scholarly journals Reconstruction of plant–pollinator networks from observational data

2019 ◽  
Author(s):  
Jean-Gabriel Young ◽  
Fernanda S. Valdovinos ◽  
M. E. J. Newman
Keyword(s):  
Food Webs ◽  
Observational Data ◽  
Network Structure ◽  
Rare Species ◽  
Statistical Technique ◽  
Ecological Networks ◽  
Statistical Analyses ◽  
Published Data ◽  
Statistical Errors ◽  
Plant Pollinator

Empirical measurements of ecological networks such as food webs and mutualistic networks are often rich in structure but also noisy and error-prone, particularly for rare species for which observations are sparse. Focusing on the case of plant–pollinator networks, we here describe a Bayesian statistical technique that allows us to make accurate estimates of network structure and ecological metrics from such noisy observational data. Our method yields not only estimates of these quantities, but also estimates of their statistical errors, paving the way for principled statistical analyses of ecological variables and outcomes. We demonstrate the use of the method with an application to previously published data on plant–pollinator networks in the Seychelles archipelago, calculating estimates of network structure, network nestedness, and other characteristics.

scholarly journals Reconstruction of plant–pollinator networks from observational data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jean-Gabriel Young ◽  
Fernanda S. Valdovinos ◽  
M. E. J. Newman
Keyword(s):  
Food Webs ◽  
Observational Data ◽  
Network Structure ◽  
Rare Species ◽  
National Park ◽  
Statistical Technique ◽  
Ecological Networks ◽  
Statistical Analyses ◽  
Published Data ◽  
Plant Pollinator

AbstractEmpirical measurements of ecological networks such as food webs and mutualistic networks are often rich in structure but also noisy and error-prone, particularly for rare species for which observations are sparse. Focusing on the case of plant–pollinator networks, we here describe a Bayesian statistical technique that allows us to make accurate estimates of network structure and ecological metrics from such noisy observational data. Our method yields not only estimates of these quantities, but also estimates of their statistical errors, paving the way for principled statistical analyses of ecological variables and outcomes. We demonstrate the use of the method with an application to previously published data on plant–pollinator networks in the Seychelles archipelago and Kosciusko National Park, calculating estimates of network structure, network nestedness, and other characteristics.

scholarly journals Extinction models of robustness for weighted ecological networks

2017 ◽  
Author(s):  
Miranda S. Bane ◽  
Michael J. O. Pocock ◽  
Richard James
Keyword(s):  
Network Structure ◽  
Structural Heterogeneity ◽  
Ecological Networks ◽  
List Type ◽  
Bipartite Networks ◽  
Opposing Effects ◽  
The Impact ◽  
Plant Pollinator ◽  
Binary Networks ◽  
New Framework

AbstractAnalysis of ecological networks is a valuable approach to understanding the vulnerability of systems to environmental change. The tolerance of ecological networks to co-extinctions, resulting from sequences of primary extinctions, is a widely-used tool for modelling network ‘robustness’. Previously, these ‘extinction models’ have been developed for and applied mostly to binary networks and recently used to predict cascades of co-extinctions in plant-pollinator networks. There is a need for robustness models that can make the most of the weighted data available and most importantly there is a need to understand how the structure of a network affects its robustness.Here, we developed a framework of extinction models for bipartite ecological networks (specifically plant-pollinator networks). In previous models co-extinctions occurred when nodes lost all their links, but by relaxing this rule (according to a set threshold) our models can be applied to binary and weighted networks, and can permit structurally correlated extinctions, i.e. the potential for avalanches of extinctions. We tested how the average and the range of robustness values is impacted by network structure and the impact of structurally-correlated extinctions sampling non-uniformly from the distribution of random extinction sequences.We found that the way that structurally-correlated extinctions are modelled impacts the results; our two ecologically-plausible models produce opposing effects which shows the importance of understanding the model. We found that when applying the models to networks with weighted interactions, the effects are amplified and the variation in robustness increases. Variation in robustness is a key feature of these extinction models and is driven by the structural heterogeneity (i.e. the skewness of the degree distribution) of nodes (specifically, plant nodes) in the network.Our new framework of models enables us to calculate robustness with weighted, as well as binary, bipartite networks, and to make direct comparisons between models and between networks. This allows us to differentiate effects of the model and of the data (network structure) which is vital for those making ecological inferences from robustness models. The models can be applied to mutualistic and antagonistic networks, and can be extended to food webs.

