Joint assessment of density correlations and fluctuations for analysing spatial tree patterns

Inferring the processes underlying the emergence of observed patterns is a key challenge in theoretical ecology. Much effort has been made in the past decades to collect extensive and detailed information about the spatial distribution of tropical rainforests, as demonstrated, e.g. in the 50 ha tropical forest plot on Barro Colorado Island, Panama. These kinds of plots have been crucial to shed light on diverse qualitative features, emerging both at the single-species or the community level, like the spatial aggregation or clustering at short scales. Here, we build on the progress made in the study of the density correlation functions applied to biological systems, focusing on the importance of accurately defining the borders of the set of trees, and removing the induced biases. We also pinpoint the importance of combining the study of correlations with the scale dependence of fluctuations in density, which are linked to the well-known empirical Taylor's power law. Density correlations and fluctuations, in conjunction, provide a unique opportunity to interpret the behaviours and, possibly, to allow comparisons between data and models. We also study such quantities in models of spatial patterns and, in particular, we find that a spatially explicit neutral model generates patterns with many qualitative features in common with the empirical ones.

Community fluctuations and local extinction in a planktonic food web

Determining statistical patterns irrespective of interacting agents (i.e. macroecology) is useful to explore the mechanisms driving population fluctuations and extinctions in natural food webs. Here, we tested four predictions of a neutral model on the distribution of community fluctuations (CF) and the distributions of persistence times (APT). Novel predictions for the food web were generated by combining (1) body size-density scaling, (2) Taylor's law and (3) low efficiency of trophic transference. Predictions were evaluated on an exceptional data set of plankton with 15 years of weekly samples encompassing c. 250 planktonic species from three trophic levels, sampled in the western English Channel. Highly symmetric non-Gaussian distributions of CF support zero-sum dynamics. Variability in CF decreased while a change from an exponential to a power law distribution of APT from basal to upper trophic positions was detected. Results suggest a predictable but profound effect of trophic position on fluctuations and extinction in natural communities.

Competition drives clumpy species coexistence in estuarine phytoplankton

Understanding the mechanisms that maintain biodiversity is a fundamental problem in ecology. Competition is thought to reduce diversity, but hundreds of microbial aquatic primary producers species coexist and compete for a few essential resources (e.g., nutrients and light). Here, we show that resource competition is a plausible mechanism for explaining clumpy distribution on individual species volume (a proxy for the niche) of estuarine phytoplankton communities ranging from North America to South America and Europe, supporting the Emergent Neutrality hypothesis. Furthermore, such a clumpy distribution was also observed throughout the Holocene in diatoms from a sediment core. A Lotka-Volterra competition model predicted position in the niche axis and functional affiliation of dominant species within and among clumps. Results support the coexistence of functionally equivalent species in ecosystems and indicate that resource competition may be a key process to shape the size structure of estuarine phytoplankton, which in turn drives ecosystem functioning.

Extended estimator approach for 2 x 2 games and its mapping to the Ising Hamiltonian

We consider a system of adaptive self-interested agents interacting by playing an iterated pairwise prisoner's dilemma (PD) game. Each player has two options: either cooperate (C) or defect (D). Agents have no (long term) memory to reciprocate nor identifying tags to distinguish C from D. We show how their 16 possible elementary Markovian (one-step memory) strategies can be cast in a simple general formalism in terms of an estimator of expected utilities Delta*. This formalism is helpful to map a subset of these strategies into an Ising Hamiltonian in a straightforward way. This connection in turn serves to shed light on the evolution of the iterated games played by agents, which can represent a broad variety of individuals from firms of a market to species coexisting in an ecosystem. Additionally, this magnetic description may be useful to introduce noise in a natural and simple way. The equilibrium states reached by the system depend strongly on whether the dynamics are synchronous or asynchronous and also on the system connectivity.

Self-organization in a simple model of adaptive agents playing 2 x 2 games with arbitrary payoff matrices

We analyze, both analytically and numerically, the self-organization of a system of "selfish" adaptive agents playing an arbitrary iterated pairwise game (defined by a 2 x 2 payoff matrix). Examples of possible games to play are the prisoner's dilemma (PD) game, the chicken game, the hero game, etc. The agents have no memory, use strategies not based on direct reciprocity nor "tags" and are chosen at random, i.e., geographical vicinity is neglected. They can play two possible strategies: cooperate (C) or defect (D). The players measure their success by comparing their utilities with an estimate for the expected benefits and update their strategy following a simple rule. Two versions of the model are studied: (1) the deterministic version (the agents are either in definite states C or D) and (2) the stochastic version (the agents have a probability c of playing C). Using a general master equation we compute the equilibrium states into which the system self-organizes, characterized by their average probability of cooperation c(eq). Depending on the payoff matrix, we show that c(eq) can take five different values. We also consider the mixing of agents using two different payoff matrices and show that any value of c(eq) can be reached by tuning the proportions of agents using each payoff matrix. In particular, this can be used as a way to simulate the effect of a fraction d of "antisocial" individuals--incapable of realizing any value to cooperation--on the cooperative regime hold by a population of neutral or "normal" agents.

Cooperation and self-regulation in a model of agents playing different games

A simple model for cooperation between "selfish" agents, which play an extended version of the prisoner's dilemma game, in which they use arbitrary payoffs, is presented and studied. A continuous variable, representing the probability of cooperation, p(k)(t) in [0,1], is assigned to each agent k at time t. At each time step t a pair of agents, chosen at random, interact by playing the game. The players update their p(k)(t) using a criterion based on the comparison of their utilities with the simplest estimate for expected income. The agents have no memory and do not use strategies based on direct reciprocity or "tags." Depending on the payoff matrix, the system self-organizes-after a transient-into stationary states characterized by their average probability of cooperation p(eq) and average equilibrium per-capita income p(eq),U(infinity). It turns out that the model exhibits some results that contradict the intuition. In particular, some games that a priori seem to favor defection most, may produce a relatively high degree of cooperation. Conversely, other games, which one would bet lead to maximum cooperation, indeed are not the optimal for producing cooperation.

Model for mutation in bacterial populations

We describe the evolution of E. coli populations through a Bak-Sneppen-type model which incorporates random mutations. We show that, for a value of the mutation level which coincides with the one estimated from experiments, this model reproduces the measures of mean fitness relative to that of a common ancestor, performed for over 10,000 bacterial generations.

Foetal safety of nitrofurantoin macrocrystals therapy during pregnancy: a retrospective analysis

Urinary tract infection during pregnancy poses increased risk to mother and foetus and warrants prompt detection and treatment. Currently, there are no antibacterials approved for use in pregnant women. A retrospective analysis was undertaken to evaluate the safety to the human foetus of nitrofurantoin macrocrystals (Macrodantin) when administered during pregnancy. The records of ninety-one pregnancies in eighty-one obstetric patients who were treated with nitrofurantoin macrocrystals for urinary tract infection were reviewed. Safety was assessed according to incidence of foetal death, neonatal death, malformation, prematurity, low birth weight, low Apgar score and jaundice. The incidence of abnormal events in the pregnancies evaluated was not significantly different from that in the United States population. No abnormal event was considered to be drug-related. This study yielded no evidence that would implicate nitrofurantoin macrocrystals as toxic to the foetus or unsafe for treatment of maternal urinary tract infection during pregnancy.