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We compared metagenomes from four replicated land uses at the KBS
LTER: one hectare plots that have been logged, tilled, fertilized, and
used for agriculture for approximately 100 years (AG), plots that were
abandoned from agriculture 20 years ago and represent an early
successional plant community (ES), successional forests on plots that
have been free from agriculture for 50 years (SF), and plots of land
that have never been used for agriculture, containing deciduous
forests (DF). We tested the hypothesis that agricultural practices
would select populations of bacteria that respire nitrate (from
fertilization), while selection would be relaxed in the native forest.
We anticipated a gradient in the strength of selection ranging from
strong in AG to weaker selection in ES and SF, ending with DF having
the most neutrally evolving codon sites.

A preliminary investigation using dN/dS for 157 amino acids of nirK
show an increase in purifying selection in AG compared to DF. The
site-specific rates for AG is lower than for DF when comparing the
number of sites with higher than baseline dN/dS (p=0.0235, two-sample
t-test with unequal variances), while the difference between ES and DF
is only marginally significant. The ratio for the successional forest
plots is indistinguishable from native DF. These results are
consistent with the hypothesis that in AG, purifying selection reduces
the rate of changes in the amino acid sequence, because there is
selection for the function of nirK. As selection is relaxed (i.e.,
when fields are abandoned from agriculture) dN/dS ratios increased.
This result is of particular interest because nirK is in the
denitrification pathway that results in the release of nitrous oxide,
and more than 50% of nitrous oxide in Earth?s atmosphere is derived
from this process in agricultural lands. This approach provides an
exciting new combination of computational molecular evolution and
microbial community ecology in natural ecosystems, where we see
evolution in action as it shapes the structure and function of
microbial communities, and it establishes a direct link between
conservation biology and anthropogenic climate change.