Author Archives: Eleni Matechou

Papers

New paper by Eleni and colleagues in Environmental and Ecological Statistics

Bayesian analysis of Jolly-Seber type models;

Incorporating heterogeneity in arrival and departure

Eleni Matechou, Geoff K. Nicholls, Byron J. T. Morgan, Jaime A. Collazo, James E. Lyons

 

Abstract

We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.

Read the full paper (open-access) Matechou_et_al_2016_Bayesian_analysis_of_Jolly_Seber_type_models_EES

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Conferences/Meetings/Workshops

NERC Advanced Training Course

Statistical models for wildlife population assessment and conservation

 

9-13 January 2017

 

University of Kent

 

Deadline for applications: 5pm on Friday 14th of October 2016.

We have 30 fully-funded places (inc. travel and accommodation) and priority is given to NERC-funded PhD students but if spaces remain we are able to offer the funded places to other PhD students and early-career researchers.

Please e-mail a completed Application Form to R.S.McCrea@kent.ac.uk.

Within the environmental sector there is currently a shortage of practitioners equipped with the statistical modelling skills to carry out reliable population assessments. Consequently, environmental impact assessments (EIAs) and development mitigation projects often use population assessment protocols that are not fit-for-purpose1. The skills shortage arises because (1) recent advances in statistical models for population assessment are largely confined to the academic sector with little penetration to the end-users; and (2) although many postgraduate programmes have a statistical modelling training component, this often fails to expose PhD students to new models in the area and the potential applications these have for conservation practice2. This training programme will provide a cohort of PhD students and early career researchers/practitioners with the relevant modelling skills required for a career that involves wildlife population assessment for conservation.

 

  1. Griffiths, Foster, Wilkinson and Sewell (2015). Science, statistics and surveys: a herpetological perspective. Journal of Applied Ecology. doi: 10.1111/1365-2664.12463
  2. McCrea and Morgan (2015). Analysis of capture-recapture data. Chapman & Hall/CRC Press, Florida.

 

Proposed programme of the course

 

The workshop will focus on ecological questions that arise in conservation practice and use real case study data. Training will include individual-based models, such as capture-recapture, but will also embrace scenarios more frequently used in EIA, such as batch-marked, presence/absence, site occupancy and counts. Applications will include newts, butterflies, birds, bees, beetles, ibex and bats. Each module will be accompanied by a practical computer session using R and each module builds on the last so that delegates build a portfolio of statistical skills.

 

Training outcomes:  By the end of the course, attendees will be able to:

  • construct, interpret and fit relevant stochastic models, use different methods of inference, understand the pros and cons of Bayesian and classical methods and the use of prior information;
  • personalise R code to undertake modelling of their own research data;
  • understand data needs for animal population assessments for EIAs and conservation;
  • analyse animal population data to meet both conservation and commercial needs.

Draft timetable:

 

Module 1: Background in statistics and R (Monday PM)
  • Likelihood and probability theory
  •  Bayesian inference
  • Basic model assessment (AIC/absolute GOF)
  • Practical session: Introduction

 

Plenary session and Round table discussions (Tuesday AM)

 

Module 2: Understanding statistical uncertainty (Tuesday PM)
  • Imperfect detection
  • Data types, relationships and summaries.
  • Introduction to data sets/case studies (bees, butterflies, newts, mallards etc)
  • Practical session: converting format of data and summarising complex data.

 

Module 3: Model fitting and assessment (Wednesday AM+PM)
  • Estimating abundance
  • M0,Mtbh, removal
  • CR/RR
  • Occupancy
  • Practical session: model fitting, optimisation, use of packages.

 

Module 4: Modern challenges (Thursday AM)
  • Citizen science data
  • Small/sparse data and big data issues
  •  Cost-effectiveness in study design and statistical power.
  • Informative prior information.
  • Practical session: power analyses and adapting models

 

Module 5: Advanced stochastic modelling (Thursday PM)
  • modelling movement
  •  state uncertainty
  • species interaction
  • spatial models
  • integrated modelling
  • Practical session: use of Rjags, Bayesian graphical models using MCMC.

