May 06, 2018
Revolution IX: descriptive statistics, hypothesis testing and quantitative ecology analysis in biological research
Place: Centre of Marine Sciences; University of Algarve
DESCRIPTION
Ecological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This course provides a practical introduction to quantitative ecology for students and practitioners who have realised that they need this opportunity.
The course is addressed to people who were perhaps more confused than enlightened by their lectures in statistics and who have never used a computer for much more than word processing and data entry. From this starting point, it slowly but surely instils an understanding of mathematics, statistics and programming, sufficient for initiating research in ecology. The course’s practical value is enhanced by extensive use of biological examples and the computer language R for graphics, programming and data analysis.
EXPECTED LEARNING OUTCOMES
This course does not intend to be a full introduction to statistics. The objective is to review the state-of-the-art statistical methods for analysis of ecological data, demonstrating the power of open source statistical software. We will provide hands-on experience for standard data analysis (cookbook), enabling participants to use the software on their own problems (take-home software).
The focus will be on giving the participants practical experience with R statistical software. The course material will be a blend of introductory lectures on R and practical sessions. Finally, we will walk through quantitative ecology concepts and methodologies, including sampling design, data preparation, diversity analyses, basic ANOVA methods, hypothesis testing, diversity analysis and linear modelling.
COURSE FORMAT
This course is divided into 10 theoretical-practical sessions of 4 hours long, including assignments through which you can practice your mastery under supervision. Sessions will take place during the afternoon (14:00 - 18:00 h).
We will provide students with a selection of data sets with which to work, however participants are encouraged to bring their own data.
LOCATION AND DURATION
Faro. Campus de Gambelas, Universidade do Algarve. Portugal
PRE-REQUISITES
This course requires some prior experience in statistics and elemental mathematics. Knowing object-oriented programming is not needed.
REGISTRATION FEE
Students: 250 €*
Other participants: 350 €
(Max. participants 10)
GRANTS
*We offer 4 grants for students. The grant will cover the half of the expenses for the course. Register to apply.
DEADLINES
Call for grants: 30 April
Resolution of grants: April
Registrations: May
Start sessions: May
March 20, 2017
Aplicaciones de la genética de poblaciones en ecología y gestión de recursos marinos y costeros
Place: Universidad Tecnológica de Panamá
November 07, 2016
Revolution VII: quantitative ecology and spatial prediction of species distribution
Place: University of Barcelona
Abstract
Ecological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This course provides a practical introduction to quantitative ecology for students and practitioners who have realised that they need this opportunity.
R is a language and environment for statistical computing and graphics (http://www.r-project.org). R provides a wide variety of statistical (linear and non-linear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques. Many users think of R as a statistics system. Furthermore, it is an environment within which statistical techniques are implemented. R can be extended (easily) via packages, covering a very wide range of modern statistics and much more. It has become the 'lingua franca' among statisticians, and is increasingly being used for data analysis among researchers. Many advanced or recent statistical and graphical/visualisation techniques are only available in R.
Expected learning outcomes
The focus will be on giving the participants practical experience with the software. The course material will be a blend of introductory lectures on R and practical sessions.
The objective is to review the state-of-the-art statistical methods for analysis of ecological data, demonstrating the power of open source statistical software. We will provide hands-on experience for standard data analysis (cookbook), enabling participants to use the software on their own problems (take-home software).
Sessions
Rspatial. Analysis of vector and raster cartography, also connecting with GRASS and QGIS.
aRtistics. Experimental design. Hypothesis contrast, ANOVA. Basic multivariate statistics.
multivaR. Diversity and multivariate analysis: ordination and gradient analyses, ENFA (Ecological Niche Factor Analysis), habitat suitability maps, metapopulation simulations.
lineaR. Construction, optimization and evaluation of linear models. Representation and spatial interpretation.
modelaRt. Construction, optimization and evaluation of non-linear models. Representation and spatial interpretation.
Prerequisites
This course requires some prior experience in statistics and elemental mathematics. Knowing object-oriented programming is not needed but R basic management is required.
Course format
This course is divided into 6 theoretical-practical sessions of 4 hours long, including assignments through which you can practice your mastery under supervision.
April 03, 2016
Revolution VI: descriptive statistics, hypothesis testing, modelling and spatial analysis of species diversity
Place: Centro de Ciências do Mar
Abstract
Ecological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This course provides a practical introduction to quantitative ecology for students and practitioners who have realised that they need this opportunity.
