Dear all!

Please note the announcement below for the next RSS Highlands group
meeting held jointly with the Ecology group at Aberdeen University. Also
note that the subseqent meeting of the Highlands group will be the joint
meeting with St. Andrews University and take place on Wednesday, May 14.
The speakers there will be Peter Bickel and Prof. Hans van Houwelingen.
A more detailed announcement of this meeting will follow later.


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Joint Aberdeen University/RSS Highland Local Group Meeting:
Statistical Methods in Population Ecology

Speakers:
Stijn Bierman (Biomathematics & Statistics Scotland, Edinburgh): The
analysis of data from two contrasting types of large-scale ecological
surveys

Thomas Cornulier (Aberdeen University/BIOresc, Mammal Research
Institute, Polish Academy of Sciences)::
New approaches for predicting farmland bird
population dynamics with data and process uncertainty


Venue:  Zoology Lecture Theatre, Zoology Building, Aberdeen University
(see http://www.abdn.ac.uk/central/vcampus/ for directions)

Time: 2:15 - 4:30pm on Weds, 30th April 2008

Timetable:
2:15 Stijn Bierman
3:15 Tea/Coffee
3:30 Thomas Cornulier

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Abstracts:

Stijn Bierman, Chris Glasbey, Adam Butler, Glenn Marion, Ingolf Kuhn
(Biomathematics & Statistics Scotland, Edinburgh):
The analysis of data from two contrasting types of large-scale
ecological surveys

We present the results of research into suitable statistical approaches
for the analysis of data arising from two contrasting types of
large-scale ecological surveys, each with different questions of
interest: biological atlas data and data on population sizes from a
sample of spatial locations. In the case of biological atlases, data
collected by large numbers of volunteers are aggregated over both space
and time in an attempt to give a coarse but as complete as possible
representation of the distribution of species over large geographical
areas. The statistical interpretation of these data is complicated
because species are not perfectly detected. We present a number of
model-based approaches for the analysis of these data, and illustrate
these using the German Atlas of Vascular plants. In contrast, many
large-scale ecological survey schemes collect data on population sizes
from a sample of spatial locations within a region, and use this sample
to estimate (trends in) regional population densities. These data can
typically be recorded with little error but only a small sample of the
total area of interest will be available. Here, we use a variety of data
sets with complete enumerations of spatial populations to explore the
relative efficiency of combinations of spatial survey designs and
design-based estimators of standard errors of sample means.


Thomas Cornulier (Aberdeen University/BIOresc, Mammal Research
Institute, Polish Academy of Sciences):
New approaches for predicting farmland bird
population dynamics with data and process uncertainty
Mechanistic models should predict population dynamics better than
descriptive ones under new environments. However, there is often
considerable uncertainty in the parameters estimated from field data and
in the demographic processes for a particular species. Within this
UKPopNet project, we aimed at aimed at harnessing new estimation methods
to fit mechanistic models to a range a data types. Using Bayesian
approaches, we improved existing models for estimating demographics
parameters such as survival. We also developed a new approach based on
mixture models for estimating so far unavailable parameters such as the
number of breeding attempts. Using state-space models, we integrated
these estimates and manipulated model structure in order to investigate
different regulation or limitation processes, e.g. density-dependence
mechanisms, variation in the number of breeding attempts, habitat loss.
We will show how data and process uncertainties affect predictions for
the yellowhammer, a declining farmland bird in the UK.

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Dr Claus-D. Mayer                    | http://www.bioss.ac.uk
Biomathematics & Statistics Scotland | email: [log in to unmask]
Rowett Research Institute            | Telephone: +44 (0) 1224 716652
Aberdeen AB21 9SB, Scotland, UK.     | Fax: +44 (0) 1224 715349
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