Modeling small-scale dairy farms in central Mexico using multi-criteria programming

Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multicriteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, rye-grass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.

Factors influencing adoption of improved grassland management by small-scale dairy farmers in central Mexico and the implications for future research on smallholder adoption in developing countries

There have been limited recent advances in understanding of what influences uptake of innovations despite the current international focus on smallholder agriculture as a means of achieving food security and rural development. This paper provides a rigorous study of factors influencing adoption by smallholders in central Mexico and builds on findings to identify a broad approach to significantly improve research on and understanding of factors influencing adoption by smallholders in developing countries. Small-scale dairy systems play an important role in providing income, employment and nutrition in the highlands of central Mexico. A wide variety of practices and technologies have been promoted by the government public services to increase milk production and economic efficiency, but there have been very low levels of uptake of most innovations, with the exception of improving grassland through introduction of grass varieties together with management practices. A detailed study was conducted with 80 farmers who are already engaged with the use of this innovation to better understand the process of adoption and identify socioeconomic and farm variables, cognitive (beliefs), and social–psychological (social norms) factors associated with farmers' use of improved grassland. The Theory of Reasoned Action (TRA) was used as a theoretical framework and Spearman Rank Order correlation was conducted to analyse the data. Most farmers (92.5%) revealed strong intention to continue to use improved grassland (which requires active management and investment of resources) for the next 12 months; whereas 7.5% of farmers were undecided and showed weak intention, which was associated with farmers whose main income was from non-farm activities as well as with farmers who had only recently started using improved grassland. Despite farmers' experience of using improved grassland (mean of 18 years) farmers' intentions to continue to adopt it was influenced almost as much by salient referents (mainly male relatives) as by their own attitudes. The hitherto unnoticed longevity of the role social referents play in adoption decisions is an important finding and has implications for further research and for the design of extension approaches. The study demonstrates the value and importance of using TRA or TPB approaches to understand social cognitive (beliefs) and social–psychological (social norms) factors in the study of adoption. However, other factors influencing adoption processes need to be included to provide fuller understanding. An approach that would enable this, and the development of more generalisable findings than from location specific case studies, and contribute to broader conceptualisation, is proposed.

Diversity for resilience : multi-scale application of agro-ecology

The integration of ecological principles into agricultural systems presents major opportunities for spreading risk at the crop and farm scale. This paper presents mechanisms by which diversity at several scales within the farming system can increase the stability of production. Diversity of above- and below-ground biota, but also genetic and phenotypic diversity within crops, has an essential role in safeguarding farm production. Novel mixtures of legume-grass leys have been shown to potentially provide significant benefits for pollinator and decomposer ecosystem services but to realise the greatest improvements carefully tailored farm management is needed such as mowing or grazing time, and the type and depth of cutivation. Complex farmland landscapes such as agroforestry systems have the potential to support pollinator abundance and diversity and spread risk across production enterprises. At the crop level, early results indicate that the vulnerability of pollen development, flowering and early grain set to abiotic stress can be ameliorated by managing flowering time through genotypic selection, and through the buffering effects of pollinators. Finally, the risk of sub-optimal quality in cereals can be mitigated through integration of near isogenic lines selected to escape specific abiotic stress events. We conclude that genotypic, phenotypic and community diversity can all be increased at multiple scales to enhance resilience in agricultural systems.

Using Distributed Temperature Sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.

Sensitivity of large-scale atmospheric analyses to humidity observations and its impact on the global water cycle and tropical and extratropical weather systems in ERA40

Reanalysis data obtained from data assimilation are increasingly used for diagnostic studies of the general circulation of the atmosphere, for the validation of modelling experiments and for estimating energy and water fluxes between the Earth surface and the atmosphere. Because fluxes are not specifically observed, but determined by the data assimilation system, they are not only influenced by the utilized observations but also by model physics and dynamics and by the assimilation method. In order to better understand the relative importance of humidity observations for the determination of the hydrological cycle, in this paper we describe an assimilation experiment using the ERA40 reanalysis system where all humidity data have been excluded from the observational data base. The surprising result is that the model, driven by the time evolution of wind, temperature and surface pressure, is able to almost completely reconstitute the large-scale hydrological cycle of the control assimilation without the use of any humidity data. In addition, analysis of the individual weather systems in the extratropics and tropics using an objective feature tracking analysis indicates that the humidity data have very little impact on these systems. We include a discussion of these results and possible consequences for the way moisture information is assimilated, as well as the potential consequences for the design of observing systems for climate monitoring. It is further suggested, with support from a simple assimilation study with another model, that model physics and dynamics play a decisive role for the hydrological cycle, stressing the need to better understand these aspects of model parametrization. .

