Mats Høglind

Research Professor

(+47) 404 75 391
mats.hoglind@nibio.no

Place
Særheim

Visiting address
Postvegen 213, NO-4353 Klepp stasjon

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Abstract

1. Grassland diversity can support sustainable intensification of grassland production through increased yields, reduced inputs and limited weed invasion. We report the effects of diversity on weed suppression from 3 years of a 31-site continental-scale field experiment. 2. At each site, 15 grassland communities comprising four monocultures and 11 four-species mixtures based on a wide range of species' proportions were sown at two densities and managed by cutting. Forage species were selected according to two crossed functional traits, “method of nitrogen acquisition” and “pattern of temporal development”. 3. Across sites, years and sown densities, annual weed biomass in mixtures and monocultures was 0.5 and 2.0 t DM ha−1 (7% and 33% of total biomass respectively). Over 95% of mixtures had weed biomass lower than the average of monocultures, and in two-thirds of cases, lower than in the most suppressive monoculture (transgressive suppression). Suppression was significantly transgressive for 58% of site-years. Transgressive suppression by mixtures was maintained across years, independent of site productivity. 4. Based on models, average weed biomass in mixture over the whole experiment was 52% less (95% confidence interval: 30%–75%) than in the most suppressive monoculture. Transgressive suppression of weed biomass was significant at each year across all mixtures and for each mixture. 5. Weed biomass was consistently low across all mixtures and years and was in some cases significantly but not largely different from that in the equiproportional mixture. The average variability (standard deviation) of annual weed biomass within a site was much lower for mixtures (0.42) than for monocultures (1.77). 6. Synthesis and applications. Weed invasion can be diminished through a combination of forage species selected for complementarity and persistence traits in systems designed to reduce reliance on fertiliser nitrogen. In this study, effects of diversity on weed suppression were consistently strong across mixtures varying widely in species' proportions and over time. The level of weed biomass did not vary greatly across mixtures varying widely in proportions of sown species. These diversity benefits in intensively managed grasslands are relevant for the sustainable intensification of agriculture and, importantly, are achievable through practical farm-scale actions.

Abstract

Farmers are exposed to climate change and uncertainty about how that change will develop. As farm incomes, in Norway and elsewhere, greatly depend on government subsidies, the risk of a policy change constitutes an additional uncertainty source. Hence, climate and policy uncertainty could substantially impact agricultural production and farm income. However, these sources of uncertainty have, so far, rarely been combined in food production analyses. The aim of this study was to determine the effects of a combination of policy and climate uncertainty on agricultural production, land use, and social welfare in Norway. Output yield distributions of spring wheat and timothy, a major forage grass, from simulations with the weatherdriven crop models, CSM-CERES-Wheat and, LINGRA, were processed in the a stochastic version Jordmod, a price-endogenous spatial economic sector model of the Norwegian agriculture. To account for potential effects of climate uncertainty within a given future greenhouse gas emission scenario on farm profitability, effects on conditions that represented the projected climate for 2050 under the emission scenario A1B from the 4th assessment report of the Intergovernmental Panel on Climate Change and four Global Climate Models (GCM) was investigated. The uncertainty about the level of payment rates at the time farmers make their management decisions was handled by varying the distribution of payment rates applied in the Jordmod model. These changes were based on the change in the overall level of agricultural support in the past. Three uncertainty scenarios were developed and tested: one with climate change uncertainty, another with payment rate uncertainty, and a third where both types of uncertainty were combined. The three scenarios were compared with results from a deterministic scenario where crop yields and payment rates were constant. Climate change resulted in on average 9% lower cereal production, unchanged grass production and more volatile crop yield as well as 4% higher farm incomes on average compared to the deterministic scenario. The scenario with a combination of climate change and policy uncertainty increased the mean farm income more than a scenario with only one source of uncertainty. On the other hand, land use and farm labour were negatively affected under these conditions compared to the deterministic case. Highlighting the potential influence of climate change and policy uncertainty on the performance of the farm sector our results underline the potential error in neglecting either of these two uncertainties in studies of agricultural production, land use and welfare.

