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Lithium (Li) abundance is an age indicator for G, K, and M stellar types, as its abundance decreases over time for these spectral types. However, despite the observational efforts made over the past few decades, the role of rotation, activity, and metallicity in the depletion of Li is still unclear. We have investigated how Li depletion is affected by rotation and metallicity in G and K members of the roughly Pleiades-aged open cluster M35. To do so, we have collected a sample of 165 candidate members observed with the WIYN/Hydra spectrograph. In addition, we have taken advantage of three previous spectroscopic studies of Li in M35. As a result, we have collected a final sample of 396 stars which we have classified as members and non-members of the cluster. We have measured iron abundances, Li equivalent widths, and Li abundances for the 110 M35 members added to the existing sample by this study. Finally, rotation periods for cluster members have been obtained from the literature or derived from Zwicky Transient Facility light curves. As a result, we have confirmed that fast G and K rotators are Li-rich in comparison with slow rotators of similar effective temperature. Furthermore, while we derived subsolar metallicity for M35 from our spectra, the distribution of Li in this cluster is similar to those observed for the Pleiades and M34, which have solar metallicity and slightly different ages. In addition, we have shown that an empirical relationship proposed to remove the contribution of the Fe I line at 670.75 nm to the blended feature at 670.78 nm overestimates the contribution of this iron line for M35 members. We conclude that a 0.2-0.3 dex difference in metallicity makes little difference in the Li distributions of open clusters with ages between 100 and 250 Myr., Comment: 14 pages, 11 figures, accepted for publication in A\&A

This work aims to investigate the behaviour of the lithium abundance in stars with and without detected planets. Our study is based on a sample of 1332 FGK main-sequence stars with measured lithium abundances, for 257 of which planets were detected. Our method reviews the sample statistics and is addressed specifically to the influence of tides and orbital decay, with special attention to planets on close orbits, whose stellar rotational velocity is higher than the orbital period of the planet. In this case, tidal effects are much more pronounced. The analysis also covers the orbital decay on a short timescale, with planets spiralling into their parent star. Furthermore, the sample allows us to study the relation between the presence of planets and the physical properties of their host stars, such as the chromospheric activity, metallicity, and lithium abundance. In the case of a strong tidal influence, we cannot infer from any of the studies described that the behaviour of Li differs between stars that host planets and those that do not. Our sample includes stars with super-solar metallicity ([Fe/H]>0.15 dex) and a low lithium abundance (A(Li) <1.0 dex). This enabled us to analyse scenarios of the origin and existence of these stars. Considering the possible explanation of the F dip, we show that it is not a plausible scenario. Our analysis is based on a kinematic study and concludes that the possible time that elapsed in the travel from their birth places in the central regions of the Galaxy to their current positions in the solar neighbourhood is not enough to explain the high lithium depletion. It is remarkable that those of our high-metallicity low-lithium stars with the greatest eccentricity (e>0.2) are closest to the Galactic centre. A dedicated study of a set of high-metallicity low-Li stars is needed to test the migration-depletion scenario., Comment: 16 pages, 9 figures, accepted for publication in A\&A

Quantitative predictions about the processes that promote species coexistence are a subject of active research in ecology. In particular, competitive interactions are known to shape and maintain ecological communities, and situations where some species out-compete or dominate over some others are key to describe natural ecosystems. Here we develop ecological theory using a stochastic, synthetic framework for plant community assembly that leads to predictions amenable to empirical testing. We propose two stochastic continuous-time Markov models that incorporate competitive dominance through a hierarchy of species heights. The first model, which is spatially implicit, predicts both the expected number of species that survive and the conditions under which heights are clustered in realized model communities. The second one allows spatially-explicit interactions of individuals and alternative mechanisms that can help shorter plants overcome height-driven competition, and it demonstrates that clustering patterns remain not only locally but also across increasing spatial scales. Moreover, although plants are actually height-clustered in the spatially-explicit model, it allows for plant species abundances not necessarily skewed to taller plants.

