# Elena N. Ieno's research while affiliated with University of Aberdeen and other places

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## Publications (107)

Nosema ceranae is an obligate intracellular parasite and the etiologic agent of Nosemosis that affects honeybees. Beside the stress caused by this pathogen, honeybee colonies are exposed to pesticides under beekeeper intervention, such as acaricides to control Varroa mites. These compounds can accumulate at high concentrations in apicultural matric...

In order to identify the best tools for stock assessment studies using fish parasites as biological indicators, different host traits (size, mass and age and their interaction with sex) were evaluated as descriptors of cumulative patterns of both parasite abundance and infracommunity species richness. The effect of such variables was analysed for a...

Scientific investigation is of value only insofar as relevant results are obtained and communicated, a task that requires organizing, evaluating, analysing and unambiguously communicating the significance of data. In this context, working with ecological data, reflecting the complexities and interactions of the natural world, can be a challenge. Re...

This book begins with an introduction to generalised additive models (GAM) using stable isotope ratios from squid. In Chapter 2 we explain additive mixed effects using polar bear movement data. In Chapter 3 we apply additive mixed effects models on coral reef data. Ruddy turnstone data are used in Chapter 4 to explain Poisson generalised additive m...

Benthic monitoring programs can be used to investigate the relationship
between shore birds and their intertidal food supply, and are particularly
helpful in areas of rapid habitat fragmentation and deterioration resulting
from human disturbance. Samborombon Bay in Buenos Aires Province,
Argentina is an area of importance for migratory shorebirds t...

The tooth histology of a total 22 and 95 short-beaked common dolphins (Delphinus delphis) from Scottish (UK) and Galician (Spain) waters, respectively, was examined to determine whether the incidence of mineralization anomalies could be related to certain stressful conditions linked with life-history events or to exposure to anthropogenic pollutant...

The book presents complete R code and explanation for estimating GLM and GLMM models from both the frequentist and Bayesian perspective. JAGS is used for Bayesian modeling.

http://www.highstat.com/BGGLM.htm

Explaining the coexistence of large numbers of rainforest tree species is a major challenge in tropical ecology. A possible coexistence mechanism is the partitioning of the forest light environment; species that grow well under a given light regime may not thrive in another. To test this hypothesis, Philipson et al. (2012) investigated how tree spe...

We measured the metabolic rate of nineteen wild and three captive, trained Southern sea lions (Otaria flavescens, Shaw 1800) during three behavioral states: resting in air (_ V O2 rest air), resting in water (_ V O2 rest water) and sub-merged swimming (_ V O2 sub swim) using open flow respirometry. We then used these values to estimate total cost o...

We analyzed long-term winter survey data (1956–2007) for three endangered waterbirds endemic to the Hawaiian Islands, the
Hawaiian moorhen (Gallinula chloropus sandvicensis), Hawaiian coot (Fulica alai), and Hawaiian stilt (Himantopus mexicanus knudseni). Time series were analyzed by species–island combinations using generalized additive models, wi...

This chapter discusses the multimetric TRophic IndeX (TRIX). It describes the effects of pollution over time, in order to inform management strategies such as cleanup operations and to set new regulations. The chapter presents two different statistical approaches. First it uses additive models incorporating temporal autocorrelation along with a spa...

Forensic pathologists and entomologists estimate the minimum post-mortem interval since a long time by describing the stage
of succession and development of the necrophagous fauna (Amendt et al. 2004). From very simple calculations at the beginning,
(Bergeret, see also Smith 1986) the discipline has evolved into a more mathematical one (e.g. Marche...

1. While teaching statistics to ecologists, the lead authors of this paper have noticed common statistical problems. If a random sample of their work (including scientific papers) produced before doing these courses were selected, half would probably contain violations of the underlying assumptions of the statistical techniques employed.
2. Some vi...

