Mostviertel

MostviertelGeneral information

Name of region Mostviertel, Austria
Global Environmental Zone(s) (Metzger) H. Cool temperate and dry/G. Cold and mesic/J/F
Population density (persons per km2)  
Contact (general) Martin Schönhart
Contact (ag. scenarios) Martin Schönhart
Location (NUTS code) AT121
Dominant regional farming system(s)
(SEAMLESS nomenclature)
Arable/cereal and mixed farming
The three most important
farming systems in region

(SEAMLESS nomenclature)
  • arable-cereal
  • beef and mixed cattle-permanent grass
  • mixed farms
Main crop species
  • maize
  • winter wheat
  • temporary grassland
Main livestock species
  • dairy cattle
  • pigs
  • suckler cows

Regional development goal in rural spatial planning

Specific issues the region deals with/will deal with

We focus on two case study landscapes in the Mostviertel region either dominated by cropland or grassland. We specifically focus on climate change impacts on landscape development and biodiversity.

Regional challenges with regard to climate change

According to previous studies, we expect moderate yield gains from climate change. This can lead to intensification and deterioration of environmental quality. Extreme events play a certain role, particularly soil erosion.

Proposed solutions to overcome the challenges

Contribution to answering the focus question

Our Regional Pilot Study should provide insights into the question whether and how climate change impacts landscape development, land abandonment/intensification, and the biotic environment. These results also allow statements on the development of agricultural productivity (food, resource production) under climate change. Furthermore, we are focusing on the trade-offs between mitigation and adaptation. Diverse adaptation strategies are modelled including soil management (e.g. cover crops), changes in crop rotations and fertilization intensity levels.

Important adaptation measures that are or will be considered in the study

Water management  
Irrigation  
Drainage  
Species/varietal choice is important to this region AND is/will be included in the modelling exercise.
Plant breeding  
Changed planting/sowing days is important to this region AND is/will be included in the modelling exercise.
Crop rotations is important to this region AND is/will be included in the modelling exercise.
Alternative tillage methods is important to this region AND is/will be included in the modelling exercise.
Pest/weed management is important to this region.
Housing of livestock  
Land consolidation is important to this region AND is/will be included in the modelling exercise.
Management of feeding and reproduction of livestock is important to this region AND is/will be included in the modelling exercise.
Structure and scale of production adjustment is important to this region
Crop insurance is important to this region AND is/will be included in the modelling exercise.
Exit from agriculture is important to this region AND is/will be included in the modelling exercise.
Climate alertness is important to this region AND is/will be included in the modelling exercise.
Political regulations at various administrative levels is important to this region AND is/will be included in the modelling exercise.
Others  
   

Models, stakeholders, advancement of knowledge

Models used in the study
Socio-economyCropsGrasslandLivestock
FAMOS[space], information is needed on socio-economic pathways (developed by the modelling team) EPIC, CropRota (crop rotation generator), climate change data from statistical model is already available EPIC is applied to model changes in grassland yields, SpatialGRAM will be applied as well Contained within socio-economic model.
How are results of of crop and livestock models assimilated in socio-economic models?How is technological progress in arable agriculture taken into account?How is technological progress in livestock farming taken into account?
We improved the interface between our model components. Furthermore, we plan to integrate a second model on grassland yield changes. We assume productivity changes based on observations in the economic model but not so in the crop model. We assume productivity changes based on observations in the economic model.

Participating stakeholders

Agro-business or agro-food chainAdministrative bodies or regional or national governments
The group of stakeholders includes agricultural experts such as teachers from agricultural schools, staff from extension services and administration, as well as farmers.  
Approaches for involving stakeholders
We organized one stakeholder workshop in the region. Further stakeholder activities will follow.

Improvement of the modelling capability by involving stakeholders

How did the modelling capability improve by involving stakeholders?Effect of the involvement of stakeholders on the questions asked, on the assessment, or on the solutions suggested
Stakeholders contributed to model validation. However, we did not change the models based on this. We revised the interpretation of our results but did not change the methods.
Points that researchers learned from stakeholdersPoints that stakeholders learned from researchers
Heterogeneity plays a role as suggested by our models; some (crop model) results are questioned and need further analysis; economic model results are more difficult to discuss with stakeholders. climate change impacts may be positive; adaptation is required; uncertainty on climate change is considerable;

Further information

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