Preview

Plant Health and Quarantine

Advanced search

Issues of assessing the potential economic significance of quarantine species of insects and mites in the process of pest risk analysis

https://doi.org/10.69536/b3192-1363-1396-b

Abstract

The article provides an analysis of existing approaches to assessing the potential economic significance of pests (insects and mites) when conducting pest risk analysis. The insufficiency of the existing international and Russian methodological framework for conducting such an assessment is shown. The applicability and accuracy of available assessment methods were analyzed. The greatest practical applicability of the method of drawing up partial budgeting is shown. Based on existing methods and practices, an improved methodology has been proposed that takes into account empirical data on the harmfulness of insects and mites to agricultural crops and the adaptation probability (taken as the suitability of conditions), determined in accordance with a mathematical model of the potential species distribution. This approach is justified by an objective correlation between harmfulness and the number of pests, in turn determined by the suitability of environmental conditions. An approach to the qualitative assessment of potential economic losses is proposed based on the correlation of calculated indicators of potential damage and gross domestic product in the pest risk analysis area. The presented methodology can significantly increase the reliability and accuracy of assessing the potential economic significance of potentially dangerous species of insects and mites when conducting pest risk analysis, meets the requirements of legislation and methodological documents in the field of plant quarantine and is mathematically equivalent to assessment methods previously used in the practice of pest risk analysis in the Russian Federation. Prospects for further improvement of methods for assessing the negative impact of pests when conducting pest risk analysis based on more detailed models of agricultural production and economic relationships are noted.

About the Author

K. A. Grebennikov
Federal State Budgetary Institution “All-Russian Plant Quarantine Center” (FGBU “VNIIKR”)
Russian Federation

Konstantin Grebennikov, Leading Researcher,
Insects and Mites Ecology and Genetics Laboratory

Bykovo, Urban district Ramensky, Moscow Oblast, 140150



References

1. Vasyutin A.S., Smetnik A.I. et al. Plant protection in the Russian Federation [Karantin rasteniy v Rossiyskoy Federatsii]. M.: Kolos, 2001, 375 p. (In Russ.)

2. Grebennikov K.A., Kulakova Yu.Yu. 2022. Development of methods for mathematical modeling of the probability of introduction, spread and negative impact of quarantine species of insects for the purpose of scientific and methodological support for performing pest risk analysis for the territory of the Russian Federation (interim report) (manuscript) [Razrabotka metodov matematicheskogo modelirovaniya veroyatnosti proniknoveniya, rasprostraneniya i negativnogo vozdeystviya karantinnykh vidov nasekomykh v tselyakh nauchno-metodicheskogo obespecheniya vypolneniya analiza fitosanitarnogo riska dlya territorii Rossiyskoy Federatsii]. Inv. No. 16-2022 BY VNIIKR. Bykovo, FGBU “VNIIKR”. No. EGISU NIOKTR 122041300171-6. 139 p. (In Russ.)

3. Zakharenko V.A., Chenkin A.F., Cherkasov V.A. Handbook of plant protection [Spravochnik po zashchite rasteniy] / Ed. Yu.N. Fadeeva. M.: Agropromizdat, 1985, 414 p. (In Russ.)

4. Zakharenko V.A. Current state and prospects of the economy of the use of pesticides in agroecosystems of Russia [Sovremennoye sostoyaniye i perspektivy ekonomiki primeneniya pestitsidov v agroekosistemakh Rossii] // Agrochemistry. 2021; 5: 68–83. URL: https://doi.org/10.31857/S0002188121050148. (In Russ.)

5. Lisovsky A.A., Dudov S.V., Obolenskaya E.V. Advantages and limitations of application of the species distribution modeling methods. 1. A general approach [Preimushchestva i ogranicheniya metodov ekologicheskogo modelirovaniya arealov. 1. Obshchiye podkhody] // Journal of General Biology. 2020; 81; 2: 123–134. (In Russ.)

6. International Standard for Phytosanitary Measures ISPM № 2 “Framework for pest risk analysis”. 2019, 20 p.

7. International Standard for Phytosanitary Measures ISPM № 11 “Pest risk analysis for quarantine pests”. 2019, 45 p.

8. Perevertin K.A. Forecasting crop losses from pests using “critical point” models [Prognozirovaniye poter’ urozhaya ot vrednykh organizmov s pomoshch’yu modeley «kriticheskoy tochki»] // Applied Phytonematology. M.: Nauka, 2006; 85–97. (In Russ.)

9. Order of the Ministry of Agriculture of the Russian Federation dated February 5, 2018 No. 46 “On approval of the Methodology for performing pest risk analysis”.

10. Riznichenko G.Yu., Rubin A.B. Mathematical models of biological production processes [Matematicheskiye modeli biologicheskikh produktsionnykh protsessov]. M.: MSU, 1993, 300 p. ISBN 5-211-01755-2. (In Russ.)

11. Aubertot J.N., Robin M.H. Injury Profile SIMulator, a qualitative aggregative modelling framework to predict crop injury profile as a function of cropping practices, and the abiotic and biotic environment. I. Conceptual bases. // PLoS ONE. 2013. Vol. 8, No. 9. P. 1–12. URL: https://doi.org/10.1371/journal.pone.0073202.

12. Economic impact assessment in pest risk analysis / Soliman T., Mourits M.C.M., Oude Lansink A.G.J.M., van der Werf W. // Crop Protection. 2010. Vol. 29, Issue 6. P. 517–524. URL: https://doi.org/10.1016/j.cropro.2009.12.014.

13. EFSA. Guidance on quantitative pest risk assessment // EFSA journal. 2018. Vol. 16, Issue 8. P. 1–86. URL: https://doi.org/10.2903/j.efsa.2018.5350.

14. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Injury Profile as a Function of Cropping Practices, and Abiotic and Biotic Environment. II. Proof of Concept: Design of IPSIM- Wheat-Eyespot / Robin M.H., Colbach N., Lucas P., Montfort F., Cholez C., Debaeke P., Aubertot J.N. // PLoS ONE. 2013. Vol. 8, No. 10. P. 1–13. URL: https://doi.org/10.1371/journal.pone.0075829.

15. Jenks G.F. The Data Model Concept in Statistical Mapping // International Yearbook of Cartography. 1967. Vol. 7. P. 186–190.

16. Modelling the impacts of pests and diseases on agricultural systems / Donatelli M., Magarey R.D., Bregaglio S., Willocquet L., Whish J.P.M., Savary S. // Agricultural Systems. 2017. Issue 155. P. 213–224. URL: https://doi.org/10.1016/j.agsy.2017.01.019.

17. Oerke E.-C. Crop losses to pests // The Journal of Agricultural Science. 2006. Vol. 144, Issue 1. P. 31–43. URL: https://doi.org/10.1017/S0021859605005708.

18. Rosstat (Federal State Statistics Service) [Electronic resource].URL: https://rosstat.gov.ru (last accessed: 15.08.2023).

19. Savary S., Willocquet L., 2014. Simulation Modeling in Botanical Epidemiology and Crop Loss Analysis. The Plant Health Instructor [Electronic resource]. URL: https://www.apsnet.org/edcenter/disimpactmngmnt/topc/BotanicalEpidemiology/Pages/default.aspx (last accessed: 15.08.2023). URL: https:// doi.org/10.1094/PHI-A-2014-0314-01.


Review

For citations:


Grebennikov K.A. Issues of assessing the potential economic significance of quarantine species of insects and mites in the process of pest risk analysis. Plant Health and Quarantine. 2024;(1):29-40. https://doi.org/10.69536/b3192-1363-1396-b

Views: 452


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2782-327X (Print)