Recent collapses of many fisheries across the globe have challenged the mathematical approach to these systems through classic bioeconomic models. Decimated populations did not recover as fast as predicted by these models and depensatory effects were introduced to better fit the dynamics at low population abundances. Alternative to depensation, modeling captures by non-linear harvesting functions produces equivalent outcomes at small abundances, and the dynamics undergoes a bifurcation leading to population collapse and recovery once catching efforts are above or below certain thresholds, respectively. The time that a population takes to undergo these transitions has been mostly overlooked in bioeconomic contexts, though. In this work we quantify analytically and numerically the times associated to these collapse and recovery transitions in a model incorporating non-linear harvesting and immigration in the presence and absence of demographic stochasticity. Counterintuitively, although species at low abundances are prone to extinction due to demographic stochasticity, our results show that stochastic collapse and recovery times are upper bounded by their deterministic estimates. This occurs over the full range of immigration rates. Our work may have relevant quantitative implications in the context of fishery management and rebuilding., Comment: 14 pages, 5 figures

Community ecology has traditionally relied on the competitive exclusion principle, a piece of common wisdom in conceptual frameworks developed to describe species assemblages. Key concepts in community ecology, such as limiting similarity and niche partitioning, are based on competitive exclusion. However, this classical paradigm in ecology relies on implications derived from simple, deterministic models. Here we show how the predictions of a symmetric, deterministic model about the way extinctions proceed can be utterly different from the results derived from the same model when ecological drift (demographic stochasticity) is explicitly considered. Using analytical approximations to the steady-state conditional probabilities for assemblages with two and three species, we demonstrate that stochastic competitive exclusion leads to a cascade of extinctions, whereas the symmetric, deterministic model predicts a multiple collapse of species. To test the robustness of our results, we have studied the effect of environmental stochasticity and relaxed the species symmetry assumption. Our conclusions highlight the crucial role of stochasticity when deriving reliable theoretical predictions for species community assembly.

Understanding the main determinants of species coexistence across space and time is a central question in ecology. However, ecologists still know little about the scales and conditions at which biotic interactions matter and how these interact with the environment to structure species assemblages. Here we use recent theory developments to analyze plant distribution and trait data across Europe and find that plant height clustering is related to both evapotranspiration and gross primary productivity. This clustering is a signal of interspecies competition between plants, which is most evident in mid-latitude ecoregions, where conditions for growth (reflected in actual evapotranspiration rates and gross primary productivities) are optimal. Away from this optimum, climate severity likely overrides the effect of competition, or other interactions become increasingly important. Our approach bridges the gap between species-rich competition theories and large-scale species distribution data analysis.

Computer viruses are evolving by developing spreading mechanisms based on the use of multiple vectors of propagation. The use of the social network as an extra vector of attack to penetrate the security measures in IP networks is improving the effectiveness of malware, and have therefore been used by the most aggressive viruses, like Conficker and Stuxnet. In this work we use interdependent networks to model the propagation of these kind of viruses. In particular, we study the propagation of a SIS model on interdependent networks where the state of each node is layer-independent and the dynamics in each network follows either a contact process or a reactive process, with different propagation rates. We apply this study to the case of existing multilayer networks, namely a Spanish scientific community of Statistical Physics, formed by a social network of scientific collaborations and a physical network of connected computers in each institution. We show that the interplay between layers increases dramatically the infectivity of viruses in the long term and their robustness against immunization., Comment: Accepted for publication in Physica A

We give an intuitive though general explanation of the finite-size effect in scale-free networks in terms of the degree distribution of the starting network. This result clarifies the relevance of the starting network in the final degree distribution. We use two different approaches: the deterministic mean-field approximation used by Barab\'asi and Albert (but taking into account the nodes of the starting network), and the probability distribution of the degree of each node, which considers the stochastic process. Numerical simulations show that the accuracy of the predictions of the mean-field approximation depend on the contribution of the dispersion in the final distribution. The results in terms of the probability distribution of the degree of each node are very accurate when compared to numerical simulations. The analysis of the standard deviation of the degree distribution allows us to assess the influence of the starting core when fitting the model to real data., Comment: Published in Europhysics Letters