An Introduction to Complex Networks

2013 ◽  
Author(s):  
Jordi Bascompte ◽  
Pedro Jordano
Keyword(s):  
Complex Systems ◽  
Complex Networks ◽  
Network Structure ◽  
Ecological Networks ◽  
Broad Context ◽  
Network Approach ◽  
Mutualistic Networks ◽  
Plant Animal Interactions

Mutualisms can involve dozens, even hundreds, of species and this complexity has precluded a serious community-wide approach to plant–animal interactions. The most straightforward way to describe such an interacting community is with a network of interactions. In this approach, species are represented as nodes of two types: plants and animals. This chapter provides the tools and concepts for characterizing mutualistic networks and placing them into a broad context. This serves as a background with which to understand the structure of mutualistic networks. The discussions cover a network approach to complex systems, measures of network structure, models of network buildup, and ecological networks.

scholarly journals Distribution and Ecology of Clathrus archeri in Romania

2014 ◽  
Vol 6 (3) ◽  
pp. 288-291
Author(s):  
Cipran BÎRSAN ◽  
Ana COJOCARIU ◽  
Elena CENUŞĂ
Keyword(s):  
Plant Communities ◽  
Environmental Conditions ◽  
Rare Species ◽  
Western Europe ◽  
Habitat Type ◽  
Published Data ◽  
Hay Meadows ◽  
Eastern Carpathians ◽  
Distribution And Ecology

Although Clathrus archeri is a widely spread species in the Western Europe, in Romania it is considered a rare species, identified from only eight sites. In July 2013, it was found in two new sites from Gurghiu and Bârgău Mountains, in the Romanian Eastern Carpathians. This paper presents a detailed description of the new recorded specimens and of the habitat where this fungus was found. Plant communities where Clathrus archeri was recorded belong to the “mountain hay meadows” habitat type (Festuco rubrae - Agrostietum capillaris community). Taking into consideration the previous published data, the comparison with other habitats types in which this species occurs suggests that Clathrus archeri has no special preferences for certain environmental conditions.

The Structure of Ecological Networks Across Levels of Organization

2020 ◽  
Vol 51 (1) ◽  
pp. 433-460 ◽  
Author(s):  
Paulo R. Guimarães
Keyword(s):  
Food Webs ◽  
Ecological Systems ◽  
Ecological Networks ◽  
Ecological Communities ◽  
Ecological Interactions ◽  
Biological Organization ◽  
Architectural Patterns ◽  
Fundamental Challenge ◽  
Spatiotemporal Scales ◽  
Multiple Levels

Interactions connect the units of ecological systems, forming networks. Individual-based networks characterize variation in niches among individuals within populations. These individual-based networks merge with each other, forming species-based networks and food webs that describe the architecture of ecological communities. Networks at broader spatiotemporal scales portray the structure of ecological interactions across landscapes and over macroevolutionary time. Here, I review the patterns observed in ecological networks across multiple levels of biological organization. A fundamental challenge is to understand the amount of interdependence as we move from individual-based networks to species-based networks and beyond. Despite the uneven distribution of studies, regularities in network structure emerge across scales due to the fundamental architectural patterns shared by complex networks and the interplay between traits and numerical effects. I illustrate the integration of these organizational scales by exploring the consequences of the emergence of highly connected species for network structures across scales.

scholarly journals Food Webs Over Time: Evaluating the Variability of Degree Distribution on Ecological Networks

2017 ◽  
Author(s):  
Daniela N Lopez ◽  
Patricio A Camus ◽  
Nelson Valdivia ◽  
Sergio A Estay
Keyword(s):  
Food Webs ◽  
Functional Form ◽  
Exponential Model ◽  
Ecological Networks ◽  
Specific Interactions ◽  
Distribution Models ◽  
Networks Analysis ◽  
Topological Characteristics ◽  
Time Specific ◽  
Over Time

