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: impact of chamber disturbance, spatial variability and seasonal evolution. Global Change Biology 6: 907–917. DOI 10.1046/j.1365-2486.2000.00369.x. Matuszkiewicz J.M. 1995. Potencjalna roślinność naturalna Polski. Mapa przeglądowa 1:300 000. Arkusz 8: Wzniesienia Południowomazowieckie i Wyżyna Środkowomałopolska. Polska Akademia Nauk. Warszawa Moncrieff J.B., Fang C. 1999. A model for soil CO 2 production and transport 2: Application to a Florida Pinus elliotte plantation. Agricultural and Forest Meteorology 95: 237–256. DOI 10.1016/S0168

Assessment and Management of Risk for Engineered Systems and Geohazards, DOI: 10.1080/17499518.2013.871189. [14] L umb P., The variability of natural soils , Canadian Geotechnical Journal, 1966, 3(2), 74–97. [15] L umb P., Safety factors and the probability distributions of soil strength , Canadian Geotechnical Journal, 1970, 7(3), 225–242. [16] L umb P., Spatial variability of soil properties , Proc. 2nd Int. Conf. on Appl. of Statistics and Probability in Soil and Struct. Eng. (ICASP) Aachen, 1975, Vol. II, 397–422. [17] P uła W., Zastosowanie teorii


Spatial environmental heterogeneity are well known characteristics of field forest genetic trials, even in small experiments (<1ha) established under seemingly uniform conditions and intensive site management. In such trials, it is commonly assumed that any simple type of experimental field design based on randomization theory, as a completely randomized design (CRD), should account for any of the minor site variability. However, most published results indicate that in these types of trials harbor a large component of the spatial variation which commonly resides in the error term. Here we applied a two-dimensional smoothed surface in an individual-tree mixed model, using tensor product of linear, quadratic and cubic B-spline bases with different and equal number of knots for rows and columns, to account for the environmental spatial variability in two relatively small (i.e., 576 m2 and 5,705 m2) forest genetic trials, with large multiple-tree contiguous plot configurations. In general, models accounting for site variability with a two-dimensional surface displayed a lower value of the deviance information criterion than the classical RCD. Linear B-spline bases may yield a reasonable description of the environmental variability, when a relatively small amount of information available. The mixed models fitting a smoothed surface resulted in a reduction in the posterior means of the error variance (σ2 e), an increase in the posterior means of the additive genetic variance (σ2 a) and heritability (h 2 HT), and an increase of 16.05% and 46.03% (for parents) or 11.86% and 44.68% (for offspring) in the accuracy of breeding values, respectively in the two experiments.

REFERENCES AHMED, EL-KADI.: Variation of Rainfall and Drought Conditions in Gaza-Palestine: on a Regional and Global Context. Journal of Islamic University Vol. 9-No.2:41-66, 2001. ALEMI, M.H., SHARIARI, M.R., NIELSON, D.R.: Kriging and co-kriging of soil water properties. Soil Technology, 1:117-132, 1998. BRAUD, I., HAVERKAMP, R., ARRUE, J.L., LOPEZ, M.V.: Spatial variability of soil surface properties and consequences for the annual and monthly water balance of a semiarid environment (EFEDA Experiment). Journal of Hydrometeorology, 4:121–137, 2003. CAMBARDELLA

mineral soils: a review. International Agrophysics 27: 335–350. Bielska A., Jaroszewicz J., 2012. Review of methods using fuzzy functions and multi-criteria analyses for the development of digital soil-agricultural maps. Acta Scientiarum Polonorum – Geodesia et Descriptio Terrarum 11 (2): 5–15 (in Polish). Bombasaro E., Kasper T., 2016. Evaluation of spatial soil variability in the Pearl River Estuary using CPTU data. Soils and Foundations 56 (3): 496–505. Bong T., Son Y., Noh S., Park J., 2014. Probabilistic analysis of consolidation that considers spatial variability

. Oxford University Press, New York, 448 pp. Domińczak, P. & Okupny, D., 2010. Przestrzenne zróżnicowanie wybranych właściwości fizykoche micznych osadów biogenicznych torfowiska Kopanicha koło Skierniewic. [Spatial variability of selected physicochemical properties of biogenic sediments in the Kopanicha peatland near Skierniewice]. [In:] R.Twardosz & W. Ziaja (Ed.): Prace Geograficzne, Jagiellonian University, Kraków, 99-110 (in Polish) Dobrowolska, B., 2006. Analiza struktury i przeciętnego poziomu cechy. [In]: W. Starzyńska (Ed.): Podstawy statystyki [ Statistical

. 96–114. E l -R aey M. 2009. Impact of climate change: Vulnerability and adaptation of coastal areas. Report of the Arab Forum for Environment and Development. Eds M.K. Tolba, N.W. Saab. Beirut, Lebanon. AFED p. 47–62. E llouze M. 2010. Development of a triangular modelfor the generation of synthetic hyetographs and spatiotemporal characterization of drought in central and southern Tunisia. PhD Thesis. Tunis, Tunisia. Faculty of Science Sfax pp. 182. E llouze M., A zri C., A bida H. 2009. Spatial variability of monthly and annual rainfall data over Southern

, Hungary. International Journal of Climatolology, 25(3): 405–418. CRESSIE, N. A. C. (1993): Statistics for spatial data. Revised edition. Wiley series in probability and mathematical statistics. New York, John Wiley & Sons. DOBROVOLNÝ, P. (2012): The surface urban heat island in the city of Brno (Czech Republic) derived from land surface temperatures and selected reasons for its spatial variability. Theoretical and Applied Climatology, 112(1–2): 89–98. DOBROVOLNÝ, P., KRAHULA, L. (2012): Vliv geometrie zástavby na pole teploty vzduchu a intenzita tepelného ostrova města

bulk snow properties in northern boreal and tundra environments based on extensive field measurements. Geoscientific Instrumentation, Methods and Data Systems, 5, 2, 347-363. DOI: 10.5194/gi-5-347-2016. Holko, L., Sokratov, S.A., Shmakin, A.B., Kostka, Z., 2009. Simulation of snow water equivalent by mathematical models of different complexity. Materialy glyatsiologicheskikh issledovanii [Data on glaciological studies], 107, 72-80. Kronholm, K., Schneebeli, M., Schweizer, J., 2004. Spatial variability of micropenetration resistance in snow layers on a small slope

. Iss. 1 p. 80–92. FAO 2006. Guidelines for soil description (4 th ed.). Rome, Italy. Food and Agriculture Organisation. ISBN 92-5-105521-1 pp. 97. F iener P., D lugob V., K orres W., S chneider K. 2012. Spatial variability of soil respiration in a small agricultural watershed – Are patterns of soil redistribution important? Catena. Vol. 94 p. 3–16. F irehun Y., T amado T. 2006. Weed flora in the Rift Valley sugarcane plantations of Ethiopia as influenced by soil types and agronomic practises. Weed Biology and Management. Vol. 6. Iss. 3 p. 139–150. G aldos M