Theory of mind tasks and executive functions: A systematic review of group studies in neurology.

A growing number of studies have been addressing the relationship between theory of mind (TOM) and executive functions (EF) in patients with acquired neurological pathology. In order to provide a global overview on the main findings, we conducted a systematic review on group studies where we aimed to (1) evaluate the patterns of impaired and preserved abilities of both TOM and EF in groups of patients with acquired neurological pathology and (2) investigate the existence of particular relations between different EF domains and TOM tasks. The search was conducted in Pubmed/Medline. A total of 24 articles met the inclusion criteria. We considered for analysis classical clinically accepted TOM tasks (first- and second-order false belief stories, the Faux Pas test, Happe's stories, the Mind in the Eyes task, and Cartoon's tasks) and EF domains (updating, shifting, inhibition, and access). The review suggests that (1) EF and TOM appear tightly associated. However, the few dissociations observed suggest they cannot be reduced to a single function; (2) no executive subprocess could be specifically associated with TOM performances; (3) the first-order false belief task and the Happe's story task seem to be less sensitive to neurological pathologies and less associated to EF. Even though the analysis of the reviewed studies demonstrates a close relationship between TOM and EF in patients with acquired neurological pathology, the nature of this relationship must be further investigated. Studies investigating ecological consequences of TOM and EF deficits, and intervention researches may bring further contributions to this question.

A framework for assessing the scale of influence of environmental factors on ecological patterns

The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.

A new perspective on the zoogeography of the sibling mouse-eared bat species Myotis myotis and Myotis blythii: Morphological, genetical and ecological evidence

The actual geographic distribution of the two sibling mouse-eared bat species Myotis myotis and Myotis blythii, which occur widely sympatrically in the western Palaearctic region, remains largely controversial. This concerns particularly the specific attribution of marginal populations from the Mediterranean islands and from adjacent areas of North Africa and Asia, which are morphologically intermediate between continental M. myotis and M. blythii from Europe. This study attempts to clarify this question by using four different approaches: cranial morphology, external morphology, genetics and trophic ecology. The three latter methods show unambiguously that North Africa, Malta, Sardinia and Corsica are presently inhabited by monospecific populations of M. myotis. In contrast, cranial morphometrics do not yield conclusive results. These results contradict all recent studies, which attribute North African and Maltese mouse-eared bats to M. blythii and consider that Sardinia and Corsica harbour sympatric populations of the two species. As concerns south-eastern populations, doubts are also expressed about the attribution of the subspecific taxon omari which may actually refer to M. myotis instead of M. blythii. Protein electrophoresis is presently the only absolute method available for determining M. myotis and M. blythii throughout their distribution ranges. However, species identification may be approached by relying on less sophisticated morphometrical methods as presented in this study. Species-specific habitat specializations are probably responsible for the differences observed between the geographic distributions of M. myotis and M. blythii, as they provide a logical groundwork for a coherent model of speciation for these two bat species.

An alternative socio-ecological strategy? International Trade Unions' engagement with climate change

In the context of a global ecological crisis, it is an important move when trade unions turn to environmentalism. Yet, the form that this environmentalism takes is often overlooked. This is especially the case with international trade unions. Based on an empirical study of international trade unions' engagement with the climate change issue, this article argues that international trade unions follow three different (and partially conflicting) strategies. I label these strategies as 'deliberative', 'collaborative growth' and 'socialist', and I examine each in turn. I argue that such analysis is important if we want to identify the potential for transforming the social relations of production that are at the root of the current climate crisis, and for identifying an alternative socio-ecological strategy.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

Ecological assembly rules in plant communities--approaches, patterns and prospects.

Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.

Arbuscular mycorrhizal fungi: genetics of multigenomic, clonal networks and its ecological consequences

Arbuscular mycorrhizal fungi are thought to have remained asexual for 400 million years although recent studies have suggested that considerable genetic and phenotypic variation could potentially exist in populations. A brief discussion of these multigenomic organisms is presented. (C) 2003 The Linnean Society of London.

