Processes models, environmental analyses, and cognitive architectures: Quo vadis quantum probability theory? (Commentary on Pothos and Busemeyer)

A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.

Auditory perceptual decision-making based on semantic categorization of environmental sounds.

Discriminating complex sounds relies on multiple stages of differential brain activity. The specific roles of these stages and their links to perception were the focus of the present study. We presented 250ms duration sounds of living and man-made objects while recording 160-channel electroencephalography (EEG). Subjects categorized each sound as that of a living, man-made or unknown item. We tested whether/when the brain discriminates between sound categories even when not transpiring behaviorally. We applied a single-trial classifier that identified voltage topographies and latencies at which brain responses are most discriminative. For sounds that the subjects could not categorize, we could successfully decode the semantic category based on differences in voltage topographies during the 116-174ms post-stimulus period. Sounds that were correctly categorized as that of a living or man-made item by the same subjects exhibited two periods of differences in voltage topographies at the single-trial level. Subjects exhibited differential activity before the sound ended (starting at 112ms) and on a separate period at ~270ms post-stimulus onset. Because each of these periods could be used to reliably decode semantic categories, we interpreted the first as being related to an implicit tuning for sound representations and the second as being linked to perceptual decision-making processes. Collectively, our results show that the brain discriminates environmental sounds during early stages and independently of behavioral proficiency and that explicit sound categorization requires a subsequent processing stage.

Origin-related, environmental, sex, and age determinants of immunocompetence, susceptibility to ectoparasites, and disease symptoms in the barn owl

Knowledge of the role of origin-related, environmental, sex, and age factors on host defence mechanisms is important to understand variation in parasite intensity. Because alternative components of parasite defence may be differently sensitive to various factors, they may not necessarily covary. Many components should therefore be considered to tackle the evolution of host-parasite interactions. In a population of barn owls (Tyto alba), we investigated the role of origin-related, environmental (i.e. year, season, nest of rearing, and body condition), sex, and age factors on 12 traits linked to immune responses [humoral immune responses towards sheep red blood cells (SRBC), human serum albumin (HSA) and toxoid toxin TT, T-cell mediated immune response towards the mitogen phytohemagglutinin (PHA)], susceptibility to ectoparasites (number and fecundity of Carnus haemapterus, number of Ixodes ricinus), and disease symptoms (size of the bursa of Fabricius and spleen, proportion of proteins that are immunoglobulins, haematocrit and blood concentration in leucocytes). Cross-fostering experiments allowed us to detect a heritable component of variation in only four out of nine immune and parasitic parameters (i.e. SRBC- and HSA-responses, haematocrit, and number of C. haemapterus). However, because nestlings were not always cross-fostered just after hatching, the finding that 44% of the immune and parasitic parameters were heritable is probably an overestimation. These experiments also showed that five out of these nine parameters were sensitive to the nest environment (i.e. SRBC- and PHA-responses, number of C. haemapterus, haematocrit and blood concentration in leucocytes). Female nestlings were more infested by the blood-sucking fly C. haemapterus than their male nestmates, and their blood was less concentrated in leucocytes. The effect of year, season, age (i.e. reflecting the degree of maturation of the immune system), brood size, position in the within-brood age hierarchy, and body mass strongly differed between the 12 parameters. Different components of host defence mechanisms are therefore not equally heritable and sensitive to environmental, sex, and age factors, potentially explaining why most of these components did not covary.

Plant species distributions along environmental gradients: do belowground interactions with fungi matter?

