scholarly journals Fitness landscapes and life-table response experiments predict the importance of local areas to population dynamics

Ecosphere ◽  
2017 ◽  
Vol 8 (7) ◽  
pp. e01869 ◽  
Author(s):  
Kristin Kane ◽  
James S. Sedinger ◽  
Daniel Gibson ◽  
Erik Blomberg ◽  
Michael Atamian
Keyword(s):  
Population Dynamics ◽  
Life Table ◽  
Fitness Landscapes ◽  
Local Areas ◽  
Life Table Response Experiments

Variation in the population dynamics of the palm Sabal yapa in a landscape shaped by shifting cultivation in the Yucatan Peninsula, Mexico

2007 ◽  
Vol 23 (2) ◽  
pp. 139-149 ◽  
Author(s):  
María T. Pulido ◽  
Teresa Valverde ◽  
Javier Caballero
Keyword(s):  
Population Dynamics ◽  
Life Table ◽  
Shifting Cultivation ◽  
Yucatan Peninsula ◽  
Positive Contribution ◽  
Matrix Population Models ◽  
Crop Fields ◽  
Mature Forest ◽  
Yucatán Peninsula ◽  
Life Table Response Experiments

To understand the population dynamics of a species, it is necessary to document the way in which its demographic behaviour varies through space and time. Anthropogenic disturbance, such as shifting cultivation, is an important factor causing demographic variation in many tropical non-timber forest products. The leaves of the palm Sabal yapa are an important non-timber forest product used for thatching by Mayan peoples. The demography of Sabal yapa was studied in three habitats (mature forest, successional forest and crop fields), representing successional phases along the slash-and-burn agricultural cycle in the Yucatan Peninsula. Matrix population models, along with elasticity analyses and life-table-response experiments were employed. Population growth rate differed between patches (MF: λ = 1.043; SF: λ = 1.027; CF: λ = 0.959). Only the λ value of the mature forest was significantly higher than unity. Fecundity and seedling survival were lowest in the crop fields and highest in the mature forest. The elasticity analyses and life-table-response experiments showed that entries with a high positive contribution to λ also showed high elasticity values, while those with a negative contribution to λ showed low elasticity. Thus, both analyses are crucial to understand the demography of a species and to aid in conservation and management practices.

Impact of temperature and dissolved oxygen level on the population dynamics of naidids and their reproduction in biological activated carbon filters: a life table demographic study

2019 ◽  
Vol 19 (5) ◽  
pp. 1363-1370
Author(s):  
Xiao-Bao Nie ◽  
Yu-Qing Wu ◽  
Yuan-Nan Long ◽  
Chang-Bo Jiang ◽  
Li Kong
Keyword(s):  
Population Dynamics ◽  
Drinking Water ◽  
Activated Carbon ◽  
Life Table ◽  
Doubling Time ◽  
Population Doubling ◽  
Population Doubling Time ◽  
Biological Activated Carbon ◽  
Water Plant ◽  
Water Plants

Abstract Aquatic macro-organisms, such as naidids, propagate excessively in biological activated carbon (BAC) filters. This has become a troublesome problem for drinking water plants. For successful control of naidid contamination risk, it is necessary to determine the population dynamics under different environmental conditions within drinking water plants, with special emphasis on BAC filters. In this study, field studies of naidid distribution in a drinking water plant were conducted, and the effects of temperature and dissolved oxygen (DO) on naidid population dynamics were investigated using the life table method. The results indicated that naidid pollution in the water plant occurred seasonally and was induced by the excessive propagation of naidids in the BAC filters. Increased temperature and DO increased the naidid intrinsic rate of natural increase and decreased the naidid population doubling time. The life table method was also used to acquire the reproductive parameters of naidids in BAC filters based on simulative experiments. These results indicated that naidids can reproduce asexually in BAC filters, and the population doubling time was 12.60 days.

scholarly journals Mean-field computational approach to HIV dynamics on a fitness landscape

2019 ◽  
Author(s):  
Hanrong Chen ◽  
Mehran Kardar
Keyword(s):  
Population Dynamics ◽  
T Cell ◽  
Population Size ◽  
Fitness Landscape ◽  
T Cell Responses ◽  
Fitness Landscapes ◽  
Stochastic Simulations ◽  
Emf Method ◽  
Cell Responses ◽  
Hiv Dynamics

