Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.

Orexin/hypocretin (Orx/Hcrt) transmission and drug-seeking behavior: is the paraventricular nucleus of the thalamus (PVT) part of the drug seeking circuitry?

The orexin/hypocretin (Orx/Hcrt) system has long been considered to regulate a wide range of physiological processes, including feeding, energy metabolism, and arousal. More recently, concordant observations have demonstrated an important role for these peptides in the reinforcing properties of most drugs of abuse. Orx/Hcrt neurons arise in the lateral hypothalamus (LH) and project to all brain structures implicated in the regulation of arousal, stress, and reward. Although Orx/Hcrt neurons have been shown to massively project to the paraventricular nucleus of the thalamus (PVT), only recent evidence suggested that the PVT may be a key relay of Orx/Hcrt-coded reward-related communication between the LH and both the ventral and dorsal striatum. While this thalamic region was not thought to be part of the "drug addiction circuitry," an increasing amount of evidence demonstrated that the PVT-particularly PVT Orx/Hcrt transmission-was implicated in the modulation of reward function in general and several aspects of drug-directed behaviors in particular. The present review discusses recent findings that suggest that maladaptive recruitment of PVT Orx/Hcrt signaling by drugs of abuse may promote persistent compulsive drug-seeking behavior following a period of protracted abstinence and as such may represent a relevant target for understanding the long-term vulnerability to drug relapse after withdrawal.

Rates of cultural change and patterns of cultural accumulation in stochastic models of social transmission.

Cultural variation in a population is affected by the rate of occurrence of cultural innovations, whether such innovations are preferred or eschewed, how they are transmitted between individuals in the population, and the size of the population. An innovation, such as a modification in an attribute of a handaxe, may be lost or may become a property of all handaxes, which we call "fixation of the innovation." Alternatively, several innovations may attain appreciable frequencies, in which case properties of the frequency distribution-for example, of handaxe measurements-is important. Here we apply the Moran model from the stochastic theory of population genetics to study the evolution of cultural innovations. We obtain the probability that an initially rare innovation becomes fixed, and the expected time this takes. When variation in cultural traits is due to recurrent innovation, copy error, and sampling from generation to generation, we describe properties of this variation, such as the level of heterogeneity expected in the population. For all of these, we determine the effect of the mode of social transmission: conformist, where there is a tendency for each naïve newborn to copy the most popular variant; pro-novelty bias, where the newborn prefers a specific variant if it exists among those it samples; one-to-many transmission, where the variant one individual carries is copied by all newborns while that individual remains alive. We compare our findings with those predicted by prevailing theories for rates of cultural change and the distribution of cultural variation.

Testing new identity models and processes in French-speaking adolescents and emerging adults students

Developing a sense of identity is a crucial psychosocial task for young people. The purpose of this study was to evaluate identity development in French-speaking adolescents and emerging adults (in France and Switzerland) using a process-oriented model of identity formation including five dimensions (i.e., exploration in breadth, commitment making, exploration in depth, identification with commitment, and ruminative exploration). The study included participants from three different samples (total N = 2239, 66.7% women): two samples of emerging adult student and one sample of adolescents. Results confirmed the hypothesized five-factor dimensional model of identity in our three samples and provided evidence for convergent validity of the model. The results also indicated that exploration in depth might be subdivided in two aspects: a first form of exploration in depth leading to a better understanding and to an increase of the strength of current commitments and a second form of exploration in depth leading to a re-evaluation and a reconsideration of current commitments. Further, the identity status cluster solution that emerged is globally in line with previous literature (i.e., achievement, foreclosure, moratorium, carefree diffusion, diffused diffusion, undifferentiated). However, despite a structural similarity, we found variations in identity profiles because identity development is shaped by cultural context. These specific variations are discussed in light of social, educational and economic differences between France and the French-speaking part of Switzerland. Implications and suggestions for future research are offered.

Contribution of in vitro neurotoxicology studies to the elucidation of neurodegenerative processes.

