scholarly journals Idea paper: An envelope model of ecological disturbance

2021 ◽  
Author(s):  
Nicholas R. Friedman

Disturbance is common in natural ecosystems, but increasingly defines them. While there are many descriptions for the dynamics of an ecosystem's response to disturbance, there are few descriptions for the dynamics of the disturbance itself. I describe a novel application of a model based on the production of amplitude envelopes in acoustics and electronic music synthesis, with varying parameters Attack, Decay, Sustain, and Release (ADSR). I show that varying the parameters of the ADSR model is sufficient to produce and vary the qualitative disturbance regimes described by previous authors, and is capable of producing dynamics not previously considered. I tested the utility of the ADSR model by applying it to a logistic growth model. I found that manipulating the attack and release parameters of the ADSR model changes the population dynamics estimated by these models. This implies that responses to disturbance are determined not only by the resilience and resistance of the ecological system, but also the dynamics of the disturbance itself. My hope is that the ADSR model will prove useful to researchers in either describing disturbances in long-term ecological data, or in producing disturbances for simulations or experiments.

2020 ◽  
Vol 287 (1930) ◽  
pp. 20200678 ◽  
Author(s):  
Claire Jacquet ◽  
Florian Altermatt

Current global change is associated with an increase in disturbance frequency and intensity, with the potential to trigger population collapses and to cause permanent transitions to new ecosystem states. However, our understanding of ecosystem responses to disturbances is still incomplete. Specifically, there is a mismatch between the diversity of disturbance regimes experienced by ecosystems and the one-dimensional description of disturbances used in most studies on ecological stability. To fill this gap, we conducted a full factorial experiment on microbial communities, where we varied the frequency and intensity of disturbances affecting species mortality, resulting in 20 different disturbance regimes. We explored the direct and long-term effects of these disturbance regimes on community biomass. While most communities were able to recover biomass and composition states similar to undisturbed controls after a halt of the disturbances, we identified some disturbance thresholds that had long-lasting legacies on communities. Using a model based on logistic growth, we identified qualitatively the sets of disturbance frequency and intensity that had equivalent long-term negative impacts on experimental communities. Our results show that an increase in disturbance intensity is a bigger threat for biodiversity and biomass recovery than the occurrence of more frequent but less intense disturbances.


2021 ◽  
Author(s):  
Alexander B. Medvedeff ◽  
Frances M. Iannucci ◽  
Linda A. Deegan ◽  
Alexander D. Huryn ◽  
William B. Bowden

1994 ◽  
Vol 1 (3) ◽  
pp. 214 ◽  
Author(s):  
Colin J. Yates ◽  
Richard J. Hobbs ◽  
Richard W. Bell

Woodlands dominated by Eucalyptus salmonophloia occur both in the fragmented landscapes of the Western Australian wheatbelt and in the adjacent unfragmented goldfields area. We examined the responses of the unfragmented woodlands to landscape-scale disturbances caused by fire, floods, windstorms and drought. Sites known to have experienced disturbances of these types over the past 50 years all had cohorts of sapling-stage E. salmonophloia and other dominant Eucalyptus species. Sites disturbed either by fire, flood or storm during 1991-92 displayed adult tree mortality and extensive seedling establishment, although rates of establishment and survival varied between sites. No regeneration was observed at equivalent undisturbed sites. These results indicate that landscape-scale disturbances of several types are important drivers of the dynamics of these semi-arid woodlands. Lack of regeneration of fragmented woodlands in the wheatbelt is likely to be due to changed disturbance regimes coupled with altered physical and biotic conditions within remnants. We argue that it may be difficult to identify processes which are important for the long-term persistence of natural ecosystems in fragmented landscapes without reference to equivalent unfragmented areas.


