scholarly journals Socio-spatial interactions of a cluster-house concept apartment in mehr als wohnen project in Zurich, Switzerland

Author(s):  
Maryam Khatibi
Keyword(s):  
2012 ◽  
Vol 9 (5) ◽  
pp. 1647-1660 ◽  
Author(s):  
J.-L. Drouet ◽  
S. Duretz ◽  
P. Durand ◽  
P. Cellier

Abstract. Spatial interactions within a landscape may lead to large inputs of reactive nitrogen (Nr) transferred from cultivated areas and farms to oligotrophic ecosystems and induce environmental threats such as acidification, nitric pollution or eutrophication of protected areas. The paper presents a new methodology to estimate Nr fluxes at the landscape scale by taking into account spatial interactions between landscape elements. This methodology includes estimates of indirect Nr emissions due to short-range atmospheric and hydrological transfers. We used the NitroScape model which integrates processes of Nr transformation and short-range transfer in a dynamic and spatially distributed way to simulate Nr fluxes and budgets at the landscape scale. Four configurations of NitroScape were implemented by taking into account or not the atmospheric, hydrological or both pathways of Nr transfer. We simulated Nr fluxes, especially direct and indirect Nr emissions, within a test landscape including pig farms, croplands and unmanaged ecosystems. Simulation results showed the ability of NitroScape to simulate patterns of Nr emissions and recapture for each landscape element and the whole landscape. NitroScape made it possible to quantify the contribution of both atmospheric and hydrological transfers to Nr fluxes, budgets and indirect Nr emissions. For instance, indirect N2O emissions were estimated at around 21% of the total N2O emissions. They varied within the landscape according to land use, meteorological and soil conditions as well as topography. This first attempt proved that the NitroScape model is a useful tool to estimate the effect of spatial interactions on Nr fluxes and budgets as well as indirect Nr emissions within landscapes. Our approach needs to be further tested by applying NitroScape to several spatial arrangements of agro-ecosystems within the landscape and to real and larger landscapes.


1982 ◽  
Vol 14 (7) ◽  
pp. 869-888 ◽  
Author(s):  
P F Lesse

This paper deals with a class of models which describe spatial interactions and are based on Jaynes's principle. The variables entering these models can be partitioned in four groups: (a) probability density distributions (for example, relative traffic flows), (b) expected values (average cost of travel), (c) their duals (Lagrange multipliers, traffic impedance coefficient), and (d) operators transforming probabilities into expected values. The paper presents several dual formulations replacing the problem of maximizing entropy in terms of the group of variables (a) by equivalent extreme problems involving groups (b)-(d). These problems form the basis of a phenomenological theory. The theory makes it possible to derive useful relationships among groups (b) and (c). There are two topics discussed: (1) practical application of the theory (with examples), (2) the relationship between socioeconomic modelling and statistical mechanics.


2006 ◽  
Vol 46 (8-9) ◽  
pp. 1302-1306 ◽  
Author(s):  
Tzvetomir Tzvetanov ◽  
Lidwine Simon

2014 ◽  
Vol 71 (6) ◽  
pp. 1342-1355 ◽  
Author(s):  
Xochitl Cormon ◽  
Christophe Loots ◽  
Sandrine Vaz ◽  
Youen Vermard ◽  
Paul Marchal

Spatial interactions between saithe (Pollachius virens) and hake (Merluccius merluccius) were investigated in the North Sea. Saithe is a well-established species in the North Sea, while occurrence of the less common hake has recently increased in the area. Spatial dynamics of these two species and their potential spatial interactions were explored using binomial generalized linear models (GLM) applied to the International Bottom Trawl Survey (IBTS) data from 1991 to 2012. Models included different types of variables: (i) abiotic variables including sediment types, temperature, and bathymetry; (ii) biotic variables including potential competitors and potential preys presence; and (iii) spatial variables. The models were reduced and used to predict and map probable habitats of saithe, hake but also, for the first time in the North Sea, the distribution of the spatial overlap between these two species. Changes in distribution patterns of these two species and of their overlap were also investigated by comparing species’ presence and overlap probabilities predicted over an early (1991–1996) and a late period (2007–2012). The results show an increase in the probability over time of the overlap between saithe and hake along with an expansion towards the southwest and Scottish waters. These shifts follow trends observed in temperature data and might be indirectly induced by climate changes. Saithe, hake, and their overlap are positively influenced by potential preys and/or competitors, which confirms spatial co-occurrence of the species concerned and leads to the questions of predator–prey relationships and competition. Finally, the present study provides robust predictions concerning the spatial distribution of saithe, hake, and of their overlap in the North Sea, which may be of interest for fishery managers.


Blood ◽  
2018 ◽  
Vol 132 (25) ◽  
pp. 2643-2655 ◽  
Author(s):  
Daniel Schuetzmann ◽  
Carolin Walter ◽  
Boet van Riel ◽  
Sabrina Kruse ◽  
Thorsten König ◽  
...  

Abstract Epigenetic control of gene expression occurs within discrete spatial chromosomal units called topologically associating domains (TADs), but the exact spatial requirements of most genes are unknown; this is of particular interest for genes involved in cancer. We therefore applied high-resolution chromosomal conformation capture sequencing to map the three-dimensional (3D) organization of the human locus encoding the key myeloid transcription factor PU.1 in healthy monocytes and acute myeloid leukemia (AML) cells. We identified a dynamic ∼75-kb unit (SubTAD) as the genomic region in which spatial interactions between PU.1 gene regulatory elements occur during myeloid differentiation and are interrupted in AML. Within this SubTAD, proper initiation of the spatial chromosomal interactions requires PU.1 autoregulation and recruitment of the chromatin-adaptor protein LDB1 (LIM domain–binding protein 1). However, once these spatial interactions have occurred, LDB1 stabilizes them independently of PU.1 autoregulation. Thus, our data support that PU.1 autoregulates its expression in a “hit-and-run” manner by initiating stable chromosomal loops that result in a transcriptionally active chromatin architecture.


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