Only a small percentage of neurodegenerative diseases like Alzheimer's disease and Parkinson's disease is directly related to familial forms. The etiology of the most abundant, sporadic forms seems to involve both genetic and environmental factors. Environmental compounds are now extensively studied for their possible contribution to neurodegeneration. Chemicals were found which were able to reproduce symptoms of known neurodegenerative diseases, others may either predispose to the onset of neurodegeneration, or exacerbate distinct pathogenic processes of these diseases. In any case, in vitro studies performed with models presenting various degrees of complexity have shown that many environmental compounds have the potential to cause neurodegeneration, through a variety of pathways similar to those described in neurodegenerative diseases. Since the population is exposed to a huge number of potentially neurotoxic compounds, there is an important need for rapid and efficient procedures for hazard evaluation. Xenobiotics elicit a cascade of reactions that, most of the time, involve numerous interactions between the different brain cell types. A reliable in vitro model for the detection of environmental toxins potentially at risk for neurodegenerative diseases should therefore allow maximal cell-cell interactions and multiparametric endpoints determination. The combined use of in vitro models and new analytical approaches using "omics" technologies should help to map toxicity pathways, and advance our understanding of the possible role of xenobiotics in the etiology of neurodegenerative diseases.

Ispol'zovanie metodov teorii vosstanovleniia v modeliakh optimal'nogo dobyvaniia pishchi [Restoration theory in models of optimal feeding behavior]

The method of stochastic dynamic programming is widely used in ecology of behavior, but has some imperfections because of use of temporal limits. The authors presented an alternative approach based on the methods of the theory of restoration. Suggested method uses cumulative energy reserves per time unit as a criterium, that leads to stationary cycles in the area of states. This approach allows to study the optimal feeding by analytic methods.

The role of NFI-C liver regeneration and its potential function as a general regulator of regenerative processes

Collectively, research aimed to understand the regeneration of certain tissues has unveiled the existence of common key regulators. Knockout studies of the murine Nuclear Factor I-C (NFI-C) transcription factor revealed a misregulation of growth factor signaling, in particular that of transforming growth factor ß-1 (TGF-ßl), which led to alterations of skin wound healing and the growth of its appendages, suggesting it may be a general regulator of regenerative processes. We sought to investigate this further by determining whether NFI-C played a role in liver regeneration. Liver regeneration following two-thirds removal of the liver by partial hepatectomy (PH) is a well-established regenerative model whereby changes elicited in hepatocytes following injury lead to a rapid, phased proliferation. However, mechanisms controlling the action of liver proliferative factors such as transforming growth factor-ßl (TGF-ß1) and plasminogen activator inhibitor-1 (PAI-1) remain largely unknown. We show that the absence of NFI-C impaired hepatocyte proliferation due to an overexpression of PAI-1 and the subsequent suppression of urokinase plasminogen (uPA) activity and hepatocyte growth factor (HGF) signaling, a potent hepatocyte mitogen. This indicated that NFI-C first acts to promote hepatocyte proliferation at the onset of liver regeneration in wildtype mice. The subsequent transient down regulation of NFI-C, as can be explained by a self- regulatory feedback loop with TGF-ßl, may limit the number of hepatocytes entering the first wave of cell division and/or prevent late initiations of mitosis. Overall, we conclude that NFI-C acts as a regulator of the phased hepatocyte proliferation during liver regeneration. Taken together with NFI-C's actions in other in vivo models of (re)generation, it is plausible that NFI-C may be a general regulator of regenerative processes. - L'ensemble des recherches visant à comprendre la régénération de certains tissus a permis de mettre en évidence l'existence de régulateurs-clés communs. L'étude des souris, dépourvues du gène codant pour le facteur de transcription NFI-C (Nuclear Factor I-C), a montré des dérèglements dans la signalisation de certains facteurs croissance, en particulier du TGF-ßl (transforming growth factor-ßl), ce qui conduit à des altérations de la cicatrisation de la peau et de la croissance des poils et des dents chez ces souris, suggérant que NFI-C pourrait être un régulateur général du processus de régénération. Nous avons cherché à approfondir cette question en déterminant si NFI-C joue un rôle dans la régénération du foie. La régénération du foie, induite par une hépatectomie partielle correspondant à l'ablation des deux-tiers du foie, constitue un modèle de régénération bien établi dans lequel la lésion induite conduit à la prolifération rapide des hépatocytes de façon synchronisée. Cependant, les mécanismes contrôlant l'action de facteurs de prolifération du foie, comme le facteur de croissance TGF-ßl et l'inhibiteur de l'activateur du plasminogène PAI-1 (plasminogen activator inhibitor-1), restent encore très méconnus. Nous avons pu montrer que l'absence de NFI-C affecte la prolifération des hépatocytes, occasionnée par la surexpression de PAI-1 et par la subséquente suppression de l'activité de la protéine uPA (urokinase plasminogen) et de la signalisation du facteur de croissance des hépatocytes HGF (hepatocyte growth factor), un mitogène puissant des hépatocytes. Cela indique que NFI-C agit en premier lieu pour promouvoir la prolifération des hépatocytes au début de la régénération du foie chez les souris de type sauvage. La subséquente baisse transitoire de NFI-C, pouvant s'expliquer par une boucle rétroactive d'autorégulation avec le facteur TGF-ßl, pourrait limiter le nombre d'hépatocytes qui entrent dans la première vague de division cellulaire et/ou inhiber l'initiation de la mitose tardive. L'ensemble de ces résultats nous a permis de conclure que NFI-C agit comme un régulateur de la prolifération des hépatocytes synchrones au cours de la régénération du foie.

