Monitoring changes in precipitation and radiative energy using satellite data and climate models

Current changes in the tropical hydrological cycle, including water vapour and precipitation, are presented over the period 1979-2008 based on a diverse suite of observational datasets and atmosphere-only climate models. Models capture the observed variability in tropical moisture while reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite instruments employed and only cursory agreement with model simulations, primarily relating to the interannual variability associated with the El Niño Southern Oscillation. All datasets display a positive relationship between precipitation and surface temperature but with a large spread. The tendency for wet, ascending regions to become wetter at the expense of dry, descending regimes is in general reproduced. Finally, the frequency of extreme precipitation is shown to rise with warming in the observations and for the model ensemble mean but with large spread in the model simulations. The influence of the Earth’s radiative energy balance in relation to changes in the tropical water cycle are discussed

Glacier shrinkage and climatic change in the Russian Altai from the mid-20th century: An assessment using remote sensing and PRECIS regional climate model

This paper examines changes in the surface area of glaciers in the North and South Chuya Ridges, Altai Mountains in 1952-2004 and their links with regional climatic variations. The glacier surface areas for 2004 were derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Data from the World Glacier Inventory (WGI)dating to 1952 and aerial photographs from 1952 were used to estimate the changes. 256 glaciers with a combined area of 253±5.1 km2 have been identified in the region in 2004. Estimation of changes in extent of 126 glaciers with the individual areas not less than 0.5 km2 in 1952 revealed a 19.7±5.8% reduction. The observed glacier retreat is primarily driven by an increase in summer temperatures since the 1980s when air temperatures were increasing at a rate of 0.10 - 0.13oC a-1 at the glacier tongue elevation. The regional climate projections for A2 and B2 CO2 emission scenarios developed using PRECIS regional climate model indicate that summer temperatures will increase in the Altai in 2071-2100 by 6-7oC and 3-5oC respectively in comparison with 1961-1990 while annual precipitation will increase by 15% and 5%. The length of the ablation season will extend from June-August to the late April – early October. The projected increases in precipitation will not compensate for the projected warming and glaciers will continue to retreat in the 21st century under both B2 and A2 scenarios.

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Forage production and nutrient availability in small-scale dairy systems in central Mexico using linear programming and partial budgeting

Small-scale dairy systems play an important role in the Mexican dairy sector and farm planning activities related to resource allocation have a significant impact on the profitability of such enterprises. Linear programming is a technique widely used for planning and ration formulation, and partial budgeting is a technique for assessing the impact of changes on the profitability of an enterprise. This study used both methods to optimise land use for forage production and nutrient availability, and to evaluate the economic impact of such changes in small-scale Mexican dairy systems. The model showed satisfactory performance when optimal solutions were compared with the traditional strategy. The strategy using fresh ryegrass, maize silage and oat hay, and the strategy using a combination of alfalfa hay, maize silage, fresh ryegrass and oat hay appeared attractive options for providing a better nutrient supply and maintaining a higher stocking rate throughout the year than the traditional strategy.

Identifying important endemic areas using ecoregions: birds and mammals in the Indo-Pacific

Concentrations of large numbers of endemic species have been singled out in prioritization exercises as significant areas for global biodiversity conservation. This paper describes bird and mammal endemicity in Indo-Pacific ecoregions. An ecoregion is a relatively large unit of land or water that contains a distinct assemblage of natural communities. We prioritize 133 ecoregions according to their levels of endemicity, and explain how variables such as biome type, whether the ecoregion is on an island or continental mass, montane or non-montane, correlate with the proportion of the total species assemblage that are endemic. Following an exploratory principal components analysis we classify all ecoregions according to the relationship between numbers of endemics and overall species richness. Endemicity is negatively correlated with species richness. We show that plotting the logit transformation of the endemicity of birds and mammals against log of species richness is a more effective and useful way of identifying important ecoregions than simply ordering ecoregions by the proportion of endemic species, or any other single measure. The plot, divided into 16 regions corresponding to the quartiles of the two variables, was used to identify ecoregions of high conservation value. These are the ecoregions with the highest endemicity and lowest species richness. Further analysis shows that island and montane ecoregions, regardless of their biome type, are by far the most important for endemic species.

Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 x 2 x 2 x 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5-13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection. (C) 2009 Elsevier B.V. All rights reserved.

Modelling 2,4-dichlorophenol bioavailability and bioaccumulation by the freshwater fingernail clam Sphaerium corneum using artificial particles and humic acids

The complex and variable composition of natural sediments makes it very difficult to predict the bioavailability and bioaccumulation of sediment-bound contaminants. Several approaches have been proposed to overcome this problem, including an experimental model using artificial particles with or without humic acids as a source of organic matter. For this work, we have applied this experimental model, and also a sample of a natural sediment, to investigate the uptake and bioaccumulation of 2,4-dichlorophenol (2,4-DCP) by Sphaerium corneum. Additionally, the particle-water partition coefficients (K-d) were calculated. The results showed that the bioaccumulation of 2,4-DCP by clams did not depend solely on the levels of chemical dissolved, but also on the amount sorbed onto the particles and the characteristics and the strength of that binding. This study confirms the value of using artificial particles as a suitable experimental model for assessing the fate of sediment-bound contaminants. (c) 2006 Elsevier Ltd. All rights reserved.

Constitutive oligomerization of human D-2 dopamine receptors expressed in Spodoptera frugiperda 9 (Sf9) and in HEK293 cells - Analysis using co-immunoprecipitation and time-resolved fluorescence resonance energy transfer

Human D-2Long (D-2L) and D-2Short (D-2S) dopamine receptor isoforms were modified at their N-terminus by the addition of a human immunodeficiency virus (HIV) or a FLAG epitope tag. The receptors were then expressed in Spodoptera frugiperda 9 (Sf9) cells using the baculovirus system, and their oligomerization was investigated by means of co-immunoprecipitation and time-resolved fluorescence resonance energy transfer (FRET). [H-3] Spiperone labelled D-2 receptors in membranes prepared from Sf9 cells expressing epitope-tagged D-2L or D-2S receptors, with a pK(d) value of approximate to 10. Co-immunoprecipitation using antibodies specific for the tags showed constitutive homo-oligomerization of D-2L and D-2S receptors in Sf9 cells. When the FLAG-tagged D-2S and HIV-tagged D-2L receptors were co-expressed, co-immunoprecipitation showed that the two isoforms can also form hetero-oligomers in Sf9 cells. Time-resolved FRET with europium and XL665-labelled antibodies was applied to whole Sf9 cells and to membranes from Sf9 cells expressing epitope-tagged D-2 receptors. In both cases, constitutive homo-oligomers were revealed for D-2L and D-2S isoforms. Time-resolved FRET also revealed constitutive homo-oligomers in HEK293 cells expressing FLAG-tagged D-2S receptors. The D-2 receptor ligands dopamine, R-(-) propylnorapomorphine, and raclopride did not affect oligomerization of D-2L and D-2S in Sf9 and HEK293 cells. Human D-2 dopamine receptors can therefore form constitutive oligomers in Sf9 cells and in HEK293 cells that can be detected by different approaches, and D-2 oligomerization in these cells is not regulated by ligands.

Syntheses and crystal structures of two new coordination polymers of Cd(II) using organic spacer and inorganic-bridging ligands

Two new cadmium (II) complexes [Cd(hmt)(dca)(2)] (n) (1) and [Cd-3(hmt)(2)(SeCN)(6)(H2O)(2)] (n) (2) (hmt=hexamethylenetetramine, dca=dicyanamide) have been synthesized and characterized by X-ray single-crystal analysis. The complex 1 is a 2D rectangular grid of octahedral cadmium (II) with CdN6 chromophore where cadmium centers are doubly bridged by dicyanamide and hmt along a-axis, which are interlinked by dicyanamide running along c-axis. Whereas, complex 2 is a 1D chain of octahedral cadmium (II) with a three-leg ladder topology running along a-axis. The Cd(II) centers are doubly bridged through SeCN (infinite rail) along a-axis and singly bridged by hmt (two-step rung) along c-axis, having cadmium centers with CdSe2N3O and CdSe2N4 chromophores. The adjacent chains through H-bonding between coordinated water and hmt, and (SeSe)-Se-... interaction are extended to 2D supramolecular architecture.