Recent activity

COURSE - Network analysis (food webs)for ecologists using R (NTWA02)

Oliver Hooker, February 27, 2018

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 seabirds.

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 with any questions.

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

Upcoming courses below

  1. February 19th – 23rd 2018 MOVEMENT ECOLOGY (MOVE01) Margam Discovery Centre, Wales, Dr Luca Borger, Dr Ronny Wilson, Dr Jonathan Potts

  2. February 19th – 23rd 2018 GEOMETRIC MORPHOMETRICS USING R (GMMR01) Margam Discovery Centre, Wales, Prof. Dean Adams, Prof. Michael Collyer, Dr. Antigoni Kaliontzopoulou

  1. March 5th - 9th 2018 SPATIAL PRIORITIZATION USING MARXAN (MRXN01) Margam Discovery Centre, Wales, Jennifer McGowan

  2. March 12th - 16th 2018 ECOLOGICAL NICHE MODELLING USING R (ENMR02) Glasgow, Scotland, Dr. Neftali Sillero

  3. March 19th – 23rd 2018 BEHAVIOURAL DATA ANALYSIS USING MAXIMUM LIKLIHOOD IN R (BDML01) Glasgow, Scotland, Dr William Hoppitt

  1. April 9th – 13th 2018 NETWORK ANAYLSIS FOR ECOLOGISTS USING R (NTWA02 Glasgow, Scotland, Dr. Marco Scotti

  2. April 16th – 20th 2018 INTRODUCTION TO STATISTICAL MODELLING FOR PSYCHOLOGISTS USING R (IPSY01) Glasgow, Scotland, Dr. Dale Barr, Dr Luc Bussierre

  3. April 23rd – 27th 2018 MULTIVARIATE ANALYSIS OF ECOLOGICAL COMMUNITIES USING THE VEGAN PACKAGE (VGNR01) Glasgow, Scotland, Dr. Peter Solymos, Dr. Guillaume Blanchet

  4. April 30th – 4th May 2018 QUANTITATIVE GEOGRAPHIC ECOLOGY: MODELING GENOMES, NICHES, AND COMMUNITIES (QGER01) Glasgow, Scotland, Dr. Dan Warren, Dr. Matt Fitzpatrick

  1. May 7th – 11th 2018 ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA USING R (MVSP02) CANADA (QUEBEC), Prof. Pierre Legendre, Dr. Guillaume Blanchet

  3. May 21st - 25th 2018 INTRODUCTION TO PYTHON FOR BIOLOGISTS (IPYB05) SCENE, Scotland, Dr. Martin Jones

  4. May 21st - 25th 2018 INTRODUCTION TO REMOTE SENISNG AND GIS FOR ECOLOGICAL APPLICATIONS (IRMS01) Glasgow, Scotland, Prof. Duccio Rocchini, Dr. Luca Delucchi

  5. May 28th – 31st 2018 STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR (SIMM04) CANADA (QUEBEC) Dr. Andrew Parnell, Dr. Andrew Jackson

  6. May 28th – June 1st 2018 ADVANCED PYTHON FOR BIOLOGISTS (APYB02) SCENE, Scotland, Dr. Martin Jones

  1. June 12th - 15th 2018 SPECIES DISTRIBUTION MODELLING (DBMR01) Myuna Bay sport and recreation, Australia, Prof. Jane Elith, Dr. Gurutzeta Guillera

  2. June 18th – 22nd 2018 STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS USING R (SEMR02) Myuna Bay sport and recreation, Australia, Dr. Jon Lefcheck

  3. June 25th – 29th 2018 SPECIES DISTRIBUTION/OCCUPANCY MODELLING USING R (OCCU01) Glasgow, Scotland, Dr. Darryl McKenzie

  1. July 2nd - 5th 2018 SOCIAL NETWORK ANALYSIS FOR BEHAVIOURAL SCIENTISTS USING R (SNAR01) Glasgow, Scotland, Prof James Curley

  2. July 8th – 12th 2018 MODEL BASE MULTIVARIATE ANALYSIS OF ABUNDANCE DATA USING R (MBMV02) Glasgow, Scotland, Prof David Warton


  4. July 23rd – 27th 2018 EUKARYOTIC METABARCODING (EUKB01) Glasgow, Scotland, Dr. Owen Wangensteen

-- 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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