Constraining ACT-R models of decision strategies: An experimental paradigm

It has been repeatedly debated which strategies people rely on in inference. These debates have been difficult to resolve, partially because hypotheses about the decision processes assumed by these strategies have typically been formulated qualitatively, making it hard to test precise quantitative predictions about response times and other behavioral data. One way to increase the precision of strategies is to implement them in cognitive architectures such as ACT-R. Often, however, a given strategy can be implemented in several ways, with each implementation yielding different behavioral predictions. We present and report a study with an experimental paradigm that can help to identify the correct implementations of classic compensatory and non-compensatory strategies such as the take-the-best and tallying heuristics, and the weighted-linear model.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.

Towards Machine Consciousness: Grounding Abstract Models as pi-Processes

We present a two-level model of concurrent communicating systems (CCS) to serve as a basis formachine consciousness. A language implementing threads within logic programming is ¯rstintroduced. This high-level framework allows for the de¯nition of abstract processes that can beexecuted on a virtual machine. We then look for a possible grounding of these processes into thebrain. Towards this end, we map abstract de¯nitions (including logical expressions representingcompiled knowledge) into a variant of the pi-calculus. We illustrate this approach through aseries of examples extending from a purely reactive behavior to patterns of consciousness.

Effect of spatial processes on the evolution of ecological niches and dispersal in metacommunity systems

