[MARMAM] COURSE Network analysis (food webs) for ecologists using R (NTWA02)

Oliver Hooker oliverhooker at prstatistics.com
Mon Feb 26 15:40:08 PST 2018


Network analysis for ecologists using R (NTWA02)

www.prstatistics.com/course/network-analysis-for-ecologists-using-r-ntwa02/

This course will be delivered b Dr Marco Scotti in Glasgow from the 9th 
- 13th April 2018

This course will cover in food web analysis using a network approach 
with a strong emphasis on marine life and is therefore relevant to many 
people studying feeding habits of marine mammals.

Course overview:
The first graphical representation of a food web dates back to 1880, 
with the pioneering works of Lorenzo Camerano. Since then, research on 
ecological networks has further developed and ecology is one of the 
fields that contributed the most to the growth of network science. 
Nowadays, ecologists routinely apply network analysis with a diverse set 
of objectives that range from studying the stability of ecological 
communities to quantifying energy flows in ecosystems.

The course is intended to provide the participants theoretical knowledge 
and practical skills for the study of food webs. First, lessons and 
exercises will introduce basic principles of network theory. Second, 
ecological examples will be focused on binary food webs, networks 
depicting who eats whom in ecosystems. Algorithms quantifying either 
global food web properties or single species features within the trophic 
network will be introduced. Third, we will study how the architecture of 
the food webs can be used to investigate robustness to biodiversity 
loss, thus helping to predict cascading extinction events. Fourth, 
ecosystem network analysis (ENA), a suite of matrix manipulation 
routines for the study of energy/matter circulation in ecosystems, will 
be presented. Then, we will apply the qualitative algorithm of loop 
analysis to describe how the impacts of perturbations (e.g. overfishing, 
species invasion and global warming) may propagate through food web 
structure. Finally, we will learn how to visualize food web graphs to 
illustrate their features in an intuitive and fancy way.

Monday 9th – Classes from 09:00 to 17:00
Module 1: Introduction to graph theory and network science.
Basic terminology for learning the language of networks: from nodes and 
links to degree distribution.
Three types of mathematical graphs and their properties: random 
networks, small-world networks, and scale-free networks.

Tuesday 10th – Classes from 09:00 to 17:00
Module 2: The use of graph theory in ecology: (1) networks representing 
various interactions in ecological communities (e.g., predator-prey and 
plant-pollinator networks); (2) networks illustrating interactions at 
different hierarchical levels (e.g., social networks at the population 
level and species dispersal in the landscape graph).
Who eats whom in ecosystems and at which rate? Binary and weighted food 
web networks.
Quantitative descriptors of food web networks (e.g., fraction of basal, 
intermediate and top species, connectance and link density).

Wednesday 11th – Classes from 09:00 to 17:00
Module 3: The structural properties of food web networks.
Biodiversity loss and food web network robustness. How to predict 
secondary extinctions using the information embedded in the network 
structure of the food webs.
The relevance of bipartite networks in ecology for the description of 
various interaction types (e.g., plant-pollinator and plant-seed 
disperser relationships).

Thursday 12th – Classes from 09:00 to 17:00
Module 4: Ecosystem network analysis (ENA): basic principles and 
algorithms.
Trophic considerations: the effective trophic position of species in 
acyclic food webs.
Finn cycling index and the amount of cycling in ecosystems.
Loop analysis: basic principles and its use for modelling signed 
digraphs.
Application of the qualitative algorithm of loop analysis to predict how 
food web interactions can mediate ecosystem responses to perturbations.

Friday 13th – Classes from 09:00 to 16:00
Module 5: Can network analysis help to better understand possible 
consequences of global warming on ecological communities?
Network visualization with R: how to change the layout of graphs 
illustrating food web interactions and bipartite networks.

Email oliverhooker at statistics.com with any questions.

Check our sister sites
www.PRstatistics.com (ecology and life sciences)
www.PRinformatics.com (bioinformatics and data science)
www.PSstatistics (behaviour and cognition)

Upcoming courses below

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1.	February 19th – 23rd 2018
MOVEMENT ECOLOGY (MOVE01)
Margam Discovery Centre, Wales, Dr Luca Borger, Dr Ronny Wilson, Dr 
Jonathan Potts
www.prstatistics.com/course/movement-ecology-move01/

2.	February 19th – 23rd 2018
GEOMETRIC MORPHOMETRICS USING R (GMMR01)
Margam Discovery Centre, Wales, Prof. Dean Adams, Prof. Michael Collyer, 
Dr. Antigoni Kaliontzopoulou
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/
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3.	March 5th - 9th 2018
SPATIAL PRIORITIZATION USING MARXAN (MRXN01)
Margam Discovery Centre, Wales, Jennifer McGowan
www.prstatistics.com/course/introduction-to-marxan-mrxn01/

4.	March 12th - 16th 2018
ECOLOGICAL NICHE MODELLING USING R (ENMR02)
Glasgow, Scotland, Dr. Neftali Sillero
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr02/

5.	March 19th – 23rd 2018
BEHAVIOURAL DATA ANALYSIS USING MAXIMUM LIKLIHOOD IN R (BDML01)
Glasgow, Scotland, Dr William Hoppitt
http://www.psstatistics.com/course/behavioural-data-analysis-using-maximum-likelihood-bdml01/
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6.	April 9th – 13th 2018
NETWORK ANAYLSIS FOR ECOLOGISTS USING R (NTWA02
Glasgow, Scotland, Dr. Marco Scotti
www.prstatistics.com/course/network-analysis-ecologists-ntwa02/

