Results 101 to 110 of about 360,351 (166)

Correction: Quantifying spatial variability in shell midden formation in the Farasan Islands, Saudi Arabia. [PDF]

PLoS One
Hausmann N, Meredith-Williams M, Douka K, Inglis RH, Bailey G.   +4 more
europepmc   +1 more source

Temporal and spatial variability of dynamic microstate brain network in disorders of consciousness. [PDF]

CNS Neurosci Ther
Li Y, Gao J, Yang Y, Zhuang Y, Kang Q, Li X, Tian M, Lv H, He J.   +8 more
europepmc   +1 more source

New insights into the spatial variability of microbial diversity and density in peatlands exposed to various electron acceptors with an emphasis on methanogenesis and CO₂ fluxes. [PDF]

Front Microbiol
Shabbir S, Qian C, Faheem M, Zhou F, Yu ZG.   +4 more
europepmc   +1 more source

Spatial variability of heavy metals concentrations in soil of auto-mechanic workshop clusters in Nsukka, Nigeria. [PDF]

Sci Rep
Duru SC, Echiegu EA, Anyadike CC, Alaneme GU, Okechukwu ME.   +4 more
europepmc   +1 more source

Spatial variability in herbaceous plant phenology is mostly explained by variability in temperature but also by photoperiod and functional traits. [PDF]

Int J Biometeorol
Rauschkolb R, Bucher SF, Hensen I, Ahrends A, Fernández-Pascual E, Heubach K, Jakubka D, Jiménez-Alfaro B, König A, Koubek T, Kehl A, Khuroo AA, Lindstädter A, Shafee F, Mašková T, Platonova E, Panico P, Plos C, Primack R, Rosche C, Shah MA, Sporbert M, Stevens AD, Tarquini F, Tielbörger K, Träger S, Vange V, Weigelt P, Bonn A, Freiberg M, Knickmann B, Nordt B, Wirth C, Römermann C.   +33 more
europepmc   +1 more source

Spatial variability in Arctic-boreal pyroregions shaped by climate and human influence

Scholten R, Veraverbeke S, Chen Y, Randerson J.   +3 more
europepmc   +1 more source

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Spatially implicit plankton population models: Transient spatial variability

Journal of Theoretical Biology, 2008
Ocean plankton models are useful tools for understanding and predicting the behaviour of planktonic ecosystems. However, when the regions represented by the model grid cells are not well mixed, the population dynamics of grid cell averages may differ from those of smaller scales (such as the laboratory scale). Here, the 'mean field approximation' fails
Wallhead, Philip J., Martin, Adrian P., Srokosz, Meric A.   +2 more
openaire   +4 more sources

Spatial Variability of Runoff

Journal of Irrigation and Drainage Engineering, 1984
Forty contiguous plots (each 27.5m×3.2m) were maintained in a cultivated fallow condition during spring and summer 1981. Twenty‐six runoff events were measured during that period. The runoff variability as expressed by differences between plots was analyzed.
Allen T. Hjelmfelt, Robert E. Burwell
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Joint variable spatial downscaling

Climatic Change, 2011
Joint Variable Spatial Downscaling (JVSD), a new statistical technique for downscaling gridded climatic variables, is developed to generate high resolution gridded datasets for regional watershed modeling and assessments. The proposed approach differs from previous statistical downscaling methods in that multiple climatic variables are downscaled ...
Feng Zhang, Aris P. Georgakakos
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Spatial image variability analysis

The 2002 45th Midwest Symposium on Circuits and Systems, 2002. MWSCAS-2002., 2003
In our analysis, each image is partitioned into a number of non-overlapping, spatial regions. Each spatial region is viewed as a Region of Interest (ROI). A grade is assigned to each ROI from a set of independent raters. The model is applied in lung image analysis, where a grade of 0/1 is assigned to each ROI.
M.S. Pattichis, T. Cacoullos, P. Soliz
openaire   +1 more source