Statistical models for the long-term monitoring of songbird populations: a Bayesian analysis of constant effort sites and ring-recovery data
Abstract
To underpin and improve advice given to government and other interested parties
on the state of Britain’s common songbird populations, new models for
analysing ecological data are developed in this thesis. These models use data
from the British Trust for Ornithology’s Constant Effort Sites (CES) scheme,
an annual bird-ringing programme in which catch effort is standardised. Data
from the CES scheme are routinely used to index abundance and productivity,
and to a lesser extent estimate adult survival rates. However, two features of
the CES data that complicate analysis were previously inadequately addressed,
namely the presence in the catch of “transient” birds not associated with the
local population, and the sporadic failure in the constancy of effort assumption
arising from the absence of within-year catch data. The current methodology
is extended, with efficient Bayesian models developed for each of these demographic
parameters that account for both of these data nuances, and from which
reliable and usefully precise estimates are obtained.
Of increasing interest is the relationship between abundance and the underlying
vital rates, an understanding of which facilitates effective conservation.
CES data are particularly amenable to an integrated approach to population
modelling, providing a combination of demographic information from a single
source. Such an integrated approach is developed here, employing Bayesian
methodology and a simple population model to unite abundance, productivity
and survival within a consistent framework. Independent data from ring-recoveries
provide additional information on adult and juvenile survival rates.
Specific advantages of this new integrated approach are identified, among which
is the ability to determine juvenile survival accurately, disentangle the probabilities
of survival and permanent emigration, and to obtain estimates of total
seasonal productivity.
The methodologies developed in this thesis are applied to CES data from Sedge
Warbler, Acrocephalus schoenobaenus, and Reed Warbler, A. scirpaceus.
Type
Thesis, PhD Doctor of Philosophy
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