The distribution of plants along environmental gradients is constrained by abiotic and biotic factors. Cumulative evidence attests of the impact of biotic factors on plant distributions, but only few studies discuss the role of belowground communities. Soil fungi, in particular, are thought to play an important role in how plant species assemble locally into communities. We first review existing evidence, and then test the effect of the number of soil fungal operational taxonomic units (OTUs) on plant species distributions using a recently collected dataset of plant and metagenomic information on soil fungi in the Western Swiss Alps. Using species distribution models (SDMs), we investigated whether the distribution of individual plant species is correlated to the number of OTUs of two important soil fungal classes known to interact with plants: the Glomeromycetes, that are obligatory symbionts of plants, and the Agaricomycetes, that may be facultative plant symbionts, pathogens, or wood decayers. We show that including the fungal richness information in the models of plant species distributions improves predictive accuracy. Number of fungal OTUs is especially correlated to the distribution of high elevation plant species. We suggest that high elevation soil show greater variation in fungal assemblages that may in turn impact plant turnover among communities. We finally discuss how to move beyond correlative analyses, through the design of field experiments manipulating plant and fungal communities along environmental gradients.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Modelling the influence of change in fire regime on the local distribution of a Mediterranean pyrophytic plant species (Cistus salviifolius) at its northern range limit

Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.

Growth decrease in Alpine whitefish: investigating the relative contribution of fishing induced selection and environmental change and its implication for conservation measures

La pression exercée par les activités humaines menace pratiquement tous les écosystèmes aquatiques du globe. Ainsi, sous l'effet de divers facteurs tels que la pollution, le réchauffement climatique ou encore la pêche industrielle, de nombreuses populations de poissons ont vu leurs effectifs chuter et divers changements morphologiques ont été observés. Dans cette étude, nous nous sommes intéressés à une menace particulière: la sélection induite par la pêche sur la croissance des poissons. En effet, la génétique des populations prédit que la soustraction régulière des individus les plus gros peut entraîner des modifications rapides de certains traits physiques comme la croissance individuelle. Cela a par ailleurs été observé dans de nombreuses populations marines ou lacustres, dont les populations de féras, bondelles et autres corégones des lacs suisses. Toutefois, malgré un nombre croissant d'études décrivant ce phénomène, peu de plans de gestion en tiennent compte, car l'importance des effets génétiques liés à la pêche est le plus souvent négligée par rapport à l'impact des changements environnementaux. Le but premier de cette étude a donc été de quantifier l'importance des facteurs génétiques et environnementaux. Dans le premier chapitre, nous avons étudié la population de palée du lac de Joux (Coregonus palaea). Nous avons déterminé les différentiels de sélection dus à la pêche, c'est-à-dire l'intensité de la sélection sur le taux de croissance, ainsi que les changements nets de croissance au cours du temps. Nous avons observé une baisse marquée de croissance et un différentiel de sélection important indiquant qu'au moins 30% de la diminution de croissance observée était due à la pression de sélection induite par la pêche. Dans le deuxième chapitre, nous avons effectué les mêmes analyses sur deux espèces proches du lac de Brienz (C. albellus et C. fatioi) et avons observé des effets similaires dont l'intensité était spécifique à chaque espèce. Dans le troisième chapitre, nous avons analysé deux autres espèces : C. palaea et C. confusus du lac de Bienne, et avons constaté que le lien entre la pression de sélection et la diminution de croissance était influencé par des facteurs environnementaux. Finalement, dans le dernier chapitre, nous avons étudié les effets potentiels de différentes modifications de la taille des mailles des filets utilisés pour la pêche à l'aide de modèles mathématiques. Nous concluons que la pêche a un effet génétique non négligeable (et donc peu réversible) sur la croissance individuelle dans les populations observée, que cet effet est lié à la compétition pour la nourriture et à la qualité de l'environnement, et que certaines modifications simples de la taille des mailles des filets de pêche pourraient nettement diminuer l'effet de sélection et ainsi ralentir, voir même renverser la diminution de croissance observée.

