Agroeconomic and agroecological aspects of spatial variation of rye (Secale cereale) yields within Polesia and the Forest-Steppe zone of Ukraine: The usage of geographically weighted principal components analysis


Keywords: geographically weighted principal component analysis; yield; rye; spatial variability; temporal dynamics

Abstract

In the present article, the patterns of the geographic variability in yields of rye within Polesia and the Forest-Steppe zone of Ukraine are presented and the correlation of the factors and dynamics of an agroeconomic and agroecological nature was determined. The dynamics of rye yields in the study area over time were determined as being characterized by three extreme points: two local maxima and one local minimum. Specific terms of the polynomial curve of the fourth order can be meaningfully interpreted and applied to describe the dynamics of productivity. Free members of the polynomial indicate culture productivity in the starting period. Dynamics of the productivity that can be explained by the regression indicate that agrotechnological and agrecological conditions of agricultural production are a pervasive factor that determines the presence of a general trend. The determination coefficient of the regression total trend can be interpreted as an indicator of the role of the agrotechnological and agroeconomic factors in the dynamics of productivity. The residue of the trend regression model can be interpreted so as to include the agroecological component of the rye yields dynamics. Their analysis revealed seven key components that together explained 58.4% of the total variability of the space feature. The principal components of vibrational patterns reflect the specific nature of variation of rye yields over time, which are spatially defined. Vibrational effects are environmental in nature. Geographically weighted principal component analysis showed the transience of environmental spatial modes which determine the oscillating component of rye yield variation over time. Spaces within which the structure of ecological interactions remains unchanged can be considered as the basis of agroecological zoning areas.

References

Andrushenko, A. Y., & Zhukov, A. V. (2016). Scale-dependent effects in structure of the wintering ecological niche of the mute swan during wintering in the gulf of Sivash. Biological Bulletin of Bogdan Chmelnitskiy Melitopol State Pedagogical University, 6(3), 234–247.


Annicchiarico, P., & Iannucci, A. (2008). Breeding strategy for faba bean in Southern Europe based on cultivar responses across climatically contrasting environments. Crop Science, 48(3), 983–991.


Anselin, L., Ibnu, S., & Youngihn, K. (2005). GeoDa: An introduction to spatial data analysis. Geographical Analysis, 38(1), 5–22.


Antrop, M. (2005). Why landscapes of the past are important for the future. Landscape and Urban Planning, 70, 21–34.


Basso, B., Ritchie, J. T., Cammarano, D., & Sartori, L. (2011). A strategic and tactical management approach to select optimal N fertilizer rates for wheat in a spatially variable field. European Journal of Agronomy, 35, 215–222.


Brown, M. E., & Funk, C. C. (2008). Food security under climate change. Science, 319, 580–581.


Brygadyrenko, V. V., & Nazimov, S. S. (2015). Trophic relations of Opatrum sabulosum (Coleoptera, Tenebrionidae) with leaves of cultivated and uncultivated species of herbaceous plants under laboratory conditions. Zookeys, 481, 57–68.


Cai, W., Borlace, S., Lengaigne, M., Van Rensch, P., Collins, M., Vecchi, G., Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., England, M. H., Wang, G., Guilyardi, E., & Jin, F. F. (2014). Increasing frequency of extreme El Niño events due to greenhouse warming. Nature Climate Change, 4(2), 111–116.


Canadell, J. G., Le Quéré, C., Raupach, M. R., Field, C. B., Buitenhuis, E. T., Ciais, P., Conway, T. J., Gillett, N. P., Houghton, R. A., & Marland, G. (2007). Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proceedings of the National Academy of Sciences, 104(47), 18866–18870.


Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245–276.


Diacono, M., Castrignano, A., Troccoli, A., De Benedetto, D., Basso, B., Rubino, P. (2012). Spatial and temporal variability of wheat grain yield and quality in a Mediterranean environment: A multivariate geostatistical approach. Field Crops Research, 131, 49–62.


Flores, F., Nadal, S., Solis, I., Winkler, J., Sass, O., Stoddard, F. L., Link, W., Raffiot, B., Muel, F., & Rubiales, D. (2012). Faba bean adaptation to autumn sowing under European climates. Agronomy for Sustainable Development, 32(3), 727–734.


Godfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., Pretty, J., Robinson, S., Thomas, S. M., & Toulmin, C. (2010). Food security: The challenge of feeding 9 billion people. Science, 327(5967), 812–818.


Gollini, I., Lu, B., Charlton, M., Brunsdon, C., & Harris, P. (2013). GWmodel: An R package for exploring spatial heterogeneity using geographically weighted models. Journal of Statistical Software, 63(17), 1–52.


Hammond, M. P., & Kolasa, J. (2014). Spatial variation as a tool for inferring temporal variation and diagnosing types of mechanisms in ecosystems. PloS One, 9(2), e89245.


