Determinants of Spatial Distribution of Organic Farming in Germany

The share of organically managed land is spread unevenly throughout Germany and shows pronounced regional concentrations. The spatial distribution of organic farming is assumed to be influenced by several factors. Location factors of farms are regionally different and thus may influence the spatial distribution of organic farming. Agglomeration effects and therefore spatial dependence are also considered important in determining spatial distribution. These factors with a potential influence on the spatial distribution of organic farming can be divided into four categories: natural factors, farm-structure factors, socio-economic factors and political factors. Their possible influence on the spatial distribution of organic farming is analysed by several statistical methods: ordinary least square regression model, spatial autoregressive models, analysis of variance and Spearman correlation. Of the analysed factors, spatial contiguity has the strongest influence on the spatial distribution of organic farming (indicating relevant agglomeration effects)

Spatial Distribution of Dicotyledonous Weed Architectures in a Shrub Vegetation of Menggala, Central Java

B. SUNARNO & F. HALLE. 1986. Distiibusi spasial model arsitektur gulma dikotil di daerah vegetasi semak, Menggala, Jawa Tengah. Berita Biologi 3(6): 253 - 260. Ketapatan dan frekuensi kehadiran model-model arsitektur gulma dikotil di daerah vegetasi semak Menggala, Jawa Tengah telah dipelajari.Model CHAMPAGNAT yang diwakili oleh Mimosa invisa dan Rubus chrysophyllus merupakan model yang nilai kerapatannya paling tinggi (17,97%) dan merupakan pola pertumbuhan yang umum dijumpai di setiap stratum.Semakin tinggi tingkat stratumnya semakin rendah jumlah model dan jumlah individunya. Perbandingan antara gulma masa mendatang dengan gulma masa kini di daerah semak ini, adalah 3 : 2, menunjukkan a,danya proses suksesi yang sedang berjala

Modelling the spatial distribution of DEM Error

Assessment of a DEM’s quality is usually undertaken by deriving a measure of DEM accuracy – how close the DEM’s elevation values are to the true elevation. Measures such as Root Mean Squared Error and standard deviation of the error are frequently used. These measures summarise elevation errors in a DEM as a single value. A more detailed description of DEM accuracy would allow better understanding of DEM quality and the consequent uncertainty associated with using DEMs in analytical applications. The research presented addresses the limitations of using a single root mean squared error (RMSE) value to represent the uncertainty associated with a DEM by developing a new technique for creating a spatially distributed model of DEM quality – an accuracy surface. The technique is based on the hypothesis that the distribution and scale of elevation error within a DEM are at least partly related to morphometric characteristics of the terrain. The technique involves generating a set of terrain parameters to characterise terrain morphometry and developing regression models to define the relationship between DEM error and morphometric character. The regression models form the basis for creating standard deviation surfaces to represent DEM accuracy. The hypothesis is shown to be true and reliable accuracy surfaces are successfully created. These accuracy surfaces provide more detailed information about DEM accuracy than a single global estimate of RMSE

Spatial Distribution of Planktonic Dinoflagellate in Makassar Waters, South Sulawesi

The objectives of this study were to determine the harmful species of dinoflagellates, to determine the concentration of nutriens in surface waters, and to analyze factors affecting the ecological aspects of the harmful dinoflagellates. The results showed that there were 7 genus of dinoflagellates found in this study i.e., Ceratium spp., Gymnodinium sp., Dinophysis sp., Gonyaulax sp., Noctiluca sp., Protoperi-dinium spp., and Peridinium sp. Protoperidinium spp. and Ceratium spp. were the predominant species, with their abundance ranged of 9-659 cells/L and 6-556 cells/L, respectively. In temporal scale, values of DO and water light penetration were not significantly different (α>0.05), while for the parameter of nutriens, salinity, and abundance were significantly different (α<0.05). Total abundance of dinoflagellates was significantly correlated with nitrate, nitrite, ammonia, phosphate, salinity, and DO. Harmful dinoflagellate species such as Dinophysis sp. (DSP), Gymnodinium spp. (NSP and PSP), Noctiluca sp. (anaerobic), and Gonyaulax sp. (anaerobic) were observed in the study area. The high concentration of ammonia (>1 mg/L) in the waters of Losari beach also indicated that the area was affected by anthropogenic activities. Minimizing nutrient inputs from the land was becoming the most priority measure to be done to avoid such effects related to dinoflagellate harmful algae bloms

The Anisotropic Spatial Distribution of Hypervelocity Stars

We study the distribution of angular positions and angular separations of unbound hypervelocity stars (HVSs). HVSs are spatially anisotropic at the 3-sigma level. The spatial anisotropy is significant in Galactic longitude, not in latitude, and the inclusion of lower velocity, possibly bound HVSs reduces the significance of the anisotropy. We discuss how the observed distribution of HVSs may be linked to their origin. In the future, measuring the distribution of HVSs in the southern sky will provide additional constraints on the spatial anisotropy and the origin of HVSs.Comment: 4 pages, accepted to ApJ Letter