Sensitivity analysis of Repast computational ecology models with R/Repast

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom-up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in-silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results

A review on substances and processes relevant for optical remote sensing of extremely turbid marine areas, with a focus on the Wadden Sea

The interpretation of optical remote sensing data of estuaries and tidal flat areas is hampered by optical complexity and often extreme turbidity. Extremely high concentrations of suspended matter, chlorophyll and dissolved organic matter, local differences, seasonal and tidal variations and resuspension are important factors influencing the optical properties in such areas. This review gives an overview of the processes in estuaries and tidal flat areas and the implications of these for remote sensing in such areas, using the Wadden Sea as a case study area. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible. However, this requires sensors with a large ground resolution, algorithms tuned for high concentrations of various substances and the local specific optical properties of these substances, a simultaneous detection of water colour and land-water boundaries, a very short time lag between acquisition of remote sensing and in situ data used for validation and sufficient geophysical and ecological knowledge of the area. © 2010 The Author(s)

Towards a Processual Microbial Ontology

types: ArticleStandard microbial evolutionary ontology is organized according to a nested hierarchy of entities at various levels of biological organization. It typically detects and defines these entities in relation to the most stable aspects of evolutionary processes, by identifying lineages evolving by a process of vertical inheritance from an ancestral entity. However, recent advances in microbiology indicate that such an ontology has important limitations. The various dynamics detected within microbiological systems reveal that a focus on the most stable entities (or features of entities) over time inevitably underestimates the extent and nature of microbial diversity. These dynamics are not the outcome of the process of vertical descent alone. Other processes, often involving causal interactions between entities from distinct levels of biological organisation, or operating at different time scales, are responsible not only for the destabilisation of pre-existing entities, but also for the emergence and stabilisation of novel entities in the microbial world. In this article we consider microbial entities as more or less stabilised functional wholes, and sketch a network-based ontology that can represent a diverse set of processes including, for example, as well as phylogenetic relations, interactions that stabilise or destabilise the interacting entities, spatial relations, ecological connections, and genetic exchanges. We use this pluralistic framework for evaluating (i) the existing ontological assumptions in evolution (e.g. whether currently recognized entities are adequate for understanding the causes of change and stabilisation in the microbial world), and (ii) for identifying hidden ontological kinds, essentially invisible from within a more limited perspective. We propose to recognize additional classes of entities that provide new insights into the structure of the microbial world, namely ‘‘processually equivalent’’ entities, ‘‘processually versatile’’ entities, and ‘‘stabilized’’ entities.Economic and Social Research Council, U

Tetracycline: production, waste treatment and environmental impact assessment

The frequent occurrence of pharmaceuticals in the aquatic environment requires an assessment of their environmental impact and their negative effects in humans. Among the drugs with high harmful potential to the environment are the antibiotics that reach the environment not only, as may be expected, through the effluents from chemical and pharmaceutical industries, but mainly through the sewage and livestock; because around 25 to 75% of the ingested drugs are excreted in unchanged form after the passage through the Gastro-Intestinal Tract. Tetracycline has high world consumption, representing a human consumption of about 23 kg/day in Brazil in 2007. At the moment, researches are being made to develop new tetracycline that incorporate heavy metals (Hg, Cd, Re, Pt, Pd) to their structures in order to increase their bactericidal effect. The conventional wastewater treatment plants are not able to degrade complex organic molecules to reduce their toxicity and improve their biodegradability. For this reason new technologies, i.e., the advanced oxidation processes, are being developed to handle this demand. The objectives of this study are to review the literature on the processes of obtaining tetracycline, presenting its waste treatment methods and evaluation of their environmental impact

Division of Labor, Bet Hedging, and the Evolution of Mixed Biofilm Investment Strategies

Bacterial cells, like many other organisms, face a tradeoff between longevity and fecundity. Planktonic cells are fast growing and fragile, while biofilm cells are often slower growing but stress resistant. Here we ask why bacterial lineages invest simultaneously in both fast- and slow-growing types. We develop a population dynamic model of lineage expansion across a patchy environment and find that mixed investment is favored across a broad range of environmental conditions, even when transmission is entirely via biofilm cells. This mixed strategy is favored because of a division of labor where exponentially dividing planktonic cells can act as an engine for the production of future biofilm cells, which grow more slowly. We use experimental evolution to test our predictions and show that phenotypic heterogeneity is persistent even under selection for purely planktonic or purely biofilm transmission. Furthermore, simulations suggest that maintenance of a biofilm subpopulation serves as a cost-effective hedge against environmental uncertainty, which is also consistent with our experimental findings

Send more data: a systematic review of mathematical models of antimicrobial resistance

Abstract Background Antimicrobial resistance is a global health problem that demands all possible means to control it. Mathematical modelling is a valuable tool for understanding the mechanisms of AMR development and spread, and can help us to investigate and propose novel control strategies. However, it is of vital importance that mathematical models have a broad utility, which can be assured if good modelling practice is followed. Objective The objective of this study was to provide a comprehensive systematic review of published models of AMR development and spread. Furthermore, the study aimed to identify gaps in the knowledge required to develop useful models. Methods The review comprised a comprehensive literature search with 38 selected studies. Information was extracted from the selected papers using an adaptation of previously published frameworks, and was evaluated using the TRACE good modelling practice guidelines. Results None of the selected papers fulfilled the TRACE guidelines. We recommend that future mathematical models should: a) model the biological processes mechanistically, b) incorporate uncertainty and variability in the system using stochastic modelling, c) include a sensitivity analysis and model external and internal validation. Conclusion Many mathematical models of AMR development and spread exist. There is still a lack of knowledge about antimicrobial resistance, which restricts the development of useful mathematical models

Advancing microbial sciences by individual-based modelling

Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage-CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (μIBE)

Análise comparativa de redes hidrológicas geradas a partir de superfícies hidrologicamente consistentes

Um dos principais desafios da análise hidrológica está na caracterização morfométrica e delineamento da rede hidrográfica associada a uma bacia. Neste contexto, objetivou-se a comparação qualitativa e quantitativa de parâmetros geomorfométricos extraídos de redes hidrológicas geradas a partir de superfícies originais, e hidrologicamente consistentes. A priori, determinaram-se dois grupos de informações. O original, derivado das superfícies sem nenhuma correção e o corrigido, derivado das superfícies hidrologicamente consistentes. As informações de drenagem foram extraídas a partir de cada modelo digital de terreno (MDT) e cada modelo digital de elevação (MDE), antes e após a correção, para uma posterior comparação entre as redes estimadas e de referência. As comparações foram feitas na escala de 1:100.000, tomando por base o MDE SRTM de menor resolução espacial. Percebeu-se que as distâncias das redes são inversamente proporcionais a resolução espacial de cada superfície, exceto para o GDEM, que, mesmo com resolução espacial de 30metros, não gerou melhores resultados do que o SRTM com resolução espacial de 90metros. Das superfícies corrigidas a Topodata foi menos sensível a mudança, com uma amplitude da distância média (antes e após a correção) de apenas 24,5 metros. Enquanto o SRTM teve a maior amplitude com 76 metros. Os MDTs de alta resolução espacial apresentaram resultados similares, com o maior ajuste para o MDT obtido por levantamento aerofotogramétrico