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Network analysis for ecologists using R (NTWA02)
9 April 2018 - 13 April 2018£275.00 - £480.00
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.
Research postgraduates, practicing academics in ecology, specifically food webs and professionals in government and industry.
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google Map
Availability – 24 places
Duration – 5 days
Contact hours – Approx. 37 hours
ECT’s – Equal to 3 ECT’s
Language – English
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, welcome dinner Monday evening, farewell dinner Thursday evening, refreshments and accommodation. Self-catering facilities are available in the accommodation. Accommodation is approximately a 6-minute walk from the PR statistics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 8th April (after 5pm) and departure Friday 13th April (accommodation must be vacated by 9am). An additional nights accommodation can be purchased, departure 9am Saturday morning email for details.
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email firstname.lastname@example.org
Cancellation policy: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com Failure to attend will result in the full cost of the course being charged. In the unfortunate event that PR~statistics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PR~statistics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
There will be morning lectures based on the modules outlined in the course timetable. In the afternoon there will be practicals based on the topics covered that morning. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data to discuss if time permits.
Assumed quantitative knowledge
Some basic understanding of how network analysis can be applied.
Assumed computer background
Familiarity with R. Ability to import/export data, manipulate data frames.
Equipment and software requirements
A laptop/personal computer with a working version of R or RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links
The following libraries should be installed:
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Meet at 43 Cook Street, Glasgow G5 8JN at approx. 17:00 onwards
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.
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)