To reduce our gaps in knowledge there is a need for greater coordination between European research programs, particularly in standardization of sampling techniques and analysis of data, for large-scale spatial and temporal patterns to be fully understood.
Indeed, intraspecific and interspecific body size frequency distributions have played important roles in the development of these fields, and particularly of macroecology, which regularly adopts univariate (i.e. frequency distribution-based), bivariate and then multivariate perspectives to understanding large-scale spatial and temporal variation in body size, range size and abundance [8].
Therefore, to dissect the functional significance of these massive forebrain projections and visualize the large-scale spatial and temporal dynamics evoked by central thalamus stimulation, we combined optical stimulation with simultaneous in vivo whole-brain functional imaging (Lee et al., 2010).
Our results and previous studies [ 47, 68] suggest a determinant effect of gaping on the small and large scale spatial distributions of P. perna lineages.
We used the coefficient of dispersion (C D = s 2 X ¯ ), a commonly used as a measure of spatial clustering, to look at large scale spatial patterns of both genes and clusters.
Antigen recognition by T cells involves large scale spatial reorganization of numerous receptor, adhesion, and costimulatory proteins within the T cell-antigen presenting cell (APC) junction.
The foraging bees were allowed to learn the larger scale spatial setting of their hive location and empty "dummy" hive boxes for 4 days.
Finally, understanding connections between settlements by human movements is needed to determine the paths and speed of large-scale spatial spread and therefore the total infected area and domain for surveillance and monitoring.
Given the air quality monitoring, meteorological, geographic, and other data available from 1988 2007, our modeling approach provides a reasonable balance of computational feasibility (using standard software) and complexity while representing the small- and large-scale spatial, temporal, and spatio-temporal features of the data.
The TASC intervention targets perspective taking because of the correlations between perspective taking and large-scale spatial cognition and map reading (Hegarty & Waller, 2004; Liben & Downs, 1993).
To address these limitations, we estimated monthly PM2.5 and PM10 2.5 concentrations using spatiotemporal models that incorporated both small- and large-scale spatial trends, and that allowed these trends to change over time.
