scholarly journals Real-world Interaction Networks Buffer Impact of Small Evolutionary Shifts On Biodiversity

2014 ◽  
Author(s):  
Gabriel E Leventhal ◽  
Liyu Wang ◽  
Roger D Kouyos
Keyword(s):  
Real World ◽  
Environmental Changes ◽  
Interaction Network ◽  
Species Interaction ◽  
Interaction Networks ◽  
Community Diversity ◽  
Ecological Communities ◽  
Interaction Structure ◽  
Evolutionary Changes ◽  
Biodiversity Maintenance

Biodiversity maintenance and community evolution depend on the species interaction network. The "diversity-stability debate" has revealed that the complex interaction structure within real-world ecosystems determines how ecological communities respond to environmental changes, but can have opposite effects depending on the community type. Here we quantify the influence of shifts on community diversity and stability at both the species level and the community level. We use interaction networks from 19 real-world mutualistic communities and simulate shifts to antagonism. We demonstrate that both the placement of the shifting species in the community, as well as the structure of the interaction network as a whole contribute to stability and diversity maintenance under shifts. Our results suggest that the interaction structure of natural communities generally enhances community robustness against small ecological and evolutionary changes, but exacerbates the consequences of large changes.

scholarly journals Effect of Localization on the Stability of Mutualistic Ecological Networks

2015 ◽  
Author(s):  
Samir Suweis ◽  
Jacopo Grilli ◽  
Jayanth Banavar ◽  
Stefano Allesina ◽  
Amos Maritan
Keyword(s):  
Species Abundance ◽  
Interaction Network ◽  
Species Interaction ◽  
Interaction Networks ◽  
Ecological Communities ◽  
Weighted Degree ◽  
Perturbation Propagation ◽  
The Stability ◽  
The Impact ◽  
The Relationship

The relationships between the core-periphery architecture of the species interaction network and the mechanisms ensuring the stability in mutualistic ecological communities are still unclear. In particular, most studies have focused their attention on asymptotic resilience or persistence, neglecting how perturbations propagate through the system. Here we develop a theoretical framework to evaluate the relationship between architecture of the interaction networks and the impact of perturbations by studying localization, a measure describing the ability of the perturbation to propagate through the network. We show that mutualistic ecological communities are localized, and localization reduces perturbation propagation and attenuates its impact on species abundance. Localization depends on the topology of the interaction networks, and it positively correlates with the variance of the weighted degree distribution, a signature of the network topological hetereogenity. Our results provide a different perspective on the interplay between the architecture of interaction networks in mutualistic communities and their stability.

scholarly journals Dynamic population stage structure due to juvenile–adult asymmetry stabilizes complex ecological communities

2021 ◽  
Vol 118 (21) ◽  
pp. e2023709118
Author(s):  
André M. de Roos
Keyword(s):  
Self Regulation ◽  
Interaction Network ◽  
Population Level ◽  
Stage Structure ◽  
Current Theory ◽  
Species Interaction ◽  
Interaction Matrix ◽  
Foraging Efficiency ◽  
Ecological Communities ◽  
The Stability

Natural ecological communities are diverse, complex, and often surprisingly stable, but the mechanisms underlying their stability remain a theoretical enigma. Interactions such as competition and predation presumably structure communities, yet theory predicts that complex communities are stable only when species growth rates are mostly limited by intraspecific self-regulation rather than by interactions with resources, competitors, and predators. Current theory, however, considers only the network topology of population-level interactions between species and ignores within-population differences, such as between juvenile and adult individuals. Here, using model simulations and analysis, I show that including commonly observed differences in vulnerability to predation and foraging efficiency between juvenile and adult individuals results in up to 10 times larger, more complex communities than observed in simulations without population stage structure. These diverse communities are stable or fluctuate with limited amplitude, although in the model only a single basal species is self-regulated, and the population-level interaction network is highly connected. Analysis of the species interaction matrix predicts the simulated communities to be unstable but for the interaction with the population-structure subsystem, which completely cancels out these instabilities through dynamic changes in population stage structure. Common differences between juveniles and adults and fluctuations in their relative abundance may hence have a decisive influence on the stability of complex natural communities and their vulnerability when environmental conditions change. To explain community persistence, it may not be sufficient to consider only the network of interactions between the constituting species.

scholarly journals Genetics-based interactions of foundation species affect community diversity, stability and network structure