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Abstract

There is a scientific consensus that the future climate change will affect grass and crop dry matter (DM) yields. Such yield changes may entail alterations to farm management practices to fulfill the feed requirements and reduce the farm greenhouse gas (GHG) emissions from dairy farms. While a large number of studies have focused on the impacts of projected climate change on a single farm output (e.g. GHG emissions or economic performance), several attempts have been made to combine bio-economic systems models with GHG accounting frameworks. In this study, we aimed to determine the physical impacts of future climate scenarios on grass and wheat DM yields, and demonstrate the effects such changes in future feed supply may have on farm GHG emissions and decision-making processes. For this purpose, we combined four models: BASGRA and CSM-CERESWheat models for simulating forage grass DM and wheat DM grain yields respectively; HolosNor for estimating the farm GHG emissions; and JORDMOD for calculating the impacts of changes in the climate and management on land use and farm economics. Four locations, with varying climate and soil conditions were included in the study: south-east Norway, south-west Norway, central Norway and northern Norway. Simulations were carried out for baseline (1961–1990) and future (2046–2065) climate conditions (projections based on two global climate models and the Special Report on Emissions Scenarios (SRES) A1B GHG emission scenario), and for production conditions with and without a milk quota. The GHG emissions intensities (kilogram carbon dioxide equivalent: kgCO2e emissions per kg fat and protein corrected milk: FPCM) varied between 0.8 kg and 1.23 kg CO2e (kg FPCM)−1 , with the lowest and highest emissions found in central Norway and south-east Norway, respectively. Emission intensities were generally lower under future compared to baseline conditions due mainly to higher future milk yields and to some extent to higher crop yields. The median seasonal aboveground timothy grass yield varied between 11,000 kg and 16,000 kg DM ha−1 and was higher in all projected future climate conditions than in the baseline. The spring wheat grain DM yields simulated for the same weather conditions within each climate projection varied between 2200 kg and 6800 kg DM ha−1 . Similarly, the farm profitability as expressed by total national land rents varied between 1900 million Norwegian krone (NOK) for median yields under baseline climate conditions up to 3900 million NOK for median yield under future projected climate conditions.

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1. Increased species diversity promotes ecosystem function; however, the dynamics of multi-speciesgrassland systems over time and their role in sustaining higher yields generated by increased diver-sity are still poorly understood. We investigated the development of species’ relative abundances ingrassland mixtures over 3 years to identify drivers of diversity change and their links to yield diver-sity effects.2. A continental-scale field experiment was conducted at 31 sites using 11 different four-speci esmixtures each sown at two seed abundances. The four species consisted of two grasses and two legumes, of which one was fast establishing and the other temporally persistent. We modelledthe dynamics of the four-species mixtures, and tested associations with diversity effects on yield.3. We found that species’ dynamics were primarily driven by differences in the relative growth rates(RGRs) of competing species, and secondarily by density dependence and climate. The temporallypersistent grass species typically had the highest RGRs and hence became dominant over time. Den-sity dependence sometimes induced stabilising processes on the dominant species and inhibitedshifts to monoculture. Legumes persisted at most sites at low or medium abundances and persistencewas improved at sites with higher annual minimum temperature.4. Significant diver sity effects were present at the majority of sites in all years and the strength ofdiversity effects was improved with higher legume abundance in the previous year. Observed diver-sity effects, when legumes had declined, may be due to (i) important effects of legumes even at lowabundance, (ii) interaction between the two grass species or (iii) a store of N because of previouspresence of legumes.5. Synthesis. Alongside major compositional changes driven by RGR differences , diversity effectswere observed at most sites, albeit at reduced strength as legumes declined. This evidence stronglysupports the sowing of multi-species mixtures that include legumes over the long-standing practiceof sowing grass monocultures. Careful and strategic selection of the identity of the species used inmixtures is suggested to facilitate the maintenance of species diversity and especially persistence oflegumes over tim e, and to preser ve the strength of yield increases associated with diversity.

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Abstract

In Scandinavia, pasture for dairy herds with automatic milking (AM) is frequently offered purely for exercise and recreation, rather than as a feed-source. In the present study, cows in an AM-system with 12 h nightly outdoor-access from summer solstice until mid-September were offered either fresh production pasture (treatment P; ≥15 kg dry matter (DM) cow‑1 nightly, combined with 6 kg DM grass silage daytime) or exercise pasture (treatment E; <1 kg DM cow‑1 combined with ad libitum silage allowance day and night). Treatment showed a significant effect on milk yield (P:31.3, E:33.0 kg, P=0.05), and a tendency for milking frequency (P:2.25, E: 2.37 milkings × day‑1, P=0.06). Group P spent more time outdoors than E, 4.0 and 3.2 h, respectively (P<0.001). Cows in P grazed approximately 2.5 h throughout the season, while E grazed less overall, 0.6 h (P<0.001) and decreased their time spent grazing over the season (1.0 to 0.3 h). In conclusion, night-time pasture is poorly exploited by cows, irrespective of the quantity of both of pasture and silage that are available.