Hansen, J., Ruedy, R., Sato, M., & Lo, K. (2010). Global surface temperature change. Reviews of Geophysics, 48(4), RG4004.


Harris, P., Brunsdon, C., & Charlton, M. (2011). Geographically weighted principal components analysis. International Journal of Geographical Information Science, 25(10), 1717–1736.


Hatzinger, R., Hornik, K., Nagel, H., & Maier, M. J. (2014). R: Einführung durch angewandte statistik (2nd ed.). Pearson Studium, München.


Horn, J. L. (1965). A rationale and a test for the number of factors in factor analysis. Psychometrika, 30, 179–185.


Iqbal, J., Thomasson, J. A., Jenkins, J. N., Owens, P. R., & Whisler, F. D. (2005). Spatial variability analysis of soil physical properties of alluvial soils. Soil Science Society of America Journal, 69(4), 1338–1350.


Jensen, E. S., Peoples, M. B., & Hauggaard-Nielsen, H. (2010). Faba bean in cropping systems. Field Crops Research, 115(3), 203–216.


Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36.


Kamran, A., & Asif, M. (2011). Climate change and crop production. Crop Science, 51(5), 2299.


Kharytonov, M., Babenko, M., Velychko, O., & Pardini, G. (2018). Prospects of medicinal herbs management in reclaimed minelands of Ukraine. Ukrainian Journal of Ecology, 8(1), 527–532.


Kunah, O. M., & Papka, O. S. (2016). Ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca) on the basis of indices of remote sensing of land images. Visnyk of Dnipropetrovsk University. Biology, Ecology, 24(1), 78–86.


Kunah, O. M., & Papka, O. S. (2016). Geomorphological ecogeographical variables definig features of ecological niche of common milkweed (Asclepias syriaca L.). Biological Bulletin of Bogdan Chmelnitskiy Melitopol State Pedagogical University, 1, 243–275.


Li, L. H. C. (2015). Assessing the spatiotemporal dynamics of crop yields and exploring the factors affecting yield synchrony. McMaster University, Hamilton, Ontario.


Lindenmayer, D., Hobbs, R., Montague-Drake, R., Alexandra, J., Bennett, B., Burgman, M., Cale, P., Calhoun, A., Cramer, V., Cullen, P., Driscol, D., Fahrig, L., Fischer, J., Franklin, J., Haila, Y., Hunter, M., Gibbons, P., Lake, S., Luck, G., MacGregor, C., McIntyre, S., Mac Nally, R., Manning, A., Miller, J., Mooney, H., Noss, R., Possingham, H., Saunders, D., Schmiegelow, F., Scott, M., Simberloff, D., Sisk, T., Tabor, G., Walker, B., Wiens, J., Woinarski, J., & Zavaleta, E. (2008). A checklist for ecological management of landscapes for conservation. Ecology Letters, 11(1), 78–91.


Lloyd, C. D. (2010). Analysing population characteristics using geographically weighted principal components analysis: a case study of Northern Ireland in 2001. Computers, Environment and Urban Systems, 34(5), 389–399.


Lobell, D. B. (2007). Changes in diurnal temperature range and national cereal yields. Agricultural and Forest Meteorology, 145, 229–238.


Lobell, D. B., Burke, M. B., Tebaldi, C., Mastrandrea, M. D., Falcon, W. P., & Naylor, R. L. (2008). Prioritizing climate change adaptation needs for food security in 2030. Science, 319, 607–610.


Maamar, B., Nouar, B., Soudani, L., Maatoug, M., Azzaoui, M., Kharytonov, M., Wiche, O., & Zhukov, O. (2018). Biodiversity and dynamics of plant groups of Chebket El Melhassa region (Algeria). Biosystems Diversity, 26(1), 62–70.


Metcalf, R. L. (1980). Changing roles of insecticides in crop protection. Annual Review of Entomology, 25, 219–256.


Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.


Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., Ramankutty, N., & Foley, J. A. (2012). Closing yield gaps through nutrient and water management. Nature, 490(7419), 254–257.


Oerke, E.-C., Dehne, H.-W. (2004). Safeguarding production – losses in major crops and the role of crop protection. Crop Protection, 23(4), 275–285.


Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine, 2(11), 559–572.


Peltonen-Sainio, P., Jauhiainen, L., Trnka, M., Olesen, J. E., Calanca, P., Eckersten, H., Eitzinger, J., Gobin, A., Kersebaum, K. C., Kozyra, J., Kumar, S., Marta, A. D., Micale, F., Schaap, B., Seguin, B., Skjelvåg, A. O., & Orlandini, S. (2010). Coincidence of variation in yield and climate in Europe. Agriculture, Ecosystems and Environment, 139, 483–489.


R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.


Ray, D. K., Gerber, J. S., MacDonald, G. K., & West, P. C. (2015). Climate variation explains a third of global crop yield variability. Nature Communications, 6, 5989.