2017 ◽  
Author(s):  
Wang Jin ◽  
Scott W McCue ◽  
Matthew J Simpson

AbstractCell proliferation is the most important cellular-level mechanism responsible for regulating cell population dynamics in living tissues. Modern experimental procedures show that the proliferation rates of individual cells can vary significantly within the same cell line. However, in the mathematical biology literature, cell proliferation is typically modelled using a classical logistic equation which neglects variations in the proliferation rate. In this work, we consider a discrete mathematical model of cell migration and cell proliferation, modulated by volume exclusion (crowding) effects, with variable rates of proliferation across the total population. We refer to this variability as heterogeneity. Constructing the continuum limit of the discrete model leads to a generalisation of the classical logistic growth model. Comparing numerical solutions of the model to averaged data from discrete simulations shows that the new model captures the key features of the discrete process. Applying the extended logistic model to simulate a proliferation assay using rates from recent experimental literature shows that neglecting the role of heterogeneity can, at times, lead to misleading results.


2021 ◽  
Author(s):  
Mohamed LOUNIS ◽  
Babu Malavika

Abstract The novel Coronavirus respiratory disease 2019 (COVID-19) is still expanding through the world since it started in Wuhan (China) on December 2019 reporting a number of more than 84.4 millions cases and 1.8 millions deaths on January 3rd 2021.In this work and to forecast the COVID-19 cases in Algeria, we used two models: the logistic growth model and the polynomial regression model using data of COVID-19 cases reported by the Algerian ministry of health from February 25th to December 2nd, 2020. Results showed that the polynomial regression model fitted better the data of COVID-19 in Algeria the Logistic model. The first model estimated the number of cases on January, 19th 2021 at 387673 cases. This model could help the Algerian authorities in the fighting against this disease.


2018 ◽  
Author(s):  
Emanuel A. Fronhofer ◽  
Lynn Govaert ◽  
Mary I. O’Connor ◽  
Sebastian J. Schreiber ◽  
Florian Altermatt

AbstractThe logistic growth model is one of the most frequently used formalizations of density dependence affecting population growth, persistence and evolution. Ecological and evolutionary theory and applications to understand population change over time often include this model. However, the assumptions and limitations of this popular model are often not well appreciated.Here, we briefly review past use of the logistic growth model and highlight limitations by deriving population growth models from underlying consumer-resource dynamics. We show that the logistic equation likely is not applicable to many biological systems. Rather, density-regulation functions are usually non-linear and may exhibit convex or both concave and convex curvatures depending on the biology of resources and consumers. In simple cases, the dynamics can be fully described by the continuous-time Beverton-Holt model. More complex consumer dynamics show similarities to a Maynard Smith-Slatkin model.Importantly, we show how population-level parameters, such as intrinsic rates of increase and equilibrium population densities are not independent, as often assumed. Rather, they are functions of the same underlying parameters. The commonly assumed positive relationship between equilibrium population density and competitive ability is typically invalid. As a solution, we propose simple and general relationships between intrinsic rates of increase and equilibrium population densities that capture the essence of different consumer-resource systems.Relating population level models to underlying mechanisms allows us to discuss applications to evolutionary outcomes and how these models depend on environmental conditions, like temperature via metabolic scaling. Finally, we use time-series from microbial food chains to fit population growth models and validate theoretical predictions.Our results show that density-regulation functions need to be chosen carefully as their shapes will depend on the study system’s biology. Importantly, we provide a mechanistic understanding of relationships between model parameters, which has implications for theory and for formulating biologically sound and empirically testable predictions.


2001 ◽  
Author(s):  
Peter Vadasz ◽  
Alisa S. Vadasz

Abstract A neoclassical model is proposed for the growth of cell and other populations in a homogeneous habitat. The model extends on the Logistic Growth Model (LGM) in a non-trivial way in order to address the cases where the Logistic Growth Model (LGM) fails short in recovering qualitative as well as quantitative features that appear in experimental data. These features include in some cases overshooting and oscillations, in others the existence of a “Lag Phase” at the initial growth stages, as well as an inflection point in the “In curve” of the population size. The proposed neoclassical model recovers also the Logistic Growth Curve as a special case. Comparisons of the solutions obtained from the proposed neoclassical model with experimental data confirm its quantitative validity, as well as its ability to recover a wide range of qualitative features captured in experiments.


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