2017 ◽  
Vol 284 (1854) ◽  
pp. 20162703 ◽  
Author(s):  
Arthur R. Keith ◽  
Joseph K. Bailey ◽  
Matthew K. Lau ◽  
Thomas G. Whitham
Keyword(s):  
Network Structure ◽  
Experimental Manipulation ◽  
Species Interaction ◽  
Foundation Species ◽  
Interaction Networks ◽  
Community Diversity ◽  
Arthropod Community ◽  
Pemphigus Betae ◽  
In The Wild ◽  
The Stability

We examined the hypothesis that genetics-based interactions between strongly interacting foundation species, the tree Populus angustifolia and the aphid Pemphigus betae , affect arthropod community diversity, stability and species interaction networks of which little is known. In a 2-year experimental manipulation of the tree and its aphid herbivore four major findings emerged: (i) the interactions of these two species determined the composition of an arthropod community of 139 species; (ii) both tree genotype and aphid presence significantly predicted community diversity; (iii) the presence of aphids on genetically susceptible trees increased the stability of arthropod communities across years; and (iv) the experimental removal of aphids affected community network structure (network degree, modularity and tree genotype contribution to modularity). These findings demonstrate that the interactions of foundation species are genetically based, which in turn significantly contributes to community diversity, stability and species interaction networks. These experiments provide an important step in understanding the evolution of Darwin's ‘entangled bank’, a metaphor that characterizes the complexity and interconnectedness of communities in the wild.

scholarly journals A novel perspective on the meaning of nestedness with conceptual and methodological solutions

2021 ◽  
Author(s):  
Rafael Barros Pereira Pinheiro ◽  
Carsten F. Dormann ◽  
Gabriel Moreira Felix ◽  
Marco A. R. Mello
Keyword(s):  
Null Model ◽  
Interaction Network ◽  
Species Interaction ◽  
Null Models ◽  
Interaction Networks ◽  
Common Pattern ◽  
Expected Values ◽  
New Perspective ◽  
Test Outcomes ◽  
Plant Pollinator

Aim: Nestedness is a common pattern in metacommunities and interaction networks, whose causes are still discussed. Nestedness inference is challenging because, beyond calculating an index, we need to compare observed values with values generated with a null model. There are different null models and the choice between them affects test outcomes. Furthermore, there is no established theoretical basis to guide this choice. Here, we propose a different look at the meaning of nestedness that improves our understanding of its causes and unveils the link between null models and hypotheses. Innovation: Nestedness of a matrix is a combination of marginal sum inequality and high overlap. The higher the overlap, the more predictable the cell values by marginal sums. Here, we show that nestedness actually measures how better one can predict cell values by marginal sums than by matrix dimensions and total sum alone. From this, we propose that two null models can be used to test for different topological hypotheses. The equiprobable model excludes all nestedness-generating mechanisms and provides the distribution of expected values for nestedness significance tests. The proportional model conserves nestedness-generating mechanisms and excludes nestedness-disrupting mechanisms, and thus, produces highly nested matrices. The proportional model provides the distribution of expected nestedness for nested matrices. Additionally, we evaluate the efficiency of several indices within this new perspective and illustrate our approach using an empirical plant-pollinator network. Main conclusions: Through a shift of perspective, our approach reconciliates contradictions in null model analysis and delimits the range of possible explanations for nestedness. The only way a process can increase nestedness in a matrix is by promoting marginal sum inequalities, without concomitantly introducing preferences. Consequently, in a species interaction network, explanations for nestedness should explain why some species interact more frequently than others.

scholarly journals Vulnerable species interactions are important for the stability of mutualistic networks

2019 ◽  
Author(s):  
Benno I. Simmons ◽  
Hannah S. Wauchope ◽  
Tatsuya Amano ◽  
Lynn V. Dicks ◽  
William J. Sutherland ◽  
...  
Keyword(s):  
Species Interactions ◽  
Species Coexistence ◽  
Species Interaction ◽  
Interaction Networks ◽  
Ecological Communities ◽  
Ecological Context ◽  
Intrinsic Properties ◽  
Network Stability ◽  
Starting Point ◽  
The Stability

AbstractSpecies are central to ecology and conservation. However, it is the interactions between species that generate the functions on which ecosystems and humans depend. Despite the importance of interactions, we lack an understanding of the risk that their loss poses to ecological communities. Here, we quantify risk as a function of the vulnerability (likelihood of loss) and importance (contribution to network stability in terms of species coexistence) of 4330 mutualistic interactions from 41 empirical pollination and seed dispersal networks across six continents. Remarkably, we find that more vulnerable interactions are also more important: the interactions that contribute most to network stability are those that are most likely to be lost. Furthermore, most interactions tend to have more similar vulnerability and importance across networks than expected by chance, suggesting that vulnerability and importance may be intrinsic properties of interactions, rather than only a function of ecological context. These results provide a starting point for prioritising interactions for conservation in species interaction networks and, in areas lacking network data, could allow interaction properties to be inferred from taxonomy alone.

