The influence of hilly terrain on canopy-atmosphere carbon dioxide exchange

Topography influences many aspects of forest-atmosphere carbon exchange; yet only a small number of studies have considered the role of topography on the structure of turbulence within and above vegetation and its effect on canopy photosynthesis and the measurement of net ecosystem exchange of CO2 (N-ee) using flux towers. Here, we focus on the interplay between radiative transfer, flow dynamics for neutral stratification, and ecophysiological controls on CO2 sources and sinks within a canopy on a gentle cosine hill. We examine how topography alters the forest-atmosphere CO2 exchange rate when compared to uniform flat terrain using a newly developed first-order closure model that explicitly accounts for the flow dynamics, radiative transfer, and nonlinear eco physiological processes within a plant canopy. We show that variation in radiation and airflow due to topography causes only a minor departure in horizontally averaged and vertically integrated photosynthesis from their flat terrain values. However, topography perturbs the airflow and concentration fields in and above plant canopies, leading to significant horizontal and vertical advection of CO2. Advection terms in the conservation equation may be neglected in flow over homogeneous, flat terrain, and then N-ee = F-c, the vertical turbulent flux of CO2. Model results suggest that vertical and horizontal advection terms are generally of opposite sign and of the same order as the biological sources and sinks. We show that, close to the hilltop, F-c departs by a factor of three compared to its flat terrain counterpart and that the horizontally averaged F-c-at canopy top differs by more than 20% compared to the flat-terrain case.

Changes in oestrogen receptor-alpha and -beta during progression to acquired resistance to tamoxifen and fulvestrant (Faslodex, ICI 182,780) in MCF7 human breast cancer cells

Cell culture models of antioestrogen resistance often involve applying selective pressures of oestrogen deprivation simultaneously with addition of tamoxifen or fulvestrant (Faslodex, ICI 182,780) which makes it difficult to distinguish events in development of antioestrogen resistance from those in loss of response to oestrogen or other components. We describe here time courses of loss of antioestrogen response using either oestrogen-maintained or oestrogen-deprived MCF7 cells in which the only alteration to the culture medium was addition of 10(-6) M tamoxifen or 10(-7) M fulvestrant. In both oestrogen-maintained and oestrogen-deprived models, loss of growth response to tamoxifen was not associated with loss of response to fulvestrant. However, loss of growth response to fulvestrant was associated in both models with concomitant loss of growth response to tamoxifen. Measurement of oestrogen receptor alpha (ER alpha) and oestrogen receptor beta (ER beta) mRNA by real-time RT-PCR together with ER alpha and ER beta protein by Western immunoblotting revealed substantial changes to ER alpha levels but very little alteration to ER beta levels following development of antioestrogen resistance. In oestrogen-maintained cells, tamoxifen resistance was associated with raised levels of ERa mRNA/protein. However by contrast, in oestrogen-deprived MCF7 cells, where oestrogen deprivation alone had already resulted in increased levels of ERa mRNA/protein, long-term tamoxifen exposure now reduced ER alpha levels. Whilst long-term exposure to fulvestrant reduced ERa. mRNA/protein levels in the oestrogen-maintained cells to a level barely detectable by Western immunoblotting and non-functional in inducing gene expression (ERE-LUC reporter or pS2), in oestrogen-deprived cells the reduction was much less substantial and these cells retained an oestrogen-induction of both the ERE-LUC reporter gene and the endogenous pS2 gene which could still be inhibited by antioestrogen. This demonstrates that whilst ER alpha can be abrogated by fulvestrant and increased by tamoxifen in some circumstances, this does not always hold true and mechanisms other than alteration to ER must be involved in the development of antioestrogen resistant growth. (c) 2006 Elsevier Ltd. All rights reserved.

A single-column model ensemble approach applied to the TWP-ICE experiment

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.