We examined the tooth ultra-structure of harbour porpoises (Phocoena phocoena) from Scottish waters to determine whether the incidence of mineralization anomalies could be related to certain life history events (e.g. the achievement of sexual maturation) as well as other factors that affect the general health of the individual (e.g. persistent orga...

Age estimation in odontocetes is based on counts of growth layer groups (GLGs) deposited in recording structures such as teeth. Generally, tooth sections are obtained using a cryostat microtome. However, some researchers prefer obtaining thin sections using a traditional paraffin microtome. Little information is available on the application of this...

In this chapter, we discuss models for zero-truncated and zero-inflated count data. Zero truncated means the response variable
cannot have a value of 0. A typical example from the medical literature is the duration patients are in hospital. For ecological
data, think of response variables like the time a whale is at the surface before re-submerging...

This chapter analyses amphibian fatalities along a road in Portugal. The data are counts of kills making a Gaussian distribution unlikely; restricting our choice of techniques. We began with generalised linear models (GLM) and generalised additive models (GAM) with a Poisson distribution, but these models were overdispersed. To solve this, you can...

In this chapter, we continue with Gaussian linear and additive mixed modelling methods and discuss their application on nested
data. Nested data is also referred to as hierarchical data or multilevel data in other scientific fields (Snijders and Boskers,
1999; Raudenbush and Bryk, 2002).

Predicting the spatial distribution of wildlife populations is an important component of the development of management strategies
for their conservation. Landscape structure and composition are important determinants of where species occur and the viability
of their populations. In particular, the amount of suitable habitat and its level of fragmen...

In this chapter, we apply mixed modelling to honeybee data. The data are considered nested because multiple observations were
taken from the same hive. A total of 24 hives were sampled.

This chapter revises the basic concepts of linear regression, shows how to apply linear regression in R, discusses model validation,
and outlines the limitations of linear regression when applied to ecological data. Later chapters present methods to overcome
some of these limitations; but as always before doing any complicated statistical analyses,...

In the previous chapter, we discussed violation of independence for measurements taken repeatedly over time and how temporal
correlation structures can be added to linear regression and additive models. We used a regular spaced data set. In this chapter,
we consider data measured at multiple spatial locations, and we show how similar correlation st...

This chapter looks at a data set where our first reaction was: ‘How in heavens name are we going to analyse these data?’ The data consist of a large number of phytoplankton species measured at 31 stations in Dutch estuarine and marine waters. Measurements took place 0–4 times per month from 1990 until present (2005). Environmental data (e.g. temper...

In Chapters 2 and 3 and in Appendix A, linear regression and additive modelling were discussed and various extensions allowing
for different variances, nested data, temporal correlation, and spatial correlation were then discussed in Chapters 4, 5,
6, and 7. In Chapters 8, 9, and 10, we discuss generalised linear modelling (GLM) and generalised add...

A generalised linear model (GLM) or a generalised additive model (GAM) consists of three steps: (i) the distribution of the
response variable, (ii) the specification of the systematic component in terms of explanatory variables, and (iii) the link
between the mean of the response variable and the systematic part. In Chapter 8, we discussed several...

In the previous chapter, we looked at linear regression, and although the word linear implies modelling only linear relationships,
this is not necessarily the case. A model of the form Y
i
= α + β
1 × X
i
+ β
2 × X
i
2 + ɛ
i
is a linear regression model, but the relationship between Y
i
and X
i
is modelled using a second-order polynomial fun...

In this chapter, we analyse three data sets; California birds, owls, and deer. In the first data set, the response variable
is the number of birds measured repeatedly over time at two-weekly intervals at the same locations. In the owl data set (Chapter
5), the response variable is the number of calls made by all offspring in the absence of the pare...

In Chapters 2 and 3, we reviewed linear regression and additive modelling techniques. In Chapters 4–7, we showed how to extend
these methods to allow for heterogeneity, nested data, and temporal or spatial correlation structures. The resulting methods
were called linear mixed modelling and additive mixed modelling (see the left hand pathway of Fig....

