AQA A2 Unit 5 Biology : control in cells and in organisms.

Guía de revisión en el área de la biología para estudiantes que estén preparando el examen AQA (Assessment and Qualifications Alliance) en el nivel AS (enseñanza secundaria de segundo ciclo). El libro está dividido en tres secciones: una introducción con información sobre el examen oficial, sugerencias, consejos y técnicas de estudio; una guía de contenido con los siguientes temas: cómo detectan y responden los organismos a los cambios en su medio ambiente, cómo coordinan sus respuestas a los estímulos, músculo esquelético, homeostasis, código genético, síntesis de proteínas y mutación genética, control de los genes y tecnología de clonación y sus aplicaciones; y un apartado final con ejemplos de preguntas y respuestas reales de los alumnos con comentarios del examinador.

Understanding El Niño in ocean-atmosphere general circulation models: progress and challenges

Determining how El Niño and its impacts may change over the next 10 to 100 years remains a difficult scientific challenge. Ocean–atmosphere coupled general circulation models (CGCMs) are routinely used both to analyze El Niño mechanisms and teleconnections and to predict its evolution on a broad range of time scales, from seasonal to centennial. The ability to simulate El Niño as an emergent property of these models has largely improved over the last few years. Nevertheless, the diversity of model simulations of present-day El Niño indicates current limitations in our ability to model this climate phenomenon and to anticipate changes in its characteristics. A review of the several factors that contribute to this diversity, as well as potential means to improve the simulation of El Niño, is presented.

Modeling the mechanisms that control in-stream dissolved organic carbon dynamics in upland and forested catchments

[1] We present a new, process-based model of soil and stream water dissolved organic carbon (DOC): the Integrated Catchments Model for Carbon (INCA-C). INCA-C is the first model of DOC cycling to explicitly include effects of different land cover types, hydrological flow paths, in-soil carbon biogeochemistry, and surface water processes on in-stream DOC concentrations. It can be calibrated using only routinely available monitoring data. INCA-C simulates daily DOC concentrations over a period of years to decades. Sources, sinks, and transformation of solid and dissolved organic carbon in peat and forest soils, wetlands, and streams as well as organic carbon mineralization in stream waters are modeled. INCA-C is designed to be applied to natural and seminatural forested and peat-dominated catchments in boreal and temperate regions. Simulations at two forested catchments showed that seasonal and interannual patterns of DOC concentration could be modeled using climate-related parameters alone. A sensitivity analysis showed that model predictions were dependent on the mass of organic carbon in the soil and that in-soil process rates were dependent on soil moisture status. Sensitive rate coefficients in the model included those for organic carbon sorption and desorption and DOC mineralization in the soil. The model was also sensitive to the amount of litter fall. Our results show the importance of climate variability in controlling surface water DOC concentrations and suggest the need for further research on the mechanisms controlling production and consumption of DOC in soils.

Eutrophication control in river-systems: an application of INCA-P to the River Lugg

The Integrated Catchments model of Phosphorus dynamics (INCA-P) was applied to the River Lugg to determine the key factors controlling delivery of phosphorus to the main channel and to quantify the relative contribution of diffuse and point sources to the in-stream phosphorus (P) load under varying hydrological conditions. The model is able to simulate the seasonal variations and inter-annual variations in the in-stream total-phosphorus concentrations. However, difficulties in simulating diffuse inputs arise due to equifinality in the model structure and parameters. The River Lugg is split into upper and lower reaches. The upper reaches are dominated by grassland and woodland, so the patterns in the stream-water total-phosphorus concentrations are typical of diffuse source inputs; application of the model leads to estimates of the relative contribution to the in-stream P load from diffuse and point sources as 9:1. In the lower reaches, which are more intensively cultivated and urbanised, the stream-water total-phosphorus concentration dynamics are influenced more by point-sources; the simulated relative diffuse/point contribution to the in-stream P load is 1: 1. The model set-up and simulations are used to identify the key source-areas of P in the catchment, the P contribution of the Lugg to the River Wye during years with contrasting precipitation inputs, and the uptake and release of P from within-reach sediment. In addition, model scenarios are run to identify the impacts of likely P reductions at sewage treatment works on the in-stream soluble-reactive P concentrations and the suitability of this as a management option is assessed for reducing eutrophication.

