1,721,031 research outputs found
Randomness and Criticality in Biological Interactions
Full text linkIn this thesis we study from a physics perspective two problems related to biological interactions. In the first part of this thesis we consider ecological interactions, that shape ecosystems and determine their fate, and their relation with stability of ecosystems. Using random matrix theory we are able to identify the key aspect, the order parameters, determining the stability of large ecosystems. We then consider the problem of determining the persistence of a population living in a randomly fragmented landscape. Using some techniques borrowed from random matrix theory applied to disordered systems, we are able to identify what are the key drivers of persistence. The second part of the thesis is devoted to the observation that many living systems seem to tune their interaction close to a critical point. We introduce a stochastic model, based on information theory, that predict the critical point as a natural outcome of a process of evolution or adaptation, without fine-tuning of parameters
Disentangling the effect of hybrid interactions and of the constant effort hypothesis on ecological community stability
No full textIn the last years, a remarkable theoretical effort has been made in order to understand the relation between stability and complexity in ecological communities. Yet, what maintains species diversity in real ecological communities is still an open question. The non-random structures of ecological interaction networks have been recognized as one key ingredient impacting the maximum number of coexisting species within the ecological community. However most of the earlier theoretical studies have considered communities with only one interaction type (either antagonistic, competitive or mutualistic). Recently, it has been proposed that multiple interaction types might stabilize ecosystems and that, in this hybrid case, increasing complexity increases stability. Here we show that these results depend on ad hoc hypothesis that the authors used in their model and we highlight the need to disentangle the role of multiple interaction types and constant interaction effort allocation on community stability. Indeed, we find that mixing of mutualistic and predator-prey interaction types does not stabilize the community dynamics and we demonstrate that a positive correlation between complexity and stability is observed only if a constant effort allocation is imposed in the ecological interactions. Synthesis In recent years a sparkling research has been devoted to the search of new theoretical mechanisms to explain way ecosystems may persist despite their complexity. Here we show that, contrary to what recently suggested (Mougi et al. 2012), the mismatch between theoretical results and empirical evidences on the stability of ecological community is still there also for communities with both mutualistic and antagonistic interactions, and the 'complexity-stability' paradox is still alive. Indeed, we demonstrate that their results arise as an artifact of the peculiar rescaling of the interaction strengths they imposed. Our study suggests that further theoretical studies and experimental evidences are still needed to better understand the role of interaction strengths in real ecological communities
Intrinsic dimension estimation for discrete metrics
Full text linkReal world-datasets characterized by discrete features are ubiquitous: from
categorical surveys to clinical questionnaires, from unweighted networks to DNA
sequences. Nevertheless, the most common unsupervised dimensional reduction
methods are designed for continuous spaces, and their use for discrete spaces
can lead to errors and biases. In this letter we introduce an algorithm to
infer the intrinsic dimension (ID) of datasets embedded in discrete spaces. We
demonstrate its accuracy on benchmark datasets, and we apply it to analyze a
metagenomic dataset for species fingerprinting, finding a surprisingly small
ID, of order 2. This suggests that evolutive pressure acts on a low-dimensional
manifold despite the high-dimensionality of sequences' space.Comment: RevTeX4.2, 13 pages, 10 figure
Reconciling cooperation, biodiversity and stability in complex ecological communities
Full text linkAbstract Empirical evidences show that ecosystems with high biodiversity can persist in time even in the presence of few types of resources and are more stable than low biodiverse communities. This evidence is contrasted by the conventional mathematical modeling, which predicts that the presence of many species and/or cooperative interactions are detrimental for ecological stability and persistence. Here we propose a modelling framework for population dynamics, which also include indirect cooperative interactions mediated by other species (e.g. habitat modification). We show that in the large system size limit, any number of species can coexist and stability increases as the number of species grows, if mediated cooperation is present, even in presence of exploitative or harmful interactions (e.g. antibiotics). Our theoretical approach thus shows that appropriate models of mediated cooperation naturally lead to a solution of the long-standing question about complexity-stability paradox and on how highly biodiverse communities can coexist
Spatial aggregation and the species-area relationship across scales
No full textThere has been a considerable effort to understand and quantify the spatial distribution of species across different ecosystems. Relative species abundance (RSA), beta diversity and species-area relationship (SAR) are among the most used macroecological measures to characterize plants communities in forests. In this paper we introduce a simple phenomenological model based on Poisson cluster processes which allows us to exactly link RSA and beta diversity to SAR. The framework is spatially explicit and accounts for the spatial aggregation of conspecific individuals. Under the simplifying assumption of neutral theory, we derive an analytical expression for the SAR which reproduces tri-phasic behavior as sample area increases from local to continental scales, explaining how the tri-phasic behavior can be understood in terms of simple geometric arguments. We also find an expression for the endemic area relationship (EAR) and for the scaling of the RSA
The sampling form of the gamma distribution predicts ASV occupancy [Dataset]
No full texta) The fraction of replicates harboring a given ASV (i.e., occupancy) can be predicted using a form of the gamma distribution that accounts for sampling across experimental treatments and transfers. b) The distribution or relative errors exhibited a similar form across treatments and transfers, suggesting that the predictions of the SLM are broadly applicable. c) By comparing ASVs that were present in both migration and no migration treatments, we can see that the errors are generally similar between treatments, if only slightly higher in the no migration treatment.Peer reviewe
Mean change in under global and no migration [Dataset]
No full textFor both a) no and b) global migration the mean of is initially higher than the stationary value of zero, though the mean relaxes to zero by transfer six for both treatments and does not appear to change after the cessation of global migration. This result is consistent with predicted consequences of global migration.Peer reviewe
Attractor status [Dataset]
No full textThe percent of communities belonging to a given attractor for each migration treatment.Peer reviewe
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