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Proper parameterisation and quantification of model uncertainty are two essential tasks in improvement and assessment of model performance. Bayesian calibration is a method that combines both tasks by quantifying probability distributions for model parameters and outputs. However, the method is rarely applied to complex models because of its high computational demand when used with high-dimensional parameter spaces. We therefore combined Bayesian calibration with sensitivity analysis, using the screening method by Morris (1991), in order to reduce model complexity by fixing parameters to which model output was only weakly sensitive to a nominal value. Further, the robustness of the model with respect to reduction in the number of free parameters were examined according to model discrepancy and output uncertainty. The process-based grassland model BASGRA was examined in the present study on two sites in Norway and in Germany, for two grass species (Phleum pratense and Arrhenatherum elatius). According to this study, a reduction of free model parameters from 66 to 45 was possible. The sensitivity analysis showed that the parameters to be fixed were consistent across sites (which differed in climate and soil conditions), while model calibration had to be performed separately for each combination of site and species. The output uncertainty decreased slightly, but still covered the field observations of aboveground biomass. Considering the training data, the mean square error for both the 66 and the 45 parameter model was dominated by errors in timing (phase shift), whereas no general pattern was found in errors when using the validation data. Stronger model reduction should be avoided, as the error term increased and output uncertainty was underestimated.

Abstract

Simulation models are widely used to assess the impact of climate change on crop production and adaptation options, but few model comparisons have been done to assess uncertainties in the simulation results of forage grass models. The aim of this study was to compare the performance of three models (BASGRA, CATIMO, and STICS) to simulate the dry matter yield of the first and second cut of timothy (Phleum pratense L.) using observed field data from a wide range of climatic conditions, cultivars, soil types and crop management practices that are associated with timothy production in its main production regions in Canada and Northern Europe. The performance of the models was assessed with both cultivarspecific and non-cultivar-specific (generic) calibrations. The results showed the strengths and weaknesses of different modelling approaches and the magnitude of uncertainty related to simulated timothy grass yield. Model results were sensitive to calibrations applied.

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Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change.

Abstract

LEgislation in Sweden and Norway requires that Dairy cattle have outdoor acess in summertime. PAsture utilization can be challenging with high-yielding cattle abd karge herd-sizes. Tehrefore, many farmers choose to offer their cows Access to an exercise- and recreation area only, rather than a full Production pasture. However, is an exercise paddoc as attractive as Production pasture for the cow? We compared part-time production and exercise grazing in an automated milking system, with outdoor acess in the morning (4.5 h) and the evening (4 h). The Production pasture group (P)was offered fresh Production pasture daily and given a Limited silage ration night-time. The exercise pasture group (E) was given Access to a small exercise paddoc and were fed silage ad libitum 24 hours. Milk yield dit not differ significantly: 36.1 kg for P and 36.0 kg for E. However, behaviour differed, with 5.5 (P) and 2.6 h(E) spent outdoors, and 3.7 h (P) and 0.6 h (E) grazing time. In conclusion, while milk-yields were similar between the Groups, lower ammounts of supplementary feed were needed for cows on treatment P, who also spent longer hours putdoors and grazing.

Abstract

Legislation in Sweden and Norway requires that Dairy cattle have outdoor acess in summertime. Pasture utilization can be challenging with high-yielding cattle abd karge herd-sizes. Tehrefore, many farmers choose to offer their cows Access to an exercise- and recreation area only, rather than a full Production pasture. However, is an exercise paddoc as attractive as Production pasture for the cow? We compared part-time production and exercise grazing in an automated milking system, with outdoor acess in the morning (4.5 h) and the evening (4 h). The Production pasture group (P)was offered fresh Production pasture daily and given a Limited silage ration night-time. The exercise pasture group (E) was given Access to a small exercise paddoc and were fed silage ad libitum 24 hours. Milk yield dit not differ significantly: 36.1 kg for P and 36.0 kg for E. However, behaviour differed, with 5.5 (P) and 2.6 h(E) spent outdoors, and 3.7 h (P) and 0.6 h (E) grazing time. In conclusion, while milk-yields were similar between the Groups, lower ammounts of supplementary feed were needed for cows on treatment P, who also spent longer hours putdoors and grazing.

