Corrado Ievoli, Roberto Giovanni Basile and Angelo Belliggiano
. & Andersson, C. (2014). Spatialpatterns of organic agriculture adoption: Evidence from Honduras. Ecological Economics 97, 120-128. DOI: 10.1016/j.ecolecon.2013.11.010.
 Xingbai, X. & Lee L. (2015). Maximum likelihood estimation of a spatial autoregressive Tobit model, Journal of Econometrics 188(1), 264-280. DOI: 10.1016/j.jeconom.2015.05.004.
 Zimmermann, A. & Heckelei, T. (2012). Structural Change of European Dairy Farms - A Cross-Regional Analysis. Journal of Agricultural Economics 63(3), 576-603. DOI: 10.1111/j.1477
Using hierarchical cluster analysis there were distinguished six spatial patterns of bird communities during the breeding season in the Lower Dnieper Sands. The differentiation of these patterns is based on a spatial heterogeneity in the area ratio of different habitats. The sites with natural and sub-natural landscapes hold three types of bird communities. Another type of the bird community is relatively similar to the previous three, but characterized by a poor quantitative and qualitative bird composition; it is associated with open landscapes with destroyed natural vegetation. Bird communities of artificial pine plantations (the most transformed landscapes of the Lower Dnieper Sands) are very different from those in the natural and sub-natural landscapes. The spectra of ecological groups of different bird communities match the spectra of different habitat types obtained using a supervised classification of remote sensing data. It makes it possible to use a topological model of the habitat types (based on remote sensing data) as a predictor for GIS modelling of spatial distribution of different birds communities throughout the Lower Dnieper Sands.
Currently, the native residents of a country are an important social phenomenon. Although extensive mobility challenges the bonds between places and their inhabitants, biographies of native residents are less often based in several spatial contexts because they are born and raised in a specific place and live there for their entire lives. This absence of residential mobility has important consequences for the ways native residents relate to their ‘home places’ and how they build local attachments. Using data from the Czech Republic, the main objective of this paper is to explore and analyse recent developments in the structure of native residents. The objects of analysis are the municipalities of the Czech Republic, and aggregate census data are used for the purpose of analysis. Spatial and non-spatial approaches to the analysis showed significant changes in the structure of native residents, revealing statistically significant spatial patterns. In general, the residents of Czech municipalities demonstrate levels of co-residence or ‘mixing’ in a significant way in recent years. Thus, further research into matters such as spatial belonging, attachment and identity should also take into account the influence of mobility.
Ondřej Slach, Igor Ivan, Jan Ženka and Andrej Sopkuliak
and cluster reproduction in Dutch architectural design. Regional Studies 44: 859-871.
Kunc J, Martinát S, Tonev P, Frantál B (2014) Destiny of urban brownfields: Spatialpatterns and perceived consequences of post-socialistic deindustrialization. Transylvanian Review of Administrative Sciences 41: 109–128.
Kuta V, Kuda F, Sedlecký J (2005) Černá louka–první poválečný brownfield v Ostravě. Urbanismus a územní rozvoj 8: 10–15.
Lazzaretti L, Boix R, Capone F (2008) Do creative industries cluster? Mapping creative local production systems in Italy and
Tomáš Orfánus, Dagmar Stojkovová, Kálmán Rajkai, Henryk Czachor and Renáta Sándor
.G.M., Oostindie, K., Nieber, J.L., 1997. Recurring fingered flow pathways in a water repellent sandy field soil. Hydrology and Earth System Sciences, 4, 777–786.
Ritsema, C.J., van Dam, J.C., Dekker, L.W., Oostindie, K., 2005. A new modelling approach to simulate preferential flow and transport in water repellent porous media: Model structure and validation. Australian Journal of Soil Research, 43, 361–369.
Schlesinger, W.H., Raikes, J.A., Hartley, A.E., Cross, A.F., 1996. On the spatialpattern of soil nutrients in desert ecosystem. Ecology, 77, 364–374.
Bożenna Czarnecka, Anna Rysiak and Łukasz Chabudziński
Ellenberg’s indicator values for Mediterranean plants be used outside their region of definition? J. Biogeogr. 34: 62–68.
G rabs T., S eibert J., B ishop K. & L audon H. 2009. Modeling spatialpatterns of saturated areas: A comparison of the topographic wetness index and a dynamic distributed model. J. Hydrol. 373: 15-23. http://dx.doi.org/10.1016/j.jhydrol.2009.03.031
H engl T. 2006. Finding the right pixel size. Comp. Geosci. 32: 1283-1298. http://dx.doi.org/10.1016/j.cageo.2005.11.008
H utchinson M. F. 1989. A new procedure for gridding
Zdeněk Vacek, Stanislav Vacek, Lukáš Bílek, Jan Král, Iva Ulbrichová, Jaroslav Simon and Daniel Bulušek
development, Central Bohemia. Forest Systems, 20:122–138.
Bulušek, D., Vacek, Z., Vacek, S., Král, J., Bílek, L., Králíček, I., 2016: Spatialpattern of relict beech ( Fagus sylvatica L.) forests in the Sudetes of the Czech Republic and Poland. Journal of Forest Science, 62:293–305.
Burrascano, S., Sabatini, F. M., Blasi, C., 2011: Testing indicators of sustainable forest management on understorey composition and diversity in southern Italy through variation partitioning. Plant Ecology, 212:829–841.
Clark, P. J., Evans, F. C., 1954: Distance to nearest
David Fiedor, Zdeněk Szczyrba, Miloslav Šerý, Irena Smolová and Václav Toušek
BINDE, P. (2013): Why people gamble: A model with five motivational dimensions. International Gambling Studies, 13: 81–97.
BROWN, M. C. (1994): Using gini-style indices to evaluate the spatialpatterns of health practitioners: Theoretical considerations and an application based on Alberta data. Social Science and Medicine, 38(9): 1243–1256.
Czech Statistical Office (2015): Veřejná databáze Českého statistického úřadu [online]. [cit. 15.01.2016]. Available at: https://vdb.czso.cz/vdbvo2/faces/cs/index.jsf?page=statistiky
DIAZ, J. D. (2000): Religion
Oleksandr V. Zhukov, Olga M. Kunah, Yuliya Y. Dubinina, Marina P. Fedushko, Vadim I. Kotsun, Yuliya O. Zhukova and Olena V. Potapenko
(1): 1–10. https://doi.org/10.1038/ncomms9444
K ing , A. W., W ith , K. A., 2002. Dispersal success on spatially structured landscapes: when do spatialpattern and dispersal behavior really matter? Ecological Modelling , 147 (1): 23–39. https://doi.org/10.1016/S0304-3800(01)00400-8 .
K rivolutsky , D.A., 1994. Pochvennaja fauna v jekologicheskom kontrole [ Soil fauna in ecological control ]. Moscow: Nauka. 240 p.
L avelle , P., S enapati , B., B arros , E., 2003. Soil macrofauna. In Schroth, G., Sinclair, F.L. (eds). Trees, crops and soil