# Fränzi Korner-NievergeltSwiss Ornithological Institute · Ecological Statistics

Fränzi Korner-Nievergelt

PhD

## About

159

Publications

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Introduction

The understanding of the needs of individual birds along their life cycle, and understanding drivers of bird populations are the ultimate interests of my research.
For this aim I am combining information from different data sources using integrated modelling techniques within a Bayesian framework.
Currently, I am working on demographic studies of a high-elevation specialist species, the White-winged Snowfinch Montifringilla nivals. In addition, I develop integrated modelling techniques for investigating movement and population dynamics in collaboration with other researchers. Therefore, I am involved in studies of a variety of different species.

## Publications

Publications (159)

Linking organism distribution to climate is key to understanding factors determining species occurrence and evaluating the potential impacts of ongoing climate change. A common analytical tool to assess the link between species and climate is represented by ecological niche modelling and by the tightly related species distribution models (SDMs). Th...

Multi-species indices (MSI) are widely used as ecological indicators and as instruments to inform environmental policies. Many of these indices combine species-specific estimates of relative population sizes using the geometric mean. Because the geometric mean is not defined when values of zero occur, usually only commoner species are included in M...

Breeding success of an Alpine black grouse Lyrurus tetrix population in southern Switzerland was monitored from 1981 to 2020. This long‐term dataset allows exploring relationships of reproductive rates with climate and habitat, which have shown marked changes during this period. Over the 40 years, the average elevation of black grouse breeding site...

Spatial variation in survival has individual fitness consequences and influences population dynamics. Which space animals use during the annual cycle determines how they are affected by this spatial variability. Therefore, knowing spatial patterns of survival and space use is crucial to understand demography of migrating animals. Extracting informa...

To track peaks in resource abundance, temperate-zone animals use predictive environmental cues to rear their offspring when conditions are most favourable. However, climate change threatens the reliability of such cues when an animal and its resource respond differently to a changing environment. This is especially problematic in alpine environment...

Infectious diseases bear a great risk for populations of naïve host species. In the present article we inform about the first microscopic and molecular detection of the bird pathogen Trichomonas gallinae in the White-winged Snowfinch ( Montifringilla nivalis subsp. nivalis ). The emergence of trichomonosis in this highly specialised alpine bird spe...

The formation of an upper distributional range limit for species breeding along mountain slopes is often based on environmental gradients resulting in changing demographic rates towards high elevations. However, we still lack an empirical understanding of how the interplay of demographic parameters forms the upper range limit in highly mobile speci...

Personalities, i.e. consistent individual differences in behaviour, have been found in many animal populations. However, the reasons why personalities emerge, how they persist and the consequences they have in a changing environment are poorly understood. Factors influencing personalities include genetic background, prenatal (e.g. hormonal) and pos...

Many animals make behavioural changes to cope with winter conditions, being gregariousness a common strategy. Several factors have been invoked to explain why gregariousness may evolve during winter, with individuals coming together and separating as they trade off the different costs and benefits of living in groups. These trade-offs may, however,...

Grazing by large herbivores is increasingly used as a management tool in European nature reserves. The aim is usually to support an open but heterogeneous habitat and its corresponding plant and animal communities. Previous studies showed that birds may profit from grazing but that the effect varies among bird species. Such studies often compared b...

The formation of the upper distributional range limit of species at mountain slopes is often based on environmental gradients resulting in changing demographic rates towards high elevations. However, we still lack an empiric understanding of how the interplay of demographic parameters forms the upper range limit in highly mobile species. Here, we s...

Glucocorticoid hormones, such as corticosterone, are crucial in regulating daily life metabolism and energy expenditure, as well as promoting short-term physiological and behavioural responses to unpredictable environmental challenges. Therefore, glucocorticoids are considered to mediate trade-offs between survival and reproduction. Relatively litt...

Mountain ecosystems are inhabited by highly specialised and endemic species which are particularly susceptible to climatic changes. However, the mechanisms by which climate change affects species population dynamics are still largely unknown, particularly for mountain birds. We investigated how weather variables correlate with survival or movement...

European farmland birds show massive large‐scale population declines due to agricultural intensification. Long‐distance migrants are particularly affected as their populations appear to undergo larger declines than those of residents and short‐distance migrants, raising the question about the impact of non‐breeding environmental conditions and thei...

The success of habitat enhancements is typically assessed by subsequent monitoring of the focal taxonomic group. However, enhancement actions are likely to affect other, non-targeted species. On a south-facing slope in the Swiss Jura mountains, a mixed-forest stand was thinned out by irregular removal cuttings to improve the habitat conditions for...

The White-winged Snowfinch Montifringilla nivalis nivalis is assumed to be highly threatened by climate change, but this high elevation species has been little studied and the current breeding distribution is accurately known only for a minor portion of its range. Here, we provide a detailed and spatially explicit identification of the potentially...

Abstract Ecosystems around the world are connected by seasonal migration. The migrant animals themselves are influenced by migratory connectivity through effects on the individual and the population level. Measuring migratory connectivity is notoriously difficult due to the simple requirement of data conveying information about the nonbreeding dist...

High-alpine ecosystems are strongly seasonal and adverse environments. In these ecosystems, the brevity of optimal breeding conditions means species must efficiently track spatiotemporal variations in resources in order to synchronise their reproductive effort with peaks in food availability. Understanding the details of prey-habitat associations a...

Glucocorticoid hormones, such as corticosterone, are fundamental in the translation of external stimuli into physiological adjustments that promote the survival of an organism in face of changes in its environment. At baseline levels, corticosterone is crucial in regulating daily life metabolism and energy expenditure, whereas the acute corticoster...

Timing of return to the breeding area presumably optimizes breeding output in migrants. How timing affects the other components of fitness — survival, has been comparatively little studied. Returning too early in spring is expected to be associated with high mortality in insectivorous migrants when weather conditions are still unsuitable. Yet, male...

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance tes...

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance tes...

Food availability is a major characteristic of habitat quality, linking habitats with demographic parameters such as reproductive performance. Parent birds adjust their food provisioning to both habitat-specific food characteristics and the demands of their young. However, because habitat quality and the brood's food intake are often correlated, th...

Populations of migratory birds often mix to a considerable extent in their wintering areas. Knowledge about the composition of wintering populations is highly relevant to management, not least for species such as the great cormorant Phalacrocorax carbo sinensis, prone to conflicts with human interests. However, few studies have been able to estimat...

In the Canton of Ticino in southern Switzerland data from the monitoring programme for black grouse from 1981 to 2016 (population density, lek size, sex ratio in chicks and adults) were analysed together with information on bag statistics and hunting regulations to evaluate if mortality from hunting had an additive effect. In the study population t...

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significan...

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science.
Given that blanket and variable alpha levels both are problematic, it is sensible to dispense
with significan...

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance tes...

Congratulations on publishing "Vertical distribution of bird migration between the Baltic Sea and the Sahara" in Journal of Ornithology. As part of the Springer Nature SharedIt initiative, you can now publicly share a full-text view-only version of your paper by using the link below. All readers of your article via the shared link will also be able...

We argue that depending on p-values to reject null hypotheses, including a recent call for changing the canonical alpha level for statistical significance from .05 to .005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable criterion levels both are problematic, it is sensible to dispense...

The widespread use of 'statistical significance' as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (according to the American Statistical Association). We review why degrading p-values into 'significant' and 'nonsignificant' contributes to making studies irreproducible, or to making t...

The widespread use of 'statistical significance' as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (according to the American Statistical Association). We review why degrading p-values into 'significant' and 'nonsignificant' contributes to making studies irreproducible, or to making t...

The widespread use of 'statistical significance' as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (according to the American Statistical Association). We review why degrading p-values into 'significant' and 'nonsignificant' contributes to making studies irreproducible, or to making t...

The widespread use of 'statistical significance' as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (American Statistical Association, Wasserstein & Lazar 2016). We review why degrading p-values into 'significant' and 'nonsignificant' contributes to making studies irreproducible, or to...

Alarmingly high numbers of bats are being killed at wind turbines worldwide, raising concerns about the cumulative effects of bat mortality on bat populations. Mitigation measures to effectively reduce bat mortality at wind turbines while maximising energy production are of paramount importance. Operational mitigation (i.e. feathering wind turbine...

Animals which spend subsequent seasons in different areas connect geographical regions. The connection between breeding and non-breeding grounds is defined as migratory connectivity. The quantification of such connectivity is important, because movements between different locations can have strong consequences for the moving animal as well as the e...

Aim
Assessing the extent of large-scale migratory connectivity is crucial for understanding the evolution of migratory systems and effective species conservation. It has been, however, difficult to elucidate the annual whereabouts of migratory populations of small animals across the annual cycle. Here, we use the reed warbler (Acrocephalus scirpac...

In this study bat activity, measured close to the ground and at heights of 50 and 100 m, was compared across six wind measurement masts in forest clearings. Results from a further measurement mast where measurements were taken close to the ground and at heights of 22 and 44 m in the middle of an old beech forest are presented separately.
Only speci...

We give a short introduction to the principles of Bayesian data analyses and guide the reader through two examples using R. Differences and similarities to frequentist statistics are explained. Bayesian analysis is combining prior information (e. g. from the literature) with information in the data to obtain a posterior distribution of the paramete...

Recoveries of marked animals hold long-term, large-scale information on survival and causes of mortality, but are prone to bias towards dead recoveries and casualties in the range of presence of potential finders. Thus, accounting for circumstance-related recovery probabilities is crucial in statistical approaches. For the little owl, a species of...

Knowledge about flyways, breeding and overwintering sites is important for conservation efforts, but little is known about migration patterns and population connectivity of declining European Turtle Doves Streptopelia turtur. EURING ring-recovery data were used to estimate directions and proportional usage of flyways. The timing of migration was co...

Mixed effects models are used to analyze nonindependent, that is, grouped or hierarchical data. These models are called mixed effects models because they contain fixed and random effects. Fixed effects are factors with a finite (“fixed”) number of levels (e.g., sex), whereas random effects have a theoretically infinite number of levels of which we...

This chapter introduces five hierarchical ecological models and corresponding BUGS and Stan code. First, a hierarchical multinomial model is used to study the use of different roosting site types by an owl species based on telemetry data in relation to environmental variables. Second, we analyze the breeding success of the black stork using a zero-...

In a generalized linear model (GLM), the distribution of the data can be chosen from a variety of statistical distributions. Therefore, these models are used when the outcome variable is a count or proportions or something else that will produce nonnormally distributed residuals in a normal linear model. We introduce the binomial, the Bernoulli, an...

We introduce a Bayesian method to assess goodness of fit and also discuss the use of the proportion of variance explained, R2, a classical measurement of goodness of fit. Posterior predictive model checking is the comparison of the simulated data from the model with the observed data. The simulated data can differ from the observed data in various...

Generalized linear mixed models (GLMM) are the combination of generalized linear models and linear mixed models, which means that the error distribution can be different from Gaussian and that a random factor is included in the model. We discuss the binomial model used to analyze proportions or binary outcome variables, and the Poisson model used t...

How to select a model or to base conclusions on more than one model depends on the purpose and the design of the study. In this chapter, we discuss the difference between confirmatory and predictive analyses and explain the tradeoff between bias and precision in statistical models. We present commonly used methods to rank models according to their...

Bayesian data analysis is the process of fitting a probability model to data and drawing inferences based on posterior distributions of the model parameters or derived quantities. Bayes’ theorem provides the theoretical background and modern computer techniques, such as the R function sim, allow for the application of these processes. The posterior...

The checklist provides a step-by-step guide through a typical data analysis. After data checking, we start with defining a model structure depending on the nature of the data-generating process. Then, the error distribution is chosen. The explanatory variables are prepared using transformations, centering, and scaling. After model fitting, goodness...

