spatial factors
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2022 ◽  
Vol 85 ◽  
pp. 102408
Bishal Bharadwaj ◽  
Yuwan Malakar ◽  
Mathew Herington ◽  
Peta Ashworth

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3448
Seid Tiku Mereta ◽  
Pieter Lemmens ◽  
Luc De Meester ◽  
Peter L. M. Goethals ◽  
Pieter Boets

The present study investigates the relative importance of human disturbance, local environmental and spatial factors on variations in bird community composition in natural Ethiopian wetlands with high biodiversity conservation value. We quantified bird abundances, local environmental variables and human disturbances at 63 sites distributed over ten wetlands in two subsequent years. Variation partitioning analyses were used to explore the unique and shared contributions of human disturbance, local environmental variables and spatial factors on variations in community compositions of wetland bird species. Local environmental variables explained the largest amount of compositional variation of wetland bird species. Productivity-related variables were the most important local environmental variables determining bird community composition. Human disturbance was also an important determinant for wetland bird community composition and affected the investigated communities mainly indirectly through its effect on local environmental conditions. Spatial factors only played a minor role in variations in bird community composition. Our study highlights the urgent need for integrated management approaches that consider both nature conservation targets and socio-economic development of the region for the sustainable use and effective conservation of wetland resources.

2021 ◽  
Vol 29 (4) ◽  
pp. 23-35
Katarzyna Kobylińska

Abstract The spatial distribution of real estate in specific geographic locations, real estate transactions, and the prices and values of properties are a highly complex spatial phenomena that should be analyzed with the use of multidimensional methods. Spatial factors are taken into account in the modeling process to increase the reliability of real estate market analyses, and spatial autoregressive models are applied to determine the effect of spatial factors on real estate prices and values. The present study relies on a review of the literature and the results of an experiment. The concept and principles of market analysis were designed with the use of spatial autoregressive models, and the influence of selected spatial factors on real estate prices was presented on maps. Analyses involving autoregressive models enable reliable modeling and support correct interpretation of the observed processes.

2021 ◽  
Vol 10 (37) ◽  
pp. 83-98
Ashkan Jafari Karimi ◽  
Ismaeil Ali Akbari ◽  
Mostafa Taleshi

2021 ◽  
Vol 1 (1) ◽  
Xiaonan Liu ◽  
Miaoxiao Wang ◽  
Yong Nie ◽  
Xiao-Lei Wu

AbstractMany organisms live in habitats with limited nutrients or space, competition for these resources is ubiquitous. Although spatial factors related to the population’s manner of colonizing space influences its success in spatial competition, what these factors are and to what extent they influence the outcome remains underexplored. Here, we applied a simulated competitive model to explore the spatial factors affecting outcomes of competition for space. By quantifying spatial factors, we show that colonizing space in a more dispersed manner contributes to microbial competitive success. We also find that the competitive edge deriving from a more dispersed manner in colonization can compensate for the disadvantage arising from either a lower growth rate or lower initial abundance. These findings shed light on the role of space colonization manners on maintaining biodiversity within ecosystems and provide novel insights critical for understanding how competition for space drives evolutionary innovation.

2021 ◽  
Zhe Xiao ◽  
Hua Li ◽  
Xiaochuang Li ◽  
Renhui Li ◽  
Shouliang Huo ◽  

Abstract Disentangling the relative contributions of deterministic and stochastic processes were critical to compressive understanding of underlying mechanism governing geographic pattern and assembly of phytoplankton community, while it was seldom performed in connected lakes under human pressure. Here, we investigated phytoplankton community pattern in relation to environmental and spatial factors over 81 lakes located in middle and lower reaches of Yangtze River (MLYR) floodplain, where many lakes suffered eutrophication and cyanobacterial blooms. A majority of MLYR lakes had higher phytoplankton abundance surpassing 107 cells/L, and were dominated by common bloom-forming cyanobacterial genera, including Pseudanabaena, Microcystis, Merismopedia, Dolichospermum, Limnothrix, and Raphidiopsis. Phytoplankton community exhibited a striking geographical pattern both for taxonomic and functional compositions, while functional groups were less sensitive and disimmilarity in communities displayed no significant increases with increasing geographical distance. Further, species richness explained much higher percentage of community variations than species turnover, indicating a reduced effect of environmental filtering of phytoplankton species with tolerance to similar environments in connected MLYR lakes. Both deterministic and stochastic processes governed assembly and biogeographic of phytoplankton community. Variation partition analysis showed spatial factors exhibited greater influence on phytoplankton community compared to environmental variables. The stronger influence of spatial factors was further demonstrated by Mantel test and neutral community model. These findings indicate deterministic and stochastic processes exhibited similar biogeographic patterns for phytoplankton community in MLYR lakes, but stochastic process was overwhelmingly dominated. Moreover, a large proportion of unexplained variation implies complex interactions exist to shape assembly mechanism of phytoplankton community in MLYR lakes.

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