A common working procedure in Ecology is to identify patterns and elaborate hypotheses about the processes that may be responsible for their occurrence (Levin, 1992). One approach to identifying and characterizing patterns in community and network ecology is through the calculation of nestedness (Bascompte et al., 2003). Nestedness is a measure of a particular type of pattern in an ecological system, referring to the order that emanates from the way elements of a particular set are linked to elements of a second set. These links may relate, for instance, to the interactions that are established between two sets of species in an ecosystem (e.g., plant-pollinator interactions, Bascompte et al., 2003), or to the occurrence of a set of species in a given set of habitat fragments of different sizes (Atmar and Patterson, 1993). Thus, in the latter case, species assemblages are nested if the species present in species-poor sites are proper subsets of the assemblages found in species-rich sites (Patterson and Atmar, 1986), and perfect nestedness occurs when all species-poor sites are proper subsets of the assemblages found in richerspecies sites (Almeida-Neto et al., 2007). It should be noted, though, that absence of nestedness does not always mean absence of pattern. Several other types of patterns, such as gradients and compartments, may also be found in ecological systems (Leibold and Mikkelson, 2002;Lewinsohn et al., 2006;Almeida-Neto et al., 2007). Nestedness can be assessed through an ordered binary presence-absence

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Disclosure of potential conflicts of interest (COIs) is used by biomedical journals to guarantee credibility and transparency of the scientific process. Conflict of interest disclosure, however, is not systematically nor consistently dealt with by journals. Recent joint editorial efforts paved the way towards the implementation of uniform vehicles for COI disclosure. This paper provides a comprehensive editorial perspective on classical COI-related issues. New insights into the current COI policies and practices among European Society of Cardiology National Cardiovascular Journals, as derived from a cross-sectional survey using a standardized questionnaire, are discussed.

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We introduce a new population dynamics model for mutualistic communities. The new model preserves the original logistic formulation. We perform an analytical stability analysis to study the model behavior. We perform numerical simulations to test the model behavior. The model shows as much richness or even more than other mutualistic models. a r t i c l e i n f o t r a c tMutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r À K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r À K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities.

In the last 15 years, a complex networks perspective has been increasingly used in the robustness assessment of ecological systems. It is therefore crucial to assess the reliability of such tools. Based on the traditional simulation of node (species) removal, mutualistic pollination networks are considered to be relatively robust because of their 1) truncated power-law degree distribution, 2) redundancy in the number of pollinators per plant and 3) nested interaction pattern. However, species removal is only one of several possible approaches to network robustness assessment. Empirical evidence suggests a decline in abundance prior to the extinction of interacting species, arguing in favour of an interaction removalbased approach (i.e. interaction disruption), as opposed to traditional species removal. For simulated networks, these two approaches yield radically different conclusions, but no tests are currently available for empirical mutualistic networks. This study compared this new robustness evaluation approach based on interaction extinction versus the traditional species removal approach for 12 alpine and subalpine pollination networks. In comparison with species removal, interaction removal produced higher robustness in the worst-case extinction scenario but lower robustness in the best-case extinction scenario. Our results indicate that: 1) these two approaches yield very different conclusions and 2) existing assessments of ecological network robustness could be overly optimistic, at least those based on a disturbance affecting species at random or beginning with the least connected species. Therefore, further empirical study of plant-pollinator interactions in disturbed ecosystems is imperative to understand how pollination networks are disassembled.

Cystic fibrosis (CF) lung microbiota composition has recently been redefined by the application of next-generation sequencing (NGS) tools, identifying, among others, previously undescribed anaerobic and uncultivable bacteria. In the present study, we monitored the fluctuations of this ecosystem in 15 CF patients during a 1-year follow-up period, describing for the first time, as far as we know, the presence of predator bacteria in the CF lung microbiome. In addition, a new computational model was developed to ascertain the hypothetical ecological repercussions of a prey-predator interaction in CF lung microbial communities. Fifteen adult CF patients, stratified according to their pulmonary function into mild (n = 5), moderate (n = 9), and severe (n = 1) disease, were recruited at the CF unit of the Ramón y Cajal University Hospital (Madrid, Spain). Each patient contributed three or four induced sputum samples during a 1-year follow-up period. Lung microbiota composition was determined by both cultivation and NGS techniques and was compared with the patients’ clinical variables. Results revealed a particular microbiota composition for each patient that was maintained during the study period, although some fluctuations were detected without any clinical correlation. For the first time, Bdellovibrio and Vampirovibrio predator bacteria were shown in CF lung microbiota and reduced-genome bacterial parasites of the phylum Parcubacteria were also consistently detected. The newly designed computational model allows us to hypothesize that inoculation of predators into the pulmonary microbiome might contribute to the control of chronic colonization by CF pathogens in early colonization stages.

PACS. 68.35.Ct -Interface structure and roughness. PACS. 68.35.Fx -Diffusion; interface formation. PACS. 89.75.Da -Systems obeying scaling laws.Abstract. -We present experimental results for the dynamical scaling properties of the development of plant calli. We have assayed two different species of plant calli, Brassica oleracea and Brassica rapa, under different growth conditions, and show that their dynamical scalings share a universality class. From a theoretical point of view, we introduce a scaling hypothesis for systems whose size evolves in time. We expect our work to be relevant for the understanding and characterization of other systems that undergo growth due to cell division and differentiation, such as, for example, tumor development.c EDP Sciences