Climate response to basin-scale warming and cooling of the North Atlantic Ocean

Using experiments with an atmospheric general circulation model, the climate impacts of a basin-scale warming or cooling of the North Atlantic Ocean are investigated. Multidecadal fluctuations with this pattern were observed during the twentieth century, and similar variations--but with larger amplitude--are believed to have occurred in the more distant past. It is found that in all seasons the response to warming the North Atlantic is strongest, in the sense of highest signal-to-noise ratio, in the Tropics. However there is a large seasonal cycle in the climate impacts. The strongest response is found in boreal summer and is associated with suppressed precipitation and elevated temperatures over the lower-latitude parts of North and South America. In August­-September-­October there is a significant reduction in the vertical shear in the main development region for Atlantic hurricanes. In winter and spring, temperature anomalies over land in the extratropics are governed by dynamical changes in circulation rather than simply reflecting a thermodynamic response to the warming or cooling of the ocean. The tropical climate response is primarily forced by the tropical SST anomalies, and the major features are in line with simple models of the tropical circulation response to diabatic heating anomalies. The extratropical climate response is influenced both by tropical and higher-latitude SST anomalies and exhibits nonlinear sensitivity to the sign of the SST forcing. Comparisons with multidecadal changes in sea level pressure observed in the twentieth century support the conclusion that the impact of North Atlantic SST change is most important in summer, but also suggest a significant influence in lower latitudes in autumn and winter. Significant climate impacts are not restricted to the Atlantic basin, implying that the Atlantic Ocean could be an important driver of global decadal variability. The strongest remote impacts are found to occur in the tropical Pacific region in June­-August and September­-November. Surface anomalies in this region have the potential to excite coupled ocean­atmosphere feedbacks, which are likely to play an important role in shaping the ultimate climate response.

Preferred structures in large-scale circulation and the effect of doubling greenhouse gas concentration in HadCM3

Preferred structures in the surface pressure variability are investigated in and compared between two 100-year simulations of the Hadley Centre climate model HadCM3. In the first (control) simulation, the model is forced with pre-industrial carbon dioxide concentration (1×CO2) and in the second simulation the model is forced with doubled CO2 concentration (2×CO2). Daily winter (December-January-February) surface pressures over the Northern Hemisphere are analysed. The identification of preferred patterns is addressed using multivariate mixture models. For the control simulation, two significant flow regimes are obtained at 5% and 2.5% significance levels within the state space spanned by the leading two principal components. They show a high pressure centre over the North Pacific/Aleutian Islands associated with a low pressure centre over the North Atlantic, and its reverse. For the 2×CO2 simulation, no such behaviour is obtained. At higher-dimensional state space, flow patterns are obtained from both simulations. They are found to be significant at the 1% level for the control simulation and at the 2.5% level for the 2×CO2 simulation. Hence under CO2 doubling, regime behaviour in the large-scale wave dynamics weakens. Doubling greenhouse gas concentration affects both the frequency of occurrence of regimes and also the pattern structures. The less frequent regime becomes amplified and the more frequent regime weakens. The largest change is observed over the Pacific where a significant deepening of the Aleutian low is obtained under CO2 doubling.

Large-scale context for the UK floods in summer 2007

This paper shows how the rainfall distribution over the UK, in the three major events on 13-15 June, 25 June and 20 July 2007, was related to troughs in the upper-level flow, and investigates the relationship of these features to a persistent large-scale flow pattern which extended around the northern hemisphere and its possible origins. Remote influences can be mediated by the propagation of large-scale atmospheric waves across the northern hemisphere and also by the origins of the air-masses that are wrapped into the developing weather systems delivering the rain to the UK. These dynamical influences are examined using analyses and forecasts produced by a range of atmospheric models.

Can the dynamical impact of the stratosphere on the troposphere be described by large-scale adjustment to the stratospheric PV distribution?

Recent numerical experiments have demonstrated that the state of the stratosphere has a dynamical impact on the state of the troposphere. To account for such an effect, a number of mechanisms have been proposed in the literature, all of which amount to a large-scale adjustment of the troposphere to potential vorticity (PV) anomalies in the stratosphere. This paper analyses whether a simple PV adjustment suffices to explain the actual dynamical response of the troposphere to the state of the stratosphere, the actual response being determined by ensembles of numerical experiments run with an atmospheric general-circulation model. For this purpose, a new PV inverter is developed. It is shown that the simple PV adjustment hypothesis is inadequate. PV anomalies in the stratosphere induce, by inversion, flow anomalies in the troposphere that do not coincide spatially with the tropospheric changes determined by the numerical experiments. Moreover, the tropospheric anomalies induced by PV inversion are on a larger scale than the changes found in the numerical experiments, which are linked to the Atlantic and Pacific storm-tracks. These findings imply that the impact of the stratospheric state on the troposphere is manifested through the impact on individual synoptic-scale systems and their self-organization in the storm-tracks. Changes in these weather systems in the troposphere are not merely synoptic-scale noise on a larger scale tropospheric response, but an integral part of the mechanism by which the state of the stratosphere impacts that of the troposphere.