RésuméLa coexistence de nombreuses espèces différentes a de tout temps intrigué les biologistes. La diversité et la composition des communautés sont influencées par les perturbations et l'hétérogénéité des conditions environnementales. Bien que dans la nature la distribution spatiale des conditions environnementales soit généralement autocorrélée, cet aspect est rarement pris en compte dans les modèles étudiant la coexistence des espèces. Dans ce travail, nous avons donc abordé, à l'aide de simulations numériques, la coexistence des espèces ainsi que leurs caractéristiques au sein d'un environnement autocorrélé.Afin de prendre en compte cet élément spatial, nous avons développé un modèle de métacommunauté (un ensemble de communautés reliées par la dispersion des espèces) spatialement explicite. Dans ce modèle, les espèces sont en compétition les unes avec les autres pour s'établir dans un nombre de places limité, dans un environnement hétérogène. Les espèces sont caractérisées par six traits: optimum de niche, largeur de niche, capacité de dispersion, compétitivité, investissement dans la reproduction et taux de survie. Nous nous sommes particulièrement intéressés à l'influence de l'autocorrélation spatiale et des perturbations sur la diversité des espèces et sur les traits favorisés dans la métacommunauté. Nous avons montré que l'autocorrélation spatiale peut avoir des effets antagonistes sur la diversité, en fonction du taux de perturbations considéré. L'influence de l'autocorrélation spatiale sur la capacité de dispersion moyenne dans la métacommunauté dépend également des taux de perturbations et survie. Nos résultats ont aussi révélé que de nombreuses espèces avec différents degrés de spécialisation (i.e. différentes largeurs de niche) peuvent coexister. Toutefois, les espèces spécialistes sont favorisées en absence de perturbations et quand la dispersion est illimitée. A l'opposé, un taux élevé de perturbations sélectionne des espèces plus généralistes, associées avec une faible compétitivité.L'autocorrélation spatiale de l'environnement, en interaction avec l'intensité des perturbations, influence donc de manière considérable la coexistence ainsi que les caractéristiques des espèces. Ces caractéristiques sont à leur tour souvent impliquées dans d'importants processus, comme le fonctionnement des écosystèmes, la capacité des espèces à réagir aux invasions, à la fragmentation de l'habitat ou aux changements climatiques. Ce travail a permis une meilleure compréhension des mécanismes responsables de la coexistence et des caractéristiques des espèces, ce qui est crucial afin de prédire le devenir des communautés naturelles dans un environnement changeant.AbstractUnderstanding how so many different species can coexist in nature is a fundamental and long-standing question in ecology. Community diversity and composition are known to be influenced by heterogeneity in environmental conditions and disturbance. Though in nature the spatial distribution of environmental conditions is frequently autocorrelated, this aspect is seldom considered in models investigating species coexistence. In this work, we thus addressed several questions pertaining to species coexistence and composition in spatially autocorrelated environments, with a numerical simulations approach.To take into account this spatial aspect, we developed a spatially explicit model of metacommunity (a set of communities linked by dispersal of species). In this model, species are trophically equivalent, and compete for space in a heterogeneous environment. Species are characterized by six life-history traits: niche optimum, niche breadth, dispersal, competitiveness, reproductive investment and survival rate. We were particularly interested in the influence of environmental spatial autocorrelation and disturbance on species diversity and on the traits of the species favoured in the metacommunity. We showed that spatial autocorrelation can have antagonistic effects on diversity depending on disturbance rate. Similarly, spatial autocorrelation interacted with disturbance rate and survival rate to shape the mean dispersal ability observed in the metacommunity. Our results also revealed that many species with various degrees of specialization (i.e. different niche breadths) can coexist together. However specialist species were favoured in the absence of disturbance, and when dispersal was unlimited. In contrast, high disturbance rate selected for more generalist species, associated with low competitive ability.The spatial structure of the environment, together with disturbance and species traits, thus strongly impacts species diversity and, more importantly, species composition. Species composition is known to affect several important metacommunity properties such as ecosystem functioning, resistance and reaction to invasion, to habitat fragmentation and to climate changes. This work allowed a better understanding of the mechanisms responsible for species composition, which is of crucial importance to predict the fate of natural metacommunities in changing environments

Literature report : a review of policy learning in five strands of political science research

This paper reviews the policy learning literature in political science. In recent years, the number of publications on learning in the political realm increased dramatically. Researchers have focused on how policymakers and administrators adapt policies based on learning processes or experiences. Thereby, learning has been discussed in very different ways. Authors have referred to learning in the context of ideas, understood as deeply held beliefs, and, as change and adaptation of policy instruments. Two other strands of literature have taken into consideration learning, namely the diffusion literature and research on transfer, which put forward learning to understand who learns from whom and what. Opposed to these views, political learning emphasizes the adaptation of new strategies by policymakers over the transfer of knowledge or broad ideas. In this approach, learning occurs due to the failure of existing policies, increasing problem pressure, scientific innovations, or a combination of these elements.