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Significant clusters, as well as outliers, are color coded by type of spatial autocorrelation.
Counties with significant spatial correlation are color coded by type of spatial autocorrelation.
The LISA cluster map showed those counties with a significant local Moran statistic classified by type of spatial correlation: bright red for the high high association, bright blue for low low, light blue for low high and light red for high low (figure 2).
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These levels appear to be defined by the type of spatial correlation characterized by the sampling correlation matrix R X.
The hot-spot analysis presents a map of the study area that is colour coded by the type of spatial autocorrelation and significance of the observed relationship.
It may be at least partially overcome by giving a semantic value type of spatial information, i.e. associating to the topological definition of an entity, also the semantic information about the characteristics of the attributes that define the various geographic objects.
These results are entirely consistent with those from previous studies in which spatial information was encoded through simultaneous viewing of all object locations, suggesting that the intrinsic reference theory is not specific to a type of spatial memory acquired by the particular learning method but instead generalizes to spatial memories learned through a variety of encoding conditions.
This study also demonstrates that the biomass estimates are primarily driven by the biomass reference data while the type of spatial maps used for their stratification has a smaller, but not negligible, impact.
Lastly, this study demonstrates that the AGB estimates were primarily driven by the biomass reference values while the type of spatial datasets used for their stratification had a smaller, but not negligible, impact.
Thus, while critics of the FFW hypothesis are correct that it neglects key developmental and physiological constraints (reviewed in Calderone and Page 1996; Calderone 1998), it is still likely that the type of spatial effects stressed by the FFW model and the physiological processes of the IDP approach interact to control the dynamics of DOL.
However, collectively these results suggest that it is possible that such a mechanism of "local spread" could be driven by mechanisms that do not involve any type of spatial interaction between the neighboring farms (e.g., introduction from a common source, simultaneous change in management or prevalence of other component causes, or recall bias).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com