|Name of region||Lublin, Poland|
|Global Environmental Zone(s) (Metzger)||H. Cool temperate and dry|
|Population density (persons per km2)||85|
|Contact (general)||Cezary Sławiński|
|Contact (ag. scenarios)||Waldemar Bojar|
|Location (NUTS code)||PL31|
|Dominant regional farming system(s)
|Arable/cereal and mixed farming|
|The three most important
farming systems in region
|Main crop species||
|Main livestock species||
Regional development goal in rural spatial planning
The main direction of intervention to stimulate the development of social (key role of the public service level municipal shaping appropriate social attitudes) and local labor markets. Thislevel of territorial policies in the areas of traditional agriculture is crucial for activation of rural inhabitants, is also responsible for local aspects of social development and economic development. Last findings can be used to create forecasts for setting water needs of given region which can be an important point for water management regional policy shaping.
Specific issues the region deals with/will deal with
Lublin region is potentially very important due to high quality soils and good natural conditions for agricultural production. Minimum factor is frittered agrarian structure and also poor retention of water.
Regional challenges with regard to climate change
A problem is a low possibility of retention of water for agricultural production needs. So, for sure, a challenge is to improve infrastructure for more effective small retention of water and yield losses reduction caused by the further water scarcity and heat stresses. For Lublin region low effectivnes of agriculture production is a result of low consolidation level of agricultural land. This prevents farms to become more efficient and competitive, and better integrated in agricultural chains and discourages farmers for looking alternative ways of agricultural production, such as good agricultural practices, prevents improved management of natural resources and better land use planning and land management. This also hinders the introduction of low-carbon land use strategies to reduce GHG emissions from agriculture.
Proposed solutions to overcome the challenges
Contribution to answering the focus question
Calculation of the future farm incomes influenced by changes in productivity of wheat and maize for grain with consideration of expected changes of their yields because of precipitation changes, different (CAP) policy instruments usage, plantation insurance usage and irrigation/small retention treatment in long term perspective (biological and technological progress is constant in forecasted period) 2020, 2030, 2050(60).This way will be produced different variants of scenarios showing also expected levels of productivity of surveyed regions about wheat and maize for grain what can have influence on food security keeping in Europe. Projections of parameters of baseline scenarios (GAMP) into farm level will be also possible over comparison of models based on regional empirical data and global models. The findings from research carried out between 2006 and 2012 within the UTP synergic project with MACSUR 2 one at poor quality soils showed that is economically justified to irrigate potatoes above 1-hectare area while irrigation of malting barley and corn for grain is not efficient because a direct surplus value is lower than costs closed to irrigation operations and an additional costs, e.g. harvest of higher volume of output. Those findings can be used to create forecasts for setting water needs of given region which can constitute an important point for water management regional policy shaping. Thus rational irrigation investments can be a one of solution to adapt regional agriculture to CC.Mitigation/adaptation to CC may involve improvement of management of crop/soil/water resources by construction/development of decision support systems adapted to local/regional conditions.Also important activities (at CAP or domestic and regional policy level) can be carried out towards agricultural land consolidation. Mentioned above activities can increase economic efficiency of farming in the context of CC.
Important adaptation measures that are or will be considered in the study
|Water management||is important to this region AND is/will be included in the modelling exercise.|
|Irrigation||is important to this region AND is/will be included in the modelling exercise.|
|Plant breeding||is important to this region.|
|Changed planting/sowing days||is important to this region.|
|Crop rotations||is important to this region.|
|Alternative tillage methods||is important to this region.|
|Housing of livestock|
|Land consolidation||is important to this region.|
|Management of feeding and reproduction of livestock|
|Structure and scale of production adjustment|
|Crop insurance||is important to this region AND is/will be included in the modelling exercise.|
|Exit from agriculture|
|Political regulations at various administrative levels||is important to this region AND is/will be included in the modelling exercise.|
|Others||is important to this region.|
|On the base of predicted yields and prices of wheat and maize for grain we will calculate future regional productivity of land for wheat and maize for grain in both surveyed regions based on forecasted output and farm land area in Lubelskie region taking attention climate changes and their impact on yields in long term perspective (2020, 2030, 2050, (60). Among effects will be slower decrease of productivity of crops influenced by extreme climatic phenomena and especially declining deficit of water reached over better small retention of water, irrigation. Appropriate agricultural policy under CC circumstances and also effective crop insurance will ensure keeping farmer incomes at stabilized level.|
Models, stakeholders, advancement of knowledge
The UTP Agroclimatic statistical models for setting dependencies between yields of selected crops (wheat, corn) and climate change parameters to predict in long term perspectives (2030, 2050) their yields
CropM partner models for setting dependencies between yields of selected crops (wheat, corn) and climate change parameters to predict in long term perspectives (2030, 2050) their yields
CropM partner SPACSYS model for setting dependencies between yields of selected crops (wheat, corn) and climate change parameters to predict in long term perspectives (2030, 2050) their yields
|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?|
|Crop and livestock models linkeage to socio-economic model was incorporated and those models were intergated.||Except for new cultivars/crops species calibration it was not taken into account||It was not taken into account|
|Agro-business or agro-food chain||Administrative bodies or regional or national governments|
Pomorsko-Kujawski Związek Hodowców Trzody Chlewnej
Pomorze & Kujawy Pig Breeders Association, http://bazy.ngo.pl/search/info.asp?id=35176
Kujawsko-Pomorski Związek Hodowców Bydła, Bydgoszcz
Kujawy & Pomorze Cattle Breeders Association, http://www.krs-online.com.pl/kujawsko-pomorski-zwiazek-hodowcow-bydla-krs-86051.html
Związek Hodowców Trzody Chlewnej (woj. lubelskie)
Pig Breeders Association (Lublin voivodeship)
LUBELSKI ZWIĄZEK HODOWCÓW BYDŁA I PRODUCENTÓW MLEKA (Lublin Cattle Breeders Association and Milk Producers)
|Approaches for involving stakeholders|
|- irrigation,- small retention, - regional strategies,- insurance policy, - cropping risk,- land consolidation|
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|
|Points that researchers learned from stakeholders||Points that stakeholders learned from researchers|
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3. Bojar W. Unification of the data and the knowledge bases At national and the EU level being a challenge facing agriculture In the knowledge societies [In:] 3rd International Conference on Information Technology in Business, Warsaw Agricultural University, 2006. p. 21-29.
4. Czarnecka M., Koźmiński C., Michalska B. Climatic risks for plant cultivation in Poland. Acta Agrophisica 169 (1) Monografie, 2009, 78-97.
6. Gocht, A. W.Britz and M. Adenäur, Farm level policy scenario analysis. IPTS, 2011.
7. Kuchar L. Application of mathematical methods for crop yield estimation under changing climatic conditions. Acta Agrophisica 169 (1) Monografie, 2009, 52-62.
8. Leśny J. (red.). Climate change and agriculture in Poland – impacts, mitigation and adaptation measures. Acta Agrophysica, 169, 2009, ss.152.
9. www.lubelskie.pl 10. „Rolnictwo w województwie lubelskim w 2011 roku (Agriculture in Lubelskie Province), GUS, Lublin, 2012.
12. Żarski J., Kuśmierek-Tomaszewska R., Dudek S. Tendencje zmian termicznych okresów rolniczych w rejonie Bydgoszczy. Trends of variation in thermal agricultural seasons in the region of Bydgoszcz. Infrastruktura i Ekologia Terenów Wiejskich, nr 3/I, 2012 7-17.