Probabilistic patterns of interaction: the effects of link-strength variability on food web structure

Patterns of species interactions affect the dynamics of food webs. An important component of species interactions that is rarely considered with respect to food webs is the strengths of interactions, which may affect both structure and dynamics. In natural systems, these strengths are variable, and can be quantified as probability distributions. We examined how variation in strengths of interactions can be described hierarchically, and how this variation impacts the structure of species interactions in predator-prey networks, both of which are important components of ecological food webs. The stable isotope ratios of predator and prey species may be particularly useful for quantifying this variability, and we show how these data can be used to build probabilistic predator-prey networks. Moreover, the distribution of variation in strengths among interactions can be estimated from a limited number of observations. This distribution informs network structure, especially the key role of dietary specialization, which may be useful for predicting structural properties in systems that are difficult to observe. Finally, using three mammalian predator-prey networks ( two African and one Canadian) quantified from stable isotope data, we show that exclusion of link-strength variability results in biased estimates of nestedness and modularity within food webs, whereas the inclusion of body size constraints only marginally increases the predictive accuracy of the isotope-based network. We find that modularity is the consequence of strong link-strengths in both African systems, while nestedness is not significantly present in any of the three predator-prey networks.

The aplication of land use and nighttime lights on the development of high-resolution emission inventories for South America

In this paper, nighttime light data are suggested as a proxy for spatial distribution of vehicles running in urban and nearby areas. Nighttime lights focus on human activities, in contrast to traditional Earth observing systems that focus on natural systems. It is the human activity being visible in the form of brightness of nocturnal lights. Two available nighttime lights dataset were used in this work. The first one was provided by the U.S. Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS), henceforth, DMSO-OLS. The second one is the NASA-NOAA Suomi National Polar-orbiting Polar-orbiting Partnership (NPP) satellite, henceforth, Suomi-NPP. To validate the new proposed methodology, hundreds of urban areas of South America were analyzed in a high degree of resolution. The results of this study showed that night-time lights are very well correlated with vehicle fleet, population, and impervious surfaces but with strong spatial variability. The results of this study suggest a better understanding of the human activities in the context of a vehicular-based city conception.

Natural history of an ant-plant-butterfly interaction in a Neotropical savanna

Non-myrmecophilous lepidopteran larvae using plants bearing ant attractants such as extrafloral nectaries are good models for studying morphological and behavioural mechanisms against ant predation. Udranomia spitzi (Hesperiidae) is a butterfly whose larvae feed on leaves of Ouratea spectabilis (Ochnaceae), a plant with extrafloral nectaries. We described the early stages of U. spitzi, and used field observations and experiments to investigate the defensive strategies of caterpillars against predatory ants. Larvae pass through five instars and pupation occurs inside larval leaf shelters. Ant-exclusion experiments revealed that the presence of ants did not affect significantly caterpillar survival. Predation experiments showed that vulnerability to ant predation decreased with increase in larval size. The present study showed that predatory ants are not as relevant as demonstrated for other systems, and also illustrates how observational data and field experiments can contribute to a better understanding of the biology and ecology of a species of interest.

Vertical distribution of biotic pollination systems in cerrado sensu stricto in the Triangulo Mineiro, MG, Brazil)

(Vertical distribution of biotic pollination systems in cerrado sensu stricto in the Triangulo Mineiro, MG, Brazil). Several factors can influence the distribution of floral resources and pollination systems in ecosystems, such as climate, altitude, geographic region, fragmentation of natural areas and differences in floristic composition along the vertical stratification. This study aimed to evaluate the distribution of the vertical stratification of biotic pollination systems in cerrado (sensu stricto) fragments in the Triangulo Mineiro. There was no significant difference (chi(2)(0.05,9)=14.17; P = 0.12) in total plant species richness among fragments, nor in the species richness of each layer (trees, shrubs, herbs and lianas) and the shrub layer was the best represented. Likewise, there was no significant difference between fragments for the systems of pollination (chi(2)(0 05,21) =13.80; P = 0.8778). Pollination by bees was the most common, corresponding to 85% of species in each fragment. In relative terms, plants pollinated by bees were dominant in all strata, reaching 100% for the lianas in fragments 1, 3 and 4 and for the herbs in fragments 1 and 4. In this study, based on floristic composition and distribution of biotic pollination systems in the vertical stratification, we could define a vertical mosaic in the cerrado studied, which has implications for the sustainability of communities in the cerrado, as well as the horizontal mosaic of vegetation types.

MODULARITY, NOISE, AND NATURAL SELECTION

Most biological systems are formed by component parts that are to some degree interrelated. Groups of parts that are more associated among themselves and are relatively autonomous from others are called modules. One of the consequences of modularity is that biological systems usually present an unequal distribution of the genetic variation among traits. Estimating the covariance matrix that describes these systems is a difficult problem due to a number of factors such as poor sample sizes and measurement errors. We show that this problem will be exacerbated whenever matrix inversion is required, as in directional selection reconstruction analysis. We explore the consequences of varying degrees of modularity and signal-to-noise ratio on selection reconstruction. We then present and test the efficiency of available methods for controlling noise in matrix estimates. In our simulations, controlling matrices for noise vastly improves the reconstruction of selection gradients. We also perform an analysis of selection gradients reconstruction over a New World Monkeys skull database to illustrate the impact of noise on such analyses. Noise-controlled estimates render far more plausible interpretations that are in full agreement with previous results.

What ethologically based models have taught us about the neural systems underlying fear and anxiety

Classical Pavlovian fear conditioning to painful stimuli has provided the generally accepted view of a core system centered in the central amygdala to organize fear responses. Ethologically based models using other sources of threat likely to be expected in a natural environment, such as predators or aggressive dominant conspecifics, have challenged this concept of a unitary core circuit for fear processing. We discuss here what the ethologically based models have told us about the neural systems organizing fear responses. We explored the concept that parallel paths process different classes of threats, and that these different paths influence distinct regions in the periaqueductal gray - a critical element for the organization of all kinds of fear responses. Despite this parallel processing of different kinds of threats, we have discussed an interesting emerging view that common cortical-hippocampal-amygdalar paths seem to be engaged in fear conditioning to painful stimuli, to predators and, perhaps, to aggressive dominant conspecifics as well. Overall, the aim of this review is to bring into focus a more global and comprehensive view of the systems organizing fear responses.

Biological evolution of replicator systems: towards a quantitative approach

The aim of this work is to study the features of a simple replicator chemical model of the relation between kinetic stability and entropy production under the action of external perturbations. We quantitatively explore the different paths leading to evolution in a toy model where two independent replicators compete for the same substrate. To do that, the same scenario described originally by Pross (J Phys Org Chem 17:312–316, 2004) is revised and new criteria to define the kinetic stability are proposed. Our results suggest that fast replicator populations are continually favored by the effects of strong stochastic environmental fluctuations capable to determine the global population, the former assumed to be the only acting evolution force. We demonstrate that the process is continually driven by strong perturbations only, and that population crashes may be useful proxies for these catastrophic environmental fluctuations. As expected, such behavior is particularly enhanced under very large scale perturbations, suggesting a likely dynamical footprint in the recovery patterns of new species after mass extinction events in the Earth’s geological past. Furthermore, the hypothesis that natural selection always favors the faster processes may give theoretical support to different studies that claim the applicability of maximum principles like the Maximum Metabolic Flux (MMF) or Maximum Entropy Productions Principle (MEPP), seen as the main goal of biological evolution.