7.	April 16th – 20th 2018
INTRODUCTION TO STATISTICAL MODELLING FOR PSYCHOLOGISTS USING R (IPSY01)
Glasgow, Scotland, Dr. Dale Barr, Dr Luc Bussierre
http://www.psstatistics.com/course/introduction-to-statistics-using-r-for-psychologists-ipsy01/

8.	April 23rd – 27th 2018
MULTIVARIATE ANALYSIS OF ECOLOGICAL COMMUNITIES USING THE VEGAN PACKAGE 
(VGNR01)
Glasgow, Scotland, Dr. Peter Solymos, Dr. Guillaume Blanchet
www.prstatistics.com/course/multivariate-analysis-of-ecological-communities-in-r-with-the-vegan-package-vgnr01/

9.	April 30th – 4th May 2018
QUANTITATIVE GEOGRAPHIC ECOLOGY: MODELING GENOMES, NICHES, AND 
COMMUNITIES (QGER01)
Glasgow, Scotland, Dr. Dan Warren, Dr. Matt Fitzpatrick
www.prstatistics.com/course/quantitative-geographic-ecology-using-r-modelling-genomes-niches-and-communities-qger01/
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10.	May 7th – 11th 2018 ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL 
ECOLOGICAL DATA USING R (MVSP02)
CANADA (QUEBEC), Prof. Pierre Legendre, Dr. Guillaume Blanchet
www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp03/
11.	May 14th - 18th 2018
INTRODUCTION TO MIXED (HIERARCHICAL) MODELS FOR BIOLOGISTS (IMBR01)
CANADA (QUEBEC), Prof Subhash Lele
www.prstatistics.com/course/introduction-to-mixed-hierarchical-models-for-biologists-using-r-imbr01/

12.	May 21st - 25th 2018
INTRODUCTION TO PYTHON FOR BIOLOGISTS (IPYB05)
SCENE, Scotland, Dr. Martin Jones
http://www.prinformatics.com/course/introduction-to-python-for-biologists-ipyb05/

13.	May 21st - 25th 2018
INTRODUCTION TO REMOTE SENISNG AND GIS FOR ECOLOGICAL APPLICATIONS 
(IRMS01)
Glasgow, Scotland, Prof. Duccio Rocchini, Dr. Luca Delucchi
www.prinformatics.com/course/introduction-to-remote-sensing-and-gis-for-ecological-applications-irms01/

14.	May 28th – 31st 2018
STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR (SIMM04)
CANADA (QUEBEC) Dr. Andrew Parnell, Dr. Andrew Jackson
www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm04/

15.	May 28th – June 1st 2018
ADVANCED PYTHON FOR BIOLOGISTS (APYB02)
SCENE, Scotland, Dr. Martin Jones
www.prinformatics.com/course/advanced-python-biologists-apyb02/
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16.	June 12th - 15th 2018
SPECIES DISTRIBUTION MODELLING (DBMR01)
Myuna Bay sport and recreation, Australia, Prof. Jane Elith, Dr. 
Gurutzeta Guillera
www.prstatistics.com/course/species-distribution-models-using-r-sdmr01/

17.	June 18th – 22nd 2018
STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS 
USING R (SEMR02)
Myuna Bay sport and recreation, Australia, Dr. Jon Lefcheck
www.prstatistics.com/course/structural-equation-modelling-for-ecologists-and-evolutionary-biologists-semr02/

18.	June 25th – 29th 2018
SPECIES DISTRIBUTION/OCCUPANCY MODELLING USING R (OCCU01)
Glasgow, Scotland, Dr. Darryl McKenzie
www.prstatistics.com/course/species-distributionoccupancy-modelling-using-r-occu01/
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19.	July 2nd - 5th 2018
SOCIAL NETWORK ANALYSIS FOR BEHAVIOURAL SCIENTISTS USING R (SNAR01)
Glasgow, Scotland, Prof James Curley
http://www.psstatistics.com/course/social-network-analysis-for-behavioral-scientists-snar01/

20.	July 8th – 12th 2018
MODEL BASE MULTIVARIATE ANALYSIS OF ABUNDANCE DATA USING R (MBMV02)
Glasgow, Scotland, Prof David Warton
www.prstatistics.com/course/model-base-multivariate-analysis-of-abundance-data-using-r-mbmv02/

21.	July 16th – 20th 2018
PRECISION MEDICINE BIOINFORMATICS: FROM RAW GENOME AND TRANSCRIPTOME 
DATA TO CLINICAL INTERPRETATION (PMBI01)
Glasgow, Scotland, Dr Malachi Griffith, Dr. Obi Griffith
www.prinformatics.com/course/precision-medicine-bioinformatics-from-raw-genome-and-transcriptome-data-to-clinical-interpretation-pmbi01/

22.	July 23rd – 27th 2018
EUKARYOTIC METABARCODING (EUKB01)
Glasgow, Scotland, Dr. Owen Wangensteen
http://www.prinformatics.com/course/eukaryotic-metabarcoding-eukb01/
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-- 
Oliver Hooker PhD.
PR statistics

2017 publications -

Ecosystem size predicts eco-morphological variability in post-glacial 
diversification. Ecology and Evolution. In press.

The physiological costs of prey switching reinforce foraging 
specialization. Journal of animal ecology.

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