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Intraspecific interactions are key drivers of population dynamics because they establish relations between individual fitness and population density. The component Allee effect is defined as a positive correlation between any fitness component of a focal organism and population density, and it can lead to positive density dependence in the population per capita growth rate. The spatial population structure is key to determining whether and to which extent a component Allee effect will manifest at the demographic level because it determines how individuals interact with one another. However, existing spatial models to study the Allee effect impose a fixed spatial structure, which limits our understanding of how a component Allee effect and the spatial dynamics jointly determine the existence of demographic Allee effects. To fill this gap, we introduce a spatially-explicit theoretical framework where spatial structure and population dynamics are emergent properties of the individual-level demographic and movement rates. Depending on the intensity of the individual-level processes the population exhibits a variety of spatial patterns, including evenly spaced aggregates of organisms, that determine the demographic-level by-products of an existing individual-level component Allee effect. We find that aggregation increases population abundance and allows populations to survive in harsher environments and at lower global population densities when compared with uniformly distributed organisms. Moreover, aggregation can prevent the component Allee effect from manifesting at the population level or restrict it to the level of each independent group. These results provide a mechanistic understanding of how component Allee effects might operate for different spatial population structures and show at the population level. Because populations subjected to demographic Allee effects exhibit highly nonlinear dynamics, especially at low abundances, our results contribute to better understanding population dynamics in the presence of Allee effects and can potentially inform population management strategies.

Self-organized spatial patterns are ubiquitous in ecological systems and allow populations to adopt non-trivial spatial distributions starting from disordered configurations. These patterns form due to diverse nonlinear interactions among organisms and between organisms and their environment, and lead to the emergence of new (eco)system-level properties unique to self-organized systems. Such pattern consequences include higher resilience and resistance to environmental changes, abrupt ecosystem collapse, hysteresis loops, and reversal of competitive exclusion. Here, we review ecological systems exhibiting self-organized patterns. We establish two broad pattern categories depending on whether the self-organizing process is primarily driven by nonlinear density-dependent demographic rates or by nonlinear density-dependent movement. Using this organization, we examine a wide range of observational scales, from microbial colonies to whole ecosystems, and discuss the mechanisms hypothesized to underlie observed patterns and their system-level consequences. For each example, we review both the empirical evidence and the existing theoretical frameworks developed to identify the causes and consequences of patterning. Finally, we trace qualitative similarities across systems and propose possible ways of developing a more quantitative understanding of how self-organization operates across systems and observational scales in ecology.

Plant interactions, understood as the net effect of an individual on the fitness of a neighbor, vary in strength and can shift from negative interference to positive facilitation as the environmental conditions change in time and space. However, the biophysical mechanisms underlying these changes are not well understood. Additionally, evolutionary theory questions the stability of antagonistic facilitation. Using a mechanistic model for belowground resource competition between individual plants, we find that, under stress conditions, antagonistic facilitation is evolutionarily stable even when both interacting plants compete for resources. This supports the theory of ecosystem engineers in primary succession and nurse plants in the stress gradient hypothesis. Furthermore, we find that the proportion of the limiting resource that spontaneously becomes available to any plant is the key environmental parameter determining the evolutionary stability of facilitation. This represents a challenge and a potential confusion factor for empirical studies.

SummaryAnimals moving through landscapes need to strike a balance between finding sufficient resources to grow and reproduce while minimizing encounters with predators1,2. Because encounter rates are determined by the average distance over which directed motion persists1,3–5, this trade-off should be apparent in individuals’ movement. Using GPS data from 1,396 individuals across 62 species of terrestrial mammals, we show how predators maintained directed motion ~7 times longer than for similarly-sized prey, revealing how prey species must trade off search efficiency against predator encounter rates. Individual search strategies were also modulated by resource abundance, with prey species forced to risk higher predator encounter rates when resources were scarce. These findings highlight the interplay between encounter rates and resource availability in shaping broad patterns mammalian movement strategies.

International audience; Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longerterm in situ data. Here, we evaluate the theoretical prediction that regular vegetation patterns are associated with empirically derived temporal indicators (autocorrelation, variance, responsiveness) of critical slowing down in a dryland ecosystem in Sudan using different remote sensing products. We use recently developed methods using remote-sensing EVI time-series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test the predicted slowing down. We tested our empirical findings against theoretical predictions from a stochastic version of a spatial explicit model that has been used to describe vegetation dynamics in drylands under aridity stress. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non-linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non-linear way. Our findings suggest that spatial self-organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non-linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions.