In this chapter, we analyse a data set consisting of signs of badger (Meles meles; see Fig. 22.1) activity around farms. The data are longitudinal and from multiple farms; so it is likely a temporal correlation
structure is required. The response variable is binary; the presence or absence of badger activity. The dataset comes from
a survey carrie...

In the previous case study, we showed how multiple samples from bacteria in honey bees from the same hive gave a nested data
structure, and mixed modelling techniques were applied to allow for correlations between observations from the same hive.
The bee data provided an example of two-way nested data, and the underlying theory for this was discuss...

In the previous chapter, count data with no upper limit were analysed using Poisson generalised linear modelling (GLM) and
negative binomial GLM. In Section 10.2 of this chapter, we discuss GLMs for 0−1 data, also called absence–presence or binary
data, and in Section 10.3 GLM for proportional data are presented. In the final section, generalised a...

The oceans, with a mean depth of 3,729 m and extending to a maximum depth of 11 km comprise the largest habitat on earth.
The distribution of living organisms in this vast environment is far from uniform and description of this variation in space
and time is challenging, both from the point of view of sampling and of statistical analysis. Most life...

This chapter, and the following three chapters, discuss solutions to the problems introduced in Chapters 2 and 3: heterogeneity,
nested data, temporal correlation, and spatial correlation. We use both the linear regression model and the additive model
as starting points. Figure 4.1 shows an overview of the methods we discuss in Chapters 4, 5, 6, a...

A catchment is an area of land defined by the origins and discharges of all tributary streams feeding large rivers flowing
into the sea. It is therefore a natural bio-physical unit distinct from adjacent catchments and forms the obvious basis for
integrated environmental management policies. In Europe, river catchments tend to be dominated by agric...

This chapter explains how correlation structures can be added to the linear regression and additive model. The mixed effects
models from Chapters 4 and 5 can also be extended with a temporal correlation structure. The title of this chapter contains
‘Part I’, suggesting that there is also a Part II. Indeed, that is the next chapter. In part I, we u...

Common or harbour seals (Phoca vitulina L.) are semi-aquatic mammals that spend time onshore at terrestrial sites where they haul-out to rest, breed, moult, engage
in social activity, and escape predation (Fig.23.1).

The earth’s climate is changing rapidly and these changes are expected to affect the structure and functioning of ecosystems.
It is now clearly established that recent climate changes have impacted on living organisms. Several studies have demonstrated
changes in population abundance, geographic distribution, and even microevolutionary changes in r...

This paper describes the diet of the Red Knot (Calidris canutus) at Punta Rasa; the southern extreme of the Ramsar Site at Bahía Samborombón, in the Buenos Aires province, Argentina. Data presented here are mostly based on fecal analysis. We also used gizzard content analyses of four casualties that occurred during the catching operations. Remains...

Limitations of linear regression applied on ecological data. - Things are not always linear additive modelling. - Dealing with hetergeneity. - Mixed modelling for nested data. - Violation of independence - temporal data. - Violation of independence spatial data. - Generalised linear modelling and generalised additive modelling. - Generalised estima...

Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The text covers how to download and install R, import and manage data, elementary plotting, an introd...

Measurements were made for the first time of the number of stimulated sources of bioluminescence from the subsurface layer to the seafloor at 14 stations over the northern Mid-Atlantic Ridge, 42°56′N to 53°18′N. Overall, light emissions decreased from typical means of 46 sources m−3 at 300–500 m down to 5 m−3 at 2800 m depth. In the vicinity of the...

In the previous chapter, we explored techniques to analyse data collected on a lattice. In this chapter, we will consider
techniques to model continuous spatial data. The term continuous does not mean that the variable of interest is continuous, but merely that the variable can be measured in any location in
the study area. Such continuously distri...

Surveys to monitor changes in population size over time are of interest for a variety of research questions and management
goals. For example, population biologists require survey data collected over time to test hypotheses concerning the patterns
and mechanisms of population regulation or to evaluate the effects on population size of interactions...

