Mekansal İstatistik Yoluyla Hayvan Yem Üretiminin Sürdürülebilir Sığır Üretimindeki Rolü

Abstract

Ekonomik krizlere bağlı olarak,  hükümetlerin tarım    sektöründe düzenleyici rolünün  azalmasından sonra, hayvancılığın       sürdürülebilirlik   şartlarını çiftçiler tarafından  nasıl bir mekan organizasyonu ile  sağladığının saptanması  bu çalışmanın amacını oluşturmaktadır.  Yem üretiminin, süt verimliliğinin  çevre şartlarının    ve hayvan ırklarının söz konusu mekan organizastyonundaki rolu  Türkiye’ye ait veriler kullanılarak  tespit edildi. Yem bitkileri  ile sığırların dağılımında nasıl bir mekansal bağımlılığın olduğunu saptamak için   açıklayıcı mekansal data analizlerinden multivariate  (LISA)  tekniği kullanıldı.   

Yapılan çalışma sonucunda sığır sayısı   20 ve üzeri  olan     orta boy işletmelerin  sürdürülebilirlik şartlarını daha kolay sağladığını,  küçük işletmelerin tarımsal faaliyetten çekildiğini ve  mekan değiştirdiğini göstermiştir.  Hayvancılık ile yem bitkisi üretimi arasındaki mekansal bağımlılık ilişkisi güçlenmiştir. Süt amaçlı selüloz oranı yüksek yem üretimi, hayvancılığın gelişmesinde yayılma etkisine sahip gösterge olmuştur. Çiftçiler, kriz şartlarına,  süt verimliği yüksek, genetiği daha kaliteli hayvan ırklarını tercih ederek uyum sağlamışlardır.

 

Keywords

• Coğrafi bilgi sistemleri,Hayvancılık sistemleri,Mekânsal otokorelasyon,Sürdürülebilir tarım

The Role of Cattle Forage Production in Sustainable Cattle Breeding in Turkey through Spatial Statistical Methods

Abstract

This study is aimed at determining the form of spatial organization that farmers have tried to meet sustainability conditions after the regulatory role of governments on the agricultural industry had been reduced due to financial crises. The roles of forage production on this spatial organization were determined using data from Turkey. The multivariate local indicators of spatial association technique was employed.  It was observed that medium-scale enterprises that have 20 or more cattle are capable of meeting sustainability conditions more easily, and that small-scale enterprises have withdrawn from agriculture and changed locations. During the 2000-2010 period, the spatial dependence between livestock and forage crop production has become stronger. The production of forage with high cellulose content has become the indicator that possesses the spillover effect for the development of livestock production. Farmers adapted themselves to the economic crisis conditions by preferring cattle breeds with higher milk productivity and genetic quality.

 

Keywords

• Geographical information systems; Livestock systems; Spatial autocorrelation; Sustainable agriculture

References

1. References
2. Anselin, L. (1995). Local indicators of spatial association-LISA. Geographical Analysis 27 (2), 93–115.
3. Anselin L., Syabri I., & Smirnov, O. (2002). Visualizing Multivariate Spatial Correlation with Dynamically Linked Windows. Urbana, IL, University of Illinois, Urbana-Campaign.
4. Anselin, L. (2005). Exploring Spatial Data with GeoDa: A Workbook: Spatial Analysis Laboratory. University of Illinois, Urbana-Champaign, pp. 155- 200.
5. Bernués, A., Ruiz, R., Olaizola, A., Villalba, D., & Casasús, I. (2011). Sustainability of pasture-based livestock farming systems in the European Mediterranean context: Synergies and trade-offs. Livestock Science 139 (1-2), 44- 57
6. Carvalho, P.C.de.F., & Batello, C. (2009). Access to land, livestock production and ecosystem conservation in the Brazilian Campos biome: The natural grasslands dilemma. Livestock Science 120 (1-2), 158–162.
7. Descheemaeker, K., Amede, T., & Haileslassie, A. (2010) Improving water productivity in mixed crop-livestock farming systems of sub-Saharan Africa. Agricultural Water Management 97 (5), 579–586.
8. Ediger, V.S., & Huvaz, O. (2006). Examining the sectoral energy use in Turkish economy (1980–2000) with the help of decomposition analysis. Energy Conversion and Management 47 (6), 732–745.