R is a language and environment for statistical computing and graphics (http://www.r-project.org). R provides a wide variety of statistical (linear and non-linear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques. Many users think of R as a statistics system. Furthermore, it is an environment within which statistical techniques are implemented. R can be extended (easily) via packages, covering a very wide range of modern statistics and much more. It has become the 'lingua franca' among statisticians, and is increasingly being used for data analysis among researchers. Many advanced or recent statistical and graphical/visualisation techniques are only available in R.
Expected learning outcomes
The focus will be on giving the participants practical experience with the software. The course material will be a blend of introductory lectures on R and practical sessions.
The objective is to review the state-of-the-art statistical methods for analysis of ecological data, demonstrating the power of open source statistical software. We will provide hands-on experience for standard data analysis (cookbook), enabling participants to use the software on their own problems (take-home software).
Sessions
aRound. Installation and management of R packages. Review of packages. Input and output of data.
useR. R session. Elements of the language.
gRaphics. Plotting functions and parameters.
autoR. Basic R programming and automatize tasks.
wRite. Preparing statistical reports using R.
Rspatial. Analysis of vector and raster cartography, also connecting with GRASS and QGIS.
aRtistics. Experimental design. Hypothesis contrast, ANOVA. Basic multivariate statistics.
multivaR. Diversity and multivariate analysis: ordination and gradient analyses, ENFA (Ecological Niche Factor Analysis), habitat suitability maps, metapopulation simulations.
lineaR. Construction, optimization and evaluation of linear models. Representation and spatial interpretation.
modelaRt. Construction, optimization and evaluation of non-linear models. Representation and spatial interpretation.
Prerequisites
This course requires some prior experience in statistics and elemental mathematics. Knowing
object-oriented programming is not needed.
Course format
This course is divided into 10 theoretical-practical sessions of 4 hours long, including assignments through which you can practice your mastery under supervision.
We will provide students with a selection of data sets with which to work, however participants are encouraged to bring their own data.
Inscriptions
Students: 250 €
Other participants: 350 €
Grants
We offer 4 grants for students. The grant will cover the half of the expenses for the course.
If you are interested, you should submit a short CV, a justification of your situation and a letter of motivation, explaining why and how do you think this course will improve you and your professional development, and how the grant will help you.
Deadlines
Call for grants: February
Resolution of grants: March
Inscriptions: February - April
Start sessions: April
February 01, 2016
aRe you Ready foR R?
Event at Mares conference 2016
Background
R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques.
Objective
R in a nutshell.
Methodology
We will start with basic R. Installation and management of packages. Review of elements of the language. Basic plotting functions and parameters.
Requirements
Participants should attend with their own PC and have the last version of R installed https://www.cran.r-project.org/). It is also recommended to install Rstudio (https://www.rstudio.com/). No previous experience with the software is required.
Expected learning outcomes
The focus of this workshop will be on giving the participants practical experience with the software. Course material will be provided during a practical sessions. This course does not intend to be a full introduction to statistics. The objective is to demonstrate the power of open source statistical software, providing hands-on experience and enabling participants to understand and use the software on their own problems.
February 01, 2016
Non statistics with R
Event at Mares conference 2016
Background
Many users think of R as a statistics system. Furthermore, it is an environment within which statistical techniques are implemented. R can be extended (easily) via packages, covering a very wide range of modern statistics and much more.
Objective
To discover new and interesting capabilities that R can provided us, such as GIS, modelling, text processor, automation and easy programming.
Methodology
We will start with some foundations and advance through the different capabilities that can be implemented or created. R programming and tasks automation. Statistical reports. Analysis of vector and raster cartography.
Requirements
Participants should attend with their own PC and have the last version of R installed https://www.cran.r-project.org/). It is also recommended to install Rstudio (https://www.rstudio.com/). Previous experience with the software is required.
Expected learning outcomes
The focus of this workshop will be on giving the participants practical experience with the software. Course material will be provided during a practical sessions.This course does not intend to be a full introduction to statistics. The objective is to demonstrate the power of open source statistical software, providing hands-on experience and enabling participants to understand and use the software on their own problems.
