Kuyavia-Pomerania

KuyaviaPomeraniaGeneral information

Name of region Kuyavia-Pomerania (Kujawy & Pomorze), Poland
Global Environmental Zone(s) (Metzger) H. Cool temperate and dry
Population density (persons per km2) 116
Contact (general) Waldemar Bojar
Contact (ag. scenarios) Waldemar Bojar
Location (NUTS code) PL61
Dominant regional farming system(s)
(SEAMLESS nomenclature)
Arable/cereal and mixed farming
The three most important
farming systems in region

(SEAMLESS nomenclature)
  • arable-cereal
  • mixed farms
  • mixed livestock
Main crop species
  • cereals, potatoes, sugar beets
  • beets
Main livestock species
  • pigs, milking cows, poultry

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

Kujawy & Pomorze is a very important region about agricultural production in Poland due to essential resources and output in relation to other regions. Deficit of water (below 500 mm and often about 400 mm yearly and still it is decreasing) is a main minimum factor of farming. Poor retention of water, so called small retention is also an important not desired fact for farming. Also poor quality soils are in majority in the region.

Regional challenges with regard to climate change

  1. A problem is a low possibility of retention of water for agricultural production needs. So, at sure a challenge for both regions is improvement of infrastructure for more effective small retention of water.
  2. Some irrigation investments can be also a one of solution to adapt regional agriculture to CC.
  3. For Kujawy & Pomorze region there will be also important activities (at CAP or domestic and regional policy level) towards agricultural land consolidation. Mentioned above activities can increase economic efficiency of farming in both surveyed regions.
  4. Selection of cereals, maize for grain and potatoes was made because they are very important crops in food supply and demand balance in global, country and regional scale. Those crops are also very important for Kujawy & Pomorze region due to their essential market meanings.
  5. Defining owned models, data bases and tools are useful for forecasts creation on climate change impact on future agricultural production according to spatial and subjective scope of analysis. Owned resources of the data and models for research let select cereals, maize for grain and potatoes as interesting crops for regional pilot study.

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. The 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.

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.
Drainage  
Species/varietal choice  
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.
Pest/weed management  
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  
Climate alertness  
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 surveyed region based on forecasted output and farm land area in Kujawsko-Pomorskie 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

Models used in the study
Socio-economyCropsGrasslandLivestock
CAPRI

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

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

None None
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?
The findings from MACSUR1 can approach impact of more frequent extreme climatic events in the future for agricultural output and agricultural economic effects being important for shaping rural and agricultural policy and farmer projected strategic decisions as well. Carried out research concerning irrigation effects of selected crops cropped at poor soils consider current genetic potential of the yielding and current costs of irrigation devices. Forecasting of bio-physical and economic effects of irrigation will consider genetic progress in varieties being more positively sensitive on delivering more water and also technical progress in irrigation equipment guarantying more efficient delivering water for crops. Indirectly through more effective crop production and because of it more forage for animals

Participating stakeholders

Agro-business or agro-food chainAdministrative 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 z siedzibą w Mnikowie 1B, powiat nakielski, gmina Nakło n. Notecią 80-120 Minikowo

Kujawy & Pomorze Cattle Breeders Association http://www.krs-online.com.pl/kujawsko-pomorski-zwiazek-hodowcow-bydla-krs-86051.html

http://www.bydgoszcz.uw.gov.pl/en/

http://www.bydgoszcz.uw.gov.pl/pl/wydzial-srodowiska-rolnictwa-i-rozwoju-wsi.html)

http://bip.lublin.uw.gov.pl/

Approaches for involving stakeholders
- irrigation policy strategies,- small retention, regional strategies,- insurance policy, cropping risk

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
It can help to define more precisely model input and output in a context of its usefulness for farmers' decision making The answer the question to what extent obtained model outputs are useful for practitioners for decision making in the future to plan their business activity more effectively
Points that researchers learned from stakeholdersPoints that stakeholders learned from researchers
The model outputs will be useful for continuing interdisciplinary research through know how to integrate bi-physical and socio-economic models according to scientific states-of-the-art. The answer the question to what extent stakeholders (practitioners) decisions are precise taking attention biophysical and economic circumstances of farming in the future

Further information

1. BANK DANYCH LOKALNYCH (LOCAL DATA BASE) GUS www.stat.gov.pl/bdl

2. Bojar W. Studium wyboru maszyn w gospodarstwach rolniczych w świetle rozwoju systemów wspomagania decyzji (Study on farm machinery selection at farms in a view of Decision Support Systems development). Rozprawy nr 114. Akademia Techniczno-Rolnicza w Bydgoszczy. 2005.

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.

5. http://www.fwie.eco.pl

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.

11. http://www.stat.gov.pl/cps/rde/xbcr/gus/RN_pkb_rachunki_regionalne_2010_notatka.pdf

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.

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