In Chapter 9, we introduced univariate regression trees and briefly discussed classification trees. In this chapter we expand
on Chapter 9 and provide a detailed explanation of classification trees applied to using radar records to identify bird movements
important in choosing sites for offshore wind farms. Tree model software tends to produce larg...

This case study illustrates the application of spatial analysis methods on a boreal forest in Tatarstan, Russia. Using remotely sensed data and spatial statistical methods, we explore the influence of relief, soil and climatic factors on the forests of the Raifa section of Volzhsko-Kamsky State Nature Biosphere.

This chapter illustrates how to decide between the application of parametric models (linear regression models) and non-parametric
methods (additive models). The techniques applied in this chapter will use as explanatory variables some abiotic (temperature,
salinity) and biotic (algal food biomass, as indicated by chlorophyll a) factors that affect...

Understanding the spatial and temporal distribution and abundance patterns of species and their relationships with environmental
variables is a key issue in ecology. All too often, despite best efforts, the quality of the collected data forces us to reduce
it to presence-absence data, which presents the ecologist with several specific statistical p...

Salt marshes are a transitional zone between the sea and land formed by flooding, sedimentation and erosion. This highly specialized
zone is characterised by a close interaction of physical and biological processes. The saline plant and animal communities
play an important role in the geomorphological development. Because the salt marshes are a sed...

Monitoring programs are vital to assess how plant community succession is affected by environmental change. Each plant community
has many biologic, climatic, and abiotic interactions that affect its species differently over time. In temperate grasslands,
plant community composition and species dominance can change rapidly in response to changes in...

The main aim of fisheries science is to interpret relevant information on the biology of the species in question, records
of fishing effort and size of catches, in order to predict the future size of the population under different fishing regimes,
allowing fishery managers to make decisions on future fishing efforts. The common approaches to evalua...

Ecologists are frequently interested in describing differences among the ecological communities that occur in habitats with
different characteristics. In an ideal world, experimental methods would standardise situations such that each habitat variable
could be altered separately in order to investigate their individual effects. This approach works...

In this chapter another example of dynamic factor analysis (DFA) and min/max auto-correlation factor analysis (MAFA) is presented.
The statistical methodology was explained in Chapters 33 and 16 and is not repeated here.

Introduction.- Data management and software.- Advice for teachers.- Exploration.- Linear regression.- Generalised linear modelling.- Additive and generalised additive modelling.- Introduction to mixed modelling.- Univariate tree models.- Measures of association.- Ordination--first encounter.- Principal component analysis and redundancy analysis.- C...

The aim of this chapter is to provide an application of canonical correspondence analysis (CCA), and we will use a lowland
tropical vegetation data set. It should be noted that the aim is not to provide a detailed statistical analysis of these data,
as other methods may be more appropriate to answer the underlying questions. The reason for this is...

Commercial multi-gear fisheries in Portugal, as in most European countries, are multi-species fisheries. For some individual
fish species, the effects of environmental conditions on abundance trends have been analysed, e.g., the effects of upwelling
on recruitment trends in sardine (Sardina pilchardus) and horse mackerel (Trachurus trachurus) (Sant...

In this chapter, we discuss our experience in teaching some of the material described in this book. Our first piece of advice is to avoid explaining too many statistical techniques in one course. When we started teaching statistics we tried to teach univariate, multivariate and time series methods in five days to between 8 and 100 biologists and en...

This chapter reviews some statistical programmes with which we have experience and reinforces some ideas of good data management practice.

This chapter gives a non-technical introduction into mixed modelling. Mixed models are also known as mixed effects models or multilevel models and are used when the data have some sort of hierarchical form such as in longitudinal or panel data, repeated measures, time series and blocked experiments, which can have both fixed and random coefficients...

Defining spatial and temporal distribution patterns of a soft-bottom benthos community and its relationship with environmental
factors has been a common task of many coastal marine ecologists. However, the choice of the most appropriate statistical
tools for benthic data has been subject to considerable debate among researchers.