IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5302-d804051.html
   My bibliography  Save this article

Correlation of Climatic Factors with the Weight of an Apis mellifera Beehive

Author

Listed:
  • Cristiano Ziegler

    (Graduate Program in Production Engineering, Federal University of Santa Maria, Santa Maria CEP 97105-900, Brazil)

  • Renan Mitsuo Ueda

    (Graduate Program in Production Engineering, Federal University of Santa Maria, Santa Maria CEP 97105-900, Brazil)

  • Tiago Sinigaglia

    (Graduate Program in Production Engineering, Federal University of Santa Maria, Santa Maria CEP 97105-900, Brazil)

  • Felipe Kreimeier

    (Center of Rural Sciences, Federal University of Santa Maria, Santa Maria CEP 97105-900, Brazil)

  • Adriano Mendonça Souza

    (Graduate Program in Production Engineering, Federal University of Santa Maria, Santa Maria CEP 97105-900, Brazil)

Abstract

The bee Apis mellifera plays an important role in the balance of the ecosystem. New technologies are used for the evaluation of hives, and to determine the quality of the honey and the productivity of the hive. Climatic factors, management, flowering, and other factors affect the weight of a hive. The objective of this research was to explain the interrelationship between climatic variables and the weight of an Apis mellifera beehive using a vector autoregressive (VAR) model. The adjustment of a VAR model was carried out with seven climatic variables, and hive weight and its lags, by adjusting an equation that represents the studied hive considering all interrelationships. It was proven that the VAR (1) model can effectively capture the interrelationship among variables. The impulse response function and the variance decomposition show that the variable that most influences the hive weight, during the initial period, is the minimum dew point, which represents 5.33% of the variance. Among the variables analyzed, the one that most impacted the hive weight, after 20 days, was the maximum temperature, representing 7.50% of the variance. This study proves that it is possible to apply econometric statistical models to bee data and to relate them to climatic data, contributing significantly to the area of applied and bee statistics.