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Abstract

Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers andplant breeders in addressing the challenges of climate change by simulating alternative roads of adap-tation. They can also provide management decision support under current conditions. A drawback ofexisting grass models is that they do not take into account the effect of winter stresses, limiting theiruse for full-year simulations in areas where winter survival is a key factor for yield security. Here, wepresent a novel full-year PBM for grassland named BASGRA. It was developed by combining the LIN-GRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winterprocesses. We present the model and show how it was parameterized for timothy (Phleum pratense L.),the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRAsimulates the processes taking place in the sward during the transition from summer to winter, includ-ing growth cessation and gradual cold hardening, and functions for simulating plant injury due to lowtemperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data fromfive different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudesfrom 59◦to 70◦N) and soil conditions. The total dataset included 11 variables, notably above-ground drymatter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used inthe calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector fromthe single, Bayesian calibration, nearly all measured variables were simulated to an overall normalizedroot mean squared error (NRMSE) < 0.5. For many site × experiment combinations, NRMSE was <0.3. Thetemporal dynamics were captured well for most variables, as evaluated by comparing simulated timecourses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robustmodel, allowing for simulation of growth and several important underlying processes with acceptableaccuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be testedfurther using independent data from a wide range of growing conditions. Finally we show an exampleof application of the model, comparing overwintering risks in two climatically different sites, and dis-cuss future model applications. Further development work should include improved simulation of thedynamics of C reserves, and validation of winter tiller dynamics against independent data.

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Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway.

Abstract

Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Østfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input.

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Norwegian agriculture is mainly dominated by grass-based milk and livestock production, so winter damage to overwintering grasses may have large economic consequences. We assessed the impact of climate change on the winter survival of timothy (Phleum pratense L) and perennial ryegrass (Lolium perenne L) under Norwegian conditions using agroclimatic indices and a simulation model of frost tolerance. This study was based on locally adjusted future climate scenarios (two for the period 2071-2100; one for the period 2020-2049) for six important agricultural regions, represented by one location each. We proposed and validated a rough way to estimate the daily minimum air temperatures from scenario data. compared with the control period 1961-1990, the future hardening period will be shortened by up to 21 days. As a consequence, the modelled maximum frost tolerance is expected to be reduced by up to 3.9 degrees C and 1.9 degrees C for timothy and perennial ryegrass, respectively, under the warmest scenario. In spite of this reduction, the plants are expected to be hardy enough to withstand the predicted autumn frosts, and we also expect a general reduction in the risk of winter frost injuries. The plant data available to this study suggest that agroclimatic indices developed for Canadian conditions can be useful for assessing the hardening status in timothy and perennial ryegrass. However, such indices are less suitable for assessing the risk of plant injury related to frost and ice encasement in Norway, since they do not account for the dynamics of cold adaptation. Although less snow is expected, in most cases this will not be accompanied by an increase in the risk of ice encasement injuries. However, a slight increase in the number of ice encasement events was predicted for one location. An earlier start of growth was predicted for all locations, accompanied at one coastal location by a slightly increased predicted risk of spring frosts. There is little risk of winter injuries related to frost and ice encasement in the hardier grass species timothy. The better overwintering conditions in general indicate that it will be possible to grow perennial ryegrass in areas where it is not grown today, provided the risk of fungal diseases does not increase. (C) 2010 Elsevier B.V. All rights reserved.

Abstract

Scenarios of climate changes indicate longer and more frequent spells of mild weather during winter in northern latitudes. De-hardening in perennial grasses could increase the risk of frost kill. In this study, the resistance to de-hardening of different grass species and cultivars was examined, and whether the resistance changes during winter or between years, was tested. In Experiment 1, two cultivars of timothy (Phleum pratense L.) and perennial ryegrass (Lolium perenne L.) of contrasting winter hardiness were grown under ambient winter conditions, transferred from the field in January and April 2006 to the laboratory for 9 d with controlled de-hardening conditions of 3°C, 9°C and 15°C. The timothy cultivars were tested at 3°C, 6°C and 9°C in a similar experiment (Experiment 2) in January 2007. De-hardening, measured as decrease in frost tolerance (LT50), was less in timothy than in perennial ryegrass and increased with increasing temperatures. The northern winter-hardy cultivar Engmo of timothy de-hardened more rapidly than the less-hardy cultivar Grindstad, but had higher initial frost tolerance in both experiments, whereas there was less difference between cultivars of perennial ryegrass in Experiment 1. Cultivar Grindstad of timothy lost all hardiness in early spring at all temperatures, whereas cultivar Engmo maintained some hardiness at 3°C. Cultivar Engmo de-hardened at a lower rate in 2007 than in 2006, in spite of similar frost tolerance at the start of de-hardening treatment in both years. This indicates that the rate of de-hardening was controlled by factors additional to the initial frost tolerance and that autumn weather conditions might be important for the resistance to de-hardening.

