Behavior Of Environmental Systems Research Articles

Transcriptomics analysis defines global cellular response of Agrobacterium tumefaciens 5A to arsenite exposure regulated through the histidine kinases PhoR and AioS.

In environments where arsenic and microbes coexist, microbes are the principal drivers of arsenic speciation, which directly affects bioavailability, toxicity and bioaccumulation. Speciation reactions influence arsenic behaviour in environmental systems, directly affecting human and agricultural exposures. Arsenite oxidation decreases arsenic toxicity and mobility in the environment, and therefore understanding its regulation and overall influence on cellular metabolism is of significant interest. The arsenite oxidase (AioBA) is regulated by a three-component signal transduction system AioXSR, which is in turn regulated by the phosphate stress response, with PhoR acting as the master regulator. Using RNA-sequencing, we characterized the global effects of arsenite on gene expression in Agrobacterium tumefaciens 5A. To further elucidate regulatory controls, mutant strains for histidine kinases PhoR and AioS were employed, and illustrate that in addition to arsenic metabolism, a host of other functional responses are regulated in parallel. Impacted functions include arsenic and phosphate metabolism, carbohydrate metabolism, solute transport systems and iron metabolism, in addition to others. These findings contribute significantly to the current understanding of the metabolic impact and genetic circuitry involved during arsenite exposure in bacteria. This informs how arsenic contamination will impact microbial activities involving several biogeochemical cycles in nature.

Wavelet analysis of correlation among Canary Islands octopus captures per unit effort, sea-surface temperatures and the North Atlantic Oscillation

Short-term fluctuations in the octopus catches off the Canary Islands have been attributed to changes in the sea surface temperature (SST) and the North Atlantic Oscillation (NAO) pattern. These results have been found using stationarity assumptions. However, the behavior of environmental systems is not always linear, and environmental time series do not always satisfy the statistical property of stationarity. Wavelet spectral analysis is a methodology which can deal with non-linear, non-stationary and noisy time series. Cross wavelet analysis (wavelet coherence) is applied to investigate the environmental effects (SST, NAO) on octopus abundance fluctuations measured as capture per unit of effort (CPUE) from 1989 to 2007 in the waters of the Canary Islands. A slightly positive correlation exists between NAO and CPUE at lags and leads of a few months. Additionally, a good relationship between SST and CPUE exists on the same seasonal scale, but there is a relatively weak relationship between SST anomalies and the NAO. When the analysis is extended to the interannual scale, the wavelet coherence identifies a statistically significant relationship between CPUE and NAO, but this does not happen when the wavelet coherence between CPUE and SST is computed. These results suggest that fluctuations in octopus catches could be the result of SST fluctuations but in synergy with other unknown environmental variables which are also affected by the NAO pattern.

Threshold behaviour in hydrological systems as (human) geo-ecosystems: manifestations, controls, implications

Abstract. In this paper we review threshold behaviour in environmental systems, which are often associated with the onset of floods, contamination and erosion events, and other degenerative processes. Key objectives of this review are to a) suggest indicators for detecting threshold behavior, b) discuss their implications for predictability, c) distinguish different forms of threshold behavior and their underlying controls, and d) hypothesise on possible reasons for why threshold behaviour might occur. Threshold behaviour involves a fast qualitative change of either a single process or the response of a system. For elementary phenomena this switch occurs when boundary conditions (e.g., energy inputs) or system states as expressed by dimensionless quantities (e.g. the Reynolds number) exceed threshold values. Mixing, water movement or depletion of thermodynamic gradients becomes much more efficient as a result. Intermittency is a very good indicator for detecting event scale threshold behavior in hydrological systems. Predictability of intermittent processes/system responses is inherently low for combinations of systems states and/or boundary conditions that push the system close to a threshold. Post hoc identification of "cause-effect relations" to explain when the system became critical is inherently difficult because of our limited ability to perform observations under controlled identical experimental conditions. In this review, we distinguish three forms of threshold behavior. The first one is threshold behavior at the process level that is controlled by the interplay of local soil characteristics and states, vegetation and the rainfall forcing. Overland flow formation, particle detachment and preferential flow are examples of this. The second form of threshold behaviour is the response of systems of intermediate complexity – e.g., catchment runoff response and sediment yield – governed by the redistribution of water and sediments in space and time. These are controlled by the topological architecture of the catchments that interacts with system states and the boundary conditions. Crossing the response thresholds means to establish connectedness of surface or subsurface flow paths to the catchment outlet. Subsurface stormflow in humid areas, overland flow and erosion in semi-arid and arid areas are examples, and explain that crossing local process thresholds is necessary but not sufficient to trigger a system response threshold. The third form of threshold behaviour involves changes in the "architecture" of human geo-ecosystems, which experience various disturbances. As a result substantial change in hydrological functioning of a system is induced, when the disturbances exceed the resilience of the geo-ecosystem. We present examples from savannah ecosystems, humid agricultural systems, mining activities affecting rainfall runoff in forested areas, badlands formation in Spain, and the restoration of the Upper Rhine river basin as examples of this phenomenon. This functional threshold behaviour is most difficult to predict, since it requires extrapolations far away from our usual experience and the accounting of bidirectional feedbacks. However, it does not require the development of more complicated model, but on the contrary, only models with the right level of simplification, which we illustrate with an instructive example. Following Prigogine, who studied structure formation in open thermodynamic systems, we hypothesise that topological structures which control response thresholds in the landscape might be seen as dissipative structures, and the onset of threshold processes/response as a switch to more efficient ways of depleting strong gradients that develop in the case of extreme boundary conditions.

