New Paper: Parameter redundancy in Jolly‐Seber tag loss models

Diana along with Wei Cai, Stephanie Yurchak and Laura Cowen have published the paper:

Parameter redundancy in Jolly‐Seber tag loss models

in Ecology and Evolution


1. Capture–recapture experiments are conducted to estimate population parameters such as population size, survival rates, and capture rates. Typically, individuals are captured and given unique tags, then recaptured over several time periods with the assumption that these tags are not lost. However, for some populations, tag loss cannot be assumed negligible. The Jolly‐Seber tag loss model is used when the no‐tag‐loss assumption is invalid. Further, the model has been extended to incorporate group heterogeneity, which allows parameters to vary by group membership. Many mark–recapture models become overparameterized resulting in the inability to independently estimate parameters. This is known as parameter redundancy.
2. We investigate parameter redundancy using symbolic methods. Because of the complex structure of some tag loss models, the methods cannot always be applied directly. Instead, we develop a simple combination of parameters that can be used to investigate parameter redundancy in tag loss models.
3. The incorporation of tag loss and group heterogeneity into Jolly‐Seber models does not result in further parameter redundancies. Furthermore, using hybrid methods we studied the parameter redundancy caused by data through case studies and generated tag histories with different parameter values.
4. Smaller capture and survival rates are found to cause parameter redundancy in these models. These problems resolve when applied to large populations.


New Paper by Emily and Byron: Integrated modelling of insect population dynamics at two temporal scales

Emily and Byron, along with Marc Kery, Armin Coray, Michael Schaub and Bruno Baur have published the paper:

Integrated modelling of insect population dynamics at two temporal scales

in Ecological Modelling.


Population size of species with birth-pulse life-cycles varies both within and between seasons, but most population dynamics models assume that a population can be characterised adequately by a single number within a season. However, within-season dynamics can sometimes be too substantial to be ignored when modelling dynamics between seasons. Typical examples are insect populations or migratory animals. Numerous models for only between-season dynamics exist, but very few have combined dynamics at both temporal scales.

In a new approach, we extend appreciably the models of Dennis et al. (2016b): we show how to adapt them for a generation time  year and fit an integrated population model for multiple data types, by maximising a joint likelihood for population counts of unmarked individuals and capture–recapture data from a study with marked individuals. We illustrate the approach using annual monitoring data for the endangered flightless beetle Iberodorcadion fuliginator from 18 populations in the Upper Rhine Valley for 1998–2016, with a 2-year life cycle. Standard likelihood methods are used for model fitting and comparison, and a concentrated (profile) likelihood approach provides computational efficiency.

Additional information from the capture–recapture data makes the population model more robust and, importantly, enables true, rather than relative, abundance to be estimated. A dynamic stopover model provides estimates of both survival and phenology parameters within a season, and also of productivity between seasons. For  I. fuliginator, we demonstrate a population decline since 1998 and how this links with productivity, which is affected by temperature. A delayed mean emergence date in recent years is also shown.

A main point of interest is the focus on the two temporal scales at which perhaps most animal populations vary: in the short-term, a population is seldom truly closed within a single season, and in the long-term (between seasons) it never is. Hence our models may serve as a template for a general description of population dynamics in many species. This includes rare species with limited data sets, for which there is a general lack of population dynamic models, yet conservation actions may greatly benefit from this kind of models.


PhD Project: Modelling Citizen-science Data for Butterflies and Moths: Where and When are they Flying?

Eleni Matechou, Emily Dennis, Richard Fox, Byron Morgan and Diana Cole are offering the statistics PhD project: Modelling Citizen-science Data for Butterflies and Moths: Where and When are they Flying?
At a time of biodiversity loss, including widely reported insect declines, citizen science data play a vital role in measuring changes in species’ populations and distributions and in seeking to understand the pressures influencing such changes. Butterflies and moths respond quickly to habitat and climatic change, and hence are valuable biodiversity indicators. In the UK, millions of species occurrence records for Lepidoptera have been gathered by two large citizen science recording schemes, of which the full potential has not been fully realized.

Analysing recording data of this nature presents unique challenges relating to their vast quantity but also associated sampling biases. Using cutting edge modelling, this project will maximise these valuable datasets to enhance our understanding of species’ phenology (flight periods), distribution and range dynamics to help inform future conservation delivery and policy for UK butterflies and moths.

The candidate will undertake new statistical model developments applied to citizen science data. The research will involve:

  • Critically assessing sampling design to determine how much data are needed to reliably estimate species’ occurrence trends – can occupancy models be used for rare species with small ranges?
  • Modelling species’ phenology from citizen science data to provide new insights on variation over space and time.
  • Applying state-of-the-art variable selection techniques to better describe drivers of species’ range and distribution change through suitable spatial and environmental covariates.

This project has been shortlisted for Aries funding. More details can be found at:



Invited talks at the RSS Conference 2020

Oscar and Alex presented their work at the (virtual) RSS conference 2020 during the invited session on “Challenges and advances of spatial modelling in ecology” organised by Rachel.