Abstract

Scenarios of climate changes indicate longer and more frequent spells of mild weather during winter in northern latitudes. De-hardening in perennial grasses could increase the risk of frost kill. In this study, the resistance to de-hardening of different grass species and cultivars was examined, and whether the resistance changes during winter or between years, was tested. In Experiment 1, two cultivars of timothy (Phleum pratense L.) and perennial ryegrass (Lolium perenne L.) of contrasting winter hardiness were grown under ambient winter conditions, transferred from the field in January and April 2006 to the laboratory for 9 d with controlled de-hardening conditions of 3°C, 9°C and 15°C. The timothy cultivars were tested at 3°C, 6°C and 9°C in a similar experiment (Experiment 2) in January 2007. De-hardening, measured as decrease in frost tolerance (LT50), was less in timothy than in perennial ryegrass and increased with increasing temperatures. The northern winter-hardy cultivar Engmo of timothy de-hardened more rapidly than the less-hardy cultivar Grindstad, but had higher initial frost tolerance in both experiments, whereas there was less difference between cultivars of perennial ryegrass in Experiment 1. Cultivar Grindstad of timothy lost all hardiness in early spring at all temperatures, whereas cultivar Engmo maintained some hardiness at 3°C. Cultivar Engmo de-hardened at a lower rate in 2007 than in 2006, in spite of similar frost tolerance at the start of de-hardening treatment in both years. This indicates that the rate of de-hardening was controlled by factors additional to the initial frost tolerance and that autumn weather conditions might be important for the resistance to de-hardening.

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Timothy (Phleum pratense L) is the most important forage grass in Scandinavia and it is therefore highly interesting to study how it will perform in a changing climate. In order to model winter survival, the dynamics of hardening and dehardening must be simulated with satisfactory precision. We investigated an early timothy frost tolerance model (LT50 model), and an LT50 model for winter wheat. Based on the assumption that timothy has no vernalization requirement, unlike winter wheat, but does have the ability to adapt to cold temperatures in a process linked to stage of development, two alternative versions of the winter wheat model were also constructed. In total, these four candidate models were calibrated by a Bayesian approach for the timothy cultivar Engmo. The candidate models were validated using independent observations on LT50 in timothy at different locations reflecting differences in climate. A sensitivity analysis, using the Morris method, to identify important model parameters suggested that there is a connection between frost tolerance and stage of plant development, even if there is no vernalization requirement. The simplified winter wheat model was selected as the best candidate model for LT50 in timothy based on model selection criteria and its ability to capture the hardening and dehardening processes. The results from the Bayesian calibration suggest that there are no major regional differences in Norway calling for regional calibration. However, cultivar-specific calibration is probably required, since there are hardy and less hardy cultivars within the same species. A functional LT50 model would allow risk assessments to be made of future winter survival using specifically tailored and downscaled climate scenarios. (C) 2010 Elsevier B.V. All rights reserved.

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The purpose of this study was to compare the effect of grazing on mountain (M) versus cultivated lowland pasture (C) on the performance and meat quality of suckling calves (Experiments 1 and 2). In addition, the effect of finishing on C after M on growth and meat quality was assessed (Experiment 2). Animals on C and M had on average similar live weight gain and carcass weight in the first experiment. However, the performance depended on year as gain and carcass weight was higher on C than on M in the first year and vice versa in the second year. In the second experiment the calves on M had lower gain and carcass weight than on C. Three weeks finishing on C after M compensated to some extent for the lower growth rate on M. Overall, the results indicate that mountain grazing may yield similar growth rates and slaughter weights as improved lowland pasture depending on year. There were only small effects of pasture type on carcass and meat quality traits like conformation, fatness, intramuscular fat and protein content, and fatty acid (FA) composition. The variation in FA composition could to a large extent be explained by difference in fatness with increase in monounsaturated and decrease in polyunsaturated FA with increasing intramuscular fat content, in turn varying between pasture type, experiment and year. There was a tendency that M led to higher proportion of C18:1n-9 and lower proportion of C18:1n-7 than C. which may be due to difference in milk and forage intake. Both pasture types resulted in meat with intramuscular fat with high nutritional value since the n-6/n-3 ratio was low. (C) 2010 Elsevier B.V. All rights reserved.