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1. Effects of stochasticity on the length and behaviour of ecological transients

   https://doi.org/10.1098/rsif.2021.0257  

   Hastings, Alan; Abbott, Karen C.; Cuddington, Kim; Francis, Tessa B.; Lai, Ying-Cheng; Morozov, Andrew; Petrovskii, Sergei; Zeeman, Mary Lou (July 2021, Journal of The Royal Society Interface)

   null (Ed.)

   There is a growing recognition that ecological systems can spend extended periods of time far away from an asymptotic state, and that ecological understanding will therefore require a deeper appreciation for how long ecological transients arise. Recent work has defined classes of deterministic mechanisms that can lead to long transients. Given the ubiquity of stochasticity in ecological systems, a similar systematic treatment of transients that includes the influence of stochasticity is important. Stochasticity can of course promote the appearance of transient dynamics by preventing systems from settling permanently near their asymptotic state, but stochasticity also interacts with deterministic features to create qualitatively new dynamics. As such, stochasticity may shorten, extend or fundamentally change a system’s transient dynamics. Here, we describe a general framework that is developing for understanding the range of possible outcomes when random processes impact the dynamics of ecological systems over realistic time scales. We emphasize that we can understand the ways in which stochasticity can either extend or reduce the lifetime of transients by studying the interactions between the stochastic and deterministic processes present, and we summarize both the current state of knowledge and avenues for future advances. 

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2. A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread

   https://doi.org/10.3934/mbe.2021381  

   Tan, Yukun; Cator III, Durward; Ndeffo-Mbah, Martial; Braga-Neto, Ulisses (January 2021, Mathematical Biosciences and Engineering)

   null (Ed.)

   Mathematical models are widely recognized as an important tool for analyzing and understanding the dynamics of infectious disease outbreaks, predict their future trends, and evaluate public health intervention measures for disease control and elimination. We propose a novel stochastic metapopulation state-space model for COVID-19 transmission, which is based on a discrete-time spatio-temporal susceptible, exposed, infected, recovered, and deceased (SEIRD) model. The proposed framework allows the hidden SEIRD states and unknown transmission parameters to be estimated from noisy, incomplete time series of reported epidemiological data, by application of unscented Kalman filtering (UKF), maximum-likelihood adaptive filtering, and metaheuristic optimization. Experiments using both synthetic data and real data from the Fall 2020 COVID-19 wave in the state of Texas demonstrate the effectiveness of the proposed model. 

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3. Dynamics of giant vesicle assembly from thin lipid films

   https://doi.org/10.1016/j.jcis.2024.02.022  

   Pazzi, Joseph; Subramaniam, Anand Bala (February 2024, Journal of Colloid and Interface Science)

   Motivation Giant unilamellar vesicles (GUVs), cell-like synthetic micrometer size structures, assemble when thin lipid films are hydrated in aqueous solutions. Quantitative measurements of static yields and distribution of sizes of GUVs obtained from thin film hydration methods were recently reported. Dynamic data such as the time evolution of yields and distribution of sizes, however, is not known. Dynamic data can provide insights into the assembly pathway of GUVs and guidelines for choosing conditions to obtain populations with desired size distributions. Approach We develop the ‘stopped-time’ technique to characterize the time evolution of the distribution of sizes and molar yields of populations of free-floating GUVs. We additionally capture high resolution time-lapse images of surface-attached GUV buds on the lipid films. We systematically study the dynamics of assembly of GUVs from three widely used thin film hydration methods, PAPYRUS (Paper-Abetted amPhiphile hYdRation in aqUeous Solutions), gentle hydration, and electroformation. Findings We find that the molar yield versus time curves of GUVs demonstrate a characteristic sigmoidal shape, with an initial yield, a transient, and then a steady state plateau for all three methods. The population of GUVs showed a right-skewed distribution of diameters. The variance of the distributions increased with time. The systems reached steady state within 120 min. We rationalize the dynamics using the thermodynamically motivated budding and merging (BNM) model. These results further the understanding of lipid dynamics and provide for the first-time practical parameters to tailor the production of GUVs of specific sizes for applications. 

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4. Exit time as a measure of ecological resilience

   https://doi.org/10.1126/science.aay4895  

   Arani, Babak M. S.; Carpenter, Stephen R.; Lahti, Leo; van Nes, Egbert H.; Scheffer, Marten (June 2021, Science)

   Ecological resilience is the magnitude of the largest perturbation from which a system can still recover to its original state. However, a transition into another state may often be invoked by a series of minor synergistic perturbations rather than a single big one. We show how resilience can be estimated in terms of average life expectancy, accounting for this natural regime of variability. We use time series to fit a model that captures the stochastic as well as the deterministic components. The model is then used to estimate the mean exit time from the basin of attraction. This approach offers a fresh angle to anticipating the chance of a critical transition at a time when high-resolution time series are becoming increasingly available. 

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5. Social-ecological models with social hierarchy and spatial structure applied to small-scale fisheries

   https://doi.org/10.1007/s12080-024-00594-4  

   Wulfing, Sophie; White, Easton R (December 2024, Theoretical Ecology)

   Socio-ecological models combine ecological systems with human social dynamics in order to better understand human interactions with the environment. To model human behavior, replicator dynamics can be used to model how societal influence and financial costs can change opinions about resource extraction. Previous research on replicator dynamics has shown how evolving opinions on conservation can change how humans interact with their environment and therefore change population dynamics of the harvested species. However, social-ecological models often assume that human societies are homogeneous with no social structure. Building on previous work on social-ecological models, we develop a two-patch socio-ecological model with social hierarchy in order to study the interactions between spatial dynamics and social inequity. We found that fish movement between patches is a major driver of model dynamics, especially when the two patches exhibit different social equality and fishing practices. Further, we found that the societal influence between groups of harvesters was essential to ensuring stable fishery dynamics. Next, we developed a case study of two independently managed fisheries that were connected by fish movement where one human group fishes sustainably while another was over-harvests, resulting in a fishery collapse of both patches. We also found that because in this model, the influence of one human patch on another only communicates the amount of each catch and no fishing strategies were employed, increased social influence decreased the sustainability of the fishery. The findings of this study indicate the importance of including spatial components to socio- ecological models and highlights the importance of understanding species’ movements when making conservation decisions. Further, we demonstrate how incorporating fishing methods from outside sources can result in higher stability of the harvested population, demonstrating the need for effective communication across management regimes. 

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