scholarly journals On Random Population Growth Punctuated by Geometric Catastrophic Events

2020 ◽  
Author(s):  
Thierry E. Huillet
Keyword(s):  
Markov Chain ◽  
Population Growth ◽  
Population Models ◽  
Recent Past ◽  
Catastrophic Events ◽  
Mass Removal ◽  
Random Immigration

Catastrophe Markov chain population models have received a lot of attention in the recent past. Besides systematic random immigration events promoting growth, we study a particular case of populations simultaneously subject to the effect of geometric catastrophes that cause recurrent mass removal. We describe the subtle balance between the two such contradictory effects.

Causes and consequences of variation in plant population growth rate: a synthesis of matrix population models in a phylogenetic context

2010 ◽  
Vol 13 (9) ◽  
pp. 1182-1197 ◽  
Author(s):  
Yvonne M. Buckley ◽  
Satu Ramula ◽  
Simon P. Blomberg ◽  
Jean H. Burns ◽  
Elizabeth E. Crone ◽  
...  
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Population Growth Rate ◽  
Population Models ◽  
Plant Population ◽  
Matrix Population Models

Resource Allocation Optimization Problem on the Population Growth Model

2013 ◽  
Vol 291-294 ◽  
pp. 1507-1513
Author(s):  
Yi Hong Luo ◽  
Shu Guang Zhang
Keyword(s):  
Resource Allocation ◽  
Population Growth ◽  
Growth Model ◽  
Economic Benefit ◽  
Optimization Problem ◽  
Industrial Structure ◽  
Population Models ◽  
Death Process ◽  
Pde Model

In this paper we mainly investigated the resource allocation optimization problem in three population models: death process, PDE model and birth and density-independent growth model. Considering the influence on population growth from different factors, find the best proportion of population to obtain the biggest economic benefit. Furthermore, we consider the effect on resource allocation from one more industrial structure on density-independent growth model. Finally, we compared the above models.

Structured Population Models

2021 ◽  
pp. 47-60
Author(s):  
Timothy E. Essington
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Matrix Model ◽  
Age Structure ◽  
Population Growth Rate ◽  
Population Models ◽  
State Variables ◽  
Elasticity Analysis ◽  
Structured Population Models ◽  
Structured Population

The chapter “Structured Population Models” illustrates how one adds more detail to a model, first through density-independent models, then by showing common matrix-model formulations and how those are used to reveal properties of structured models (e.g. population growth rate, stage/age structure). Structured population models have more detail than their nonstructured counterparts. They account for the differences among individuals within a population, usually by explicitly modeling them as distinct state variables. Elasticity analysis is introduced as a way to identify life stages that have a disproportionately large influence on population growth rate. Structured density-dependent models are briefly introduced as extensions on these models.

scholarly journals Assessing the Viability of the Sarasota Bay Community of Bottlenose Dolphins

2021 ◽  
Vol 8 ◽  
Author(s):  
Robert C. Lacy ◽  
Randall S. Wells ◽  
Michael D. Scott ◽  
Jason B. Allen ◽  
Aaron A. Barleycorn ◽  
...  
Keyword(s):  
Life History ◽  
Population Growth ◽  
Adult Survival ◽  
Model Parameters ◽  
Catastrophic Events ◽  
Demographic Rates ◽  
Sarasota Bay ◽  
Population Demographic ◽  
Over Time

Population models, such as those used for Population Viability Analysis (PVA), are valuable for projecting trends, assessing threats, guiding environmental resource management, and planning species conservation measures. However, rarely are the needed data on all aspects of the life history available for cetacean species, because they are long-lived and difficult to study in their aquatic habitats. We present a detailed assessment of population dynamics for the long-term resident Sarasota Bay common bottlenose dolphin (Tursiops truncatus) community. Model parameters were estimated from 27 years of nearly complete monitoring, allowing calculation of age-specific and sex-specific mortality and reproductive rates, uncertainty in parameter values, fluctuation in demographic rates over time, and intrinsic uncertainty in the population trajectory resulting from stochastic processes. Using the Vortex PVA model, we projected mean population growth and quantified causes of variation and uncertainty in growth. The ability of the model to simulate the dynamics of the population was confirmed by comparing model projections to observed census trends from 1993 to 2020. When the simulation treated all losses as deaths and included observed immigration, the model projects a long-term mean annual population growth of 2.1%. Variance in annual growth across years of the simulation (SD = 3.1%) was due more to environmental variation and intrinsic demographic stochasticity than to uncertainty in estimates of mean demographic rates. Population growth was most sensitive to uncertainty and annual variation in reproduction of peak breeding age females and in calf and juvenile mortality, while adult survival varied little over time. We examined potential threats to the population, including increased anthropogenic mortality and impacts of red tides, and tested resilience to catastrophic events. Due to its life history characteristics, the population was projected to be demographically stable at smaller sizes than commonly assumed for Minimum Viable Population of mammals, but it is expected to recover only slowly from any catastrophic events, such as disease outbreaks and spills of oil or other toxins. The analyses indicate that well-studied populations of small cetaceans might typically experience slower growth rates (about 2%) than has been assumed in calculations of Potential Biological Removal used by management agencies to determine limits to incidental take of marine mammals. The loss of an additional one dolphin per year was found to cause significant harm to this population of about 150 to 175 animals. Beyond the significance for the specific population, demographic analyses of the Sarasota Bay dolphins provide a template for examining viability of other populations of small cetaceans.