Oscar’s talk, titled “The Importance of spatio-temporal modelling in Ecology” described the importance spatio-temporal models to understand the relationship between species in a common area. Oscar explains the problem caused due to the wolf eradication in Yellowstone National Park in 1920’s and how the landscape changed from this eradication to the reintroduction in 1990’s.

Alex’s talk, titled “Interaction point processes in spatially explicit capture-recapture models” described his work on a spatial capture-recapture model incorporating interactions within and between individuals of two species. The model relies on the theory of interaction point processes. As inference for these processes cannot be performed using standard techniques due to the intractability of the likelihood, specific MCMC methods have to be used. The model is applied to a capture-recapture data-set of leopards and tigers collected in India.




RSS meeting on eDNA: Challenges and Opportunities now virtual

The meeting, initially planned for May 2020, will now take place virtually on the 16th of October.

The timetable for the day is

9.30-10  Kerry Walsh, Environment Agency: “Challenges and opportunities: A regulator’s perspective.”

10-10.15 discussion/change over

10.15-10.45  Naomi Ewald, FreshWater Habitats Trust: “Analysis of eDNA data to inform conservation priorities: case studies of long term species monitoring and short term before-after surveys.”

10.45-11 discussion/change over

11-11.30 morning break

11.30-12 Francesco Ficetola, University of Milan:  “Environmental DNA to track long-term changes of mountain ecosystem.”

12-12.15 discussion/change over

12.15-12.45 lunch break

12.45-13.15 Jim Griffin, University College London: “Modelling environmental DNA data; Bayesian variable selection accounting for false positive and false negative errors.”

13.15-13.30 discussion/change over

13.30-14 Doug Yu, University of East Anglia: “Managing wildlife with eDNA data: salmon, leeches, insects, and forests.”

14-14.30 discussion/close


Participants can register on the RSS website.


New paper: A Generic Method for Estimating and Smoothing Multispecies Biodiversity Indicators Using Intermittent Data

The paper, A Generic Method for Estimating and Smoothing Multispecies Biodiversity Indicators Using Intermittent Data, by Stephen Freeman, Nicholas Isaac, Panagiotis Besbeas, Emily Dennis and Byron Morgan has just been published in the Journal of Agricultural, Biological and Environmental Statistics



Biodiversity indicators summarise extensive, complex ecological data sets and are important in influencing government policy. Component data consist of time-varying indices for each of a number of different species. However, current biodiversity indicators suffer from multiple statistical shortcomings. We describe a state-space formulation for new multispecies biodiversity indicators, based on rates of change in the abundance or occupancy probability of the contributing individual species. The formulation is flexible and applicable to different taxa. It possesses several advantages, including the ability to accommodate the sporadic unavailability of data, incorporate variation in the estimation precision of the individual species’ indices when appropriate, and allow the direct incorporation of smoothing over time. Furthermore, model fitting is straightforward in Bayesian and classical implementations, the latter adopting either efficient Hidden Markov modelling or the Kalman filter. Conveniently, the same algorithms can be adopted for cases based on abundance or occupancy data—only the subsequent interpretation differs. The procedure removes the need for bootstrapping which can be prohibitive. We recommend which of two alternatives to use when taxa are fully or partially sampled. The performance of the new approach is demonstrated on simulated data, and through application to three diverse national UK data sets on butterflies, bats and dragonflies. We see that uncritical incorporation of index standard errors should be avoided.


New Paper: Predicting potential cambium damage and fire resistance in Pinus nigra Arn. ssp. salzmannii

The paper: Predicting potential cambium damage and fire resistance in Pinus nigra Arn. ssp. salzmannii by: ESPINOSA, J.; RODRÍGUEZ DE RIVERA, O.; MADRIGAL, J.; GUIJARRO, M; HERNANDO, C. , has just been published in Forest Ecology and Management.


Fire management can play a key role in ensuring stand maintenance in future scenarios of global change, particularly in Pinus nigra stands, which are known to be adapted to low-intensity surface fires through characteristics such as thick bark. In this study, laboratory tests were carried out to quantify cambium damage and fire resistance in P. nigra, by using a mass loss colorimeter device in a vertical configuration for the first time. In addition, low-intensity prescribed burning treatments were conducted in the field, and the field and laboratory data were compared. The following variables were used as proxy measures to assess cambium damage: time that temperature remained above 60 °C, heating rate and maximum absolute temperature in the inner bark area. The data were analysed using a Bayesian hierarchical approach (generalized linear mixed model). A threshold heat flux (25 kW m-2) for the time to ignition of bark was identified. A critical temperature of 60 °C was reached in the cambium during the combustion phase, after the flame was extinguished. The laboratory experiments showed, for the first time, the influence of flame residence time on the potential cambium damage. A bark thickness of 17 mm can be considered the threshold level for preventing critical temperatures being reached in Pinus nigra stands. The influence of bark thickness on protection against fire was confirmed, as was the importance of the coefficient of variation of bark thickness. The field results showed that flame characteristics (maximum temperature and residence time) were the most significant predictors of cambium damage. The combination of fire intensity and exposure time at low heat fluxes is more important than bark in determining cambium damage and may have important implications in the field of forest fuel management and in the ecology of pine forests.