Do Differing Levels of Boldness Influence the Success of Translocation? : A Pilot Study on Red Squirrels (Sciurus vulgaris)

Peer reviewedPublisher PD

Mapping Surface Cover Parameters Using Aggregation Rules and Remotely Sensed Cover Classes

A coupled model, which combines the Biosphere-Atmosphere Transfer Scheme (BATS) with an advanced atmospheric boundary-layer model, was used to validate hypothetical aggregation rules for BATS-specific surface cover parameters. The model was initialized and tested with observations from the Anglo-Brazilian Amazonian Climate Observational Study and used to simulate surface fluxes for rain forest and pasture mixes at a site near Manaus in Brazil. The aggregation rules are shown to estimate parameters which give area-average surface fluxes similar to those calculated with explicit representation of forest and pasture patches for a range of meteorological and surface conditions relevant to this site, but the agreement deteriorates somewhat when there are large patch-to-patch differences in soil moisture. The aggregation rules, validated as above, were then applied to remotely sensed 1 km land cover data set to obtain grid-average values of BATS vegetation parameters for 2.8 deg x 2.8 deg and 1 deg x 1 deg grids within the conterminous United States. There are significant differences in key vegetation parameters (aerodynamic roughness length, albedo, leaf area index, and stomatal resistance) when aggregate parameters are compared to parameters for the single, dominant cover within the grid. However, the surface energy fluxes calculated by stand-alone BATS with the 2-year forcing, data from the International Satellite Land Surface Climatology Project (ISLSCP) CDROM were reasonably similar using aggregate-vegetation parameters and dominant-cover parameters, but there were some significant differences, particularly in the western USA

The continuum of spreading depolarizations in acute cortical lesion development: Examining Leao's legacy.

A modern understanding of how cerebral cortical lesions develop after acute brain injury is based on Aristides Leao's historic discoveries of spreading depression and asphyxial/anoxic depolarization. Treated as separate entities for decades, we now appreciate that these events define a continuum of spreading mass depolarizations, a concept that is central to understanding their pathologic effects. Within minutes of acute severe ischemia, the onset of persistent depolarization triggers the breakdown of ion homeostasis and development of cytotoxic edema. These persistent changes are diagnosed as diffusion restriction in magnetic resonance imaging and define the ischemic core. In delayed lesion growth, transient spreading depolarizations arise spontaneously in the ischemic penumbra and induce further persistent depolarization and excitotoxic damage, progressively expanding the ischemic core. The causal role of these waves in lesion development has been proven by real-time monitoring of electrophysiology, blood flow, and cytotoxic edema. The spreading depolarization continuum further applies to other models of acute cortical lesions, suggesting that it is a universal principle of cortical lesion development. These pathophysiologic concepts establish a working hypothesis for translation to human disease, where complex patterns of depolarizations are observed in acute brain injury and appear to mediate and signal ongoing secondary damage

Aggregation rules for surface parameters in global models

International audienceAggregation rules are derived for calculating the effective value of parameters that determine the exchange of momentum and energy between the land surface and the atmosphere at the length scales used in General Circulation Models (GCMs). The derivation involves starting from theories that link parameters relevant at grid scale and patch scale, and then imposing the limitations necessarily present when models are operated in a free-standing, predictive mode. The application of these rules is illustrated by example for the case of the Biosphere-Atmosphere Transfer Scheme (BATS). Remotely sensed global maps of land cover classes at 1 km x 1 km pixel scale for North America, South America, and Africa are used with these new aggregation rules to calculate area-average values of parameters for the 3° x 3° grid mesh used in the National Center for Atmospheric Research Community Climate Model. There are significant differences between the parameters calculated using aggregation rules and the values selected on the basis of the dominant vegetation cover in each grid, this being the selection procedure conventionally applied with BATS

COSMOS: the COsmic-ray Soil Moisture Observing System

The newly-developed cosmic-ray method for measuring area-average soil moisture at the hectometer horizontal scale is being implemented in the COsmic-ray Soil Moisture Observing System (or the COSMOS). The stationary cosmic-ray soil moisture probe measures the neutrons that are generated by cosmic rays within air and soil and other materials, moderated by mainly hydrogen atoms located primarily in soil water, and emitted to the atmosphere where they mix instantaneously at a scale of hundreds of meters and whose density is inversely correlated with soil moisture. The COSMOS has already deployed more than 50 of the eventual 500 cosmic-ray probes, distributed mainly in the USA, each generating a time series of average soil moisture over its horizontal footprint, with similar networks coming into existence around the world. This paper is written to serve a community need to better understand this novel method and the COSMOS project. We describe the cosmic-ray soil moisture measurement method, the instrument and its calibration, the design, data processing and dissemination used in the COSMOS project, and give example time series of soil moisture obtained from COSMOS probes

