scholarly journals Quantifying the impact of ecological memory on the dynamics of interacting communities

2021 ◽  
Author(s):  
Moein Khalighi ◽  
Didier Gonze ◽  
Karoline Faust ◽  
Guilhem Sommeria-Klein ◽  
Leo Lahti
Keyword(s):  
Community Dynamics ◽  
Initial Conditions ◽  
Alternative Stable States ◽  
Interaction Model ◽  
Ecological Communities ◽  
Stable States ◽  
Ecological Memory ◽  
Recovery Times ◽  
Key Aspects ◽  
The Impact

Ecological memory refers to the influence of past events on the response of an ecosystem to exogenous or endogenous changes. Memory has been widely recognized as a key contributor to the dynamics of ecosystems and other complex systems, yet quantitative community models often ignore memory and its implications. Recent studies have shown how interactions between community members can lead to the emergence of resilience and multistability under environmental perturbations. We demonstrate how memory can complement such models. We use the framework of fractional calculus to study how the outcomes of a well-characterized interaction model are affected by gradual increases in ecological memory under varying initial conditions, perturbations, and stochasticity. Our results highlight the implications of memory on several key aspects of community dynamics. In general, memory slows down the overall dynamics and recovery times after perturbation, thus reducing the system's resilience. However, it simultaneously mitigates hysteresis and enhances the system's capacity to resist state shifts. Memory promotes long transient dynamics, such as long-standing oscillations and delayed regime shifts, and contributes to the emergence and persistence of alternative stable states. Collectively, these results highlight the fundamental role of memory on ecological communities and provide new quantitative tools to analyse its impact under varying conditions.

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.

scholarly journals Model analysis for plant disease dynamics co-mediated by herbivory and herbivore-borne phytopathogens

2012 ◽  
Vol 8 (4) ◽  
pp. 685-688 ◽  
Author(s):  
Takefumi Nakazawa ◽  
Takehiko Yamanaka ◽  
Satoru Urano
Keyword(s):  
Plant Disease ◽  
Initial Conditions ◽  
Alternative Stable States ◽  
Model Analysis ◽  
Plant Diseases ◽  
Disease Dynamics ◽  
Stable States ◽  
Tripartite Interactions ◽  
Model Combining ◽  
Nutritive Quality

Plants are subject to diseases caused by pathogens, many of which are transmitted by herbivorous arthropod vectors. To understand plant disease dynamics, we studied a minimum hybrid model combining consumer–resource (herbivore–plant) and susceptible–infected models, in which the disease is transmitted bi-directionally between the consumer and the resource from the infected to susceptible classes. Model analysis showed that: (i) the disease is more likely to persist when the herbivore feeds on the susceptible plants rather than the infected plants, and (ii) alternative stable states can exist in which the system converges to either a disease-free or an endemic state, depending on the initial conditions. The second finding is particularly important because it suggests that the disease may persist once established, even though the initial prevalence is low (i.e. the R 0 rule does not always hold). This situation is likely to occur when the infection improves the plant nutritive quality, and the herbivore preferentially feeds on the infected resource (i.e. indirect vector–pathogen mutualism). Our results highlight the importance of the eco-epidemiological perspective that integration of tripartite interactions among host plant, plant pathogen and herbivore vector is crucial for the successful control of plant diseases.

scholarly journals An altered metabolism could contribute to the low activation of neonatal CD8+T cells

2019 ◽  
Author(s):  
Sánchez-Villanueva José Antonio ◽  
Rodríguez-Jorge Otoniel ◽  
Ramírez-Pliego Oscar ◽  
Rosas Salgado Gabriela ◽  
Abou-Jaoudé Wassim ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Alternative Stable States ◽  
Population Level ◽  
Stochastic Simulations ◽  
Stable States ◽  
T Cell Signaling ◽  
Cell Fates ◽  
Activation Rate ◽  
The Impact

AbstractA low response of neonatal T cells to infections contributes to a high incidence of morbidity and mortality of neonates. Here we evaluated the impact of the cytoplasmic and mitochondrial levels of Reactive Oxygen Species (ROS) of adult and neonatal CD8+T cells on their activation potential. We further constructed a logical model to decipher the interplay of metabolism and ROS on T cell signaling. Our model captures the interplay between antigen recognition, ROS and metabolic status in T cell responses. This model displays alternative stable states corresponding to different cell fates, i.e. quiescent, activated and anergic states, depending on ROS status. Stochastic simulations with this model further indicate that differences in ROS status at the cell population level tentatively explain the lower activation rate of neonatal compared to adult CD8+T cells upon TCR engagement.

