Population modelling including spatially explicit models.

2021 ◽  
pp. 303-321
Author(s):  
Donald L. J. Quicke ◽  
Buntika A. Butcher ◽  
Rachel A. Kruft Welton
Keyword(s):  
Natural Selection ◽  
Statistical Analysis ◽  
Open Source ◽  
Programming Language ◽  
Genetic Drift ◽  
Spatially Explicit ◽  
Population Modelling ◽  
Mathematical Functions ◽  
The Third ◽  
Spatially Explicit Models

Abstract R is an open-source statistical environment modelled after the previously widely used commercial programs S and S-Plus, but in addition to powerful statistical analysis tools, it also provides powerful graphics outputs. R can be used for some quite fast modelling jobs but its speed is nowhere near that of a compiled programming language such as C++. This chapter shows how user-defined functions can be used to perform highly repetitive jobs efficiently, and demonstrates various mathematical functions. The first example shows how a vector can be incremented and the calculated points plotted on a graph as the simulation proceeds. The second example runs a loop, and each time passes values to a user-defined function, and receives back multiple values from that function, which it then stores for plotting later. The third example is necessarily more complex and shows how R code can be used to carry out spatially explicit analyses. Finally, a simple example shows how R can be used to teach how evolution takes place, even in the absence of natural selection due to genetic drift and population bottle-necking.

Population modelling including spatially explicit models.

2021 ◽  
pp. 303-321
Author(s):  
Donald L. J. Quicke ◽  
Buntika A. Butcher ◽  
Rachel A. Kruft Welton
Keyword(s):  
Natural Selection ◽  
Statistical Analysis ◽  
Open Source ◽  
Programming Language ◽  
Genetic Drift ◽  
Spatially Explicit ◽  
Population Modelling ◽  
Mathematical Functions ◽  
The Third ◽  
Spatially Explicit Models

Abstract R is an open-source statistical environment modelled after the previously widely used commercial programs S and S-Plus, but in addition to powerful statistical analysis tools, it also provides powerful graphics outputs. R can be used for some quite fast modelling jobs but its speed is nowhere near that of a compiled programming language such as C++. This chapter shows how user-defined functions can be used to perform highly repetitive jobs efficiently, and demonstrates various mathematical functions. The first example shows how a vector can be incremented and the calculated points plotted on a graph as the simulation proceeds. The second example runs a loop, and each time passes values to a user-defined function, and receives back multiple values from that function, which it then stores for plotting later. The third example is necessarily more complex and shows how R code can be used to carry out spatially explicit analyses. Finally, a simple example shows how R can be used to teach how evolution takes place, even in the absence of natural selection due to genetic drift and population bottle-necking.

scholarly journals Sisvar: a computer statistical analysis system

2011 ◽  
Vol 35 (6) ◽  
pp. 1039-1042 ◽  
Author(s):  
Daniel Furtado Ferreira
Keyword(s):  
Statistical Analysis ◽  
Programming Language ◽  
Scientific Community ◽  
Free Software ◽  
Exact Science ◽  
Analysis Software ◽  
The Third ◽  
Statistical Analysis System ◽  
Analysis System ◽  
Statistical Analysis Software

Sisvar is a statistical analysis system, first released in 1996 although its development began in 1994. The first version was done in the programming language Pascal and compiled with Borland Turbo Pascal 3. Sisvar was developed to achieve some specific goals. The first objective was to obtain software that could be used directly on the statistical experimental course of the Department of Exact Science at the Federal University of Lavras. The second objective was to initiate the development of a genuinely Brazilian free software program that met the demands and peculiarities of research conducted in the country. The third goal was to present statistical analysis software for the Brazilian scientific community that would allow research results to be analyzed efficiently and reliably. All of the initial goals were achieved. Sisvar gained acceptance by the scientific community because it provides reliable, accurate, precise, simple and robust results, and allows users a greater degree of interactivity.

