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).