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 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.

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 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 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 The balance of interaction types determines the assembly and stability of ecological communities

2019 ◽  
Author(s):  
Jimmy J. Qian ◽  
Erol Akçay
Keyword(s):  
Species Interactions ◽  
Community Dynamics ◽  
Theoretical Work ◽  
Species Interaction ◽  
Ecological Communities ◽  
External Stability ◽  
Ecological Selection ◽  
Interaction Types ◽  
The Stability ◽  
Almost All

What determines the assembly and stability of complex communities is a central question in ecology. Past work has suggested that mutualistic interactions are inherently destabilizing. However, this conclusion relies on assuming that benefits from mutualisms never stop increasing. Furthermore, almost all theoretical work focuses on the internal (asymptotic) stability of communities assembled all-at-once. Here, we present a model with saturating benefits from mutualisms and sequentially assembled communities. We show that such communities are internally stable for any level of diversity and any combination of species interaction types. External stability, or resistance to invasion, is thus an important but overlooked measure of stability. We demonstrate that the balance of different interaction types governs community dynamics. Mutualisms may increase external stability and diversity of communities as well as species persistence, depending on how benefits saturate. Ecological selection increases the prevalence of mutualisms, and limits on biodiversity emerge from species interactions. Our results help resolve longstanding debates on the stability, saturation, and diversity of communities.

Respiratory Sinus Arrhythmia During Sleep and Waking

2019 ◽  
Vol 33 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Elizabeth M. Stoakley ◽  
Karen J. Mathewson ◽  
Louis A. Schmidt ◽  
Kimberly A. Cote
Keyword(s):  
Individual Differences ◽  
Respiratory Sinus Arrhythmia ◽  
Slow Wave Sleep ◽  
Self Regulation ◽  
Nrem Sleep ◽  
Sinus Arrhythmia ◽  
Affective Style ◽  
Waking State ◽  
Optimal Period ◽  
The Stability

Abstract. Resting respiratory sinus arrhythmia (RSA) is related to individual differences in waking affective style and self-regulation. However, little is known about the stability of RSA between sleep/wake stages or the relations between RSA during sleep and waking affective style. We examined resting RSA in 25 healthy undergraduates during the waking state and one night of sleep. Stability of cardiac variables across sleep/wake states was highly reliable within participants. As predicted, greater approach behavior and lower impulsivity were associated with higher RSA; these relations were evident in early night Non-REM (NREM) sleep, particularly in slow wave sleep (SWS). The current research extends previous findings by establishing stability of RSA within individuals between wake and sleep states, and by identifying SWS as an optimal period of measurement for relations between waking affective style and RSA.

Applications of random graphs

2017 ◽  
Author(s):  
A.C.C. Coolen ◽  
A. Annibale ◽  
E.S. Roberts
Keyword(s):  
Social Networks ◽  
Random Graphs ◽  
Interaction Network ◽  
Power Grids ◽  
Protein Protein Interaction ◽  
Topological Features ◽  
First Case ◽  
The Stability ◽  
Protein Protein Interaction Network

This chapter reviews graph generation techniques in the context of applications. The first case study is power grids, where proposed strategies to prevent blackouts have been tested on tailored random graphs. The second case study is in social networks. Applications of random graphs to social networks are extremely wide ranging – the particular aspect looked at here is modelling the spread of disease on a social network – and how a particular construction based on projecting from a bipartite graph successfully captures some of the clustering observed in real social networks. The third case study is on null models of food webs, discussing the specific constraints relevant to this application, and the topological features which may contribute to the stability of an ecosystem. The final case study is taken from molecular biology, discussing the importance of unbiased graph sampling when considering if motifs are over-represented in a protein–protein interaction network.

The impacts of anthropogenic ocean noise on cetaceans and implications for management

2007 ◽  
Vol 85 (11) ◽  
pp. 1091-1116 ◽  
Author(s):  
L.S. Weilgart
Keyword(s):  
Oil And Gas ◽  
Synergistic Effects ◽  
Noise Pollution ◽  
Population Level ◽  
Seismic Exploration ◽  
Foraging Efficiency ◽  
Cetacean Species ◽  
Ocean Noise ◽  
Beaked Whales ◽  
Noise Impacts

