Effective livelihood adaptation to climate change disturbance: scale dimensions of practice in Mozambique

Natural resource-dependent societies in developing countries are facing increased pressures linked to global climate change. While social-ecological systems evolve to accommodate variability, there is growing evidence that changes in drought, storm and flood extremes are increasing exposure of currently vulnerable populations. In many countries in Africa, these pressures are compounded by disruption to institutions and variability in livelihoods and income. The interactions of both rapid and slow onset livelihood disturbance contribute to enduring poverty and slow processes of rural livelihood renewal across a complex landscape. We explore cross-scale dynamics in coping and adaptation response, drawing on qualitative data from a case study in Mozambique. The research characterises the engagements across multiple institutional scales and the types of agents involved, providing insight into emergent conditions for adaptation to climate change in rural economies, The analysis explores local responses to climate shocks, food security and poverty reduction, through informal institutions, forms of livelihood diversification and collective land-use systems that allow reciprocity, flexibility and the ability to buffer shocks. However, the analysis shows that agricultural initiatives have helped to facilitate effective livelihood renewal, through the reorganisation of social institutions and opportunities for communication, innovation and micro-credit. Although there are challenges to mainstreaming adaptation at different scales, this research shows why it is critical to assess how policies can protect conditions for emergence of livelihood transformation. (C) 2008 Elsevier Ltd. All rights reserved.

Year to year variation in the small scale distribution of shuttle mosses

A detailed spore investigation of spore release and dispersal from an isolated colony of Phascum cuspidatum Hedw. indicated that approximately 98% of the spores originally present remained within the colony. The spatial distribution of colonies of P.cuspidatum and Pottia truncata (Hedw.) Fürer. in relation to those of the previous year was investigated by mapping the occurrence of colonies in five permanent quadrats for each species during two successive years. Phascum cuspidatum reoccurred in three quadrats during the second year, and P. truncata in only one, in the latter case apparently due to invasion by other mosses, principally Barbula hornschuchiana Schultz. A substantial proportion of the second year colonies overlapped in position with the first year colonies, particularly in P.cuspidatum. The results are discussed in relation to data on spore dispersal and other aspects of the life-history of these annual or short-lived shuttle mosses.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model

1.There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6.Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

Evaluation of the inclusion of a mixture of organic acids or lactulose into the feed of pigs experimentally challenged with Salmonella Typhimurium

A mixture of organic acids and lactulose for preventing or reducing colonization of the gut by Salmonella Typhimurium was evaluated in pigs. A total of 63 4-week-old commercial piglets were randomly distributed into three different experimental dietary groups: a plain diet without additives (PD) and the same diet supplemented with either 0.4% (w/v) formic acid and 0.4% lactic acid (w/v) (AC) or 1% (w/v) lactulose (LC). After 7 days of adaptation, two-thirds of the pigs (14 from each diet) were challenged with a 2-mL oral dose of 10(8) CFU/mL of Salmonella Typhimurium, leaving the remaining animals unchallenged (UC). After 4 and 10 days post-challenge, pigs were euthanized and the ileum and caecum content were aseptically sampled to (a) quantify lactic, formic, and short-chain fatty acids (SCFA), (b) quantify bacterial populations and Salmonella by fluorescence in situ hybridization and (c) qualitatively analyse bacterial populations through denaturing gradient gel electrophoresis (DGGE). Modification of fermentation products and counts of some of the bacterial groups analysed in the challenged pigs receiving the treatments AC and LC were minimal. Treatments only influenced the bacterial diversity after 10 days post-challenge, with AC generating a lower number of DGGE bands than UC(P < 0.05). Neither the inclusion of a mixture of 0.4% (w/v) formic and 0.4% (w/v) lactic acids nor of 1% (w/v) lactulose in the feed influenced numbers of Salmonella in the ileum and caecum of experimentally challenged pigs. (C) 2009 Elsevier B.V. All rights reserved.