Ecologists use the net biotic interactions among plants as a major factor to predict other ecosystem features, such as species diversity, community structure, or plant atmospheric carbon uptake. By adopting this approach, ecologists have built a giant body of theory founded on observational evidence. However, growing evidence points out that this may not be the right approach. The literature addressing the biophysical mechanisms underlying the plant interactions is much scarcer. A rising number of scientists claim the need for a mechanistic understanding of plant interactions due to the limitations that a phenomenological approach raises both in empirical and theoretical studies. Scattered studies have recently taken such a mechanistic approach, but we still lack a general theoretical framework to study mechanistically plant interactions. In this review, we first recapitulate the elementary units of plant interactions, i.e., all the known biophysical processes affected by the presence of an influencing plant and the possible phenotypic responses of plants influenced by those processes. Second, we discuss how a net interaction between two plants emerges from the simultaneous effect of these elementary units. Third, we touch upon the spatial and temporal variability of the net interaction and discuss the links between this variability and the underlying biophysical processes. We conclude by discussing how to integrate these processes into a mechanistic framework for plant interactions that must necessarily focus on the individual scale and explicitly incorporate the spatial structure of the community and environmental factors: the plant interaction models (PIM). A PIM incorporates a pair or few plants interacting with their physical environment so that the biotic interaction is not imposed but emerges from the model. This type of model can provide concise, mechanistic hypotheses to be tested empirically. This review calls for a paradigm shift in the ecology of plant interactions, from the classic species interaction study towards a more mechanistic individual-level approach. It also presents a comprehensive foundation for studying the mechanisms underpinning the net interaction between two plants.

Increased fragmentation caused by habitat loss presents a major threat to the persistence of animal populations. Whereas the negative effects of habitat loss on biodiversity are well-known, the effects of fragmentation per se on population dynamics and ecosystem stability remain less understood. How fragmentation affects populations is strongly determined by the rate at which individuals can move between separated habitat patches within the fragmented landscape. Here, we use a computational, spatially explicit predator-prey model to investigate how the interplay between fragmentation per se and optimal foraging behavior influences predator-prey interactions and, ultimately, ecosystem stability. We study cases where prey occupies isolated habitat patches and let predators disperse between patches following a Levy random walk. Our results show that both the Levy exponent and the degree of fragmentation strongly determine coexistence probabilities. Brownian and ballistic predators go extinct in highly fragmented landscapes and only scale-free predators can coexist with prey. Furthermore, our results reveal that predation causes irreversible loss of prey habitat in highly fragmented landscapes due to the overexploitation of smaller patches. Moreover, our results show that predator movement can reduce, but not prevent not minimize, the amount of irreversibly lost habitat. Our results suggest that incorporating optimal foraging theory into population- and landscape ecology models is crucial to assess the impact of fragmentation on biodiversity and ecosystem stability.

Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer-term in situ data. Here, we use recently developed methods using remote-sensing EVI time-series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test these predictions. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non-linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non-linear way. Our findings suggest that spatial self-organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non-linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions.

Plant roots determine carbon uptake, survivorship, and agricultural yield and represent a large proportion of the world's vegetation carbon pool. Study of belowground competition, unlike aboveground shoot competition, is hampered by our inability to observe roots. We developed a consumer-resource model based in game theory that predicts the root density spatial distribution of individual plants and tested themodel predictions in a greenhouse experiment. Plants in the experiment reacted to neighbors as predicted by the model's evolutionary stable equilibrium, by both overinvesting in nearby roots and reducing their root foraging range. We thereby provide a theoretical foundation for belowground allocation of carbon by vegetation that reconciles seemingly contradictory experimental results such as root segregation and the tragedy of the commons in plant roots., This work was supported by the Princeton University May Fellowship in the department of Ecology and Evolutionary Biology, the Gordon and Betty Moore Foundation through grant GBMF2550.06,Instituto Serrapilheira through grant Serra-1911-31200, FAPESP through grants ICTP-SAIFR 2016/01343-7, and Programa Jovens Pesquisadores em Centros Emergentes 2019/24433-0, the Simons Foundation, the Spanish 235 Ministry for Science, Innovation and Universities (COMEDIAS grant CGL2017-83170-R), and the Princeton Environmental Institute Carbon Mitigation Initiative.

Introduction Coronary artery bypass grafting (CABG) continues to be the most commonly performed cardiac surgical procedure in the world. The use of multiarterial grafting may confer a long-term survival benefit over the use of vein grafts. However, there is a paucity of data comparing the use of in situ versus free right internal mammary artery (RIMA) in isolated CABG. Methods Patients that underwent isolated CABG between 2010 and 2018 where RIMA was used in addition to a left internal mammary artery graft. Patients with prior cardiac surgery or percutaneous coronary intervention were excluded. Propensity matching was used for subanalysis. Mortality and major adverse cardiac and cerebrovascular events (MACCE) were analyzed with Kaplan-Meier survival curves and Cox multivariable regression. Heart failure-specific readmissions were assessed with cumulative incidence curves with Fine and Gray competing risk regression. Results A total of 667 patients underwent isolated CABG. Of those, 422 had free RIMA and 245 had in situ RIMA utilized. Mortality was similar between cohorts (p = 0.199) with 5-year mortality rates of 6.6% (free) and 4.1% (in situ). MACCE was similar between cohorts, with 5-year event rates of 33.6% and 33.9% (p = 0.99). RIMA style was not a significant predictor of any outcome. Conclusion There was no difference in long-term mortality, complications, MACCE, or heart failure readmissions when comparing a contemporary cohort of patients undergoing isolated CABG utilizing RIMA as a conduit. These data may allow surgeons to consider using RIMA either as an in situ or a free conduit.