Research Note:<br>Derivation of temperature lapse rates in semi-arid south-eastern Arizona

International audienceEcological and hydrological modelling at the regional scale requires distributed information on weather variables, and temperature is important among these. In an area of basin and range topography with a wide range of elevations, such as south-eastern Arizona, measurements are usually available only at a relatively small number of locations and elevations, and temperatures elsewhere must be estimated from atmospheric lapse rate. This paper derives the lapse rates to estimate maximum, minimum and mean daily temperatures from elevation. Lapse rates were calculated using air temperatures at 2 m collected during 2002 at 18 locations across south-eastern Arizona, with elevations from 779 to 2512 m. The lapse rate predicted for the minimum temperature was lower than the mean environmental lapse rate (MELR), i.e. 6 K km?1, whereas those predicted for the mean and maximum daily temperature were very similar to the MELR. Lapse rates were also derived from radiosonde data at 00 and 12 UTC (5 pm and 5 am local time, respectively). The lapse rates calculated from radiosonde data were greater than those from the 2 m measurements, presumably because the effect of the surface was less. Given temperatures measured at Tucson airport, temperatures at the other sites were predicted using the different estimates of lapse rates. The best predictions of temperatures used the locally predicted lapse rates. In the case of maximum and mean temperature, using the MELR also resulted in accurate predictions. Keywords: near surface lapse rates, semi-arid climate, mean minimum and maximum temperatures, basin and range topograph

Implementing surface parameter aggregation rules in the CCM3 global climate model: regional responses at the land surface

International audienceThe land-surface parameters required as input to a GCM grid box (typically a few degrees) are often set to be those of the dominant vegetation type within the grid box. This paper discusses the use and effect of aggregation rules for specifying effective values of these land cover parameters by taking into account the relative proportion of each land-cover type within each individual grid box. Global land-cover classification data at 1 km resolution were used to define Biosphere Atmosphere Transfer Scheme (BATS) specific aggregate (using aggregation rules) land-cover parameters. Comparison of the values of the aggregate parameters and those defined using the single dominant vegetation type (default parameters) shows significant differences in some regions, particularly in the semi-desert and in forested regions, e.g. the Sahara Desert and the tropical forest of South America. These two different sets of parameters were used as input data for two 10-year simulations of the NCAR CCM3 model coupled to the BATS land-surface scheme. Statistical analyses comparing the results of the two model runs showed that the resulting effects on the land-surface diagnostics are significant only in specific regions. For example, the sensible heat flux in the Sahara Desert calculated for the aggregate parameter run increased due to the marked increase in the minimum stomatal resistance and the decrease in fractional vegetation cover in the aggregate parameters over the default parameters. The modelled global precipitation and surface air temperature fields were compared to observations: there is a general improvement in the performance of the aggregate parameter run over the default parameter run in areas where the differences between the aggregate and default parameter run are significant. However, most of the difference between the modelled and observed fields is attributable to other model deficiencies. It can be concluded that the use of aggregation rules to derive land-surface parameters results in significant changes in modelled climate and in some improvements in the land-surface diagnostics in selected regions. There is also some evidence that there is a response in the global circulation pattern, which is a focus of further work

Corrigendum to &quot;COSMOS: the COsmic-ray Soil Moisture Observing System&quot; published in Hydrol. Earth Syst. Sci., 16, 4079–4099, 2012

No abstract available

Ion channel model reduction using manifold boundaries

Mathematical models of voltage-gated ion channels are used in basic research, industrial and clinical settings. These models range in complexity, but typically contain numerous variables representing the proportion of channels in a given state, and parameters describing the voltage-dependent rates of transition between states. An open problem is selecting the appropriate degree of complexity and structure for an ion channel model given data availability. Here, we simplify a model of the cardiac human Ether-à-go-go Related Gene (hERG) potassium ion channel, which carries cardiac IKr, using the manifold boundary approximation method (MBAM). The MBAM approximates high-dimensional model-output manifolds by reduced models describing their boundaries, resulting in models with fewer parameters (and often variables). We produced a series of models of reducing complexity starting from an established 5-state hERG model with 15 parameters. Models with up to 3 fewer states and 8 fewer parameters were shown to retain much of the predictive capability of the full model and were validated using experimental hERG1a data collected in HEK293 cells at 37°C. The method provides a way to simplify complex models of ion channels that improves parameter identifiability and will aid in future model development

Amazonian evaporation.

Medições de evaporação da cobertura vegetal seca e perdas por intercepção obtidas durante um estudo de dois anos de evaporação na floresta tropical no centro da Amazônia são utilizados para calibrar um modelo micrometeorológico de evaporação