Neil J. Walker

Bio: Neil J. Walker is an academic researcher from Central Science Laboratory. The author has contributed to research in topics: Badger & Meles. The author has an hindex of 21, co-authored 40 publications receiving 13034 citations. Previous affiliations of Neil J. Walker include Food and Environment Research Agency & Veterinary Laboratories Agency.

Mixed Effects Models and Extensions in Ecology with R

Abstract: 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 estimation equations. - GLMM and GAMM. - Estimating trends for Antarctic birds in relation to climate change. - Large-scale impacts of land-use change in a Scottish farming catchment. - Negative binomial GAM and GAMM to analyse amphibian road killings. - Additive mixed modelling applied on deep-sea plagic bioluminescent organisms. - Additive mixed modelling applied on phyoplankton time series data. - Mixed modelling applied on American Fouldbrood affecting honey bees larvae. - Three-way nested data for age determination techniques applied to small cetaceans. - GLMM applied on the spatial distribution of koalas in a fragmented landscape. - GEE and GLMM applied on binomial Badger activity data.

Comprar Mixed Effects Models and Extensions in Ecology with R | Zuur, Alain F. | 9780387874579 | Springer

Abstract: Tienda online donde Comprar Mixed Effects Models and Extensions in Ecology with R al precio 66,45 € de Zuur, Alain F. | Ieno, Elena N. | Walker, Neil J. | Saveliev, Anatoly A. | Smith, Graham M., tienda de Libros de Medicina, Libros de Biologia - Ecologia

Zero-Truncated and Zero-Inflated Models for Count Data

Abstract: 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, counts of fin rays on fish (e.g. used for stock identification), dolphin group size, age of an animal in years or months, or the number of days that carcasses of road-killed animals (amphibians, owls, birds, snakes, carnivores, small mammals, etc.) remain on the road. These are all examples for which the response variable cannot take a value of 0.

Mixed Effects Modelling for Nested Data

Abstract: 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).

Bovine tuberculosis infection in wild mammals in the South-West region of England: a survey of prevalence and a semi-quantitative assessment of the relative risks to cattle.

Abstract: In the United Kingdom, badgers are implicated in the transmission of Mycobacterium bovis to cattle, but little information is available on the potential role of other wild mammals. This paper presents the results of the largest systematic UK survey of M. bovis infection in other wild mammals. Mammal carcasses (4715) from throughout the South-West region of England were subjected to a systematic post mortem examination, microbiological culture of tissues and spoligotyping of isolates. Infection was confirmed in fox, stoat, polecat, common shrew, yellow-necked mouse, wood mouse, field vole, grey squirrel, roe deer, red deer, fallow deer and muntjac. Prevalence in deer may have been underestimated because the majority were incomplete carcasses, which reduced the likelihood of detecting infection. Infected cases were found in Wiltshire, Somerset, Devon and Cornwall, Gloucestershire and Herefordshire. Lesions were found in a high proportion of spoligotype-positive fallow, red and roe deer, and a single fox, stoat and muntjac. M. bovis spoligotypes occurred in a similar frequency of occurrence to that in cattle and badgers. Data on prevalence, pathology, abundance and ecology of wild mammals was integrated in a semi-quantitative risk assessment of the likelihood of transmission to cattle relative to badgers. Although most species presented a relatively low risk, higher values and uncertainty associated with muntjac, roe, red and in particular fallow deer, suggest they require further investigation. The results suggest that deer should be considered as potential, although probably localised, sources of infection for cattle.

A protocol for data exploration to avoid common statistical problems

Abstract: Summary 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 violations have little impact on the results or ecological conclusions; yet others increase type I or type II errors, potentially resulting in wrong ecological conclusions. Most of these violations can be avoided by applying better data exploration. These problems are especially troublesome in applied ecology, where management and policy decisions are often at stake. 3. Here, we provide a protocol for data exploration; discuss current tools to detect outliers, heterogeneity of variance, collinearity, dependence of observations, problems with interactions, double zeros in multivariate analysis, zero inflation in generalized linear modelling, and the correct type of relationships between dependent and independent variables; and provide advice on how to address these problems when they arise. We also address misconceptions about normality, and provide advice on data transformations. 4. Data exploration avoids type I and type II errors, among other problems, thereby reducing the chance of making wrong ecological conclusions and poor recommendations. It is therefore essential for good quality management and policy based on statistical analyses.

glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling

Abstract: Count data can be analyzed using generalized linear mixed models when observations are correlated in ways that require random effects However, count data are often zero-inflated, containing more zeros than would be expected from the typical error distributions We present a new package, glmmTMB, and compare it to other R packages that fit zero-inflated mixed models The glmmTMB package fits many types of GLMMs and extensions, including models with continuously distributed responses, but here we focus on count responses glmmTMB is faster than glmmADMB, MCMCglmm, and brms, and more flexible than INLA and mgcv for zero-inflated modeling One unique feature of glmmTMB (among packages that fit zero-inflated mixed models) is its ability to estimate the Conway-Maxwell-Poisson distribution parameterized by the mean Overall, its most appealing features for new users may be the combination of speed, flexibility, and its interface’s similarity to lme4

Global effects of land use on local terrestrial biodiversity

Abstract: Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

Temporal Dynamics of the Human Vaginal Microbiota

Abstract: Elucidating the factors that impinge on the stability of bacterial communities in the vagina may help in predicting the risk of diseases that affect women’s health. Here, we describe the temporal dynamics of the composition of vaginal bacterial communities in 32 reproductive-age women over a 16-week period. The analysis revealed the dynamics of five major classes of bacterial communities and showed that some communities change markedly over short time periods, whereas others are relatively stable. Modeling community stability using new quantitative measures indicates that deviation from stability correlates with time in the menstrual cycle, bacterial community composition, and sexual activity. The women studied are healthy; thus, it appears that neither variation in community composition per se nor higher levels of observed diversity (co-dominance) are necessarily indicative of dysbiosis.