Background The purpose of this study is to provide an update on trends in physician volume and payments for enteric tube placement and maintenance procedures by method, provider specialty, and practice setting amongst Medicare beneficiaries from 2010 to 2018. Materials and methods Claims from the Medicare Part B Physician/Supplier Procedure Summary Master File (PSPSMF) for the years 2010 to 2018 were extracted using current procedural terminology (CPT) codes for gastrostomy and jejunostomy placement, as well as conversion of gastrostomy to gastrojejunostomy, fluoroscopy guided and non-image guided replacement. Total volumes and provider reimbursement were analyzed by provider specialty and practice setting. Results Volume of de novo placement of all enteric tubes decreased from 157,123 to 106,549 (−32.2%). While endoscopic placement decreased from 133,658 to 81,171 (−39.3%), the volume of fluoroscopic placement increased from 17,999 to 21,277 (18.2%). Fluoroscopic placement was largely performed by interventional radiology (IR) (91.7% in 2018). Surgical placement decreased from 5466 to 4101 (−25.0%). Volume of fluoroscopic replacement increased from 24,799 to 38,470 (55.1%), while non-image guided replacements decreased from 61,377 to 55,116 (−10.2%). Share of both fluoroscopic and non-image guided replacements by advanced practice providers (APPs) more than doubled over this time period. Conclusion De novo placement of enteric tubes decreased from 2010 to 2018, likely related to increased awareness of the complications and limited benefits in scenarios such as end of life care. In contrast to the diminishing volume for gastroenterologists, there was increased participation by IR in both placement and maintenance procedures under fluoroscopic guidance. Summary statement Decreasing placement of enteric tubes suggests shifting attitudes and recommendations around end-of-life care. Increase in role by IR/APPs highlights the need for comprehensive care in these patients.

The exploitative segregation of plant roots (ESPR) is a theory that uses a game-theoretical model to predict plant root foraging behavior in space. The original model returns the optimal root distribution assuming exploitative competition between a pair of identical plants in soils with homogeneous resource dynamics. In this short communication, we explore avenues to develop this model further. We discuss: (i) the response of single plants to soil heterogeneity; (ii) the variability of the plant response under uneven competition scenarios; (iii) the importance of accounting for the constraints and limitations to root growth that may be imposed from the plant shoot; (iv) the importance of root functional traits to predict root foraging behavior; (v) potential model extensions to investigate facilitation by incorporating facilitative traits to roots, and (vi) the possibility of allowing plants to tune their response by accounting for non-self and non-kin root recognition. For each case, we introduce the topic briefly and present possible ways to encode those ingredients in the mathematical equations of the ESPR model, providing preliminary results when possible., We thank four anonymous reviewers for their constructive comments on previous versions of this text. CC was supported by the Princeton University May Fellowship in the Department of Ecology and Evolutionary Biology and by the Princeton Environmental Institute Carbon Mitigation Initiative (PEI-CMI); RMG by Instituto Serrapilheira (grant Serra-1911-31200), FAPESP (grants ICTP-SAIFR 2016/01343-7 Programa Jovens Pesquisadores em Centros Emergentes 2019/24433-0, 2019/05523-8) and the Simons Foundation; FV by the Spanish Ministry for Science, Innovation and Universities (COMEDIAS grant CGL2017-83170-R).

