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Similar to above, I quantified two morphological divergence vectors, one for the population effect (population divergence vector) and one for the treatment effect (predator divergence vector).
Similarly, population (= 0.44), treatment (= 0.19), and parents (= 0.14) had significant effects on the predator divergence vector.
I first reduced the dimensionality of the 11 shape variables by calculating morphological divergence scores for each individual along the stream reservoir gradient based on a divergence vector (referred to as habitat divergence vector hereafter) as defined by Langerhans (2009).
Testing the population divergence vector revealed that population-of-origin had the strongest effect (= 0.37) followed by parents (= 0.20).
I also assessed individual landmark movement between habitat types by quantifying correlation coefficients between landmark positions and the habitat divergence vector scores of field-collected specimens.
The ANCOVA testing the habitat divergence vector demonstrated similar results (Table 2); however, habitat (= 0.37) and population (= 0.22) had the strongest effects followed by basin and centroid size.
Similar(51)
The ANCOVAs testing effects on the population and predator divergence vectors offered similar results.
Population-of-origin had strong effects on overall shape variation as well as the population and predator divergence vectors.
The regions of maximal MEP response were calculated by the divergence vectors from three different scalp fiducial markers.
The average deviation vector composes of divergences in all three spatial directions.
Both equations require field evaluation of constrained (divergence free) vector valued quantities (velocity, vorticity) and cross terms from these.
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