November 23, 2015
Aplicación de las herramientas moleculares a la gestión pesquera, acuicultura y repoblamiento de los pepinos de mar
Curso de introducción y actualización (in spanish)
Dirigido a Profesionales de la biología, biología marina, acuicultura y ciencias pesqueras, investigadores y estudiantes de pregrado y postgrado relacionados con el tema
Instructores
Mercedes González-Wangüemert & Jorge Domínguez-Godino
Centro de Ciencias del Mar (CCMAR), Faro, Portugal
Objetivos
Crear y fortalecer capacidades en el uso y manejo de técnicas moleculares en labores de investigación, evaluación, gestión y conservación de organismos marinos con énfasis en pepinos de mar
Contenido
1) Pepinos de mar como recurso pesquero
2) Desarrollo de la acuicultura de los pepinos de mar
3) Fundamentos básicos en genética
4) Marcadores genéticos: parámetros de diversidad y diferenciación
5) Gestión pesquera mediante el uso de herramientas moleculares
6) Aplicación de herramientas moleculares a la acuicultura
Fechas y horarios
Lunes 23 y martes 24 de noviembre de 8:00 am a 5:00 pm
miércoles 25 de noviembre de 8:00 am a 12:30 pm
20 horas
Coste
B/. 55.00 para profesionales y B/. 35.00 para estudiantes
El coste incluye certificado, refrigerio, almuerzos y materiales del curso
Lugar
Salón Elena Guardia de Lombardo
Centro de Visitantes del Parque Natural Metropolitano
Avenida Juan Pablo II
Ciudad de Panamá
November 24, 2014
Place: Centro de Ciências do Mar, Faro, Portugal
Ecological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This course provides a practical introduction to quantitative ecology for students and practitioners who have realised that they need this opportunity.
The course is addressed to people who were perhaps more confused than enlightened by their lectures in statistics and who have never used a computer for much more than word processing and data entry. From this starting point, it slowly but surely instils an understanding of mathematics, statistics and programming, sufficient for initiating research in ecology. The course’s practical value is enhanced by extensive use of biological examples and the computer language R for graphics, programming and data analysis.
R is a language and environment for statistical computing and graphics (http://www.r-project.org). R provides a wide variety of statistical (linear and non-linear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques. Many users think of R as a statistics system. Furthermore, it is an environment within which statistical techniques are implemented. R can be extended (easily) via packages, covering a very wide range of modern statistics and much more. It has become the \texit{lingua franca} among statisticians, and is increasingly being used for data analysis among researchers. Many advanced or recent statistical and graphical/visualisation techniques are only available in R.
This course is also intended for anyone who wishes to learn how to use the powerful open source statistical software package R. The course requires no previous knowledge of R. However, some prior experience in statistics and elemental mathematics is required.
May 13, 2014
CUMFISH Workshop: a new resource for a hungry fishery
Place: Centro de Ciências do Mar, Faro, Portugal
Sea cucumber stocks have been overfished in many countries from Indian and Pacific oceansas result of ever-increasing market demand, uncontrolled exploitation and/or inadequate fisheriesmanagement. The life-history traits of holothurians make them especially vulnerable to over-fishing because they have low or infrequent recruitment, high longevity and density-dependentreproductive success.
This situation has resulted in catch of new target species from Mediterranean Sea and North-eastern Atlantic Ocean whose fisheries are in the process of development. The main problemof these new fisheries is the existence of several sea cucumber species living at the same regionwith similar external morphology, very difficult identification and with scarce information aboutlife strategies, population dynamics and evolution history.
Therefore, the main goals of this project are to study the incipient sea cucumber fisheries ofthe Mediterranean Sea and Atlantic Ocean and to assess the genetic structure of these speciesincluding the selection effects of fisheries. To reach these aims we have carried out studieson ecology, reproduction, genetics, behaviour, growth and fisheries of six target species fromMediterranean Sea and North Atlantic Ocean. These results will be shown and discussed duringthe CUMFISH workshop.
April 07, 2013
Revolution IV: quantitative ecology and spatial prediction of species distribution
Place: Centro de Ciências do Mar, Faro, Portugal
Ecological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This course provides a practical introduction to quantitative ecology for students and practitioners who have realised that they need this opportunity.
The course is addressed to people who were perhaps more confused than enlightened by their lectures in statistics and who have never used a computer for much more than word processing and data entry. From this starting point, it slowly but surely instils an understanding of mathematics, statistics and programming, sufficient for initiating research in ecology. The course’s practical value is enhanced by extensive use of biological examples and the computer language R for graphics, programming and data analysis.
R is a language and environment for statistical computing and graphics (http://www.r-project.org). R provides a wide variety of statistical (linear and non-linear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques. Many users think of R as a statistics system. Furthermore, it is an environment within which statistical techniques are implemented. R can be extended (easily) via packages, covering a very wide range of modern statistics and much more. It has become the \texit{lingua franca} among statisticians, and is increasingly being used for data analysis among researchers. Many advanced or recent statistical and graphical/visualisation techniques are only available in R.
This course is also intended for anyone who wishes to learn how to use the powerful open source statistical software package R. The course requires no previous knowledge of R. However, some prior experience in statistics and elemental mathematics is required.
June 06, 2013
[OpenWorkshops]: Scientific writing using LaTeX advanced formatting of tables and figures, and bibliography management using BibTeX
Place: Centro de Ciências do Mar, Faro, Portugal
Background
This workshop intend to be a continuation of the previous LaTeX workshop.
Objective
To get you up to speed on the advanced formatting of tables and figures using LaTeX, and introduce the management of bibliographic databases and their incorporation into LaTeX.
Methodology
We will learn to format tables and advanced creation of figures. Finally, we will make presentations with Beamer. Then, we will introduce to the bibliographic management through the use of BIBTeX editors. We will be also introduced the styles support in LaTeX.
May 09, 2013
[OpenWorkshops]: Scientific writing using LaTeX
Place: Centro de Ciências do Mar, Faro, Portugal
Background
Latex handles all the formatting/presentation, allowing you to concentrate on content in a natural way of thinking. Latex produces “book quality” documents with an excellent support for formula and equations. It allows to handle labeling references, figures, tables and bibliography. Almost all of the journals accept this format. LaTeX could also help to create high quality documents which can be easily incorporated to open databases such as Sapientia.
Objective
This workshop does not intend to be a complete introduction to LaTeX. There are plenty of tutorials written on the internet. There is a simple goal: get you up to speed on using LaTeX for a correct way to communicate science.
Methodology
We will begin by writing a simple “Hello, World!” document, just to get you up and running. Then, we will show how to set the title page and abstract and spend some time discussing section headers. We will spend quite some time discussing tables and figures.
April 04, 2013
[OpenWorkshops]: Introduction to web publishing: Drupal
Place: Centro de Ciências do Mar, Faro, Portugal
Background
Drupal is an open source content management platform powering millions of websites and applications. It is built, used, and supported by an active and diverse community of people around the world.
Objective
This workshop shows how to get the most out of the self-hosted version of Drupal and create feature-rich blogs and websites.
Methodology
How to get a web host, set up a domain, download and configure. The workshop will dive fully into the tools in Drupal, demonstrating how to set up your profile and create content to share with your web audience.Installation, notes about Apache, PHP, MySql (database creation, permissions). Configuration, distributions and modules.
March 01, 2013
[OpenWorkshops]: Open Source GIS
Place: Centro de Ciências do Mar, Faro, Portugal
Background
The Open Source GIS space includes products to fill every level of the OpenGIS spatial data infrastructure stack. Existing products are now entering a phase of rapid refinement and enhancement, using the core software structures that are already in place. Open Source software can provide a feature-complete alternative to proprietary software in most system designs.
Objective
This workshop will make the framework of the state of the Open Source GIS. We will also introduce some of the most used GIS software.
Methodology
We will start introducing the different options, which are currently available. We will know about the different projects and their major characteristics.
Finally, we will make a practical GIS session, using some of the most used libraries (GDAL/OGR, Proj4) and software (GRASS, QGIS).
February 06, 2013
[OpenWorkshops]: Non statistics with R
Place: Centro de Ciências do Mar, Faro, Portugal
Background
R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques.Many users think of R as a statistics system. Furthermore, it is an environment within which statistical techniques are implemented. R can be extended (easily) via packages, covering a very wide range of modern statistics and much more.
Objective
To discover new and interesting capabilities that R can provided us, such as GIS, modelling, text processor, automation and easy programming.
Methodology
We will start with the foundations and advance through the different capabilities that can be implemented or created.