Suggested Citation

  • Cristiano Ziegler & Renan Mitsuo Ueda & Tiago Sinigaglia & Felipe Kreimeier & Adriano Mendonça Souza, 2022. "Correlation of Climatic Factors with the Weight of an Apis mellifera Beehive," Sustainability, MDPI, vol. 14(9), pages 1-13, April.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5302-:d:804051
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5302/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/9/5302/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    2. Juliet L. Osborne, 2012. "Bumblebees and pesticides," Nature, Nature, vol. 491(7422), pages 43-45, November.
    3. de Senna, Viviane & Souza, Adriano Mendonça, 2016. "Assessment of the relationship of government spending on social assistance programs with Brazilian macroeconomic variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 21-30.
    4. Qing Wang & Xinjian Xu & Xiangjie Zhu & Lin Chen & Shujing Zhou & Zachary Y Huang & Bingfeng Zhou, 2016. "Low-Temperature Stress during Capped Brood Stage Increases Pupal Mortality, Misorientation and Adult Mortality in Honey Bees," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-13, May.
    5. Bellido-Jiménez, Juan Antonio & Estévez Gualda, Javier & García-Marín, Amanda Penélope, 2021. "Assessing new intra-daily temperature-based machine learning models to outperform solar radiation predictions in different conditions," Applied Energy, Elsevier, vol. 298(C).
    6. de Souza Ramser, Claudia Aline & Souza, Adriano Mendonça & Souza, Francisca Mendonça & da Veiga, Claudimar Pereira & da Silva, Wesley Vieira, 2019. "The importance of principal components in studying mineral prices using vector autoregressive models: Evidence from the Brazilian economy," Resources Policy, Elsevier, vol. 62(C), pages 9-21.
    7. Brahmasrene, Tantatape & Huang, Jui-Chi & Sissoko, Yaya, 2014. "Crude oil prices and exchange rates: Causality, variance decomposition and impulse response," Energy Economics, Elsevier, vol. 44(C), pages 407-412.
    8. Yonglian Wang & Lijun Wang & Changchun Pan, 2022. "Tourism–Growth Nexus in the Presence of Instability," Sustainability, MDPI, vol. 14(4), pages 1-11, February.
    9. Ueda, Renan Mitsuo & Souza, Adriano Mendonça & Menezes, Rui Manuel Campilho Pereira, 2020. "How macroeconomic variables affect admission and dismissal in the Brazilian electro-electronic sector: A VAR-based model and cluster analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    10. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    11. Laura Christ & Daniel C. Dreesmann, 2022. "SAD but True: Species Awareness Disparity in Bees Is a Result of Bee-Less Biology Lessons in Germany," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
    12. Cristiano Ziegler & Tiago Sinigaglia & Mario Eduardo Santos Martins & Adriano Mendonça Souza, 2021. "Technological Advances to Reduce Apis mellifera Mortality: A Bibliometric Analysis," Sustainability, MDPI, vol. 13(15), pages 1-13, July.
    13. Coral Oliver Hernández & Shimeng Li & María Dolores Merino Rivera & Inmaculada Mateo Rodríguez, 2022. "Does Postural Feedback Reduce Musculoskeletal Risk?: A Randomized Controlled Trial," Sustainability, MDPI, vol. 14(1), pages 1-14, January.
    14. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ueda, Renan Mitsuo & Souza, Adriano Mendonça & Menezes, Rui Manuel Campilho Pereira, 2020. "How macroeconomic variables affect admission and dismissal in the Brazilian electro-electronic sector: A VAR-based model and cluster analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    2. Zhou, Kaile & Hu, Dingding & Li, Fangyi, 2022. "Impact of COVID-19 on private driving behavior: Evidence from electric vehicle charging data," Transport Policy, Elsevier, vol. 125(C), pages 164-178.
    3. Eleni Constantinou & Avo Kazandjian & Georgios P. Kouretas & Vera Tahmazian, 2008. "Common Stochastic Trends Among The Cyprus Stock Exchange And The Ase, Lse And Nyse," Bulletin of Economic Research, Wiley Blackwell, vol. 60(4), pages 327-349, October.
    4. Pami Dua & Nishita Raje & Satyananda Sahoo, 2004. "Interest Rate Modeling and Forecasting in India," Occasional papers 3, Centre for Development Economics, Delhi School of Economics.
    5. Diamandis, Panayiotis F., 2009. "International stock market linkages: Evidence from Latin America," Global Finance Journal, Elsevier, vol. 20(1), pages 13-30.
    6. Climent, Francisco & Meneu, Vicente, 2003. "Has 1997 Asian crisis increased information flows between international markets," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 111-143.
    7. Huang, Shupei & An, Haizhong & Lucey, Brian, 2020. "How do dynamic responses of exchange rates to oil price shocks co-move? From a time-varying perspective," Energy Economics, Elsevier, vol. 86(C).
    8. Pami Dua, 2008. "Analysis of Consumers’ Perceptions of Buying Conditions for Houses," The Journal of Real Estate Finance and Economics, Springer, vol. 37(4), pages 335-350, November.
    9. Tsangyao Chang & WenRong Liu & Steven Caudill, 2004. "A re-examination of Wagner's law for ten countries based on cointegration and error-correction modelling techniques," Applied Financial Economics, Taylor & Francis Journals, vol. 14(8), pages 577-589.
    10. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2017. "Do oil price asymmetric effects on the stock market persist in multiple time horizons?," Applied Energy, Elsevier, vol. 185(P2), pages 1799-1808.
    11. Jin, Xiaoye, 2015. "Volatility transmission and volatility impulse response functions among the Greater China stock markets," Journal of Asian Economics, Elsevier, vol. 39(C), pages 43-58.
    12. Ewing, Bradley T. & Sari, Ramazan & Soytas, Ugur, 2007. "Disaggregate energy consumption and industrial output in the United States," Energy Policy, Elsevier, vol. 35(2), pages 1274-1281, February.
    13. Hondroyiannis, George & Papapetrou, Evangelia, 2001. "Demographic changes, labor effort and economic growth: empirical evidence from Greece," Journal of Policy Modeling, Elsevier, vol. 23(2), pages 169-188, February.
    14. M. T. Alguacil & V. Orts, 2003. "Inward Foreign Direct Investment and Imports in Spain," International Economic Journal, Taylor & Francis Journals, vol. 17(3), pages 19-38.
    15. Drakos, Anastassios A., 2016. "Does the relationship between small and large portfolios’ returns confirm the lead–lag effect? Evidence from the Athens Stock Exchange," Research in International Business and Finance, Elsevier, vol. 36(C), pages 546-561.
    16. Andrés Felipe Londoño & Jorge Andrés Tamayo & Carlos Alberto Velásquez, 2012. "Dinámica de la política monetaria e inflación objetivo en Colombia: una aproximación FAVAR," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 30(68), pages 14-71, June.
    17. Fredj Jawadi & Catherine Bruneau & Nadia Sghaier, 2009. "Nonlinear Cointegration Relationships Between Non‐Life Insurance Premiums and Financial Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 753-783, September.
    18. Crowder, William J., 1995. "Covered interest parity and international capital market efficiency," International Review of Economics & Finance, Elsevier, vol. 4(2), pages 115-132.
    19. Sheng‐Tun Li & Kuei‐Chen Chiu & Chien‐Chang Wu, 2023. "Apply big data analytics for forecasting the prices of precious metals futures to construct a hedging strategy for industrial material procurement," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 942-959, March.
    20. Levent KORAP, 2008. "Exchange Rate Determination Of Tl/Us$:A Co-Integration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 7(1), pages 24-50, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5302-:d:804051. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.