Self-organized spatial patterns of vegetation are frequent in water-limited regions and have been suggested as important indicators of ecosystem health. However, the mechanisms underlying their emergence remain unclear. Some theories hypothesize that patterns could result from a scale-dependent feedback (SDF), whereby interactions favoring plant growth dominate at short distances and growth-inhibitory interactions dominate in the long range. However, we know little about how net plant-to-plant interactions may change sign with inter-individual distance, and in the absence of strong empirical support, the relevance of this SDF for vegetation pattern formation remains disputed. These theories predict a sequential change in pattern shape from gapped to labyrinthine to spotted spatial patterns as precipitation declines. Nonetheless, alternative theories show that the same sequence of patterns could emerge even if net interactions between plants were always inhibitory (purely competitive feedbacks, PCF). Although these alternative hypotheses lead to visually indistinguishable patterns they predict very different desertification dynamics following the spotted pattern. Moreover, vegetation interaction with other ecosystem components can introduce additional spatio-temporal scales that reshape both the patterns and the desertification dynamics. Therefore, to make reliable ecological predictions for a focal ecosystem, it is crucial that models accurately capture the mechanisms at play in the system of interest. Here, we review existing theories for vegetation self-organization and their conflicting predictions about desertification dynamics. We further discuss possible ways for reconciling these predictions and potential empirical tests via manipulative experiments to improve our understanding of how vegetation self-organizes and better predict the fate of the ecosystems where they form., This work is supported by FAPESP through grants ICTP-SAIFR 2016/01343-7, and Programa Jovens Pesquisadores em Centros Emergentes 2019/24433-0 and 2019/05523-8, Instituto Serrapilheira through grant Serra-1911-31200, and the Simons Foundation (RMG); the Princeton University May Fellowship in the department of Ecology and Evolutionary Biology (CC); MINECO/AEI/FEDER through the María de Maeztu Program for Units of Excellence in R&D (MDM-2017-0711, Spain) (EHG & CL); The Gordon and Betty Moore Foundation, grant #7800 (CET & JAB); and the NSF grant DMS-2052616 (JAB). This work was partially funded by the Center of Advanced Systems Understanding (CASUS) which is financed by Germany’s Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament (JMC).

Made available in DSpace on 2021-06-25T10:58:24Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 Ecologists have long been interested in linking individual behaviour with higher level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modelling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounter rates while the relationship between individual movement and the spatial locations of encounter events in the environment has remained conspicuously understudied. Here, we bridge this gap by introducing a method for describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open-source software and demonstrate the broad ecological relevance of this distribution. We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: (a) a population of individuals with home ranges that overlap with neighbours; (b) a pair of individuals with a hard territorial border between their home ranges; and (c) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins Cebus capucinus, tracked on Barro Colorado Island, Panama, and sleepy lizards Tiliqua rugosa, tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the potential for competitive or predatory interactions and/or identify any changes in behaviour that directly result from location-specific encounter probability. The CDE enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialized data collection protocols. This method is now openly available via the ctmm R package. Department of Biology The Irving K. Barber Faculty of Science The University of British Columbia Smithsonian Conservation Biology Institute National Zoological Park ICTP South American Institute for Fundamental Research & Instituto de Fisica Teorica – UNESP Department of Anthropology University of California Smithsonian Tropical Research Institute Department for the Ecology of Animal Societies Max Planck Institute of Animal Behavior Department of Biology University of Konstanz Centre for the Advanced Study of Collective Behaviour University of Konstanz North Carolina Museum of Natural Sciences and North Carolina State University College of Science and Engineering James Cook University Department of Environmental Science and Policy University of California Davis School of Zoology Faculty of Life Sciences Tel Aviv University Department of Biology University of Maryland Center for Advanced Systems Understanding (CASUS) Helmholtz-Zentrum Dresden Rossendorf (HZDR) Department of Ecological Modelling Helmholtz Centre for Environmental Research (UFZ) ICTP South American Institute for Fundamental Research & Instituto de Fisica Teorica – UNESP

Made available in DSpace on 2022-04-29T08:32:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-12-07 We introduce and analyze a spatial Lotka-Volterra competition model with local and nonlocal interactions. We study two alternative classes of nonlocal competition that differ in how each species’ characteristics determine the range of the nonlocal interactions. In both cases, nonlocal interactions can create spatial patterns of population densities in which highly populated clumps alternate with unpopulated regions. These non-populated regions provide spatial niches for a weaker competitor to establish in the community and persist in conditions in which local models predict competitive exclusion. Moreover, depending on the balance between local and nonlocal competition intensity, the clumps of the weaker competitor vary from M-like structures with higher densities of individuals accumulating at the edges of each clump to triangular structures with most individuals occupying their centers. These results suggest that long-range competition, through the creation of spatial patterns in population densities, might be a key driving force behind the rich diversity of species observed in natural ecological communities. ICTP South American Institute for Fundamental Research & Instituto de Física Teórica Universidade Estadual Paulista - UNESP, Rua Dr. Bento Teobaldo Ferraz 271, Bloco 2 - Barra Funda ICTP South American Institute for Fundamental Research & Instituto de Física Teórica Universidade Estadual Paulista - UNESP, Rua Dr. Bento Teobaldo Ferraz 271, Bloco 2 - Barra Funda