Pattern recognition ecological niche models fit to presence-only and presence-absence data

1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.

Ecological-economic optimization of biodiversity conservation under climate change

Substantial investment in climate change research has led to dire predictions of the impacts and risks to biodiversity. The Intergovernmental Panel on Climate Change fourth assessment report(1) cites 28,586 studies demonstrating significant biological changes in terrestrial systems(2). Already high extinction rates, driven primarily by habitat loss, are predicted to increase under climate change(3-6). Yet there is little specific advice or precedent in the literature to guide climate adaptation investment for conserving biodiversity within realistic economic constraints(7). Here we present a systematic ecological and economic analysis of a climate adaptation problem in one of the world's most species-rich and threatened ecosystems: the South African fynbos. We discover a counterintuitive optimal investment strategy that switches twice between options as the available adaptation budget increases. We demonstrate that optimal investment is nonlinearly dependent on available resources, making the choice of how much to invest as important as determining where to invest and what actions to take. Our study emphasizes the importance of a sound analytical framework for prioritizing adaptation investments(4). Integrating ecological predictions in an economic decision framework will help support complex choices between adaptation options under severe uncertainty. Our prioritization method can be applied at any scale to minimize species loss and to evaluate the robustness of decisions to uncertainty about key assumptions.

Behavioural types and ecological effects in a natural population of the cooperative cichlid Neolamprologus pulcher

The ecological relevance of behavioural syndromes is little studied in cooperative breeding systems where it is assumed that the behavioural type might influence individual decisions on helping and dispersal (e.g. shy, nonaggressive and nonexplorative individuals remain philopatric and helpful, whereas bold, aggressive, explorative individuals compete for vacancies outside their group and disperse). We measured the behavioural type of 19 subordinates in the cooperatively breeding cichlid fish Neolamprologus pulcher in their natural environment by quantifying six behavioural traits up to four times ('trials') in three different contexts, by presenting them with a conspecific intruder, a predator or nothing inside a tube. We found only moderate within-context repeatability (intraclass correlation coefficients) of the focal individual's behaviour, except for attacking either the conspecific or the predator inside the tube. The focal individual's attack rate of the tube was also positively affected by its group size. Averaging traits per context removed the between-trial variation, and consequently the across-context repeatability was very high for all six traits, except for territory maintenance. Trait values depended significantly on the context, except for territory defence. Consequently, individuals could be classified into different behavioural types based on their reaction towards the tube, but surprisingly, and opposite to laboratory studies in this species, ranging propensity and territory maintenance were not included in this behavioural syndrome. We suggest that more studies are needed to compare standardized focal personality tests (e.g. exploration propensity) with actual behaviour observed in nature (e.g. ranging and dispersal).

Morphological, hydrological, biogeochemical and ecological changes and challenges in river restoration - the Thur River case study

River restoration can enhance river dynamics, environmental heterogeneity and biodiversity, but the underlying processes governing the dynamic changes need to be understood to ensure that restoration projects meet their goals, and adverse effects are prevented. In particular, we need to comprehend how hydromorphological variability quantitatively relates to ecosystem functioning and services, biodiversity as well as ground-and surface water quality in restored river corridors. This involves (i) physical processes and structural properties, determining erosion and sedimentation, as well as solute and heat transport behavior in surface water and within the subsurface; (ii) biogeochemical processes and characteristics, including the turnover of nutrients and natural water constituents; and (iii) ecological processes and indicators related to biodiversity and ecological functioning. All these aspects are interlinked, requiring an interdisciplinary investigation approach. Here, we present an overview of the recently completed RECORD (REstored CORridor Dynamics) project in which we combined physical, chemical, and biological observations with modeling at a restored river corridor of the perialpine Thur River in Switzerland. Our results show that river restoration, beyond inducing morphologic changes that reshape the river bed and banks, triggered complex spatial patterns of bank infiltration, and affected habitat type, biotic communities and biogeochemical processes. We adopted an interdisciplinary approach of monitoring the continuing changes due to restoration measures to address the following questions: How stable is the morphological variability established by restoration? Does morphological variability guarantee an improvement in biodiversity? How does morphological variability affect biogeochemical transformations in the river corridor? What are some potential adverse effects of river restoration? How is river restoration influenced by catchment-scale hydraulics [GRAPHICS] and which feedbacks exist on the large scale? Beyond summarizing the major results of individual studies within the project, we show that these overarching questions could only be addressed in an interdisciplinary framework.

