plant -herbivore interactions. Networks describing interactions with low intimacy were more connected, more nested and less modular than high-intimacy networks. Moreover, the performance of the models differed across networks with different levels of intimacy. All models reproduced well low-intimacy networks, whereas the more elaborate models were also capable of reproducing networks depicting interactions with higher levels of intimacy. Our results indicate the key role of interaction intimacy in organizing antagonisms, suggesting that greater interaction intimacy might be associated with greater complexity in the assembly rules shaping ecological networks.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interaction intimacy organizes networks of antagonistic interactions in different ways

Pires

Guimarães

2013

J. R. Soc. Interface.

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“…Accordingly, the system operates under conditions imposed by interaction neutrality (consumption in proportion to prey abundance) [74,92], as opposed to ultrageneralism (consumption in proportion to the number of prey available to the consumer).…”

Section: Incorporating Biological Informationmentioning

confidence: 99%

“…Alternatively, if p(✓) represents measures of prey availability to a consumer and p(y|✓) is the likelihood shaped by isotopic (dietary) data, it is unclear what p(✓|y) describes, unless it is assumed that availability is directly correlated with diet. Prey availability would be an indirect measure of diet if species interactions follow neutral dynamics [74,92]. For predator-prey interactions that are influenced by non-neutral, prey-specific ecological factors such as predator preference, prey defense, or habitat variability, measurements of prey availability cannot lend themselves to indiscriminate use as prior distributions as they no longer have a one-to-one relationship with their contribution to a consumer's diet.…”

Section: Post-hoc Adjustments Vs the Formulation Of Prior Distributionsmentioning

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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Relative impacts of environmental variation and evolutionary history on the nestedness and modularity of tree–herbivore networks

Robinson

Hauzy

Loeuille

et al. 2015

Ecology and Evolution

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Nestedness and modularity are measures of ecological networks whose causative effects are little understood. We analyzed antagonistic plant–herbivore bipartite networks using common gardens in two contrasting environments comprised of aspen trees with differing evolutionary histories of defence against herbivores. These networks were tightly connected owing to a high level of specialization of arthropod herbivores that spend a large proportion of the life cycle on aspen. The gardens were separated by ten degrees of latitude with resultant differences in abiotic conditions. We evaluated network metrics and reported similar connectance between gardens but greater numbers of links per species in the northern common garden. Interaction matrices revealed clear nestedness, indicating subsetting of the bipartite interactions into specialist divisions, in both the environmental and evolutionary aspen groups, although nestedness values were only significant in the northern garden. Variation in plant vulnerability, measured as the frequency of herbivore specialization in the aspen population, was significantly partitioned by environment (common garden) but not by evolutionary origin of the aspens. Significant values of modularity were observed in all network matrices. Trait-matching indicated that growth traits, leaf morphology, and phenolic metabolites affected modular structure in both the garden and evolutionary groups, whereas extra-floral nectaries had little influence. Further examination of module configuration revealed that plant vulnerability explained considerable variance in web structure. The contrasting conditions between the two gardens resulted in bottom-up effects of the environment, which most strongly influenced the overall network architecture, however, the aspen groups with dissimilar evolutionary history also showed contrasting degrees of nestedness and modularity. Our research therefore shows that, while evolution does affect the structure of aspen–herbivore bipartite networks, the role of environmental variations is a dominant constraint.

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A neutral-niche theory of nestedness in mutualistic networks

Cited by 94 publications

References 43 publications

Interaction intimacy organizes networks of antagonistic interactions in different ways

Interaction intimacy organizes networks of antagonistic interactions in different ways

Dedication. Acknowledgments

Relative impacts of environmental variation and evolutionary history on the nestedness and modularity of tree–herbivore networks

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