Optimal environmental window hypothesis Tomayo 2016

Optimal environmental window hypothesis, explore by interests

Crane observed that the TH held in rainfall fields up to a time scale of around 30 min for spatial scales less than 20 km, after which it broke down.

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In addition, we test the TH for each of the smaller time periods illustrated in Fig. The results inform forest management by illustrating areas in host dominated landscapes that are most susceptible to defoliation in a given year, allowing for improved planning of insect optimal environmental window hypothesis activities.

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This is consistent with the mean wind plotted in Fig. That time scale is related to the life cycles of convective cells in the region.

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Significant spatial heterogeneity in phenological asynchrony clarifies its potential to affect gypsy moth population dynamics and patterns of defoliation disturbance, in contrast with previous field-based research conducted at smaller spatial scales. TH is also of interest for many other fields such as the cloud and radiation test bed measurements Sun and Thorne other than rainfall.

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It is important to mention here that although the curves do appear close especially at smaller time lagsthe error bars not shown around the mean correlations corresponding to the shortest time lag of 15 min are small and do not overlap, thereby indicating that the curves are indeed statistically different.

Of specific interest is whether there is a cutoff francesco sottile phd thesis decorrelation time scale for which the TH holds for a given mean flow velocity v. The larger effect appears to come via income itself: