Using simulations to evaluate Mantel‐based methods for assessing landscape resistance to gene flow

Mantel‐based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel‐based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual‐based, genetic simulations to examine the effects of the following on the performance of Mantel‐based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel‐based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell‐wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test‐based methods to fine‐tune resistance values will often not be effective.     

Conservation genetics: Linking science with practice

Conservation genetics is a well‐established scientific field. However, limited information transfer between science and practice continues to hamper successful implementation of scientific knowledge in conservation practice and management. To mitigate this challenge, we have established a conservation genetics community, which entails an international exchange‐and‐skills platform related to genetic methods and approaches in conservation management. First, it allows for scientific exchange between researchers during annual conferences. Second, personal contact between conservation professionals and scientists is fostered by organising workshops and by popularising knowledge on conservation genetics methods and approaches in professional journals in national languages. Third, basic information on conservation genetics has been made accessible by publishing an easy‐to‐read handbook on conservation genetics for practitioners. Fourth, joint projects enabled practitioners and scientists to work closely together from the start of a project in order to establish a tight link between applied questions and scientific background. Fifth, standardised workflows simplifying the implementation of genetic tools in conservation management have been developed. By establishing common language and trust between scientists and practitioners, all these measures help conservation genetics to play a more prominent role in future conservation planning and management.     

Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges

Environmental heterogeneity is considered to be one of the main factors associated with biodiversity given that areas with highly heterogeneous environments can host more species due to their higher number of available niches. In this view, spatial variability extracted from remotely sensed images has been used as a proxy of species diversity, as these data provide an inexpensive means of deriving environmental information for large areas in a consistent and regular manner. The aim of this review is to provide an overview of the state of the art in the use of spectral heterogeneity for estimating species diversity. We will examine a number of issues related to this theme, dealing with: i) the main sensors used for biodiversity monitoring, ii) scale matching problems between remotely sensed and field diversity data, iii) spectral heterogeneity measurement techniques, iv) types of species taxonomic diversity measures and how they influence the relationship between spectral and species diversity, v) spectral versus genetic diversity, and vi) modeling procedures for relating spectral and species diversity. Our review suggests that remotely sensed spectral heterogeneity information provides a crucial baseline for rapid estimation or prediction of biodiversity attributes and hotspots in space and time.     

Tinnitus: distinguishing between subjectively perceived loudness and tinnitus-related distress

Objectives

Overall success of current tinnitus therapies is low, which may be due to the heterogeneity of tinnitus patients. Therefore, subclassification of tinnitus patients is expected to improve therapeutic allocation, which, in turn, is hoped to improve therapeutic success for the individual patient. The present study aims to define factors that differentially influence subjectively perceived tinnitus loudness and tinnitus-related distress.

Methods

In a questionnaire-based cross-sectional survey, the data of 4705 individuals with tinnitus were analyzed. The self-report questionnaire contained items about subjective tinnitus loudness, type of onset, awareness and localization of the tinnitus, hearing impairment, chronic comorbidities, sleep quality, and psychometrically validated questionnaires addressing tinnitus-related distress, depressivity, anxiety, and somatic symptom severity. In a binary step-wise logistic regression model, we tested the predictive power of these variables on subjective tinnitus loudness and tinnitus-related distress.

Results

The present data contribute to the distinction between subjective tinnitus loudness and tinnitus-related distress. Whereas subjective loudness was associated with permanent awareness and binaural localization of the tinnitus, tinnitus-related distress was associated with depressivity, anxiety, and somatic symptom severity.

Conclusions

Subjective tinnitus loudness and the potential presence of severe depressivity, anxiety, and somatic symptom severity should be assessed separately from tinnitus-related distress. If loud tinnitus is the major complaint together with mild or moderate tinnitus-related distress, therapies should focus on auditory perception. If levels of depressivity, anxiety or somatic symptom severity are severe, therapies and further diagnosis should focus on these symptoms at first.     

Influence of polymorphisms of the human glutathione transferases and cytochrome P450 2E1 enzyme on the metabolism and toxicity of ethylene oxide and acrylonitrile

A cohort of 59 persons with industrial handling of low levels of acrylonitrile is being studied as part of a medical surveillance programme. Previously, an extended haemoglobin adduct monitoring (N-(cyanoethyl)valine and N-(hydroxyethyl)-valine) was performed regarding the glutathione transferases hGSTM1 and hGSTT1 polymorphisms but no influence of hGSTM1 or hGSTT1 polymorphisms on specific adduct levels was found. A compilation of case reports of human accidental poisonings had pointed to significant individual differences in human acrylonitrile metabolism and toxicity. Therefore, a re-evaluation of the industrial cohort included known polymorphisms of the glutathione transferases hGSTM3 and hGSTP1 as well as of the cytochrome P450 CYP2E1. A detailed statistical analysis revealed that exposed carriers of the allelic variants of hGSTP1, hGSTP1*B/hGSTP1*C, characterized by a single nucleotide polymorphism at nucleotide 313 which results in a change from Ile to Val at codon 104, had higher levels of the acrylonitrile-specific haemoglobin adduct N-(cyanoethyl)valine compared to the carriers of the codon 113 alleles hGSTP1*A and hGSTP1*D. The single nucleotide polymorphism at codon 113 of hGSTP1 (hGSTP1*A/hGSTP1*B versus hGSTP1*C/hGSTP1*D) did not show an effect, and also no influence was seen on specific haemoglobin adduct levels of the polymorphisms of hGSTM3 or CYP2E1. The data, therefore, point to a possible influence of a human enzyme polymorphism of the GSTP1 gene at codon 104 on the detoxication of acrylonitrile which calls for experimental toxicological investigation. The study also confirmed the impact of GSTT1 polymorphism on background N-(hydroxyethyl)-valine adduct levels in haemoglobin which are caused by endogenous ethylene oxide.     

A multi‐method approach for analyzing hierarchical genetic structures: a case study with cougars Puma concolor

Genetic data are increasingly used to describe the structure of wildlife populations and to infer landscape influences on functional connectivity. To accomplish this, genetic structure can be described with a multitude of methods that vary in their assumptions, advantages and limitations. While some methods discriminate distinct subpopulations separated by sharp genetic boundaries (i.e. barrier detection or clustering methods), other methods estimate gradient genetic structures using individual‐based genetic distances. We present an analytical framework based on individual ancestry values that combines these different approaches and can be used to a) test for local barriers to gene flow and b) evaluate effects of landscape gradients through individual‐based genetic distances that account for hierarchical genetic structure. We illustrate the approach with a data set of 371 cougars Puma concolor from a 217 000 km² study area in Idaho and western Montana (USA) that were genotyped at 12 microsatellite loci. Results suggest that cougars in the region show a complex, hierarchical genetic structure that is influenced by a local barrier to gene flow (an urban population cluster connected by high traffic volumes), different landscape features (the Snake River Plain, forested habitat), and geographic distance. Our novel approach helped to elucidate the relative influence of these factors on different hierarchical levels of population structure, which was not possible when using either clustering methods or standard genetic distances. Results obtained with our analytical framework highlight the need for multi‐scale management of cougars in the region and show that landscape heterogeneity can create complex genetic structures, even in generalist species with high dispersal capabilities.     

A plea for simultaneously considering matrix quality and local environmental conditions when analysing landscape impacts on effective dispersal

Landscape genetics has tremendous potential for enhancing our understanding about landscape effects on effective dispersal and resulting genetic structures. However, the vast majority of landscape genetic studies focus on effects of the landscape among sampling locations on dispersal (i.e. matrix quality), while effects of local environmental conditions are rather neglected. Such local environmental conditions include patch size, habitat type or resource availability and are commonly used in (meta‐) population ecology and population genetics. In our opinion, landscape genetic studies would greatly benefit from simultaneously incorporating both matrix quality and local environmental conditions when assessing landscape effects on effective dispersal. To illustrate this point, we first outline the various ways in which environmental heterogeneity can influence different stages of the dispersal process. We then propose a three‐step approach for assessing local and matrix effects on effective dispersal and review how both types of effects can be considered in landscape genetic analyses. Using simulated data, we show that it is possible to correctly disentangle the relative importance of matrix quality vs. local environmental conditions for effective dispersal. We argue that differentiating local and matrix effects in such a way is crucial for predicting future species distribution and persistence, and for optimal conservation decisions that are based on landscape genetics. In sum, we think it is timely to move beyond purely statistical, pattern‐oriented analyses in landscape genetics and towards process‐oriented approaches that consider the full range of possible landscape effects on dispersal behaviour and resulting gene flow.     

