Ecosystem process models at multiple scales for mapping tropical forest productivity

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Valuing water resources in developing countries: A semiparametric approach to valuation models

Valuation of projects for the preservation of water resources provides important information to policy makers and funding institutions. Standard contingent valuation models rely on distributional assumptions to provide welfare measures. Deviations from assumed and actual distribution of benefits are important when designing policies in developing countries, where inequality is a concern. This article applies semiparametric methods to obtain estimates of the benefit from a project for the preservation of an important Brazilian river basin. These estimates lead to significant differences from those obtained using the standard parametric approach.

Azana atlantica, n.sp., with reduced mouthparts and two ocelli: first record of Azana for the Neotropical region (Diptera : Mycetophilidae : Sciophilinae)

A new Sciophilinae-Azana atlantica, sp. n. - is described from the Atlantic Forest in southeastern Brazil. The species has a number of distinctive apomorphic features, including loss of the mid ocellus, reduced mouthparts, Sc short and incomplete, first section of Rs missing, r-m elongated, longitudinal in position, aligned with the second section of Rs ( R(5)), unforked medial and cubital veins, R(4) missing, M(4) entirely absent, gonostyle triangular, with an inner row of elongated spines and a basal, digitiform inner projection. Some of these features are shared with other genera of the Azana-group of Sciophilinae. The shape of the scutum and the strong spines on the gonostyle make it clear that the species belongs in Azana, despite the features that are distinctive from the remaining species in the genus. There are ten species described in Azana to date, from United States, Europe, Sri Lanka, Canary Islands, tropical Africa and Baltic amber. This is the first Neotropical species belonging to the genus. The complete loss of M(4) and the separated gonocoxites suggest that Azana atlantica, sp. n. forms a monophyletic group with the Afrotropical species of the genus. Azana, Morganiella, Neoaphelomera, Neotrizygia, and Trizygia are shown to compose a small clade within the Azana-group of genera. The division of the genus into two subgenera - A. ( Azana) and A. ( Jugazana) - most probably renders A. ( Azana) paraphyletic and it is suggested that this should be for the time being abandoned.

Use of bulk density profiles from X-radiography to examine structural crust models

Exponential and sigmoidal functions have been suggested to describe the bulk density profiles of crusts. The present work aims to evaluate these conceptual models using high resolution X-radiography. Repacked seedbeds from two soil materials, air-dried or prewetted by capillary rise, were subjected to simulated rain, which resulted in three types of structural crusts, namely, slaking, infilling, and coalescing. Bulk density distributions with depth were generated using high-resolution (70 mum), calibrated X-ray images of slices from the resin-impregnated crusted seedbeds. The bulk density decreased progressively with depth, which supports the suggestion that a crust should be considered as a nonuniform layer. For the slaking and the coalescing crusts, the exponential function underestimated the strong change in bulk density across the morphologically defined transition between the crust and the underlying material; the sigmoidal function provided a better description. Neither of these crust models effectively described the shape of the bulk density profiles through the whole seedbed. Below the infilling and slaking crusts, bulk density increased linearly with depth as a result of slumping. In the coalescing crusted seedbed, the whole seedbed uniformly collapsed and most of the bulk density change within the crust could be ascribed to slumping (0.33 g cm(-3)) rather than to crusting (0.12 g cm(-3)). Finally, (i) X-radiography appears as a unique tool to generate high resolution bulk density profiles and (ii) in structural crusts, bulk density profiles could be modeled using the existing exponential and sigmoidal crusting models, provided a slumping model would be coupled.

Ladder operators for integrable one-dimensional lattice models

A generalised ladder operator is used to construct the conserved operators for any one-dimensional lattice model derived from the Yang-Baxter equation. As an example, the low order conserved operators for the XYh model are calculated explicitly.

Protection against Paracoccidioides brasiliensis infection conferred by the prophylactic administration of native and recombinant ArtinM

We determined the prophylactic effect of both the d-mannose-binding lectin ArtinM extracted from the seeds of Artocarpus integrifolia (jackfruit) and its recombinant counterpart during the course of experimental paracoccidioidomycosis induced in BALB/c mice. Four experimental protocols of prophylaxis were employed to evaluate the most protective regimen of ArtinM administration. It was demonstrated that the best effect was obtained by administration of two ArtinM doses on days 10 and 3 before the challenge with Paracoccidioides brasiliensis. By following this protocol, the lungs of mice that received native or recombinant ArtinM exhibited reduced fungal burden and granuloma incidence. In addition, the protocol augmented contents of IL-12, IFN-gamma, TNF-alpha and NO. On the other hand, the control group consisting of untreated infected mice had higher pulmonary levels of IL-4 and IL-10. In conclusion, prophylaxis with ArtinM significantly reproduces the effect of its therapeutic administration, i.e, it confers resistance to P. brasiliensis infection in mouse models by promoting IL-12 production and favours Th1-immunity.