We introduce an asymmetric noisy voter model to study the joint effect of immigration and a competition-dispersal tradeoff in the dynamics of two species competing for space in regular lattices. Individuals of one species can invade a nearest-neighbor site in the lattice, while individuals of the other species are able to invade sites at any distance but are less competitive locally, i.e., they establish with a probability g≤1. The model also accounts for immigration, modeled as an external noise that may spontaneously replace an individual at a lattice site by another individual of the other species. This combination of mechanisms gives rise to a rich variety of outcomes for species competition, including exclusion of either species, mono-stable coexistence of both species at different population proportions, and bi-stable coexistence with proportions of populations that depend on the initial condition. Remarkably, in the bi-stable phase, the system undergoes a discontinuous transition as the intensity of immigration overcomes a threshold, leading to a half loop dynamics associated to a cusp catastrophe, which causes the irreversible loss of the species with the shortest dispersal range., RMG acknowledges financial support from the Simons Foundation, Instituto Serrapilheira through grant Serra-1911-31200, and FAPESP through the ICTP-SAIFR grant2016/01343-7 and Programa Jovens Pesquisadores em Centros Emergentes 2019/24433-0, 2019/05523-8. CL acknowledges financial support from the Spanish State Research Agency through the María de Maeztu Programfor Units of Excellence in R&D (MDM-2017-0711). FV acknowledges the University of the Balearic Islands for agrant under program Visiting of lecturers and financial support from CONICET (Grant No. PIP 0443/2014)and from Agencia Nacional de Promoción Científica yTecnológica (Grant No. PICT 2016 Nro 201 0215).

Ecologists have long been interested in linking individual behavior with higher-level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors, and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modeling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounterrateswhile no theoretical framework exists for directly relating individual movement with the spatiallocationsof encounter events in the environment.Here, we bridge this gap by introducing a new theoretical concept describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open source software, and demonstrate the broad ecological relevance of this novel concept.We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: i) a population of individuals with home ranges that overlap with neighbors; ii) a pair of individuals with a hard territorial border between their home ranges; and iii) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins (Cebus capucinus) tracked on Barro Colorado Island, Panama, and sleepy lizards (Tiliqua rugosa) tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the location-specific potential for competition, and/or identify any changes in behaviour that directly result from location-specific encounter probability.This novel target distribution enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialised data collection protocols. This method is now openly available via the ctmm R package.

Eco-evolutionary frameworks can explain certain features of communities in which ecological and evolutionary processes occur over comparable timescales. Here, we investigate whether an evolutionary dynamics may interact with the spatial structure of a prey-predator community in which both species show limited mobility and predator perceptual ranges are subject to natural selection. In these conditions, our results unveil an eco-evolutionary feedback between species spatial mixing and predators perceptual range: different levels of mixing select for different perceptual ranges, which in turn reshape the spatial distribution of prey and its interaction with predators. This emergent pattern of interspecific interactions feeds back to the efficiency of the various perceptual ranges, thus selecting for new ones. Finally, since prey-predator mixing is the key factor that regulates the intensity of predation, we explore the community-level implications of such feedback and show that it controls both coexistence times and species extinction probabilities., This work is partially funded by the Gordon and Betty Moore Foundation through Grant GBMF2550.06, the Simons Foundation, and FAPESP through ICTP-SAIFR grant 2016/01343-7 and Programa Jovens Pesquisadores em Centros Emergentes grant 2019/24433-0 (RMG); and by the Spanish Research Agency, through grant ESOTECOS FIS2015-63628-C2-1-R (AEI/FEDER, EU) and grant MDM-2017-0711 from the Maria de Maeztu Program for units of Excellence in R&D (EHC, CL and EH-G).

D. discoideum has been recently suggested as an example of bet-hedging. Upon starvation a population of unicellular amoebae splits between aggregators, which form a fruiting body made of a stalk and resistant spores, and non-aggregators. Spores are favored by long starvation periods, but vegetative cells can exploit resources in fast-recovering environments. This partition can be understood as a bet-hedging strategy that evolves in response to stochastic starvation times. A genotype is defined by a different balance between each type of cells. In this framework, if the ecological conditions are defined in terms of the mean starvation time (i.e. time between onset of starvation and the arrival of a new food pulse), a single genotype dominates each environment, which is inconsistent with the huge genetic diversity observed in nature. We investigate whether seasonality, represented by a periodic alternation in the mean starvation times, allows the coexistence of several strategies. We use a non-spatial (well-mixed) setting where different strains compete for a pulse of resources. We find that seasonality, which we model via two seasons, induces a temporal storage effect that can promote the stable coexistence of multiple genotypes. Two conditions need to be met. First, the distributions of starvation times in each season cannot overlap in order to create two well differentiated habitats within the year. Second, numerous growth-starvation cycles have to occur during each season to allow well-adapted strains to grow and survive the subsequent unfavorable period. Additional tradeoffs among life-history traits can expand the range of coexistence and increase the number of coexisting strategies, contributing towards explaining the genetic diversity observed in D. discoideum, Comment: 33 pages, 7 figures

