  Knowledge of galaxy evolution rests on cross-sectional observations of
different objects at different times. Understanding of galaxy evolution rests
on longitudinal interpretations of how these data relate to individual objects
moving through time. The connection between the two is often assumed to be
clear, but we use a simple "physics-free" model to show that it is not, and
that exploring its nuances can yield new insights. Comprising nothing more than
$2094$ loosely constrained lognormal star formation histories (SFHs), the model
faithfully reproduces the following data it was not designed to match: stellar
mass functions at $z\leq8$; the slope of the star formation rate/stellar mass
relation (the SF "Main Sequence") at $z\leq6$; the mean ${\rm sSFR}(\equiv{\rm
SFR}/M_*)$ of low-mass galaxies at $z\leq7$; "fast-" and "slow-track"
quenching; downsizing; and a correlation between formation timescale and ${\rm
sSFR}(M_*; t)$ similar to results from simulations that provides a natural
connection to bulge growth. We take these findings---which suggest that
quenching is the natural downturn of all SFHs affecting galaxies at rates/times
correlated with their densities---to mean that: (1) models in which galaxies
are diversified on Hubble timescales by something like initial conditions rival
the dominant grow-and-quench framework as good descriptions of the data; or (2)
absent spatial information, many metrics of galaxy evolution are too
undiscriminating---if not inherently misleading---to confirm a unique
explanation. We outline future tests of our model but stress that, even if
ultimately incorrect, it illustrates how exploring different paradigms can aid
learning and, we hope, more detailed modeling efforts.