Normal linear models (LM) are used when the outcome variable can be modeled directly with predictor variables, that is, no link function is needed, and when the resulting residuals are approximately normally distributed. These models include widely used techniques: simple linear regression for a continuous predictor, one-way ANOVA for a categorical...

The likelihood is a relative measure of the probability of obtaining a specific data set given a model. If the likelihood of model 1 is twice as high as the likelihood of model 2, the probability of obtaining precisely this data set is twice as large for model 1 than for model 2. The likelihood function is the likelihood for a fixed data set and va...

Markov chain Monte Carlo (MCMC) is a simulation technique that can be used to find the posterior distribution and to sample from it. Thus, it is used to fit a model and to draw samples from the joint posterior distribution of the model parameters. The different MCMC algorithms differ in their performance in relation to speed and convergence dependi...

Statistical models serve to communicate information in data, to think about systems, to learn from data, and to make predictions and decisions. Our daily life is governed by models. This book is about linear models and extensions of these. In a linear model, the expected value of the outcome variable itself, or a transformation thereof, is a linear...

Prior distributions, or “priors” are important parts of the model. Improper, flat, and weakly informative prior distributions are discussed. Informative or weakly informative prior distributions have computational as well as conceptual advantages over flat priors. Conjugate priors ease the calculation of posterior distributions by hand. The influen...

The results of the data analysis are the basis for your conclusions. They contain estimates of the effects that have been studied including a measurement of uncertainty. Often, derived parameters are more meaningful than model parameters. In addition, it is helpful to present the information needed to judge the biological (or other) relevance of th...

Model assumptions need to be checked before drawing conclusions from any model. Usually, the residuals are independent and identically distributed (iid), when the model assumptions are met. We discuss several graphical methods for assessing independence and distribution of the residuals such as the Tukey–Anscombe or the QQ plot. We further discuss...

Spatial autocorrelation is a general property of most ecological data sets. When data are spatially autocorrelated, the value of a random variable characterizing a site can be partially predicted by the values at neighboring sites. Spatial autocorrelation can thus be described as one of the mechanisms leading to pseudoreplication. Uncertainty will...

Vulture populations are declining steeply worldwide. Vulture ‘restaurants’ or feeding stations are a tool for maintaining and monitoring numbers, but individual species may be disadvantaged by the effects of carcass distribution, carcass size and interspecific aggression. To test the degree to which restaurants give opportunities for each species t...

In migratory birds, morphological adaptations for efficient migratory flight often oppose morphological adaptations for efficient behavior during resident periods. This includes adaptations in wing shape for either flying long distances or foraging in the vegetation and in climate-driven variation of body size. In addition, the timing of migratory...

Table S1. Morphometry of nightingales (Luscinia m. megarynchos) across its distribution range.
Figure S1. Longitudinal pattern of migration distance and four environmental factors at specific breeding sites of local populations used in the study.

Count data of animals observed from multiple sites are commonly used to study variation in abundance across space and time. Because some individuals typically go undetected in such surveys, count data alone have traditionally been thought to not contain information about absolute abundance. In a recent paper, we showed that estimates of absolute ab...

The Alpine Rock Ptarmigan Lagopus muta helvetica is considered to be particularly vulnerable to climate warming because it lives exclusively above the tree-line in alpine habitats and is adapted to cold climates. Its Swiss population index has decreased over the last two decades. A considerable shrinkage in distributional area is predicted with fur...

Key Features
Offers Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest
Written in a step-by-step approach, which is accessible to non-statisticians
Includes companion website containing R-code to help users conduct Bayesian data analyses on their own data
Description
Bayesian Da...

The Alpine Rock Ptarmigan (Lagopus muta helvetica)—which is adapted to arctic and alpine environments—is suspected to be vulnerable to climate warming, but direct evidence is limited. Microclimates within a landscape may allow species to exist in regions where the general climate appears to be unsuitable for them. We therefore investigated the dive...

This article is a tutorial for the R-package carcass. It starts with a short overview of common methods used to estimate mortality based on carcass searches. Then, it guides step by step through a simple example. First, the proportion of animals that fall into the search area is estimated. Second, carcass persistence time is estimated based on expe...

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, mode...