Encounter rates link movement strategies to intra- and inter-specific interactions, and therefore translate individual movement behavior into higher-level ecological processes. Indeed, a large body of interacting population theory rests on the law of mass action, which can be derived from assumptions of Brownian motion in an enclosed container with exclusively local perception. These assumptions imply completely uniform space use, individual home ranges equivalent to the population range, and encounter dependent on movement paths actually crossing. Mounting empirical evidence, however, suggests that animals use space non-uniformly, occupy home ranges substantially smaller than the population range, and are often capable of nonlocal perception. Here, we explore how these empirically supported behaviors change pairwise encounter rates. Specifically, we derive novel analytical expressions for encounter rates under Ornstein-Uhlenbeck motion, which features non-uniform space use and allows individual home ranges to differ from the population range. We compare OU-based encounter predictions to those of Reflected Brownian Motion, from which the law of mass action can be derived. For both models, we further explore how the interplay between the scale of perception and home range size affects encounter rates. We find that neglecting realistic movement and perceptual behaviors can systematically bias encounter rate predictions., 21 pages, 7 figures, 10 appendices

Mathematical modelling is nowadays a central tool in microbial ecology. Ecological theory and numerical modelling are essential for developing a deeper understanding of the mechanisms that shape the assembly and evolution of microbial communities. Microbes interact among themselves and with their environment in complex ways, and can display a very rich set of spatiotemporal dynamics. Modelling these processes is thus a challenging enterprise that needs to be subject to experimental validation. This article provides a review of the state-of-the-art of models in microbial ecology, ranging from the microscopic level (e.g., resource uptake) to the macroscopic level (e.g., spatial organization). Special emphasis is given to the modelling of (i) uptake kinetics, elemental stoichiometry and functional trade-offs; (ii) food web and eco-evolutionary dynamics; (iii) micro-scale variability and social behavior in microbes. The overarching point of view is the use of theoretical models to improve our understanding of how microbial communities operate and affect ecosystem functioning.

Loners—individuals out of sync with a coordinated majority—occur frequently in nature. Are loners incidental byproducts of large-scale coordination attempts, or are they part of a mosaic of life-history strategies? Here, we provide empirical evidence of naturally occurring heritable variation in loner behavior in the model social amoeba Dictyostelium discoideum. We propose that Dictyostelium loners—cells that do not join the multicellular life stage—arise from a dynamic population-partitioning process, the result of each cell making a stochastic, signal-based decision. We find evidence that this imperfectly synchronized multicellular development is affected by both abiotic (environmental porosity) and biotic (signaling) factors. Finally, we predict theoretically that when a pair of strains differing in their partitioning behavior coaggregate, cross-signaling impacts slime-mold diversity across spatiotemporal scales. Our findings suggest that loners could be critical to understanding collective and social behaviors, multicellular development, and ecological dynamics in D. discoideum. More broadly, across taxa, imperfect coordination of collective behaviors might be adaptive by enabling diversification of life-history strategies., Loners (individuals out of sync with a coordinated majority) occur frequently in nature and are generally assumed to be incidental by-products of imperfect coordination attempts. Experimental and theoretical work on the slime mold Dictyostelium discoideum suggests that "lonerism" might actually be an alternative life-history strategy.

Se describe un método simple y barato para la fabricación de moldes de alúmina nanoporosa, con potenciales aplicaciones para la fabricación de nanohilos. Se utiliza como materia prima un aluminio de grado comercial. Los moldes nanoporosos fabricados tienen un diámetro promedio de poros de (20 ± 4) nm. El proceso de fabricación consta de dos etapas de anodizado. Se detallan ambas etapas de anodizado y se caracteriza el material que se obtiene como resultado de cada una de ellas. Los moldes nanoporosos obtenidos con dos pasos de anodizado tienen la distribución más estrecha de tamaño de poros, mejor circularidad y orden espacial. En dichos moldes se crecen nanohilos a base de ferrita de cobalto (CoFe2O4). Para hacerlo, se usa un método simple y un equipamiento sencillo. Mediante microscopía electrónica se hace una caracterización morfológica de las plantillas y de los nanohilos obtenidos. A simple and low cost method for the fabrication of Nanoporous alumina templates with potential applications for nanowires fabrication is described. As raw material, commercial aluminum has been used. The nanoporous templates obtained have a mean pore diameter of (20 ± 4) nm. The fabrication process consists mainly of two-step anodization. Both steps are described in detail, the obtained material for each anodization step is characterized. The Nanoporous template obtained after two-step anodization present a narrow distribution of the porous size, a better circularity and homogeneous distribution. Cobalt ferrite (CoFe2O4) nanowires structures have been synthesized from the obtained alumina templates. A simple equipment method has been developed. A morphological characterization of the obtained templates and nanowires, by the use of electron microscopy techniques, is also presented. Fil: Londoño Calderon, Cesar Leandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnología en Polímeros y Nanotecnología. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnología en Polímeros y Nanotecnología; Argentina Fil: Menchaca Nal, Sandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnología en Polímeros y Nanotecnología. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnología en Polímeros y Nanotecnología; Argentina Fil: Pardo Saavedra, Diana Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería ; Argentina Fil: Silveyra, Josefina María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería ; Argentina Fil: Socolovsky, Leandro Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería ; Argentina Fil: Pampillo, Laura Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnologías y Ciencias de la Ingeniería ; Argentina Fil: Martinez Garcia, Ricardo. Universidad Nacional de Formosa. Facultad de Recursos Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina

Biofilms are microbial collectives that occupy a diverse array of surfaces. It is well known that the function and evolution of biofilms are strongly influenced by the spatial arrangement of different strains and species within them, but how spatiotemporal distributions of different genotypes in biofilm populations originate is still underexplored. Here, we study the origins of biofilm genetic structure by combining model development, numerical simulations, and microfluidic experiments using the human pathogen Vibrio cholerae. Using spatial correlation functions to quantify the differences between emergent cell lineage segregation patterns, we find that strong adhesion often, but not always, maximizes the size of clonal cell clusters on flat surfaces. Counterintuitively, our model predicts that, under some conditions, investing in adhesion can reduce rather than increase clonal group size. Our results emphasize that a complex interaction between fluid flow and cell adhesiveness can underlie emergent patterns of biofilm genetic structure. This structure, in turn, has an outsize influence on how biofilm-dwelling populations function and evolve., Author summary Biofilms are bacterial groups, often attached to surfaces, in which a broad variety of cooperative and competitive interactions typically occur. The spatial organization of different strains and species within biofilm communities strongly influences their global functioning, but little is known about how such structure arises. Combining experiments on V. cholerae and simulations of a cellular automaton, we show that the complex interaction between bacterial traits (cell adhesion) and environmental factors (fluid flow intensity) strongly influences the early origins of biofilm spatial structure. In most cases, we found that highly-adhesive strains form larger clusters than the weakly-adhesive ones. Against intuition, however, we also found the opposite outcome: weakly-adhesive tend to form larger clusters than the highly adhesive ones when flows are weak or the population density of colonizing cells is high.

Cellular slime molds, including the well-studied Dictyostelium discoideum, are amoebae whose life cycle includes both a single-cellular and a multicellular stage. To achieve the multicellular stage, individual amoebae aggregate upon starvation to form a fruiting body made of dead stalk cells and reproductive spores, a process that has been described in terms of cooperation and altruism. When amoebae aggregate they do not perfectly discriminate against nonkin, leading to chimeric fruiting bodies. Within chimeras, complex interactions among genotypes have been documented, which should theoretically reduce genetic diversity. This is however inconsistent with the great diversity of genotypes found in nature. Recent work has shown that a little-studied component of D. discoideum fitness—the loner cells that do not participate in the aggregation—can be selected for depending on environmental conditions and that, together with the spores, they could represent a bet-hedging strategy. We suggest that in all cellular slime molds the existence of loners could resolve the apparent diversity paradox in two ways. First, if loners are accounted for, then apparent genotypic skew in the spores of chimeras could simply be the result of different investments into spores versus loners. Second, in an ecosystem with multiple local environments differing in their food recovery characteristics and connected globally via weak-to-moderate dispersal, coexistence of multiple genotypes can occur. Finally, we argue that the loners make it impossible to define altruistic behavior, winners or losers, without a clear description of the ecology.

El presente documento electronico describe una aplicacion practica para la reutilizacion de lectores de CD/DVD, implementando una CNC con dichos materiales reciclados.

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches., This work is funded by the Gordon and Betty Moore Foundation through Grant GBMF2550.06 to RMG, Universitat de les Illes Balears through a 2015 Young Visiting Scholar grant to RMG, the US National Science Foundation through grant ABI 1458748 to JMC and Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional through project CTM2015-66407-P (MINECO/FEDER) to CL.

Fil: Cerrutti, Patricia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Tecnologia En Polimeros y Nanotecnologia. Universidad de Buenos Aires. Facultad de Ingenieria. Instituto de Tecnologia En Polimeros y Nanotecnologia; Argentina

© 2015 Martínez-García et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. We study the spatial patterns formed by a system of interacting particles where the mobility of any individual is determined by the population crowding at two different spatial scales. In this way we model the behavior of some biological organisms (like mussels) that tend to cluster at short ranges as a defensive strategy, and strongly disperse if there is a high population pressure at large ranges for optimizing foraging. We perform stochastic simulations of a particle-level model of the system, and derive and analyze a continuous density description (a nonlinear diffusion equation). In both cases we show that this interplay of scaledependent- behaviors gives rise to a rich formation of spatial patterns ranging from labyrinths to periodic cluster arrangements. In most cases these clusters have the very peculiar appearance of ring-like structures, i.e., organisms arranging in the perimeter of the clusters, which we discuss in detail., RMG was supported by the JAEPredoc program of Consejo Superior de Investigacion Cientificas. CM was supported by the IFISC-Intro program of Instituto de Fisica Interdisciplinar y Sistemas Complejos. EHG and CL are supported by Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional through grant no. FIS2012-30634 (INTENSE@COSYP) and no. CTM2012-39025-C02-01 (ESCOLA).