Simultaneous determination of Pu and Am radioisotopes in environmental samples: a tool for determining origin and release date

A radiochemical procedure was developed for the sequential determination of Pu and Am radioisotopes in environmental samples. The radioisotope activities were then used to assess the origin and release date of the environmental plutonium. The radioanalytical procedure is based on the separation of Pu and Am on selective extraction chromatographic resins (Eichrom TEVA and DGA). Alpha sources were prepared by electrodeposition on stainless steel discs, and the alpha emitting radionuclides (238Pu, 239,240Pu and 241Am) were measured by alpha spectrometry. For the determination of the beta emitting 241Pu, the Pu alpha source was leached in hot concentrated nitric acid and the Pu fraction further purified by extraction chromatography on a small column of TEVA resin (100 μg of resin in a pipette tip). 241Pu is then measured by ultra low level liquid scintillation counting. Due to the lack of reference material for 241Pu, the proposed radiochemical method was nevertheless validated using four IAEA reference sediments with information values of 241Pu. The proposed method was then used to determine the 238Pu, 239,240Pu, 241Pu and 241Am activity concentrations in alpine soils of France and Switzerland. The soil is the primary receptor of the atmospheric radioactive fallout and, because of the strong binding interaction with soils particles, the isotopes are little fractionated. Therefore, the activity ratios 241Pu/239+240Pu and 238Pu/239,240Pu in soil samples were used to determine the origin (source) and date of the Pu contamination in the investigated alpine sites. The 241Pu/239,240Pu and 238Pu/239,240Pu activity ratios confirmed that the main origin of Pu in the alpine soils was the global fallout from the nuclear bomb tests (NBT) in the fifties and sixties. Furthermore, the 241Pu/241Am activity ratios were used to determine the age of the Pu contamination, which is also an important data for distinguishing the Pu sources. The estimation of the date of the contamination, by the 241Pu/241Am age-dating method, further confirmed the NBT as the Pu source. However, the 241Pu/241Am dating method was limited to samples where Pu-Am fractionation was insignificant. If any, the contribution of the Chernobyl accident in the studied sites is negligible.

What drives invasibility? A multi-model inference test and spatial modelling of alien plant species richness patterns in northern Portugal

Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.

Anthropogenic disturbance as a driver of microspatial and microhabitat segregation of cytotypes of Centaurea stoebe and cytotype interactions in secondary contact zones.

BACKGROUND AND AIMS: In a mixed-ploidy population, strong frequency-dependent mating will lead to the elimination of the less common cytotype, unless prezygotic barriers enhance assortative mating. However, such barriers favouring cytotype coexistence have only rarely been explored. Here, an assessment is made of the mechanisms involved in formation of mixed-ploidy populations and coexistence of diploid plants and their closely related allotetraploid derivates from the Centaurea stoebe complex (Asteraceae). METHODS: An investigation was made of microspatial and microhabitat distribution, life-history and fitness traits, flowering phenology, genetic relatedness of cytotypes and intercytotype gene flow (cpDNA and microsatellites) in six mixed-ploidy populations in Central Europe. KEY RESULTS: Diploids and tetraploids were genetically differentiated, thus corroborating the secondary origin of contact zones. The cytotypes were spatially segregated at all sites studied, with tetraploids colonizing preferentially drier and open microhabitats created by human-induced disturbances. Conversely, they were rare in more natural microsites and microsites with denser vegetation despite their superior persistence ability (polycarpic life cycle). The seed set of tetraploid plants was strongly influenced by their frequency in mixed-ploidy populations. Triploid hybrids originated from bidirectional hybridizations were extremely rare and almost completely sterile, indicating a strong postzygotic barrier between cytotypes. CONCLUSIONS: The findings suggest that tetraploids are later immigrants into already established diploid populations and that anthropogenic activities creating open niches favouring propagule introductions were the major factor shaping the non-random distribution and habitat segregation of cytotypes at fine spatial scale. Establishment and spread of tetraploids was further facilitated by their superior persistence through the perennial life cycle. The results highlight the importance of non-adaptive spatio-temporal processes in explaining microhabitat and microspatial segregation of cytotypes.

Accuracy of plant assemblage predictions from species distribution models varies along environmental gradients

Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.