Congratulations to Ming Zhou who won the runner up prize for her poster at the Royal Statistical Society’s Conference held 7 to 10 September 2015 at Exeter University. Her poster was entitled Novel removal models for amphibian and reptile populations.
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Rachel, Eleni, Ming, Anita, Byron and Diana attend the Royal Statistical Society Conference in Exeter.
On Tuesday evening Ming presented a poster on Novel removal models for amphibian and reptile populations. We are delighted that Ming won the runner-up prize for her poster.
n Wednesday afternoon Diana and Anita gave talks in the contributed session on ecology. Diana’s talk was on Parameter Redundancy in Ecological Integrated Population Models and Anita’s talk was on Detecting heterogeneity in capture-recapture models: diagnostic goodness-of-fit tests and score tests.
Later Wednesday afternoon Eleni and Rachel, along with Roland from St Andrews, gave invited talks in a session on Recent Advances in Statistical Ecology. This was part of the invited sessions organized by The Environmental Statistics Section of Royal Statistical Society. Eleni talked on Bayesian non-parametric population ecology models and Rachel talked on Integrated population model selection in ecology.
Wednesday evening Byron gave a talk on Multivariate methods and ecology as part of a special session celebrating the work of Wojtek Krzanowoski.
NCSE summer Meeting
Byron Morgan, Rachel McCrea, Anita Jeyam, Ming Zhou, Natoya Jourdain, Takis Besbeas, Emily Dennis, Bee Kumphakarm and Diana Cole attended the NCSE summer meeting from 29th June to 1st July at the Penryn campus of the University of Exeter, outside Falmouth, Cornwall.
Rachel gave a talk on Multistate modelling of guppy data.
Guppies inhabit streams in Trinidad and habitats can be categorised into high and low predation areas. Experimental transplants of guppies from high to low predation streams were performed in 2008 and 2009. All introduced fish were adult and individually marked at introduction and mark-recapture data is collected each month, along with individual level data is also collected as well as location in the steam data. She discussed the challenges of analysing these data and presented modelling approaches for answering key ecological questions.
Natoya gave a talk on Abundance estimation using integrated modelling of unmarked animal data from camera traps.
She talked about using camera trap data to estimate animal density when the animals do not have unique markings, using the random encounter model.
Byron gave a talk on Modelling meetkats
He presented results from a multi-state analysis of Meerkats. Interesting features include the facts that the animals live in social groups, and are cooperative breeders: usually only the dominant female in each group reproduces, and other females assist the dominant female. There is a remarkable discrepancy in lifespans, with the dominant females greatly outliving other females.
Anita gave a talk on Detecting heterogeneity in capture-recapture models: diagnostic goodness-of-fit tests
Capture-recapture models have increased in complexity in order to be more biologically realistic. It is possible to fit many models to the same dataset, and the best model is generally chosen using information criteria, which will select the least worst model among the subset of tested models. Hence, it is important to check that candidate models fit the data adequately. She presented work investigating the use of diagnostic goodness-of-fit tests to find out whether this type of heterogeneity can be detected and specifically identified: for instance, does heterogeneity in capture affect the tests differently from a combination of trap-dependence and transience? She derived a specific diagnostic test for heterogeneity in capture and use simulation to assess its performance.
Takis talked about Efficient model-fitting for N-mixtures
Estimating population abundance is an important component of ecological research. N-mixture models can be used to estimate animal abundance from counts with both spatial and temporal replication without requiring individuals to be indentified. The original N-mixture model was developed for closed populations but the model has been recently extended to open populations by including population dynamics parameters. The models offer great potential but require an upper bound to be set, which complicates computations. Takis discussed efficient methods for fitting N-mixtures based on latent-state modelling.
Emily talked about Dynamic models for longitudinal butterfly data
Butterfly populations are undergoing changes in abundance, phenology and voltinism. As they respond sensitively and rapidly to changes in habitat and climate, their population status is a valuable indicator for changes in biodiversity and phenology. Emily presented models which provide succinct descriptions of seasonal insect count data from consecutive years. She demonstrated that her approach produced estimates of the key parameters of brood productivities, making the data from each brood a function of those in the previous brood.
Diana talked about Likelihood Profiles and Parameter Redundancy
She talked about how likelihood profiles can be used to detect parameter redundancy and also find estimable parameter combinations in parameter redundant models.
Bee talked about Approximate pseudo likelihood estimation of species richness
The distribution of the number of distinct species in a random sample of individuals from a population, where different species have unequal probabilities of selection, is known exactly, but the exact form is computationally intractable except for small samples. She talked an improved approximation is proposed and the performance of Hidaka’s method is explored.