© 2015 American Physical Society. We introduce a model of interacting random walkers on a finite one-dimensional chain with absorbing boundaries or targets at the ends. Walkers are of two types: informed particles that move ballistically towards a given target and diffusing uninformed particles that are biased towards close informed individuals. This model mimics the dynamics of hierarchical groups of animals, where an informed individual tries to persuade and lead the movement of its conspecifics. We characterize the success of this persuasion by the first-passage probability of the uninformed particle to the target, and we interpret the speed of the informed particle as a strategic parameter that the particle can tune to maximize its success. We find that the success probability is nonmonotonic, reaching its maximum at an intermediate speed whose value increases with the diffusing rate of the uninformed particle. When two different groups of informed leaders traveling in opposite directions compete, usually the largest group is the most successful. However, the minority can reverse this situation and become the most probable winner by following two different strategies: increasing its attraction strength or adjusting its speed to an optimal value relative to the majority's speed., R.M-G. is supported by the JAEPredoc program of CSIC. R.M-G. and C.L acknowledge support from MINECO (Spain) and FEDER (EU) through Grants No. FIS2012-30634 (INTENSE@COSYP) and No. CTM2012-39025-C02-01 (ESCOLA).

We investigated the relationships between search efficiency, movement strategy, and nonlocal communication in the biological context of animal foraging. We considered situations where the members of a population of foragers perform either Gaussian jumps or Lévy flights, and show that the search time is minimized when communication among individuals occurs at intermediate ranges, independently of the type of movement. Additionally, while Brownian strategies are more strongly influenced by the communication mechanism, Lévy flights still result in shorter overall search durations. © 2014 American Physical Society., R.M.-G. is supported by the JAEPredoc program of CSIC. R.M.-G. and C.L. acknowledge support from MINECO (Spain) and FEDER (EU) through Grants No. FIS2012-30634 (Intense-COSYP) and No. CTM2012-39025-C02-01 (ESCOLA). J.M.C. is supported by US National Science Foundation Grant No. ABI-1062411.

arXiv:1402.1077, © 2014 The Author(s) Published by the Royal Society. The minimal ecological requirements for the formation of regular vegetation patterns in semiarid systems have been recently questioned. Against the general belief that a combination of facilitative and competitive interactions is necessary, recent theoretical studies suggest that, under broad conditions, non-local competition among plants alone may induce patterns. In this paper, we review results along this line, presenting a series of models that yield spatial patterns when finite-range competition is the only driving force. A preliminary derivation of this type of model from a more detailed one that considers water-biomass dynamics is also presented., R.M-G. is supported by the JAEPredoc program of CSIC. R.M-G., C.L. and E.H-G acknowledge support from FEDER and MINECO (Spain) through Grants No. FIS2012-30634 INTENSE@COSYP and CTM2012-39025-C02-01 ESCOLA.

We investigate the relationship between communication and search efficiency in a biological context by proposing a model of Brownian searchers with long-range pairwise interactions. After a general study of the properties of the model, we show an application to the particular case of acoustic communication among Mongolian gazelles, for which data are available, searching for good habitat areas. Using Monte Carlo simulations and density equations, our results point out that the search is optimal (i.e., the mean first hitting time among searchers is minimum) at intermediate scales of communication, showing that both an excess and a lack of information may worsen it. © 2013 American Physical Society., R. M.-G. is supported by the JAEPredoc program of CSIC. R. M.-G. and C. L. acknowledge support from MICINN (Spain) and FEDER (EU) through Grant No. FIS2007-60327 FISICOS. J. M. C. and T. M. were supported by a U.S. National Science Foundation grant (ABI 1062411).

Regular vegetation patterns in semiarid ecosystems are believed to arise from the interplay between long-range competition and facilitation processes acting at smaller distances. We show that, under rather general conditions, long-range competition alone may be enough to shape these patterns. To this end we propose a simple, general model for the dynamics of vegetation, which includes only long-range competition between plants. Competition is introduced through a nonlocal term, where the kernel function quantifies the intensity of the interaction. We recover the full spectrum of spatial structures typical of vegetation models that also account for facilitation in addition to competition. Key Points Spatial vegetation model only considering long-range competition for water. The model does not consider short-range facilitation. Patterns in the system are determined by the kernel competition function. ©2013. American Geophysical Union. All Rights Reserved., R.M-G. is supported by the JAEPredoc program of CSIC. R.M-G., C.L., and E.H-G acknowledge support from FEDER and MICINN (Spain) through grants FIS2012-30634 INTENSE@COSYP and CTM2012-39025-C02-01 ESCOLA.