MIMO Wiener model identification for large scale fading of wireless mobile communications links

The large scale fading of wireless mobile communications links is modelled assuming the mobile receiver motion is described by a dynamic linear system in state-space. The geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A Wiener system subspace identification algorithm in conjunction with polynomial regression is used to identify a model from time-domain estimates of the field intensity assuming a multitude of emitters and an antenna array at the receiver end.

A mixture of experts network structure construction algorithm for modelling and control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.

Neurofuzzy mixture of experts network parallel learning and model construction algorithms

A connection between a fuzzy neural network model with the mixture of experts network (MEN) modelling approach is established. Based on this linkage, two new neuro-fuzzy MEN construction algorithms are proposed to overcome the curse of dimensionality that is inherent in the majority of associative memory networks and/or other rule based systems. The first construction algorithm employs a function selection manager module in an MEN system. The second construction algorithm is based on a new parallel learning algorithm in which each model rule is trained independently, for which the parameter convergence property of the new learning method is established. As with the first approach, an expert selection criterion is utilised in this algorithm. These two construction methods are equivalent in their effectiveness in overcoming the curse of dimensionality by reducing the dimensionality of the regression vector, but the latter has the additional computational advantage of parallel processing. The proposed algorithms are analysed for effectiveness followed by numerical examples to illustrate their efficacy for some difficult data based modelling problems.

Effect of linseed oil and fish oil alone or as an equal mixture of ruminal fatty acid metabolism in growing steers fed maize silage-based diets

Based on the potential benefits to human health there is interest in increasing 18:3n-3, 20:5n-3, 22:6n-6, and cis-9,trans-11 conjugated linoleic acid (CLA) in ruminant foods. Four Aberdeen Angus steers (406 ± 8.2 kg BW) fitted with rumen and duodenal cannulae were used in a 4 x 4 Latin square experiment with 21 d periods to examine the potential of fish oil (FO) and linseed oil (LO) in the diet to increase ruminal outflow of trans-11 18:1 and total n-3 polyunsaturated fatty acids (PUFA) in growing cattle. Treatments consisted of a control diet (60:40; forage:concentrate ratio, on a DM basis, respectively) based on maize silage, or the same basal ration containing 30 g/kg DM of FO, LO or a mixture (1:1, w/w) of FO and LO (LFO). Diets were offered as total mixed rations and fed at a rate of 85 g DM/kg BW0.75/d. Oils had no effect (P = 0.52) on DM intake. Linseed oil had no effect (P > 0.05) on ruminal pH or VFA concentrations, while FO shifted rumen fermentation towards propionate at the expense of acetate. Compared with the control, LO increased (P < 0.05) 18:0, cis 18:1 (Δ9, 12-15), trans 18:1 (Δ4-9, 11-16), trans 18:2, geometric isomers of ∆9,11, ∆11,13, and ∆13,15 CLA, trans-8,cis-10 CLA, trans-10,trans-12 CLA, trans-12,trans-14 CLA, and 18:3n-3 flow at the duodenum. Inclusion of FO in the diet resulted in higher (P < 0.05) flows of cis-9 16:1, trans 16:1 (Δ6-13), cis 18:1 (Δ9, 11, and 13), trans 18:1 (Δ6-15), trans 18:2, 20:5n-3, 22:5n-3, and 22:6n-3, and lowered (P < 0.001) 18:0 at the duodenum relative to the control. For most fatty acids at the duodenum responses to LFO were intermediate of FO and LO. However, LFO resulted in higher (P = 0.04) flows of total trans 18:1 than LO and increased (P < 0.01) trans-6 16:1 and trans-12 18:1 at the duodenum compared with FO or LO. Biohydrogenation of cis-9 18:1 and 18:2n-6 in the rumen was independent of treatment, but both FO and LO increased (P < 0.001) the extent of 18:3n-3 biohydrogenation compared with the control. Ruminal 18:3n-3 biohydrogenation was higher (P < 0.001) for LO and LFO than FO, while biohydrogenation of 20:5n-3 and 22:6n-3 in the rumen was marginally lower (P = 0.05) for LFO than FO. In conclusion, LO and FO at 30 g/kg DM altered the biohydrogenation of unsaturated fatty acids in the rumen causing an increase in the flow of specific intermediates at the duodenum, but the potential of these oils fed alone or as a mixture to increase n-3 PUFA at the duodenum in cattle appears limited.

