4.1.1 Microbiomes as complementary sources of connectivity
information
While geochemistry and microbiome membership were broadly similar when
calculating connectivity metrics such as connectivity duration (Figure
5), we also observed key distinctions that illustrate how microbiome
membership may provide additional information about connectivity not
observed in hydrologic and geochemical metrics. Within our system,
σm was strongly negatively correlated with time to peak
during our tracer experiments suggesting that σm is
responsive to residence times (Figure 4). In contrast,
σg was less well correlated with time to peak (Figure
4). This is consistent with known differences in drivers between the two
metrics. Geochemistry will reflect mixing of source waters which may or
may not be related to residence times. In contrast, ecological theory
states that microbial communities are shaped not just by dispersal but
also by local ecological dynamics that come to dominate microbiome
assembly as residence time becomes greater than growth rate (Lindström
et al., 2005). As flow decreases and residence times increase in a water
body, selection driven by local environmental conditions is likely to
become a larger factor relative to dispersal (i.e., immigration and
emigration) in determining microbiome membership (Mayr et al., 2020),
which could result in increasing dissimilarity in microbiome membership
between a source and target location.
This shift towards a selection driven microbial community assembly may
be most observable when residence times increase above a certain
threshold, which might help explain the differences we observed at
Pond-Con-01 between the microbial and geochemical connectivity metrics
(Figure 3 & 5, Table S1). At Pond-Con-01, σm had a
gradual, mostly linear relationship with Inflow stage with an inflection
point at moderate Inflow stage (Imicro: 456 mm, see
Figure 3), while pond stage remained high at these flows. In contrast,
σg was relatively invariant with Inflow stage until a
sudden drop at low Inflow stage (Igeo: 360 mm), which
occurred at nearly the same Inflow threshold (Istage =
368 mm) that stage in the pond began falling (Figure 3). The surface
flowpath between the river and Pond-Con-01 passed through several beaver
ponds before reaching the site. As a result, even at peak river flows,
water velocities through Pond-Con-01 were low, and travel times were
long, relative to other sites (Table 1). As streamflow declined, the
water flux into the pond also decreased and residence times increased
because pond levels and volume remained stable. Through this period, the
stable levels and persistence of high geochemical connectivity strength
suggest a surface flow connection to the river was maintained, but the
degree of influence of the river on the pond microbiome declined. Thus,
from a functional connectivity perspective, one could either say the
site was at different connectivity strengths with the Inflow depending
on which metric was examined. This reinforces that functional
connectivity is defined by the metric of interest and interpretation
requires considering what aspects of connectivity are being reflected by
each measurement approach (Wohl et al., 2019).