scholarly journals Lessons learned from comparing spatially explicit models and the Partners in Flight approach to estimate population sizes of boreal birds in Alberta, Canada

The Condor ◽  
2020 ◽  
Vol 122 (2) ◽  
Author(s):  
Péter Sólymos ◽  
Judith D Toms ◽  
Steven M Matsuoka ◽  
Steven G Cumming ◽  
Nicole K S Barker ◽  
...  
Keyword(s):  
North America ◽  
Time Of Day ◽  
Lessons Learned ◽  
Population Estimates ◽  
Spatially Explicit ◽  
Species Variation ◽  
Detection Distance ◽  
Spatially Explicit Models ◽  
Population Sizes ◽  
Partners In Flight

Abstract Estimating the population abundance of landbirds is a challenging task complicated by the amount, type, and quality of available data. Avian conservationists have relied on population estimates from Partners in Flight (PIF), which primarily uses roadside data from the North American Breeding Bird Survey (BBS). However, the BBS was not designed to estimate population sizes. Therefore, we set out to compare the PIF approach with spatially explicit models incorporating roadside and off-road point-count surveys. We calculated population estimates for 81 landbird species in Bird Conservation Region 6 in Alberta, Canada, using land cover and climate as predictors. We also developed a framework to evaluate how the differences between the detection distance, time-of-day, roadside count, and habitat representation adjustments explain discrepancies between the 2 estimators. We showed that the key assumptions of the PIF population estimator were commonly violated in this region, and that the 2 approaches provided different population estimates for most species. The average differences between estimators were explained by differences in the detection-distance and time-of-day components, but these adjustments left much unexplained variation among species. Differences in the roadside count and habitat representation components explained most of the among-species variation. The variation caused by these factors was large enough to change the population ranking of the species. The roadside count bias needs serious attention when roadside surveys are used to extrapolate over off-road areas. Habitat representation bias is likely prevalent in regions sparsely and non-representatively sampled by roadside surveys, such as the boreal region of North America, and thus population estimates for these regions need to be treated with caution for certain species. Additional sampling and integrated modeling of available data sources can contribute towards more accurate population estimates for conservation in remote areas of North America.

Exploring Genetic Drift & Natural Selection through a Simulation Activity

1998 ◽  
Vol 60 (9) ◽  
pp. 681-683 ◽  
Author(s):  
Timothy J. Maret ◽  
Steven W. Rissing
Keyword(s):  
Natural Selection ◽  
Genetic Drift

scholarly journals Incoherent dimensionality in fisheries management: consequences of misaligned stock assessment and population boundaries

2020 ◽  
Author(s):  
Aaron M Berger ◽  
Jonathan J Deroba ◽  
Katelyn M Bosley ◽  
Daniel R Goethel ◽  
Brian J Langseth ◽  
...  
Keyword(s):  
Population Structure ◽  
Stock Assessment ◽  
Spatially Explicit ◽  
Spatial Simulation ◽  
Management Options ◽  
Spatially Explicit Models ◽  
Fisheries Policy ◽  
Simulation Estimation ◽  
Definition Of ◽  
Dynamic Population

Abstract Fisheries policy inherently relies on an explicit definition of management boundaries that delineate the spatial extent over which stocks are assessed and regulations are implemented. However, management boundaries tend to be static and determined by politically negotiated or historically identified population (or multi-species) units, which create a potential disconnect with underlying, dynamic population structure. The consequences of incoherent management and population or stock boundaries were explored through the application of a two-area spatial simulation–estimation framework. Results highlight the importance of aligning management assessment areas with underlying population structure and processes, especially when fishing mortality is disproportionate to vulnerable biomass among management areas, demographic parameters (growth and maturity) are not homogenous within management areas, and connectivity (via recruitment or movement) unknowingly exists among management areas. Bias and risk were greater for assessments that incorrectly span multiple population segments (PSs) compared to assessments that cover a subset of a PS, and these results were exacerbated when there was connectivity between PSs. Directed studies and due consideration of critical PSs, spatially explicit models, and dynamic management options that help align management and population boundaries would likely reduce estimation biases and management risk, as would closely coordinated management that functions across population boundaries.