scholarly journals Interaction capacity underpins community diversity

2020 ◽  
Author(s):  
Masayuki Ushio
Keyword(s):  
Interspecific Interactions ◽  
Experimental Studies ◽  
Interaction Strength ◽  
Single Species ◽  
Species Interaction ◽  
Community Diversity ◽  
Ecological Communities ◽  
Total Dna ◽  
Mathematical Equations ◽  
The Mean

AbstractHow patterns in community diversity emerge is a long-standing question in ecology. Theories and experimental studies suggested that community diversity and interspecific interactions are interdependent. However, evidence from multitaxonomic, high-diversity ecological communities is lacking because of practical challenges in characterizing speciose communities and their interactions. Here, I analyzed time-varying causal interaction networks that were reconstructed using 1197 species, DNA-based ecological time series taken from experimental rice plots and empirical dynamic modeling, and show that species interaction capacity, namely, the sum of interaction strength that a single species gives and receives, underpins community diversity. As community diversity increases, the number of interactions increases exponentially but the mean species interaction capacity of a community becomes saturated, weakening interaction among species. These patterns are explicitly modeled with simple mathematical equations, based on which I propose the “interaction capacity hypothesis”, namely, that species interaction capacity and network connectance are proximate drivers of community diversity. Furthermore, I show that total DNA concentrations and temperature influence species interaction capacity and connectance nonlinearly, explaining a large proportion of diversity patterns observed in various systems. The interaction capacity hypothesis enables mechanistic explanations of community diversity, and how species interaction capacity is determined is a key question in ecology.

scholarly journals LifeWebs: A (global) database of bipartite ecological interaction networks

2021 ◽  
Vol 5 ◽  
Author(s):  
Philip Butterill ◽  
Leonardo Jorge ◽  
Shuang Xing ◽  
Tom Fayle
Keyword(s):  
Interaction Network ◽  
Community Level ◽  
Interaction Networks ◽  
Sampling Effort ◽  
Ecological Communities ◽  
Bipartite Networks ◽  
Data Types ◽  
User Friendliness ◽  
Global Database ◽  
Machine Readable

The structure and dynamics of ecological interactions are nowadays recognized as a crucial challenge to comprehend the assembly, functioning and maintenance of ecological communities, their processes and the services they provide. Nevertheless, while standards and databases for information on species occurrences, traits and phylogenies have been established, interaction networks have lagged behind on the development of these standards. Here, we discuss the challenges and our experiences in developing a global database of bipartite interaction networks. LifeWebs*1 is an effort to compile community-level interaction networks from both published and unpublished sources. We focus on bipartite networks that comprise one specific type of interaction between two groups of species (e.g., plants and herbivores, hosts and parasites, mammals and their microbiota), which are usually presented in a co-occurrence matrix format. However, with LifeWebs, we attempt to go beyond simple matrices by integrating relevant metadata from the studies, especially sampling effort, explicit species information (traits and taxonomy/phylogeny), and environmental/geographic information on the communities. Specifically, we explore 1) the unique aspects of community-level interaction networks when compared to data on single inter-specific interactions, occurrence data, and other biodiversity data and how to integrate these different data types. 2) The trade-off between user friendliness in data input/output vs. machine-readable formats, especially important when data contributors need to provide large amounts of data usually compiled in a non-machine-readable format. 3) How to have a single framework that is general enough to include disparate interaction types while retaining all the meaningful information. We envision LifeWebs to be in a good position to test a general standard for interaction network data, with a large variety of already compiled networks that encompass different types of interactions. We provide a framework for integration with other types of data, and formalization of the data necessary to represent networks into established biodiversity standards.

scholarly journals Mutual Information as a General Measure of Structure in Interaction Networks

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 528 ◽  
Author(s):  
Gilberto Corso ◽  
Gabriel M. F. Ferreira ◽  
Thomas M. Lewinsohn
Keyword(s):  
Mutual Information ◽  
Biological Diversity ◽  
Spatial Scales ◽  
Interaction Networks ◽  
Ecological Communities ◽  
Bipartite Networks ◽  
General Measure ◽  
Interaction Structure ◽  
Interactive Networks ◽  
Modes Of Interaction