Vulnerability analysis in environmental management: widening and deepening its approach

Current threshold-dominated methodologies of vulnerability analysis do not give sufficient emphasis to the processes that shape the environment and define the behaviour of environmental systems. While there has been widespread recognition for developing comprehensive approaches to assessing vulnerability, there has been relatively little theoretical debate on limitations and opportunities for improving the application of vulnerability analysis to environmental management, particularly in terms of a more complex systems perspective. A functional-based approach to ‘vulnerability’ is a means whereby the dynamics of vulnerable systems could be more fully integrated within vulnerability analysis. Functionality is seen as the ability of the environment to deliver outputs through time. Vulnerability analysis that is focused not only on thresholds that define the limits of system behaviour, but also on the process-defined capacity of systems to maintain this behaviour and deliver those outputs, could emerge as a useful element in integrated environmental management. Linking threshold analysis with a clear understanding of the interactions, differences and similarities between system processes which define coping ranges and system performance is a relatively simple conceptual development in vulnerability analysis. Such a development could, if successful, be of great value to those managing complex environments.

River model calibration, from guidelines to operational support tools

Numerical modelling is now used routinely to make predictions about the behaviour of environmental systems. Model calibration remains a critical step in the modelling process and different approaches have been taken to develop guidelines to support engineers and scientists in this task. This article reviews currently available guidelines for a river hydraulics modeller by dividing them into three types: on the calibration process, on hydraulic parameters, and on the use of hydraulic simulation codes. The article then presents an integration of selected guidelines within a knowledge-based calibration support system. A prototype called CaRMA-1 (Calibration of River Model Assistant) has been developed for supporting the calibration of models based on a specific 1D code. Two case studies illustrate the ability of the prototype to face operational situations in river hydraulics engineering, for which both data quality and quantity are not sufficient for an optimal calibration. Using CaRMA-1 allows the modeller to achieve the calibration task in accordance with good calibration practice implemented in the knowledge base. Relevant reasoning rules can easily be added to the knowledge base to extend the prototype range of applications. This study thus provides a framework for building operational support tools from various types of existing engineering guidelines.

Semantic integration of environmental models for application to global information systems and decision-making

Global information systems have the potential of providing decision makers with timely spatial information about earth systems. This information will come from diverse sources, including field monitoring, remotely sensed imagery, and environmental models. Of the three the latter has the greatest potential of providing regional and global scale information on the behavior of environmental systems, which may be vital for setting multi-governmental policy and for making decisions that are critical to quality of life. However, environmental models have limited prootocol for quality control and standardization. They tend to have weak or poorly defined semantics and so their output is often difficult to interpret outside a very limited range of applications for which they are designed. This paper considers this issue with respect to spatially distributed environmental models. A method of measuring the semantic proximity between components of large, integrated models is presented, along with an example illustrating its application. It is concluded that many of the issues associated with weak model semantics can be resolved with the addition of self-evaluating logic and context-based tools that present the semantic weaknesses to the end-user.

MODELLING THE SOLID-SOLUTION PARTITIONING OF METALS IN ENVIRONMENTAL SYSTEMS

Metal behaviour in environmental systems is strongly dependent upon speciation, the distribution of a metal among different chemical forms (Florence, 1977; Tessier and Turner, 1995). Speciation is dependent upon the reactions of metal ions with dissolved and particulate chemical species. These range in complexity from small ionic species such as the chloride ion, to highly complex molecules such as humic substances, particulate matter such as clays, and living organisms like algae and bacteria. Complex molecules and solid phases may be polyfunctional, possessing a large number of chemical sites that interact with metal ions to different extents. The challenge when modelling metal speciation is to simulate the reactions between metals and these species, and to model the complex mixtures of materials which make up both the dissolved and particulate phases in natural environments. Modelling work at the IFE centres on using laboratory data to simulate natural materials and conditions. Certain components of natural systems, particularly organic matter and metal oxides, are believed to exert the strongest influence on metal speciation (Tipping and Hurley, 1988; Tessier et al., 1985). A large body of data exists on the interactions between metals and pure forms of these materials (i.e. Dzombak and Morel, 1990). Our approach is to combine models for these interactions and to simulate natural materials as mixtures of the pure phases. The work presented here focuses on simulating the distribution of metals between their dissolved and particulate forms. This is a highly important distribution; it influences, for example, the cycling of metals within lakes, the fluxes of metals along rivers and across the riverine/estuarine interface, and the mobility of metals in soils. Four examples are presented, two of which relate to laboratory experiments on natural materials, and two that look at metal distributions under field conditions.