Rockstrom, J., Steffen, W., Noone, K., Persson, A., Chapin, F. S., Lambin, E. F., Lenton, T. M., Scheffer, M., Folke, C., Schellnhuber, H. J., Nykvist, B., de Wit, C. A., Hughes, T., van der Leeuw, S., Rodhe, H., Sorlin, S., Snyder, P. K., Costanza, R., Svedin, U., Falkenmark, M., Karlberg, L., Corell, R. W., Fabry, V. J., Hansen, J., Walker, B., Liverman, D., Richardson, K., Crutzen, P., & Foley, J. A. (2009). A safe operating space for humanity. Nature, 461, 472–475.


Rohde, R., Muller, R. A., Jacobsen, R., Muller, E., Perlmutter, S., Rosenfeld, A., Wurtele, J., Groom, D., & Wickham, C. (2013). A new estimate of the average earth surface land temperature spanning 1753 to 2011. Geoinformatics and Geostatistics: An Overview, 1, 1.


Roschewitz, I., Gabriel, D., Tscharntke, T., & Thies, C. (2005). The effects of landscape complexity on arable weed species diversity in organic and conventional farming. Journal of Applied Ecology, 42, 873–882.


Tao, F., Yokozawa, M., Liu, J., & Zhang, Z. (2008). Climate – crop yield relationships at provincial scales in China and the impacts of recent climate trends. Climate Research, 38, 83–94.


Tester, M., & Langridge, P. (2010). Breeding technologies to increase crop production in a changingworld. Science, 327, 818–822.


Tscharntke, T., Tylianakis, J., Rand, T., Didham, R., Fahrig, L., Batary, P., Bengtsson, J., Clough, Y., Crist, T., Dormann, C., Ewers, R., Holt, R., Holzschuh, A., Klein, A., Kremen, C., Landis, D., Laurance, W., Lindenmayer, D., Scherber, C., Sodhi, N., Steffan-Dewenter, I., Thies, C., Van der Putten, W., & Westphal, C. (2012). Landscape moderation of biodiversity patterns and processes – eight hypotheses. Biological Review, 87, 661–685.


Turner, M. G. (1990). Spatial and temporal analysis of landscape patterns. Landscape Ecology, 4(1), 21–30.


Turner, M. G., O'Neill, R. V., Gardner, R. H., & Milne, B. T. (1989). Effects of changing spatial scale on the analysis of landscape pattern. Landscape Ecology, 3, 153–162.


Urban, D., Roberts, M. J., Schlenker, W., & Lobell, D. B. (2012). Projected temperature changes indicate significant increase in interannual variability of US maize yields. Climatic Change, 112(2), 525–533.


Zhukov, A. V. (2015). Phytoindicator estimation of the multidimensional scaling of the plant community structure. Biological Bulletin of Bogdan Chmelnitskiy Melitopol State Pedagogical University, 5(1), 69–93.


Zhukov, A. V., Andrusevich, K. V., Lapko, K. V., & Sirotina, V. O. (2015). Geostatistical estimation of soil aggregate structure as a composite variable. Biological Bulletin, 3, 101–121.


Zhukov, A. V., Sirovatko, V. O., & Ponomarenko, N. O. (2017). Spatial dynamic of the agriculture fields towards their shape and size. Ukrainian Journal of Ecology, 7(3), 14–31.


Zhukov, O. V., & Ponomarenko, S. V. (2017). Spatial-temporal dynamics of sunflower yield – the ecological and agricultural approach. Ukrainian Journal of Ecology, 7(3), 186–207.


Zhukov, O. V., Ganzha, D. S., & Dubinina, Y. Y. (2017). Remote sensing modeling of vegetation phylogenetic diversity spatial variation. Ukrainian Journal of Ecology, 7(2), 37–54.


Zhukov, O. V., Kunah, O. M., & Dubinina, Y. Y. (2017). Sensitivity and resistance of communities: Evaluation on the example of the influence of edaphic, vegetation and spatial factors on soil macrofauna. Biosystems Diversity, 25(4), 328–341.


Zhukov, O. V., Pelina, T. O., Demchuk, O. M., Demchuk, N. I., & Koberniuk, S. O. (2018). Agroecological and agroeconomic aspects of the grain and grain legumes (pulses) yield dynamic within the Dnipropetrovsk region (period 1966–2016). Biosystems Diversity, 26(2), 170–176.


Zhukov, O. V., Pisarenko, P. V., Kunah, O. M., & Dichenko, O. J. (2015). Role of landscape diversity in dynamics of abundance of sugar beet pests population in Poltava region. Visnyk of Dnipropetrovsk University. Biology, Ecology, 23(1), 21–27.


Zymaroieva, A. A. (2018). Features of the spatiotemporal trend of grain and grain legumes yields in Forest and Forest-Steppe zone of Ukraine. Bulletin of Poltava State Agrarian Academy, 3, 66–73.


 

Published
2018-11-10
Section
Articles

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.