AbstractAlthough networks analysis has moved from static to dynamic, ecological networks are still analyzed as time-aggregated units where time-specific interactions are aggregated into one single network. As a result, several questions arise such as what is the functional form of and how variable is the topology of time-specific versus time-aggregated ecological networks? Furthermore, it is yet unknown to what extent the structure of time-aggregated networks is representative of the dynamics of the community. Here, we compared the topology of time-specific and time-aggregated networks by analyzing a set of intertidal networks containing more than 1,000 interactions, and assessed the spatiotemporal dynamics of their degree distributions. By fitting different distribution models, we found that the out-degree distributions of seasonal and time-aggregated networks were best described by an exponential model while the in-degree distributions were best described by a discrete generalized beta model. The degree distributions of the seasonal networks were highly temporally variable and are significantly different from those of time-aggregated networks. We observed that seasonal degree distributions converged toward time-aggregated network distributions after 1.5 years of sampling. Our results highlight the importance of understanding the dynamics of ecological networks, which can show topological characteristics significantly different from those of time-aggregated networks.

scholarly journals On the temporally flexible structure of plant-pollinator interaction networks

2020 ◽  
Author(s):  
Paul J. CaraDonna ◽  
Nickolas M. Waser
Keyword(s):  
Temporal Variation ◽  
Network Structure ◽  
Species Interactions ◽  
Interspecific Interactions ◽  
Activity Period ◽  
Individual Species ◽  
Ecological Communities ◽  
Short Term ◽  
Temporal Flexibility ◽  
Plant Pollinator

AbstractEcological communities consist of species that are joined in complex networks of interspecific interaction. The interactions that networks depict often form and dissolve rapidly, but this temporal variation is not well integrated into our understanding of the causes and consequences of network structure. If interspecific interactions exhibit temporal flexibility across time periods over which organisms co-occur, then the emergent structure of the corresponding network may also be temporally flexible, something that a temporally-static perspective would miss. Here, we use an empirical system to examine short-term flexibility in network structure (connectance, nestedness, and specialization), and in individual species interactions that contribute to that structure. We investigated weekly plant-pollinator networks in a subalpine ecosystem across three summer growing seasons. To link the interactions of individual species to properties of their networks, we examined weekly temporal variation in species’ contributions to network structure. As a test of the potential robustness of networks to perturbation, we also simulated the random loss of species from weekly networks. We then compared the properties of weekly networks to the properties of cumulative networks that aggregate field observations over each full season. A week-to-week view reveals considerable flexibility in the interactions of individual species and their contributions to network structure. For example, species that would be considered relatively generalized across their entire activity period may be much more specialized at certain times, and at no point as generalized as the cumulative network may suggest. Furthermore, a week-to-week view reveals corresponding temporal flexibility in network structure and potential robustness throughout each summer growing season. We conclude that short-term flexibility in species interactions leads to short-term variation in network properties, and that a season-long, cumulative perspective may miss important aspects of the way in which species interact, with implications for understanding their ecology, evolution, and conservation.

scholarly journals Phenotypic evolution is more constrained in simpler food webs

2019 ◽  
Author(s):  
Matthew A. Barbour ◽  
Christopher J. Greyson-Gaito ◽  
Arezoo Sootodeh ◽  
Brendan Locke ◽  
Jordi Bascompte
Keyword(s):  
Food Web ◽  
Food Webs ◽  
Ecological Networks ◽  
Community Context ◽  
Relative Fitness ◽  
Adaptive Landscape ◽  
Phenotypic Traits ◽  
Phenotypic Evolution ◽  
Adaptive Landscapes ◽  
Food Web Complexity

AbstractGlobal change is simplifying the structure of ecological networks; however, we are currently in a poor position to predict how these simplified communities will affect the evolutionary potential of remaining populations. Theory on adaptive landscapes provides a framework for predicting how selection constrains phenotypic evolution, but often treats the community context of evolving populations as a “black box”. Here, we integrate ecological networks and adaptive landscapes to examine how changes in food-web complexity shape evolutionary constraints. We conducted a field experiment that manipulated the diversity of insect parasitoids (food-web complexity) that were able to impose selection on an insect herbivore. We then measured herbivore survival as a function of three key phenotypic traits. We found that more traits were under selection in simpler vs. more complex food webs. The adaptive landscape was more neutral in complex food webs because different parasitoid species impose different selection pressures, minimizing relative fitness differences among phenotypes. Our results suggest that phenotypic evolution becomes more constrained in simplified food webs. This indicates that the simplification of ecological communities may constrain the adaptive potential of remaining populations to future environmental change. “What escapes the eye, however, is a much more insidious kind of extinction: the extinction of ecological interactions.” Janzen (1974)

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