An Open Source Finance System for Stocks Backtesting Trade Strategies

2021 ◽  
Vol 12 (2) ◽  
pp. 52-65
Author(s):  
Eviatar Rosenberg ◽  
Dima Alberg
Keyword(s):  
User Interface ◽  
Open Source ◽  
Programming Language ◽  
Capital Market ◽  
Historical Data ◽  
Trading Strategies ◽  
Market Volatility ◽  
Finance System ◽  
Python Programming Language ◽  
Python Programming

A significant part of pension savings is in the capital market and exposed to market volatility. The COVID-19 pandemic crisis, like the previous crises, damaged the gains achieved in those funds. This paper presents a development of open-source finance system for stocks backtesting trade strategies. The development will be operated by the Python programming language and will implement application user interface. The system will import historical data of stocks from financial web and will produce charts for analysis of the trends in stocks price. Based on technical analysis, it will run trading strategies which will be defined by the user. The system will output the trade orders that should have been executed in retrospect and concluding charts to present the profit and loss that would occur to evaluate the performance of the strategy.

De pensioenbescherming van flexibele werknemers in België

2006 ◽  
Vol 22 (2) ◽  
Author(s):  
Annelies Debels ◽  
Hans Peeters ◽  
Gert Verschraegen ◽  
Jos Berghman
Keyword(s):  
Statistical Analysis ◽  
Old Age ◽  
Pension System ◽  
Panel Study ◽  
Research Strategy ◽  
The Third ◽  
Temporal Flexibility ◽  
Part Time ◽  
Coordinated Regulation ◽  
Pension Benefits

Old age protection of flexible workers in Belgium Old age protection of flexible workers in Belgium This article investigates to what extent the Belgian pension system is adapted to the proliferation of a-typical forms of employment. Are there any differences between the old age protection of flexible and non-flexible workers? What are the effects of flexible employment on participation in the three pension pillars and on the level of pension benefits? To answer these questions, the article pursues a double research strategy: an analysis of Belgian legislation and relevant collective labour agreements is complemented with a statistical analysis on the Panel Study of Belgian Households (PSBH). The analyses show that part-time employment results in a lower pension, while other forms of temporal flexibility such as temporary leave arrangements and temporary unemployment do not. In the second pillar we find that contractual and transitional flexible workers are discriminated. Finally, the results indicate that flexible workers do not compensate for lower pension protection through increased participation in the third pension pillar. Our findings suggest that a re-assessment of the system of ‘assimilated’ periods is required, as well as the development of a system of coordinated regulation for the three pension pillars.

The Causal Structure of Natural Selection

2021 ◽  
Author(s):  
Charles H. Pence
Keyword(s):  
Natural Selection ◽  
Case Studies ◽  
Genetic Drift ◽  
Evolutionary Theory ◽  
Causal Structure ◽  
Philosophy Of Biology ◽  
Philosophy Of Physics ◽  
Potential Value ◽  
Multi Level ◽  
Evolutionary Explanations

Recent arguments concerning the nature of causation in evolutionary theory, now often known as the debate between the 'causalist' and 'statisticalist' positions, have involved answers to a variety of independent questions – definitions of key evolutionary concepts like natural selection, fitness, and genetic drift; causation in multi-level systems; or the nature of evolutionary explanations, among others. This Element offers a way to disentangle one set of these questions surrounding the causal structure of natural selection. Doing so allows us to clearly reconstruct the approach that some of these major competing interpretations of evolutionary theory have to this causal structure, highlighting particular features of philosophical interest within each. Further, those features concern problems not exclusive to the philosophy of biology. Connections between them and, in two case studies, contemporary metaphysics and philosophy of physics demonstrate the potential value of broader collaboration in the understanding of evolution.

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