Genome scale reconstruction of a Salmonella metabolic model comparison of similarity and differences with a commensal Escherichia coli strain

Salmonella are closely related to commensal Escherichia coli but have gained virulence factors enabling them to behave as enteric pathogens. Less well studied are the similarities and differences that exist between the metabolic properties of these organisms that may contribute toward niche adaptation of Salmonella pathogens. To address this, we have constructed a genome scale Salmonella metabolic model (iMA945). The model comprises 945 open reading frames or genes, 1964 reactions, and 1036 metabolites. There was significant overlap with genes present in E. coli MG1655 model iAF1260. In silico growth predictions were simulated using the model on different carbon, nitrogen, phosphorous, and sulfur sources. These were compared with substrate utilization data gathered from high throughput phenotyping microarrays revealing good agreement. Of the compounds tested, the majority were utilizable by both Salmonella and E. coli. Nevertheless a number of differences were identified both between Salmonella and E. coli and also within the Salmonella strains included. These differences provide valuable insight into differences between a commensal and a closely related pathogen and within different pathogenic strains opening new avenues for future explorations.

Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation

Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.

Scale sensitivity of drivers of environmental change across Europe

The development of effective environmental management plans and policies requires a sound understanding of the driving forces involved in shaping and altering the structure and function of ecosystems. However, driving forces, especially anthropogenic ones, are defined and operate at multiple administrative levels, which do not always match ecological scales. This paper presents an innovative methodology of analysing drivers of change by developing a typology of scale sensitivity of drivers that classifies and describes the way they operate across multiple administrative levels. Scale sensitivity varies considerably among drivers, which can be classified into five broad categories depending on the response of ‘evenness’ and ‘intensity change’ when moving across administrative levels. Indirect drivers tend to show low scale sensitivity, whereas direct drivers show high scale sensitivity, as they operate in a non-linear way across the administrative scale. Thus policies addressing direct drivers of change, in particular, need to take scale into consideration during their formulation. Moreover, such policies must have a strong spatial focus, which can be achieved either by encouraging local–regional policy making or by introducing high flexibility in (inter)national policies to accommodate increased differentiation at lower administrative levels. High quality data is available for several drivers, however, the availability of consistent data at all levels for non-anthropogenic drivers is a major constraint to mapping and assessing their scale sensitivity. This lack of data may hinder effective policy making for environmental management, since it restricts the ability to fully account for scale sensitivity of natural drivers in policy design.

Synoptic scale disturbances of the Indian Summer Monsoon as simulated in a high resolution climate model

Hamburg atmospheric general circulation model ECHAM3 at T106 resolution (1.125' lat.Aon.) has considerable skill in reproducing the observed seasonal reversal of mean sea level pressure, the location of the summer heat low as well as the position of the monsoon trough over the Indian subcontinent. The present-day climate and its seasonal cycle are realistically simulated by the model over this region. The model simulates the structure, intensity, frequency, movement and lifetime of monsoon depressions remarkably well. The number of monsoon depressions/storms simulated by the model in a year ranged from 5 to 12 with an average frequency of 8.4 yr-', not significantly different from the observed climatology. The model also simulates the interannual variability in the formation of depressions over the north Bay of Bengal during the summer monsoon season. In the warmer atmosphere under doubled CO2 conditions, the number of monsoon depressions/cyclonic storms forming in Indian seas in a year ranged from 5 to 11 with an average frequency of 7.6 yr-', not significantly different from those inferred in the control run of the model. However, under doubled CO2 conditions, fewer depressions formed in the month of June. Neither the lowest central pressure nor the maximum wind speed changes appreciably in monsoon depressions identified under simulated enhanced greenhouse conditions. The analysis suggests there will be no significant changes in the number and intensity of monsoon depressions in a warmer atmosphere.