1,721,050 research outputs found
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
An exactly solvable coarse-grained model for species diversity
No full textWe present novel analytical results concerning ecosystem species diversity that stem from a proposed coarse-grained neutral model based on birth-death processes. The relevance of the problem lies in the urgency for understanding and synthesizing both theoretical results from ecological neutral theory and empirical evidence on species diversity preservation. The neutral model of biodiversity deals with ecosystems at the same trophic level, where per capita vital rates are assumed to be species independent. Closed-form analytical solutions for the neutral theory are obtained within a coarse-grained model, where the only input is the species persistence time distribution. Our results pertain to: the probability distribution function of the number of species in the ecosystem, both in transient and in stationary states; the n-point connected time correlation function; and the survival probability, defined as the distribution of time spans to local extinction for a species randomly sampled from the community. Analytical predictions are also tested on empirical data from an estuarine fish ecosystem. We find that emerging properties of the ecosystem are very robust and do not depend on specific details of the model, with implications for biodiversity and conservation biology
Species survival and scaling laws in hostile and disordered environments
No full textIn this work we study the likelihood of survival of single-species in
the context of hostile and disordered environments. Population dynamics
in this environment, as modeled by the Fisher equation, is characterized
by negative average growth rate, except in some random spatially
distributed patches that may support life. In particular, we are
interested in the phase diagram of the survival probability and in the
critical size problem, i.e., the minimum patch size required for
surviving in the long-time dynamics. We propose a measure for the
critical patch size as being proportional to the participation ratio of
the eigenvector corresponding to the largest eigenvalue of the
linearized Fisher dynamics. We obtain the (extinction-survival) phase
diagram and the probability distribution function (PDF) of the critical
patch sizes for two topologies, namely, the one-dimensional system and
the fractal Peano basin. We show that both topologies share the same
qualitative features, but the fractal topology requires higher spatial
fluctuations to guarantee species survival. We perform a finite-size
scaling and we obtain the associated scaling exponents. In addition, we
show that the PDF of the critical patch sizes has an universal shape for
the 1D case in terms of the model parameters (diffusion, growth rate,
etc.). In contrast, the diffusion coefficient has a drastic effect on
the PDF of the critical patch sizes of the fractal Peano basin, and it
does not obey the same scaling law of the 1D case
Species coexistence in a neutral dynamics with environmental noise
No full textEnvironmental fluctuations have important consequences in the
organization of ecological communities, and understanding how such a
variability influences the biodiversity of an ecosystem is a major
question in ecology. In this paper, we analyze the case of two species
competing for the resources within the framework of the neutral theory
in the presence of environmental noise, devoting special attention on
how such a variability modulates species fitness. The environment is
dichotomous and stochastically alternates between periods favoring one
of the species while disfavoring the other one, preserving neutrality on
the long term. We study two different scenarios: in the first one
species fitness varies linearly with the environment, and in the second
one the effective fitness is re-scaled by the total fitness of the
individuals competing for the same resource. We find that, in the former
case environmental fluctuations always reduce the time of species
coexistence, whereas such a time can be enhanced or reduced in the
latter case, depending on the correlation time of the environment. This
phenomenon can be understood as a direct consequence of Chesson's
storage effect
Neutral dynamics with environmental noise: Age-size statistics and species lifetimes
Full text linkNeutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to
demographic O( N^1/2) noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems.
Here we analyze two of these problems—age-size relationships and species extinction time—in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of “zero mean” environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics
A data driven network approach to rank countries production diversity and food specialization
Full text linkThe easy access to large data sets has allowed for leveraging methodology in network physics and complexity science to disentangle patterns and processes directly from the data, leading to key insights in the behavior of systems. Here we use country specific food production data to study binary and weighted topological properties of the bipartite country-food production matrix. This country-food production matrix can be: 1) transformed into overlap matrices which embed information regarding shared production of products among countries, and or shared countries for individual products, 2) identify subsets of countries which produce similar commodities or subsets of commodities shared by a given country allowing for visualization of correlations in large networks, and 3) used to rank country fitness (the ability to produce a diverse array of products weighted on the type of food commodities) and food specialization (quantified on the number of countries producing a specific food product weighted on their fitness). Our results show that, on average, countries with high fitness produce both low and high specializion food commodities, whereas nations with low fitness tend to produce a small basket of diverse food products, typically comprised of low specializion food commodities
Early warning signs in social-ecological networks.
Full text linkA number of social-ecological systems exhibit complex behaviour associated with nonlinearities, bifurcations, and interaction with stochastic drivers. These systems are often prone to abrupt and unexpected instabilities and state shifts that emerge as a discontinuous response to gradual changes in environmental drivers. Predicting such behaviours is crucial to the prevention of or preparation for unwanted regime shifts. Recent research in ecology has investigated early warning signs that anticipate the divergence of univariate ecosystem dynamics from a stable attractor. To date, leading indicators of instability in systems with multiple interacting components have remained poorly investigated. This is a major limitation in the understanding of the dynamics of complex social-ecological networks. Here, we develop a theoretical framework to demonstrate that rising variance--measured, for example, by the maximum element of the covariance matrix of the network--is an effective leading indicator of network instability. We show that its reliability and robustness depend more on the sign of the interactions within the network than the network structure or noise intensity. Mutualistic, scale free and small world networks are less stable than their antagonistic or random counterparts but their instability is more reliably predicted by this leading indicator. These results provide new advances in multidimensional early warning analysis and offer a framework to evaluate the resilience of social-ecological networks
Information-based fitness and the emergence of criticality in living systems
No full textEmpirical evidence suggesting that living systems might operate in the vicinity of critical points, at the borderline between order and disorder, has proliferated in recent years, with examples ranging from spontaneous brain activity to flock dynamics. However, a well-founded theory for understanding how and why interacting living systems could dynamically tune themselves to be poised in the vicinity of a critical point is lacking. Here we use tools from statistical mechanics and information theory to show that complex adaptive or evolutionary systems can be much more efficient in coping with diverse heterogeneous environmental conditions when operating at criticality. Analytical as well as computational evolutionary and adaptive models vividly illustrate that a community of such systems dynamically self-tunes close to a critical state as the complexity of the environment increases while they remain noncritical for simple and predictable environments. A more robust convergence to criticality emerges in coevolutionary and coadaptive setups in which individuals aim to represent other agents in the community with fidelity, thereby creating a collective critical ensemble and providing the best possible tradeoff between accuracy and flexibility. Our approach provides a parsimonious and general mechanism for the emergence of critical-like behavior in living systems needing to cope with complex environments or trying to efficiently coordinate themselves as an ensemble
Stochastic modeling of soil salinity
No full textA minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a single stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant ( or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trends, with significant consequences e. g. for climate change impacts on rain-fed agriculture
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