Maternal investment in egg production: environmental and population-specific effects on offspring performance in the snapping shrimp Alpheus nuttingi (Schmitt, 1924) (Decapoda, Alpheidae)

Among marine invertebrates, the overall biomass invested in egg production varies widely within populations, which can result from the interaction of endogenous and exogenous factors. Species that have constant reproduction throughout the year can be good models to study the influence of environmental factors on reproductive processes. We conducted a seasonal comparison of egg production in the intertidal snapping shrimp Alpheus nuttingi, which shows a continuous reproductive pattern, to examine the hypothesis that differences in egg production are driven by environmental conditions and population features. This population showed an uncommon strategy, characterized by females that produce eggs of varying sizes within their clutches, with reduced egg volume when the number of eggs is higher (Spring-Summer). In these seasons, higher temperatures and greater food availability may allow the production of more eggs compared to the Autumn-Winter seasons. Compared to other alpheid shrimps, this population produces small eggs, but in larger numbers. Despite the higher fecundity, the reproductive output is relatively low, this production being supported by the large size of females from the southern Atlantic region. Our findings showed that the egg production of A. nuttingi was greatly influenced by environmental factors. Therefore, this shrimp, and probably other decapods that possess continuous reproduction, adopt different reproductive strategies during the year. (C) Koninklijke Brill NV, Leiden, 2010.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

A prospective comparison of two models of cannabis use and psychotic relapse in early psychosis

No abstract

Virtual models of the HLA class I antigen processing pathway

Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.

Dermaseptin 01 as antimicrobial peptide with rich biotechnological potential: study of peptide interaction with membranes containing Leishmania amazonensis lipid-rich extract and membrane models

This article addresses the interactions of the synthetic antimicrobial peptide dermaseptin 01 (GLWSTIKQKGKEAAIAAA-KAAGQAALGAL-NH(2), DS 01) with phospholipid (PL) monolayers comprising (i) a lipid-rich extract of Leishmania amazonensis (LRE-La), (ii) zwitterionic PL (dipalmitoylphosphatidylcholine, DPPC), and (iii) negatively charged PL (dipalmitoylphosphatidylglycerol, DPPG). The degree of interaction of DS 01 with the different biomembrane models was quantified from equilibrium and dynamic liquid-air interface parameters. At low peptide concentrations, interactions between DS 01 and zwitterionic PL, as well as with the LRE-La monolayers were very weak, whereas with negatively charged PLs the interactions were stronger. For peptide concentrations above 1 mu g/ml, a considerable expansion of negatively charged monolayers occurred. In the case of DPPC, it was possible to return to the original lipid area in the condensed phase, suggesting that the peptide was expelled from the monolayer. However, in the case of DPPG, the average area per lipid molecule in the presence of DS 01 was higher than pure PLs even at high surface pressures, suggesting that at least part of DS 01 remained incorporated in the monolayer. For the LRE-La monolayers, DS 01 also remained in the monolayer. This is the first report on the antiparasitic activity of AMPs using Langmuir monolayers of a natural lipid extract from L. amazonensis. Copyright (C) 2011 European Peptide Society and John Wiley & Sons, Ltd.

Attentional modulation of neural responses to action observation: Implications for models of the human 'mirror' system

In primates, the observation of meaningful, goaldirected actions engages a network of cortical areas located within the premotor and inferior parietal lobules. Current models suggest that activity within these regions arises relatively automatically during passive action observation without the need for topdown control. Here we used functional magnetic resonance imaging to determine whether cortical activit)' associated with action observation is modulated by the strategic allocation of selective attention. Normal observers viewed movie clips of reach-to-grasp actions while performing an easy or difficult visual discrimination at the fovea. A wholebrain analysis was performed to determine the effects of attentional load on neural responses to observed hand actions. Our results suggest that cortical areas involved in action observation are significantiy modulated by attentional load. These findings have important implications for recent attempts to link the human action-observation system to response properties of "mirror neurons" in monkeys.

Reduced pH induces an inactive non-native conformation of the monomeric bothropstoxin-I (Lys49-PLA(2))

Bothropstoxin-I (BthTx-I), a Lys49-PLA(2) from Bothrops jararacussu venom, permeabilizes membranes by a non-hydrolytic Ca(2+)-independent mechanism. The BthTx-I showed activity against liposomes including 10% and 50% negatively charged lipids at pH 7.0, but not at pH 5.0. Nevertheless, ultracentrifugation and FRET demonstrated that at pH 5.0 the BthTx-I is bound to 50% negatively charged membranes. ANS binding identified a non-native monomeric conformation at pH 5.0, suggesting that tertiary structure alterations result in activity loss of the BthTx-I at low pH. (C) 2009 Elsevier Ltd. All rights reserved.

Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models

We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.