scholarly journals Burrowing fauna mediate alternative stable states in the redox cycling of salt marsh sediments

2020 ◽  
Author(s):  
Sebastiaan van de Velde ◽  
Gilad Antler ◽  
Filip Meysman
Keyword(s):  
Salt Marsh ◽  
Salt Marshes ◽  
Solid Phase ◽  
Alternative Stable States ◽  
Redox Cycling ◽  
Iron Cycling ◽  
Stable States ◽  
Positive Feedbacks ◽  
Sediment Biogeochemistry ◽  
The Impact

<p>The East Anglian salt marsh system (UK) has recently generated intriguing data with respect to sediment biogeochemistry. Neighbouring ponds in these salt marshes show two distinct regimes of redox cycling: the sediments are either iron-rich and bioturbated, or they are sulphide-rich and unbioturbated. No conclusive explanation has yet been given for this remarkable spatial co-occurrence.  Using pore-water analysis and solid-phase speciation, I will demonstrate that differences in solid-phase carbon and iron inputs are likely small between pond types, so these cannot act as the direct driver of the observed redox dichotomy. Instead, the results suggest that the presence of bioturbation is the driving force behind the transition from sulphur-dominated to iron-dominated sediments. The presence of burrowing fauna in marine sediments stimulates the mineralisation of organic matter, increases the iron cycling and limits the build-up of free sulphide. Subsequent early diagenetic modelling confirms that the observed regimes in pond geochemistry are caused by negligible differences in solid-phase inputs, which are amplified by positive feedbacks resulting from the impact of bioturbation on iron and sulphur cycling.</p>

scholarly journals Inferring Models with Alternative Stable States from Independent Observations

2020 ◽  
Author(s):  
Edward W. Tekwa ◽  
Martin Krkošek ◽  
Malin L. Pinsky
Keyword(s):  
Initial Conditions ◽  
Alternative Stable States ◽  
Ecological Systems ◽  
Process Models ◽  
Stable States ◽  
Multiple Attractors ◽  
Natural Systems ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Independent Observations

AbstractMultiple attractors and alternative stable states are defining features of scientific theories in ecology and evolution, implying that abrupt regime shifts can occur and that outcomes can be hard to reverse. Here we describe a statistical inferential framework that uses independent, noisy observations with low temporal resolution to support or refute multiple attractor process models. The key is using initial conditions to choose among a finite number of expected outcomes using a nonstandard finite mixture methodology. We apply the framework to contemporary issues in social-ecological systems, coral ecosystems, and chaotic systems, showing that incorporating history allows us to statistically infer process models with alternative stable states while minimizing false positives. Further, in the presence of disturbances and oscillations, alternative stable states can help rather than hamper inference. The ability to infer models with alternative stable states across natural systems can help accelerate scientific discoveries, change how we manage ecosystems and societies, and place modern theories on firmer empirical ground.

scholarly journals Untangling the complexity of priority effects in multi-species communities

2021 ◽  
Author(s):  
Chuliang Song ◽  
Tadashi Fukami ◽  
Serguei Saavedra
Keyword(s):  
Species Interactions ◽  
Alternative Stable States ◽  
Experimental Studies ◽  
Theoretical Framework ◽  
Priority Effects ◽  
Ecological Communities ◽  
Stable States ◽  
Small Communities ◽  
History Of ◽  
Local Species

AbstractPriority effects arise when the history of species arrival influences local species interactions, thereby affecting the composition of ecological communities. The outcome of some priority effects may be more difficult to predict than others, but this possibility remains to be fully investigated. Here, we provide a graph-based, non-parametric, theoretical framework to understand the classification of priority effects and the predictability of multi-species communities. We show that we can classify priority effects by decomposing them into four basic dynamical sources: the number of alternative stable states, the number of alternative transient paths, the length of composition cycles, and the interaction between alternative stable states and composition cycles. Although the number of alternative stable states has received most of the attention, we show that the other three sources can contribute more to the predictability of community assembly, especially in small communities. We discuss how this theoretical framework can guide new experimental studies.

scholarly journals Regime shifts in exploited marine food webs: detecting mechanisms underlying alternative stable states using size-structured community dynamics theory

2015 ◽  
Vol 370 (1659) ◽  
pp. 20130262 ◽  
Author(s):  
Anna Gårdmark ◽  
Michele Casini ◽  
Magnus Huss ◽  
Anieke van Leeuwen ◽  
Joakim Hjelm ◽  
...  
Keyword(s):  
Community Dynamics ◽  
Prey Availability ◽  
Alternative Stable States ◽  
Individual Performance ◽  
Regime Shifts ◽  
Trophic Levels ◽  
Stable States ◽  
Ecosystem Recovery ◽  
Piscivorous Fish ◽  
Combining Data