Large area used by squirrel gliders in an urban area,uncovered using GPS telemetry

The squirrel glider (Petaurus norfolcensis) is a threatened, gliding marsupial that persists in fragmented landscapes despite its restricted capacity to cross large gaps. As measures to maintain and/or restore suitable habitat depend on knowledge about the species'' ecological requirements, we investigated the area used by squirrel gliders in an urban area near Newcastle, Australia. Using GPS telemetry data and the autocorrelated kernel density estimator, we estimated area used to average 10.8 ha and varied from 4.6 to 15 ha, which is equal to or greater than found in previous studies that spanned longer time periods. This has implications when identifying the minimum patch size necessary for ensuring the long‐term conservation of a squirrel glider population.     

Three‐dimensional stratification pattern in an old‐growth lowland forest: How does height in canopy and season influence temperate bat activity?

The study of animal–habitat interactions is of primary importance for the formulation of conservation recommendations. Flying, gliding, and climbing animals have the ability to exploit their habitat in a three‐dimensional way, and the vertical canopy structure in forests plays an essential role for habitat suitability. Forest bats as flying mammals may seasonally shift their microhabitat use due to differing energy demands or changing prey availability, but the patterns are not well understood. We investigated three‐dimensional and seasonal habitat use by insectivorous bats in a temperate lowland old‐growth forest, the Belovezhskaya Pushcha in Belarus. We acoustically sampled broadleaved and mixed coniferous plots in the forest interior and in gaps in three heights during two reproductive periods (pregnancy/lactation vs. postlactation). In canopy gaps, vertical stratification in bat activity was less pronounced than in the forest interior. Vertical activity patterns differed among species. The upper canopy levels were important foraging habitats for the open‐space forager guild and for some edge‐space foragers like the Barbastelle bat Barbastella barbastellus and the soprano pipistrelle Pipistrellus pygmaeus. Myotis species had highest activity levels near the ground in forest gaps. Moreover, we found species‐dependent seasonal microhabitat shifts. Generally, all species and species groups considered except Myotis species showed higher activity levels during postlactation. Myotis species tended toward higher activity in the forest interior during postlactation. P. pygmaeus switched from high activity levels in the upper canopy during pregnancy and lactation to high activity levels near the ground during postlactation. We conclude that a full comprehension of forest bat habitat use is only possible when height in canopy and seasonal patterns are considered.     

Simulation modelling in landscape genetics: on the need to go further

With the emergence of landscape genetics, the basic assumptions and predictions of classical population genetic theories are being re‐evaluated to account for more complex spatial and temporal dynamics. Within the last decade, there has been an exponential increase in such landscape genetic studies ( Holderegger & Wagner 2006 ; Storfer et al. 2010 ), and both methodology and underlying concepts of the field are under rapid and constant development. A number of major innovations and a high level of originality are required to fully merge existing population genetic theory with landscape ecology and to develop novel statistical approaches for measuring and predicting genetic patterns. The importance of simulation studies for this specific research has been emphasized in a number of recent articles (e.g., Balkenhol et al. 2009a ; Epperson et al. 2010 ). Indeed, many of the major questions in landscape genetics require the development and application of sophisticated simulation tools to explore gene flow, genetic drift, mutation and natural selection in landscapes with a wide range of spatial and temporal complexities. In this issue, Jaquiéry et al. (2011) provide an excellent example of such a simulation study for landscape genetics. Using a metapopulation simulation design and a novel ‘scale of phenomena’ approach, Jaquiéry et al. (2011) demonstrate the utility and limitations of genetic distances for inferring landscape effects on effective dispersal.