AbstractDuring infection by the human immunodeficiency virus (HIV), mutations accumulate in the intra-host viral population due to selection imposed by host T cell responses. The timescales at which HIV residues acquire mutations in a host range from days to years, correlating with their diversity in the global population of hosts, and with the relative strengths at which different regions of the HIV sequence are targeted by the host. In recent years, “fitness landscapes” of HIV proteins have been estimated from the global HIV sequence diversity, and stochastic simulations ofin silicoHIV infection, using these inferred landscapes, were shown to generate escape mutations whose locations and relative timescales correlate with those measured in patients with known T cell responses. These results suggest that the residue-specific fitness costs and epistatic interactions in the inferred landscapes encode useful information allowing for predictions of the dynamics of HIV mutations; however, currently available computational approaches to HIV dynamics that make use of realistic fitness landscapes are limited to these fixed-population-size stochastic simulations, which require many simulation runs and do not provide further insight as to why certain mutations tend to arise in a given host and for a given sequence background. In this paper, we introduce and examine an alternative approach, which we designate the evolutionary mean-field (EMF) method. EMF is an approximate high-recombination-rate model of HIV replication and mutation, in whose limit the dynamics of a large, diverse population of HIV sequences becomes computationally tractable. EMF takes as input the fitness landscape of an HIV protein, the locations and strengths of a host’s T cell responses, and the infecting HIV strain(s), and outputs a set of time-dependent “effective fitnesses” and frequencies of mutation at each HIV residue over time. Importantly, the effective fitnesses depend crucially on the fitness costs, epistatic interactions, and time-varying sequence background, thus automatically encoding how their combined effect influences the tendency for an HIV residue to mutate, in a time-dependent manner. As a proof of principle, we apply EMF to the dynamics of the p24 gag protein infecting a host whose T cell responses are known, and show how features of the fitness landscape, relative strengths of host T cell responses, and the sequence background impact the locations and time course of HIV escape mutations, which is consistent with previous work employing stochastic simulations. Furthermore, we show how features of longer-term HIV dynamics, specifically reversions, may be described in terms of these effective fitnesses, and also quantify the mean fitness and site entropy of the intra-host population over time. Finally, we introduce a stochastic population dynamics extension of EMF, where population size changes depend crucially on the fitness of strains existing in the population at each time, unlike prior stochastic simulation approaches with a fixed population size or a time-varying one that is externally defined. The EMF method offers an alternative framework for studying how genetic-level attributes of the virus and host immune response impact both the evolutionary and population dynamics of HIV, in a computationally tractable way.Author summaryFitness landscapes of HIV proteins have recently been inferred from HIV sequence diversity in the global population of hosts, and have been used in simulations ofin silicoHIV infection to predict the locations and relative timescales of mutations arising in hosts with known immune responses. However, computational approaches to HIV dynamics using realistic fitness landscapes are currently limited to these fixed-population-size stochastic simulations, which require many simulation runs and do not provide further insight as to why certain mutations tend to arise in a given host and for a given sequence background. Here, we introduce an alternative approach designated the evolutionary mean-field (EMF) method, which is an approximate high-recombination-rate model of HIV dynamics. It takes as input an HIV fitness landscape, the locations and strengths of a host’s immune responses, and the infecting HIV strain(s), and outputs a set of time-dependent “effective fitnesses” and frequencies of mutation at each HIV residue over time. We apply EMF on an example to show how features of the fitness landscape, relative strengths of host immune responses, and the HIV sequence background modify the effective fitnesses and hence the locations and time course of HIV mutations. We also develop a stochastic population dynamics extension of EMF where population size changes depend crucially on the fitness of strains existing in the population at each time. The EMF method enables more detailed study of how genetic-level attributes of the virus and host immune response shape the evolutionary and population dynamics of HIV, in a computationally tractable way.

Demographic Responses of Estuarine Polychaetes to Pollutants: Life Table Response Experiments

1996 ◽  
Vol 6 (4) ◽  
pp. 1295-1313 ◽  
Author(s):  
Lisa Levin ◽  
Hal Caswell ◽  
Todd Bridges ◽  
Claudio DiBacco ◽  
Debra Cabrera ◽  
...  
Keyword(s):  
Life Table ◽  
Life Table Response Experiments ◽  
Demographic Responses
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