In this work we analyze the possibility that soliton dynamics in a simple nonlinear model allows functionally relevant predictions of the behaviour of DNA. This suggestion was first put forward by Salerno [Phys. Rev. A, vol. 44, p. 5292 (1991)] by showing results indicating that sine-Gordon kinks were set in motion at certain regions of a DNA sequence that include promoters. We revisit that system and show that the observed behaviour has nothing to do with promoters; on the contrary, it originates from the bases at the boundary, which are not part of the studied genome. We explain this phenomenology in terms of an effective potential for the kink center. This is further extended to disprove recent claims that the dynamics of kinks [Lenholm and H\"ornquist, Physica D, vol. 177, p. 233 (2003)] or breathers [Bashford, J. Biol. Phys., vol. 32, p. 27 (2006)] has functional significance. We conclude that no such information can be extracted from this simple nonlinear model or its associated effective potential., Comment: 17 pages, 7 figures

As a first step in the search of an analytical study of mechanical denaturation of DNA in terms of the sequence, we study stable, stationary solutions in the discrete, finite and homogeneous Peyrard-Bishop DNA model. We find and classify all the stationary solutions of the model, as well as analytic approximations of them, both in the continuum and in the discrete limits. Our results explain the structure of the solutions reported by Theodorakopoulos {\em et al.} [Phys. Rev. Lett. {\bf 93}, 258101 (2004)] and provide a way to proceed to the analysis of the generalized version of the model incorporating the genetic information., Comment: 15 pages, 12 figures

We study the phenomenon of length scale competition, an instability of solitons and other coherent structures that takes place when their size is of the same order of some characteristic scale of the system in which they propagate. Working on the framework of nonlinear Klein-Gordon models as a paradigmatic example, we show that this instability can be understood by means of a collective coordinate approach in terms of soliton position and width. As a consequence, we provide a quantitative, natural explanation of the phenomenon in much simpler terms than any previous treatment of the problem. Our technique allows to study the existence of length scale competition in most soliton bearing nonlinear models and can be extended to coherent structures with more degrees of freedom, such as breathers., Comment: 5 pages, 3 figures

We study the effects of the sequence on the propagation of nonlinear excitations in simple models of DNA in which we incorporate actual DNA sequences obtained from human genome data. We show that kink propagation requires forces over a certain threshold, a phenomenon already found for aperiodic sequences [F. Dom\'\i nguez-Adame {\em et al.}, Phys. Rev. E {\bf 52}, 2183 (1995)]. For forces below threshold, the final stop positions are highly dependent on the specific sequence. The results of our model are consistent with the stick-slip dynamics of the unzipping process observed in experiments. We also show that the effective potential, a collective coordinate formalism introduced by Salerno and Kivshar [Phys. Lett. A {\bf 193}, 263 (1994)] is a useful tool to identify key regions in DNA that control the dynamical behavior of large segments. Additionally, our results lead to further insights in the phenomenology observed in aperiodic systems., Comment: Final version, accepted in Physical Review E, minor changes in text, figures improved

We study the effects of the sequence on the propagation of nonlinear excitations in simple models of DNA, and how those effects are modified by noise. Starting from previous results on soliton dynamics on lattices defined by aperiodic potentials, [F. Dom\'\i nguez-Adame {\em et al.}, Phys. Rev. E {\bf 52}, 2183 (1995)], we analyze the behavior of lattices built from real DNA sequences obtained from human genome data. We confirm the existence of threshold forces, already found in Fibonacci sequences, and of stop positions highly dependent on the specific sequence. Another relevant conclusion is that the effective potential, a collective coordinate formalism introduced by Salerno and Kivshar [Phys. Lett. A {\bf 193}, 263 (1994)] is a useful tool to identify key regions that control the behaviour of a larger sequence. We then study how the fluctuations can assist the propagation process by helping the excitations to escape the stop positions. Our conclusions point out to improvements of the model which look promising to describe mechanical denaturation of DNA. Finally, we also consider how randomly distributed energy focus on the chain as a function of the sequence., Comment: 14 pages, final version, accepted in Fluctuation and Noise Letters, scheduled to apper in vol. 4, issue 3 (2004)