Carter, T. (2015). Scenarios and related data for MACSUR2 Timothy Carter Finnish Environment (Vol. 5).
Abstract: Framing scenario selection (RCP/SSP)Ongoing scenario development in FP7 IMPRESSIONSSome examples of sources of data and scenarios No Label
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Brzezinska, M. (2015). What is a stronger determinant of soil respiration: soil temperature or moisture (Vol. 5).
Abstract: Increased atmospheric concentrations of greenhouse gases have led to global warming and climatic changes. Both experimental and modelling studies are necessary to predict and to quantify gas exchange in agroecosystems. We studied the effect of the important environmental factors (soil moisture and temperature) on CO2 emission from agricultural soil (Orthic Luvisol developed from loess) under field and laboratory conditions. In the field experiment (winter wheat, permanent meadow or black fallow), the in situ CO2 efflux form the soil, soil moisture and temperature were measured from April to December 2013. The CO2 efflux was influenced by plant cover (F=7.96; p<0.001), and was related to both, soil temperature (p<0.001) and slightly less by soil moisture (p<0.01). In the second experiment, soil was collected from a depth of 0-10 cm, air-dried, and passed through an 2 mm sieve. Next, soil samples were rewetted to obtain soil moisture in a range from water saturation (pF 0) to plant wilting point (pF 4.2), and incubated at different temperatures (from 5oC to 30oC). Multifactor analysis of variance has shown that the soil respiration, as measured under controlled conditions, was much more affected by soil temperature (F=237.0; p<0.0001), than by soil moisture (F=4.99; p<0.01). No Label
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Ahmadi, V. (2015). Impacts of Common Agricultural Policy 2015 reforms on animal health and welfare of Scottish dairy herds (Vol. 5).
Abstract: The latest Common Agricultural Policy (CAP) 2015 reforms bring a substantial change in the way farm support is paid in Scotland where previous direct CAP payments were largely based on historical entitlements. Under the new payment scheme, three rates of payment are designated based on land uses and capabilities. As a result, it is anticipated that, average large dairy farms will lose out up to 32% of their farm net margins, while small dairy farms will lose out between 7-20% of their farm net margins. Such reductions of payment support may force dairy farmers to cut costs of production on farms especially livestock variable costs including labour costs and costs of prevention, control, treatment and management of livestock diseases and welfare conditions. This will have direct and indirect consequences on health and welfare of dairy cattle. This study aims to assess the impact of new support payments under CAP 2015 reforms on financial capabilities of dairy herds in tackling three conditions namely: infertility, mastitis and lameness. A detailed inventory of 42 commercial dairy farms in Scotland that contains both physical (i.e. farm area, nutrition and labour supply, etc.) and health data collected in 2013 and was used to parameterise an optimisation model. The model is a linear programme (LP) model which optimises farm net margin under limiting farm resources. The model also consists of feed demand and supply components that are used to determine monthly feed requirements for each of the animals on a farm as well as grass yield for pasture area of the land. The model is run for both ‘healthy’ and ‘diseased’ herds under previous and future CAP support payments. Details of the model and the dataset used as well as some results will be presented at the conference. No Label
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Lehtonen, H. (2015). Evaluating clover grass as a climate change adaptation measure in agriculture at the sector level (Vol. 4).
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Kipling, R. (2015). LiveM and the knowledge hub concept: Grassland and livestock modelling in MACSUR Phase 2 (Vol. 4).
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