Ocean noise pollution is of special concern for cetaceans, as they are highly dependent on sound as their principal sense. Sound travels very efficiently underwater, so the potential area impacted can be thousands of square kilometres or more. The principal anthropogenic noise sources are underwater explosions (nuclear and otherwise), shipping, seismic exploration by mainly the oil and gas industries, and naval sonar operations. Strandings and mortalities of especially beaked whales (family Ziphiidae) have in many cases been conclusively linked to noise events such as naval maneuvers involving tactical sonars or seismic surveys, though other cetacean species may also be involved. The mechanisms behind this mortality are still unknown, but are most likely related to gas and fat emboli at least partially mediated by a behavioral response, such as a change in diving pattern. Estimated received sound levels in these events are typically not high enough to cause hearing damage, implying that the auditory system may not always be the best indicator for noise impacts. Beaked whales are found in small, possibly genetically isolated, local populations that are resident year-round. Thus, even transient and localized acoustic impacts can have prolonged and serious population consequences, as may have occurred following at least one stranding. Populations may also be threatened by noise through reactions such as increased stress levels, abandonment of important habitat, and “masking” or the obscuring of natural sounds. Documented changes in vocal behavior may lead to reductions in foraging efficiency or mating opportunities. Responses are highly variable between species, age classes, behavioral states, etc., making extrapolations problematic. Also, short-term responses may not be good proxies of long-term population-level impacts. There are many examples of apparent tolerance of noise by cetaceans, however. Noise can also affect cetaceans indirectly through their prey. Fish show permanent and temporary hearing loss, reduced catch rates, stress, and behavioral reactions to noise. Management implications of noise impacts include difficulties in establishing “safe” exposure levels, shortcomings of some mitigation tools, the need for precaution in the form of reducing noise levels and distancing noise from biologically important areas, and the role of marine protected areas and monitoring in safeguarding cetaceans especially from cumulative and synergistic effects.

scholarly journals The importance of motivation, weapons, and foul odors in driving encounter competition in carnivores

2020 ◽  
Author(s):  
ML Allen ◽  
CC Wilmers ◽  
LM Elbroch ◽  
JM Golla ◽  
Heiko Wittmer
Keyword(s):  
Interference Competition ◽  
Current Theory ◽  
Lynx Rufus ◽  
Natural Environments ◽  
Ecological Communities ◽  
Competitive Advantages ◽  
Ecological Society ◽  
Strategic Behaviors ◽  
Species Specific ◽  
Occurrence Patterns

© 2016 by the Ecological Society of America. Encounter competition is interference competition in which animals directly contend for resources. Ecological theory predicts the trait that determines the resource holding potential (RHP), and hence the winner of encounter competition, is most often body size or mass. The difficulties of observing encounter competition in complex organisms in natural environments, however, has limited opportunities to test this theory across diverse species. We studied the outcome of encounter competition contests among mesocarnivores at deer carcasses in California to determine the most important variables for winning these contests. We found some support for current theory in that body mass is important in determining the winner of encounter competition, but we found that other factors including hunger and species-specific traits were also important. In particular, our top models were "strength and hunger" and "size and hunger," with models emphasizing the complexity of variables influencing outcomes of encounter competition. In addition, our wins above predicted (WAP) statistic suggests that an important aspect that determines the winner of encounter competition is species-specific advantages that increase their RHP, as bobcats (Lynx rufus) and spotted skunks (Spilogale gracilis) won more often than predicted based on mass. In complex organisms, such as mesocarnivores, species-specific adaptations, including strategic behaviors, aggressiveness, and weapons, contribute to competitive advantages and may allow certain species to take control or defend resources better than others. Our results help explain how interspecific competition shapes the occurrence patterns of species in ecological communities.

scholarly journals Relation between stability and resilience determines the performance of early warning signals under different environmental drivers

2015 ◽  
Vol 112 (32) ◽  
pp. 10056-10061 ◽  
Author(s):  
Lei Dai ◽  
Kirill S. Korolev ◽  
Jeff Gore
Keyword(s):  
Early Warning ◽  
Alternative Stable States ◽  
Basin Of Attraction ◽  
Environmental Drivers ◽  
Ecological Communities ◽  
Stable States ◽  
Warning Signals ◽  
Early Warning Signals ◽  
The Stability ◽  
Stability And Resilience

Shifting patterns of temporal fluctuations have been found to signal critical transitions in a variety of systems, from ecological communities to human physiology. However, failure of these early warning signals in some systems calls for a better understanding of their limitations. In particular, little is known about the generality of early warning signals in different deteriorating environments. In this study, we characterized how multiple environmental drivers influence the dynamics of laboratory yeast populations, which was previously shown to display alternative stable states [Dai et al., Science, 2012]. We observed that both the coefficient of variation and autocorrelation increased before population collapse in two slowly deteriorating environments, one with a rising death rate and the other one with decreasing nutrient availability. We compared the performance of early warning signals across multiple environments as “indicators for loss of resilience.” We find that the varying performance is determined by how a system responds to changes in a specific driver, which can be captured by a relation between stability (recovery rate) and resilience (size of the basin of attraction). Furthermore, we demonstrate that the positive correlation between stability and resilience, as the essential assumption of indicators based on critical slowing down, can break down in this system when multiple environmental drivers are changed simultaneously. Our results suggest that the stability–resilience relation needs to be better understood for the application of early warning signals in different scenarios.

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