News, Papers, Publications

New paper by Eleni and colleagues published in JABES

The paper, titled  “Caste-Specific Demography and Phenology in Bumblebees: Modelling BeeWalk Data”, by Eleni Matechou, Stephen N. Freeman, and Richard Comont is available open-access. 

The work presents novel dynamic mixture models for the monitoring of bumblebee populations on an unprecedented geographical scale, motivated by the UK citizen science BeeWalk.

The models allow us for the first time to estimate bumblebee phenology and within-season productivity, defined as the number of individuals in each caste per colony in the population in that year, from citizen science data.

All of these parameters are estimated separately for each caste, giving a means of considerable ecological detail in examining temporal changes in the complex life cycle of a social insect in the wild. Due to the dynamic nature of the models, we are able to produce population trends for a number of UK bumblebee species using the available time-series. Via an additional simulation exercise, we show the extent to which useful information will increase if the survey continues, and expands in scale, as expected.

Bumblebees are extraordinarily important components of the ecosystem, providing pollination services of vast economic impact and functioning as indicator species for changes in climate or land use. Our results demonstrate the changes in both phenology and productivity between years and provide an invaluable tool for monitoring bumblebee populations, many of which are in decline, in the UK and around the world.

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Books, Papers, Publications

50th anniversary of the Cormack-Jolly-Seber model

 

Just over 50 years ago, three papers appeared which independently described the fundamental approach for analyzing capture-recapture data. It is now called the Cormack-Jolly-Seber model. This anniversary is celebrated in the second issue of Statistical Science, 2016, guest edited by Steve Buckland and Byron Morgan. It features transcribed interviews with George Seber and Richard Cormack. In addition there are eight research papers that demonstrate how the capture- recapture area is still developing, with applications to genetics, social and medical areas, as well as ecology.

steve    rachel     byron

Shown in the photographs are Steve presenting a copy of the issue to Richard, in St Andrews University, Rachel Fewster, a co-author of two of the papers in the issue, presenting a copy to George, in the University of Auckland, and Byron presenting two copies to George Jolly’s two daughters Heather Hannah and Fiona Davies. A third copy goes to their brother David Jolly, who lives in Saudi Arabia.

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Publications

Rachel and Byron have had a paper published in Journal of the Royal Statistical Society – series C (Applied Statistics).

A new strategy for diagnostic model assessment in capture–recapture

Common to both diagnostic tests used in capture–recapture and score tests is the idea that starting from a simple base model it is possible to interrogate data to determine whether more complex parameter structures will be supported. Current recommendations advise that diagnostic tests are performed as a precursor to a model selection step. We show that certain well-known diagnostic tests for examining the fit of capture–recapture models to data are in fact score tests. Because of this direct relationship we investigate a new strategy for model assessment which combines the diagnosis of departure from basic model assumptions with a step-up model selection, all based on score tests. We investigate the power of such an approach to detect common reasons for lack of model fit and compare the performance of this new strategy with the existing recommendations by using simulation. We present motivating examples with real data for which the extra flexibility of score tests results in an improved performance compared with diagnostic tests.

The full pdf of the paper can be accessed at: http://onlinelibrary.wiley.com/doi/10.1111/rssc.12197/pdf

 

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Publications

New paper by Eleni, Rachel, Byron and colleagues

The Annals of Applied Statistics
2016, Vol. 10, No. 3, 1572–1589
DOI: 10.1214/16-AOAS949
© Institute of Mathematical Statistics, 2016

OPEN MODELS FOR REMOVAL DATA

BY ELENI MATECHOU, RACHEL S. MCCREA1, BYRON J. T. MORGAN,
DARRYN J. NASH AND RICHARD A. GRIFFITHS

University of Kent

Individuals of protected species, such as amphibians and reptiles, often
need to be removed from sites before development commences. Usually, the
population is considered to be closed. All individuals are assumed to (i) be
present and available for detection at the start of the study period and (ii) remain
at the site until the end of the study, unless they are detected. However,
the assumption of population closure is not always valid. We present
new removal models which allow for population renewal through birth and/or
immigration, and population depletion through sampling as well as through
death/emigration. When appropriate, productivity may be estimated and a
Bayesian approach allows the estimation of the probability of total population
depletion. We demonstrate the performance of the models using data on
common lizards, Zootoca vivipara, and great crested newts, Triturus cristatus.

Read the full paper here https://kar.kent.ac.uk/55734/

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Publications

Reproductive consequences of the timing of seasonal movements in a nonmigratory wild bird population – Publication in Ecology

 by Eleni Matechou1,4, San Chye Cheng2, Lindall R. Kidd3, and Colin J. Garroway3

Abstract:

Animal movement patterns, whether related to dispersal, migration, or ranging behaviors, vary in time. Individual movements reflect the outcomes of interactions between an individual’s condition and a multitude of underlying ecological processes. Theory predicts that when competition for breeding territories is high, individuals should arrive at breeding sites earlier than what would otherwise be optimal for breeding in the absence of competition. This is because priority at a site can confer significant competitive advantages leading to better breeding outcomes. Empirical data from long-distance migrants support this theory. However, it has not been tested within the context of fine-scale movements in nonmigratory populations. We assessed the effect of arrival time at a breeding site on reproductive outcomes in an intensively monitored resident population of Great Tits (Parus major). The population was monitored passively, via passive integrated transponder (PIT) tag loggers, and actively, via catching, during breeding and nonbreeding seasons. We developed new capture–recapture–resight models that use both data types to model breeding outcome conditional on the unknown individual arrival times. In accordance with theory, individuals arrived at the woods synchronously in waves that were large at the beginning of the nonbreeding season and small toward the end, with very few arrivals in the intervening period. There was a strong effect of arrival time on the probability of breeding; the earlier an individual arrived, the more likely it was to successfully establish a nest that reached the incubation period. However, once nests were established, they had equal probabilities of failing early, regardless of arrival time. Finally, there was moderate evidence of a negative effect of arrival time on the probability of successfully fledging nestlings. These empirical findings are consistent with theoretical models that suggest an important role for competition in shaping fine-scale seasonal movements. Our capture–recapture–resight models are extensible and suitable for a variety of applications, particularly when the goal is to estimate the effects of unobservable arrival times on subsequent ecological outcomes.  Read more.

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1School of Mathematics, Statistics and Actuarial Science, Cornwallis Building, University of Kent, Canterbury CT2 7NF United Kingdom

2Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG United Kingdom

3Edward Grey Institute of Ornithology, Department of Zoology, Tinbergen Building, University of Oxford, South Parks Road, Oxford OX1 3PS United Kingdom

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