Selection on a genetic polymorphism counteracts ecological speciation in a stick insect.

The interplay between selection and aspects of the genetic architecture of traits (such as linkage, dominance, and epistasis) can either drive or constrain speciation [1-3]. Despite accumulating evidence that speciation can progress to "intermediate" stages-with populations evolving only partial reproductive isolation-studies describing selective mechanisms that impose constraints on speciation are more rare than those describing drivers. The stick insect Timema cristinae provides an example of a system in which partial reproductive isolation has evolved between populations adapted to different host plant environments, in part due to divergent selection acting on a pattern polymorphism [4, 5]. Here, we demonstrate how selection on a green/melanistic color polymorphism counteracts speciation in this system. Specifically, divergent selection between hosts does not occur on color phenotypes because melanistic T. cristinae are cryptic on the stems of both host species, are resistant to a fungal pathogen, and have a mating advantage. Using genetic crosses and genome-wide association mapping, we quantify the genetic architecture of both the pattern and color polymorphism, illustrating their simple genetic control. We use these empirical results to develop an individual-based model that shows how the melanistic phenotype acts as a "genetic bridge" that increases gene flow between populations living on different hosts. Our results demonstrate how variation in the nature of selection acting on traits, and aspects of trait genetic architecture, can impose constraints on both local adaptation and speciation.

Archiving Primary Data: Solutions for Long-Term Studies.

The recent trend for journals to require open access to primary data included in publications has been embraced by many biologists, but has caused apprehension amongst researchers engaged in long-term ecological and evolutionary studies. A worldwide survey of 73 principal investigators (Pls) with long-term studies revealed positive attitudes towards sharing data with the agreement or involvement of the PI, and 93% of PIs have historically shared data. Only 8% were in favor of uncontrolled, open access to primary data while 63% expressed serious concern. We present here their viewpoint on an issue that can have non-trivial scientific consequences. We discuss potential costs of public data archiving and provide possible solutions to meet the needs of journals and researchers.

The Association of H1N1 Pandemic Influenza with Congenital Anomaly Prevalence in Europe: An Ecological Time Series Study.

BACKGROUND: In the context of the European Surveillance of Congenital Anomalies (EUROCAT) surveillance response to the 2009 influenza pandemic, we sought to establish whether there was a detectable increase of congenital anomaly prevalence among pregnancies exposed to influenza seasons in general, and whether any increase was greater during the 2009 pandemic than during other seasons. METHODS: We performed an ecologic time series analysis based on 26,967 pregnancies with nonchromosomal congenital anomaly conceived from January 2007 to March 2011, reported by 15 EUROCAT registries. Analysis was performed for EUROCAT-defined anomaly subgroups, divided by whether there was a prior hypothesis of association with influenza. Influenza season exposure was based on World Health Organization data. Prevalence rate ratios were calculated comparing pregnancies exposed to influenza season during the congenital anomaly-specific critical period for embryo-fetal development to nonexposed pregnancies. RESULTS: There was no evidence for an increased overall prevalence of congenital anomalies among pregnancies exposed to influenza season. We detected an increased prevalence of ventricular septal defect and tricuspid atresia and stenosis during pandemic influenza season 2009, but not during 2007-2011 influenza seasons. For congenital anomalies, where there was no prior hypothesis, the prevalence of tetralogy of Fallot was strongly reduced during influenza seasons. CONCLUSIONS: Our data do not suggest an overall association of pandemic or seasonal influenza with congenital anomaly prevalence. One interpretation is that apparent influenza effects found in previous individual-based studies were confounded by or interacting with other risk factors. The associations of heart anomalies with pandemic influenza could be strain specific.