Density-Independent Population Growth

2020 ◽  
pp. 15-28
Author(s):  
Michael J. Fogarty ◽  
Jeremy S. Collie
Keyword(s):  
Population Growth ◽  
Continuous Time ◽  
Essential Feature ◽  
Survival Rates ◽  
Aquatic Organisms ◽  
Population Models ◽  
Life History Stage ◽  
Death Rates ◽  
Independent Population ◽  
The Difference

Population growth rate depends on the difference between birth and death rates. The simplest population models assume that these rates are constant and do not depend on population size or density. Nor do they consider the size or age of the individuals in the population. These models predict exponential growth or decline depending on the balance between birth and death rates. Aquatic organisms of different life stages and ages typically have different survival rates and produce different numbers of offspring; therefore, depending on the objectives of the analysis, it may be necessary to structure population models by age, size, or life-history stage to capture this essential feature. Population models are typically cast in either continuous time using differential equations or in discrete time using difference equations. The former may be more appropriate in ‘constant’ environments while the latter may be better suited for application in seasonal environments.

scholarly journals A modelling exercise to show why population models should incorporate distinct life histories of dispersers

2018 ◽  
Author(s):  
Jacques A. Deere ◽  
Ilona van den Berg ◽  
Gregory Roth ◽  
Isabel M. Smallegange
Keyword(s):  
Life History ◽  
Population Growth ◽  
Life Histories ◽  
Population Level ◽  
Population Models ◽  
Integral Projection Model ◽  
Projection Model ◽  
Individual Level ◽  
Population Growth Rates ◽  
Dispersal Probability

AbstractDispersal is an important form of movement influencing population dynamics, species distribution, and gene flow between populations. In population models, dispersal is often included in a simplified manner by removing a random proportion of the population. Many ecologists now argue that models should be formulated at the level of individuals instead of the population-level. To fully understand the effects of dispersal on natural systems, it is therefore necessary to incorporate individual-level differences in dispersal behaviour in population models. Here we parameterised an integral projection model (IPM), which allows for studying how individual life histories determine population-level processes, using bulb mites, Rhizoglyphus robini, to assess to what extent dispersal expression (frequency of individuals in the dispersal stage) and dispersal probability affect the proportion of dispersers and natal population growth rate. We find that allowing for life-history differences between resident phenotypes and disperser phenotypes shows that multiple combinations of dispersal probability and dispersal expression can produce the same proportion of leaving individuals. Additionally, a given proportion of dispersing individuals results in different natal population growth rates. The results highlight that dispersal life histories, and the frequency with which disperser phenotypes occur in the natal population, significantly affect population-level processes. Thus, biological realism of dispersal population models can be increased by incorporating the typically observed life history differences between resident phenotypes and disperser phenotypes, and we here present a methodology to do so.

scholarly journals UNDERSTANDING URBAN REGENERATION IN TURKEY

2016 ◽  
Vol XLI-B4 ◽  
pp. 669-675
Author(s):  
E. Candas ◽  
J. Flacke ◽  
T. Yomralioglu
Keyword(s):  
Population Growth ◽  
Natural Hazards ◽  
Spatial Data ◽  
Urban Regeneration ◽  
Disaster Risk ◽  
Regeneration Process ◽  
Land Values ◽  
Planning Tool ◽  
Recent Past ◽  
Rapid Population Growth

In Turkey, rapid population growth, informal settlements, and buildings and infrastructures vulnerable to natural hazards are seen as the most important problems of cities. Particularly disaster risk cannot be disregarded, as large parts of various cities are facing risks from earthquakes, floods and landslides and have experienced loss of lives in the recent past. Urban regeneration is an important planning tool implemented by local and central governments in order to reduce to disaster risk and to design livable environments for the citizens. The Law on the Regeneration of Areas under Disaster Risk, commonly known as the Urban Regeneration Law, was enacted in 2012 (Law No.6306, May 2012). The regulation on Implementation of Law No. 6306 explains the fundamental steps of the urban regeneration process. The relevant institutions furnished with various authorities such as expropriation, confiscation and changing the type and place of your property which makes urban regeneration projects very important in terms of property rights. Therefore, urban regeneration projects have to be transparent, comprehensible and acceptable for all actors in the projects. In order to understand the urban regeneration process, the legislation and projects of different municipalities in Istanbul have been analyzed. While some steps of it are spatial data demanding, others relate to land values. In this paper an overview of the urban regeneration history and activities in Turkey is given. Fundamental steps of the urban regeneration process are defined, and particularly spatial-data demanding steps are identified.

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