 

One-to-one consultation sessions (Friday AM)

 

Module 6: Advanced aspects of R (Friday AM)
  • Practical session: self-lead worksheets
  • Multistate examples
  • PR diagnosis
  • Diagnostic GOF testing
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Uncategorized

Statistical Ecology Research Festival (SERF)

The Statistical Ecology Research Festival (SERF) is a one day event for postgraduate students in Statistics and/or Ecology. SERF is a great opportunity for  statistics students to learn more about ecological data, how they are collected, what specific questions ecologists are trying to answer by collecting the data and the practical problems that can be encountered in the field. Ecology students will have the chance to learn more about the wide array of statistical techniques used to analyse ecological data, the challenges faced from a statistician’s perspective and emerging areas of statistical research.

SERF will comprise of oral presentations and posters, a round table discussion which will allow attendees to share their research and establish better connections, a discussion on future funding opportunities and a networking reception at the end of the day.

It will be a wonderful opportunity for research postgraduates from both statistical and ecological disciplines to interact with each other and showcase their research. As a result of sharing knowledge among attendees, SERF will generate ideas and approaches for future research in statistical ecology as well as partnerships among participants.

SE@K

We are the Statistical Ecology @Kent (SE@K) group at the School of Mathematics, Statistics & Actuarial Science at University of Kent. We are members of the National Centre for Statistical Ecology (NCSE). SERF is fully funded by Eastern Academic Research Consortium (Eastern ARC) in order to encourage interdisciplinary research.

Submitting an abstract

SERF is open to postgraduate research students/postdocs in statistical ecology or quantitative ecology, but priority will be given to those from Eastern ARC partner institutions (University of Kent, Essex and East Anglia).

Abstracts of no more than 500 words for a talk of 15 minutes including questions must be submitted using the online submission form accompanied by the name of the applicant and their institution and contact details by the 8th May 2016.

The abstracts will be judged on quality, novelty and relevance to SERF. The abstracts selected for oral presentation will be chosen to ensure a wide range of topics are covered during the day. Successful applicants will be notified by the 16th May.

Registration

Registration is free. Lunch and refreshments will be provided free of charge to all participants.

Please note that a limited number of travel expenses (up to £50) are available for presenters whose abstracts were accepted for oral presentations.

Programme for the day

Coming soon…

Location and directions

SERF  will take place on the 7th June at the University of Kent in Canterbury. The talks will take place in  Cornwallis Octagon Lecture Theatre 3 and the round table discussion and networking  in Cornwallis East Seminar Room 2. Both venues are one-minute away from Darwin College bus stop. The link below gives more information on travel and direction. Direction Guidelines

Follow-up material

Presentation slides and posters will be published here. Coming soon…

 Contact information

If you have further enquiries, please contact us at SERF@kent.ac.uk

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grants, Prizes

SE@K project awarded Sciences Faculty Competition scholarship

The project, titled  Studying migration patterns of UK bird populations using Bayesian nonparametric models, was proposed by Dr Eleni Matechou in collaboration with Dr Alison Johnston from the British Trust for Ornithology and Professor Jim Griffin from SMSAS.

Summary of the proposal: The PhD student on this collaborative project will develop and use novel and sophisticated statistical models, namely Bayesian nonparametric models, to understand patterns of bird migration within the UK. The data to be analysed refer to bird species that breed in the UK and spend the winter in Africa. These are collected by the BTO as part of the Constant Effort Sites (CES) monitoring scheme. The analyses will describe the migration patterns, phenology, population sizes and distribution of these species. Links between these demographic parameters and environmental covariates will be explored to explain the mechanisms leading to patterns and changes (for example, climate change leading to earlier migration). The results will also be used to inform conservation management strategies. As well as a number of scientific manuscripts describing the statistical models and the ecological processes, the student will also produce freely-available software that will be used by the BTO in the future and by any interested researchers to fit the models to their own data.

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Conferences, grants, Prizes

Congratulations to Ming for her IBC bursary

SE@K student Ming Zhou was awarded £500 for attending IBC 2016 in Victoria BC, Canada.

Ming’s application was judged by the Biometric Society and the Fisher Memorial Trust.

As a recipient of a bursary Ming will provide a one page report after the conference summarising how she has benefited scientifically from attendance, to be published on the Regional website.

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Conferences/Meetings/Workshops

Occupancy workshop

Diana, Eleni and Rachel gave a 3 day long workshop on occupancy modelling.

The workshop took place 13-15 of January at the University of Kent.

The 20 or so participants were exposed to the ideas behind basic and advanved occupancy models from classical and Bayesian perspectives.

There  were theory and practical sessions, the latter covering R and Presence.

On the last day, participants discussed about their own projects and data with the SE@K group. All of the projects were interesting and some will undoubtedly lead to more collaborations in the future.

 

 

 

 

 

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