Coronal mass ejections and magnetic flux buildup in the heliosphere

To test for magnetic flux buildup in the heliosphere from coronal mass ejections (CMEs), we simulate heliospheric flux as a constant background open flux with a time-varying interplanetary CME (ICME) contribution. As flux carried by ejecta can only contribute to the heliospheric flux budget while it remains closed, the ICME flux opening rate is an important factor. Two separate forms for the ICME flux opening rate are considered: (1) constant and (2) exponentially decaying with time. Coronagraph observations are used to determine the CME occurrence rates, while in situ observations are used to estimate the magnetic flux content of a typical ICME. Both static equilibrium and dynamic simulations, using the constant and exponential ICME flux opening models, require flux opening timescales of ∼50 days in order to match the observed doubling in the magnetic field intensity at 1 AU over the solar cycle. Such timescales are equivalent to a change in the ICME closed flux of only ∼7–12% between 1 and 5 AU, consistent with CSE signatures; no flux buildup results. The dynamic simulation yields a solar cycle flux variation with high variability that matches the overall variability of the observed magnetic field intensity remarkably well, including the double peak forming the Gnevyshev gap.

Understanding electron heat flux signatures in the solar wind

Suprathermal electrons (E > 80 eV) carry heat flux away from the Sun. Processes controlling the heat flux are not well understood. To gain insight into these processes, we model heat flux as a linear dependence on two independent parameters: electron number flux and electron pitch angle anisotropy. Pitch angle anisotropy is further modeled as a linear dependence on two solar wind components: magnetic field strength and plasma density. These components show no correlation with number flux, reinforcing its independence from pitch angle anisotropy. Multiple linear regression applied to 2 years of Wind data shows good correspondence between modeled and observed heat flux and anisotropy. The results suggest that the interplay of solar wind parameters and electron number flux results in distinctive heat flux dropouts at heliospheric features like plasma sheets but that these parameters continuously modify heat flux. This is inconsistent with magnetic disconnection as the primary cause of heat flux dropouts. Analysis of fast and slow solar wind regimes separately shows that electron number flux and pitch angle anisotropy are equally correlated with heat flux in slow wind but that number flux is the dominant correlative in fast wind. Also, magnetic field strength correlates better with pitch angle anisotropy in slow wind than in fast wind. The energy dependence of the model fits suggests different scattering processes in fast and slow wind.

Quantifying mesoscale variability in ocean transient tracer fields

A powerful way to test the realism of ocean general circulation models is to systematically compare observations of passive tracer concentration with model predictions. The general circulation models used in this way cannot resolve a full range of vigorous mesoscale activity (on length scales between 10–100 km). In the real ocean, however, this activity causes important variability in tracer fields. Thus, in order to rationally compare tracer observations with model predictions these unresolved fluctuations (the model variability error) must be estimated. We have analyzed this variability using an eddy‐resolving reduced‐gravity model in a simple midlatitude double‐gyre configuration. We find that the wave number spectrum of tracer variance is only weakly sensitive to the distribution of (large scale slowly varying) tracer sources and sinks. This suggests that a universal passive tracer spectrum may exist in the ocean. We estimate the spectral shape using high‐resolution measurements of potential temperature on an isopycnal in the upper northeast Atlantic Ocean, finding a slope near k −1.7 between 10 and 500 km. The typical magnitude of the variance is estimated by comparing tracer simulations using different resolutions. For CFC‐ and tritium‐type transient tracers the peak magnitude of the model variability saturation error may reach 0.20 for scales shorter than 100 km. This is of the same order as the time mean saturation itself and well over an order of magnitude greater than the instrumental uncertainty.