Ming talked about The development of removal models with a hidden state: A case study for reptile and amphibian data
She talked about a new class of removal models which incorporate a hidden state, allowing the modelling of movement into and out of the observable study area.
3rd Meeting on Statistics, Athens
SE@K was represented at the 3rd Meeting on Statistics which took place in Athens, 24-26 June 2015: Official website.
The meeting, organised by Athens University of Economics and Business, was hosted at the Athens University Museum in Plaka, which offered great views of the Acropolis and the city of Athens: Some photos of the meeting.
There were sessions on Bayesian Modelling, Big Data and a session on capture-recapture models, organised by Luca Tardella. The session featured Chao and Zelterman estimators accounting for identified sources of heterogeneity, applied to data on whalesharks (by Alessio Farcomeni) and an R package for fitting flexible behavioral capture-recapture models to closed populations: BBRecapture R package (by Danillo Alunni Fegatelli).
Ben Hubbard’s Graduation
Congratulations to Dr Ben Hubbard who graduated in a congregation ceremony at Canterbury Cathedral on 13th July. Ben Hubbard did his PhD with Diana Cole, on parameter redundancy with applications in statistical ecology.
His thesis, and the computer code that supports the thesis, is available at http://www.kent.ac.uk/smsas/personal/djc24/benhubbardthesis.htm
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.
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
Anita Jeyam – 2015 Best Interdisciplinary Poster
Congratulations to Anita Jeyam for winning 2015 Best Interdisciplinary Poster at University of Kent Postgraduate Research Festival 2015.
Chen Yu’s Viva
Congratulation to Chen Yu, who passed his viva with minor corrections on 27th May. Chen’s project, The Use of Mixture Models in Capture-Recapture, was supervised by Byron Morgan and Diana Cole.
Abstract
Mixture models have been widely used to model heterogeneity. In this thesis,
we focus on the use of mixture models in capture{recapture, for both closed
populations and open populations. We provide both practical and theoretical
investigations. A new model is proposed for closed populations and the practical
diculties of model tting for mixture models are demonstrated for open
populations. As the number of model parameters can increase with the number
of mixture components, whether we can estimate all of the parameters using
the method of maximum likelihood is an important issue. We explore this
using formal methods and develop general rules to ensure that all parameters
are estimable.
Emily Dennis PhD Viva
Congratulation to Emily Dennis who passed her Viva on 27th May. Her project, on Development of statistical methods for monitoring insect abundance, was supervised by Byron Morgan and Martin Ridout.
Abstract
During a time of habitat loss, climate change and loss of biodiversity, efficient analytical tools are vital for population monitoring. This thesis concerns the modelling of butterflies, whose populations are undergoing various changes in abundance, range, phenology and voltinism. In particular, three-quarters of UK butterfly species have shown declines in their distribution, abundance, or both over a ten-year period. As the most comprehensively monitored insect taxon, known to respond rapidly and sensitively to change, butterflies are particularly valuable, but devising methods that can be fitted to large data sets is challenging and they can be computer intensive. We use occupancy models to formulate occupancy maps and novel regional indices, which will allow for improved reporting of changes in butterfly distributions. The remainder of the thesis focuses on models for count data. We show that the popular N-mixture model can sometimes produce infinite estimates of abundance and describe the equivalence of multivariate Poisson and negative-binomial models. We then present a variety of approaches for modelling butterfly abundance, where complicating features are the seasonal nature of the counts and variation among species. A generalised abundance index is very efficient compared to generalised additive models, which are currently used for annual reporting, and new parametric descriptions of seasonal variation produce novel and meaningful parameters relating to phenology and survival. We develop dynamic models which explicitly model dependence between broods and years. These new models will improve our understanding of the complex processes and drivers underlying changes in butterfly populations.
Congratulations to Emily Dennis for winning Faculty of Sciences prize for Postgraduate Research
In 2015 the University launched a new annual award scheme to recognise excellence in research as part of its 50th anniversary celebrations. 40 applications were received from across all three Faculties, and the Pro Vice-Chancellor for Research & Innovation, Prof Philippe De Wilde, led the panel that selected the winners. We are delighted to announce that Statistics PhD student Emily Dennis was among the award winners, receiving the Faculty of Sciences prize for Postgraduate Research.
The aim of Emily’s research is to develop new statistical methods for analysing national butterfly data and she has developed several novel statistical approaches for analysing data collected under the UK Butterfly Monitoring Scheme (UKBMS). Possibly the best insect data set in the world, it was not being put to optimal use. However, the method published by Emily in Methods in Ecology and Evolution is now being used in the reporting of UKBMS data and has received interest from Europe and North America.
Professor De Wilde said “The standard was extremely high, and reflects the diverse, exciting and vibrant research culture across the University.” Full details of all prize winners.