Entropy-based indices are long-established measures of biological diversity, nowadays used to gauge partitioning of diversity at different spatial scales. Here, we tackle the measurement of diversity of interactions among two sets of organisms, such as plants and their pollinators. Actual interactions in ecological communities are depicted as bipartite networks or interaction matrices. Recent studies concentrate on distinctive structural patterns, such as nestedness or modularity, found in different modes of interaction. By contrast, we investigate mutual information as a general measure of structure in interactive networks. Mutual information (MI) measures the degree of reciprocal matching or specialization between interacting organisms. To ascertain its usefulness as a general measure, we explore (a) analytical solutions for different models; (b) the response of MI to network parameters, especially size and occupancy; (c) MI in nested, modular, and compound topologies. MI varies with fundamental matrix parameters: dimension and occupancy, for which it can be adjusted or normalized. Apparent differences among topologies are contingent on dimensions and occupancy, rather than on topological patterns themselves. As a general measure of interaction structure, MI is applicable to conceptually and empirically fruitful analyses, such as comparing similar ecological networks along geographical gradients or among interaction modalities in mutualistic or antagonistic networks.

scholarly journals Consequences of plant invasions on compartmentalization and species’ roles in plant–pollinator networks

2014 ◽  
Vol 281 (1788) ◽  
pp. 20140773 ◽  
Author(s):  
Matthias Albrecht ◽  
Benigno Padrón ◽  
Ignasi Bartomeus ◽  
Anna Traveset
Keyword(s):  
Invasive Plants ◽  
Native Species ◽  
Plant Invasions ◽  
Interaction Networks ◽  
Ecological Communities ◽  
Interaction Structure ◽  
Plant Invaders ◽  
Functional Implications ◽  
Species Roles ◽  
Plant Pollinator

Compartmentalization—the organization of ecological interaction networks into subsets of species that do not interact with other subsets (true compartments) or interact more frequently among themselves than with other species (modules)—has been identified as a key property for the functioning, stability and evolution of ecological communities. Invasions by entomophilous invasive plants may profoundly alter the way interaction networks are compartmentalized. We analysed a comprehensive dataset of 40 paired plant–pollinator networks (invaded versus uninvaded) to test this hypothesis. We show that invasive plants have higher generalization levels with respect to their pollinators than natives. The consequences for network topology are that—rather than displacing native species from the network—plant invaders attracting pollinators into invaded modules tend to play new important topological roles (i.e. network hubs, module hubs and connectors) and cause role shifts in native species, creating larger modules that are more connected among each other. While the number of true compartments was lower in invaded compared with uninvaded networks, the effect of invasion on modularity was contingent on the study system. Interestingly, the generalization level of the invasive plants partially explains this pattern, with more generalized invaders contributing to a lower modularity. Our findings indicate that the altered interaction structure of invaded networks makes them more robust against simulated random secondary species extinctions, but more vulnerable when the typically highly connected invasive plants go extinct first. The consequences and pathways by which biological invasions alter the interaction structure of plant–pollinator communities highlighted in this study may have important dynamical and functional implications, for example, by influencing multi-species reciprocal selection regimes and coevolutionary processes.

scholarly journals Dynamic population stage-structure stabilizes complex ecological communities

2020 ◽  
Author(s):  
André M. de Roos
Keyword(s):  
Self Regulation ◽  
Interaction Network ◽  
Population Level ◽  
Stage Structure ◽  
Current Theory ◽  
Species Interaction ◽  
Interaction Matrix ◽  
Foraging Efficiency ◽  
Ecological Communities ◽  
The Matrix

SummaryNatural ecological communities are diverse, complex and often surprisingly stable, but the mechanisms underlying their stability remain a theoretical enigma1-5. Interactions such as competition and predation presumably structure communities6, yet theory predicts that complex communities are only stable when species growth rates are mostly limited by intraspecific self-regulation rather than by interactions with resources, competitors and predators3,5,7. Current theory, however, only considers the network topology of population-level interactions between species and neglects within-population differences among juvenile and adult individuals. Here, using model simulations, I show that including commonly observed differences in vulnerability to predation and foraging efficiency between juvenile and adult individuals results in up to ten times larger, more complex communities than in simulations without population stage-structure. These diverse communities are stable or fluctuate with limited amplitude, even though in the model only a single basal species is self-regulated and the population-level interaction network is highly connected. Analysis of the species interaction matrix predicts the simulated communities to be unstable but extending the matrix with a population structure subsystem reveals that dynamic changes in population stage-structure completely cancel out this instability. Common differences between juveniles and adults and fluctuations in their relative abundance hence have a decisive influence on the stability of complex natural communities and their vulnerability when environmental conditions change. Thus, community persistence can not be explained by the network of interactions between the constituting species alone.

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