Many marine ecosystems have undergone ‘regime shifts’, i.e. abrupt reorganizations across trophic levels. Establishing whether these constitute shifts between alternative stable states is of key importance for the prospects of ecosystem recovery and for management. We show how mechanisms underlying alternative stable states caused by predator–prey interactions can be revealed in field data, using analyses guided by theory on size-structured community dynamics. This is done by combining data on individual performance (such as growth and fecundity) with information on population size and prey availability. We use Atlantic cod ( Gadus morhua ) and their prey in the Baltic Sea as an example to discuss and distinguish two types of mechanisms, ‘cultivation-depensation’ and ‘overcompensation’, that can cause alternative stable states preventing the recovery of overexploited piscivorous fish populations. Importantly, the type of mechanism can be inferred already from changes in the predators' body growth in different life stages. Our approach can thus be readily applied to monitored stocks of piscivorous fish species, for which this information often can be assembled. Using this tool can help resolve the causes of catastrophic collapses in marine predatory–prey systems and guide fisheries managers on how to successfully restore collapsed piscivorous fish stocks.

scholarly journals A macroecological description of alternative stable states reproduces intra- and inter-host variability of gut microbiome

2021 ◽  
Author(s):  
Silvia Zaoli ◽  
Jacopo Grilli
Keyword(s):  
Gut Microbiome ◽  
Community Dynamics ◽  
Temporal Dynamics ◽  
Alternative Stable States ◽  
Individual Variability ◽  
Statistical Properties ◽  
Stable States ◽  
Environmental Fluctuations ◽  
The Rich ◽  
Community Variability

The most fundamental questions in microbial ecology concern the diversity and variability of communities. Their composition varies widely across space and time, as it is determined by a non-trivial combination of stochastic and deterministic processes. The interplay between non-linear community dynamics and environmental fluctuations determines the rich statistical structure of community variability, with both rapid temporal dynamics fluctuations and non-trivial correlations across habitats. Here we analyze long time-series of gut microbiome and compare intra- and inter-community dissimilarity. Under a macroecological framework we characterize their statistical properties. We show that most taxa have large but stationary fluctuations over time, while a minority is characterized by quick changes of average abundance which cluster in time, suggesting the presence of alternative stable states. We disentangle inter-individual variability in a major stochastic component and a deterministic one, the latter recapitulated by differences in the carrying capacities of taxa. Finally, we develop a model which includes environmental fluctuations and alternative stable states. This model quantitatively predicts the statistical properties of both intra- and inter-individual community variability, therefore summarizing variation in a unique macroecological framework.

scholarly journals Resources, mortality, and disease ecology: importance of positive feedbacks between host growth rate and pathogen dynamics

2015 ◽  
Vol 61 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Val H. Smith ◽  
Robert D. Holt ◽  
Marilyn S. Smith ◽  
Yafen Niu ◽  
Michael Barfield
Keyword(s):  
Growth Rate ◽  
Disease Ecology ◽  
Community Dynamics ◽  
Physiological State ◽  
Alternative Stable States ◽  
Stable States ◽  
Metabolic Scaling ◽  
Pathogen Dynamics ◽  
Host Growth ◽  
Resource Effects

Resource theory and metabolic scaling theory suggest that the dynamics of a pathogen within a host should strongly depend upon the rate of host cell metabolism. Once an infection occurs, key ecological interactions occur on or within the host organism that determine whether the pathogen dies out, persists as a chronic infection, or grows to densities that lead to host death. We hypothesize that, in general, conditions favoring rapid host growth rates should amplify the replication and proliferation of both fungal and viral pathogens. If a host population experiences an increase in mortality, to persist it must have a higher growth rate, per host, often reflecting greater resource availability per capita. We hypothesize that this could indirectly foster the pathogen, which also benefits from increased within-host resource turnover. We first bring together in a short review a number of key prior studies which illustrate resource effects on viral and fungal pathogen dynamics. We then report new results from a semi-continuous cell culture experiment with SHIV, demonstrating that higher mortality rates indeed can promote viral proliferation. We develop a simple model that illustrates dynamical consequences of these resource effects, including interesting effects such as alternative stable states and oscillatory dynamics. Our paper contributes to a growing body of literature at the interface of ecology and infectious disease epidemiology, emphasizing that host abundances alone do not drive community dynamics: the physiological state and resource content of infected hosts also strongly influence host–pathogen interactions.

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