9. FAO, (2006). Livestock’s Long Shadow–Environmental Issues and Options. Rome: Food and Agriculture Organization of the United Nations. FAO, Rome, Italy.
10. FAO, ( 2007) . The State of the World’s Animal Genetic Resources for Food and Agriculture -in brief, edited by Dafydd Pilling & Barbara Rischkowsky. Rome.
11. GÖÇER, K. (2015a) "Türkiye’de Tarım üretimindeki değişim dinamiklerinin buğday üretimindeki mekânsal yansımaları." Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi 254-268.
12. GÖÇER, K. (2015b) . "Analysis of the role of milk yield in sustainable cattle breeding using geographically weighted regression." Yüzüncü Yil Üniversitesi Ziraat Fakültesi Tarim Bilimleri Dergisi 25.1 (2015): 58-68.
13. Hasanov, M., Ayşen, A., & Telatar, F. (2010). Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey. Economic Modelling 27 (5), 1103–1115.
14. Henrioud, A. N. (2011). Towards sustainable parasite control practices in livestock production with emphasis in Latin America. Veterinary Parasitology 180 (1-2), 2– 11.
15. Herrero, M., Thornton, P.K., Gerber, P., & Reid, R.S. (2009). Livestock, livelihoods and the environment: understanding the trade-offs. Current Opinions in Environmental Sustainability 1(2), 111–120.
16. Herrero, M., Thornton, P.K., Notenbaert, A.M., Wood, S., Msangi, S., Freeman, H.A., Bossio, D., Dixon, J., Peters, M., van de Steeg, J., Lynam, J., Parthasrathy Rao, P., Macmillan, S., Gerard, B., McDermott, J., Seré, C. and Rosegrant, M. 2010. Smart investments in sustainable food production: revisiting mixed crop livestock systems. Science. 327: 822–825.
17. Kristensen, T., Søegaard, K., & Kristensen, I.S. (2005). Management of grasslands in intensive dairy livestock farming. Livestock Production Science 96 (1), 61–73.
18. Kruska, R.L., Reid, R.S., Thornton, P.K., Henningerb, N., & Kristjanson, P.M. ( 2003). Mapping livestock-oriented agricultural production systems for the developing world. Agricultural Systems 77 (1), 39–63.
19. Martinez, J., Dabert, P., Barrington, S., & Burton., C. (2009). Livestock waste treatment systems for environmental quality, food safety, and sustainability. Bioresource Technology 100 (22), 5527–5536.
20. Moran, P.A.P. 1950. Notes on continuous stochastic phenomena, Biometrika. 37: 17-23.
21. Mushtaq, S., Maraseni, T.N., Maroulis, J., & Hafeez, M. (2009). Energy and water tradeoffs in enhancing food security: A selective international assessment. Energy Policy 37 (9), 3635–3644.
22. Nardone, A., Ronchi, B., Lacetera, N., Ranieri, M.S., & Bernabucci, U. (2010). Effects of climate changes on animal production and sustainability of livestock systems. Livestock Science 130 (1-3), 57–69.
23. Nienaber, J.A., Hahn, G.L. (2007). Livestock production system management responses to thermal challenges. International Journal of Biometeorology 52 (2), 149–157.
24. Nienaber, J.A., Hahn, G.L., & Eigenberg, R.A. (1999). Quantifying livestock responses for heat stress management: a review. International Journal of Biometeorology 42 (4), 183-8.
25. OECD Workshop, (2009). Livestock waste treatment systems of the future: A challenge to environmental quality, food safety, and sustainability. Bioresource Technology 100 (22), 5371–5373.
26. Özmucur, S. (2007). Liberalization and concentration: Case of Turkey. The Quarterly Review of Economics and Finance 46 (5), 762–777.
27. Rougoor, C.W., Sundaram, R., & van Arendonk, J.A.M. (2000). The relation between breeding management and 305-day milk production, determined via principal components regression and partial least squares. Livestock Production Science 66 (1), 71–83.
28. Schiere, J.B., Ibrahim, M.N.M., & Keulen, H. (2002). The role of livestock for sustainability in mixed farming: criteria and scenario studies under varying resource allocation. Agriculture, Ecosystems and Environment 90 (2), 139–153.
29. Sumberg, J. (1999). The Dar es Salaam Milk System: Dynamics of Change and Sustainability. Habitat International 23(2), 189- 200.
30. Tarawali, S., Herrero, M., Descheemaeker, K., Grings, E., & Blümmel, M. (2011). Pathways for sustainable development of mixed crop livestock systems: Taking a livestock and pro-poor approach. Livestock Science 139 (1-2), 11–21.
31. Türkekul, B., & Unakıtan, G. (2011). A co-integration analysis of the price and income elasticities of energy demand in Turkish agriculture. Energy Policy, 39 (5) 2416–2423.
32. TUIK 2001. Agricultural census village ınformation. Turkish Statistical Institute . Ankara.
33. TUIK, (2008). Tarımsal işletme yapı araştırması, number: 196 17.12.2008 newsletter. http://tuik.gov.tr/PreHaberBultenleri.do?id=3977 Accessed 15.01.2011..
34. TUIK 2011. Statistical Indicators, 1923-2010. Turkish Statistical Institute. Ankara.
35. TUIK 2012. Crop roduction statistics 1995-2012 Turkish Statistical Institute. Ankara.
36. Wartenberg, D. 1985. Multivariate spatial correlation: A method for exploratory geographical analysis. Geographical Analysis. 17: 263–283.
37. WCED, (1987). Our common future : Report of the world commission on environment and development: From A/42/427 Annex. UN Documents: Gathering a body of global agreements. http://www.un-documents.net/wced-ocf.htm Accessed 06.06.2011.
38. Yong-Zhong, S., Yu-Lin, L., Jian-Yuan, C., & Wen-Zhi, Z. (2005). Influences of continuous grazing and livestock exclusion on soil properties in a degraded sandy grassland, Inner Mongolia, Northern China. Catena 59 (3), 267–27814