Unraveling the Contribution of Turbulence and Bubbles to Air-Water Gas Exchange in Running Waters.

Quantifying air-water gas exchange is critical for estimating greenhouse gas fluxes and metabolism in aquatic ecosystems. In high-energy streams, the gas exchange rate k is poorly constrained, due to an incomplete understanding of turbulence and bubble contributions to k. We performed a flume experiment with air bubble additions to evaluate the combined effects of turbulence and bubbles on k for helium, argon, xenon, and methane. We created contrasting hydraulic conditions by varying channel slope, bed roughness, water discharge, and bubble flux. We found that k increased from 1-4 to 17-66 m d-1 with increases in turbulence and bubble flux metrics. Mechanistic models that explicitly account for these metrics, as well as gas diffusivity and solubility, agreed well with the data and indicated that bubble-mediated gas exchange accounted for 64-93% of k. Bubble contributions increased with bubble flux but were independent of gas type, as bubbles did not equilibrate with the water. This was evident through modeled bubble life and equilibration times inferred from bubble size distributions obtained from underwater sound spectra. Sound spectral properties correlated well with turbulence and bubble flux metrics. Our results demonstrate that (a) mechanistic models can be applied to separate free surface- and bubble-mediated gas exchange in running waters, (b) bubble life and equilibration times are critical for accurate scaling of k between different gases, and (c) ambient sound spectra can be used to approximate contributions of turbulence and bubbles.

Dynamic spatio-temporal patterns of metapopulation occupancy in patchy habitats.

Spatio-temporal dynamics in habitat suitability and connectivity among mosaics of heterogeneous wetlands are critical for biological diversity and species persistence in aquatic patchy landscapes. Despite the recognized importance of stochastic hydroclimatic forcing in driving wetlandscape hydrological dynamics, linking such effects to emergent dynamics of metapopulation poses significant challenges. To fill this gap, we propose here a dynamic stochastic patch occupancy model (SPOM), which links parsimonious hydrological and ecological models to simulate spatio-temporal patterns in species occupancy in wetlandscapes. Our work aims to place ecological studies of patchy habitats into a proper hydrologic and climatic framework to improve the knowledge about metapopulation shifts in response to climate-driven changes in wetlandscapes. We applied the dynamic version of the SPOM (D-SPOM) framework in two wetlandscapes in the US with contrasting landscape and climate properties. Our results illustrate that explicit consideration of the temporal dimension proposed in the D-SPOM is important to interpret local- and landscape-scale patterns of habitat suitability and metapopulation occupancy. Our analyses show that spatio-temporal dynamics of patch suitability and accessibility, driven by the stochasticity in hydroclimatic forcing, influence metapopulation occupancy and the topological metrics of the emergent wetlandscape dispersal network. D-SPOM simulations also reveal that the extinction risk in dynamic wetlandscapes is exacerbated by extended dry periods when suitable habitat decreases, hence limiting successful patch colonization and exacerbating metapopulation extinction risks. The proposed framework is not restricted only to wetland studies but could also be applied to examine metapopulation dynamics in other types of patchy habitats subjected to stochastic external disturbances.

The Stream Length Duration Curve: A Tool for Characterizing the Time Variability of the Flowing Stream Length.

In spite of the importance of stream network dynamics for hydrology, ecology, and biogeochemistry, there is limited availability of analytical tools suitable for characterizing the temporal variability of the active fraction of river networks. To fill this gap, we introduce the concept of Stream Length Duration Curve (SLDC), the inverse of the exceedance probability of the total length of active streams. SLDCs summarize efficiently the effect of hydrological variability on the length of the flowing streams under a variety of settings. A set of stochastic network models is developed to link the features of the local hydrological status of the network nodes with the shape of the SLDC. We show that the mean network length is dictated by the mean persistency of the nodes, whereas the shape of the SLDC is driven by the spatial distribution of the local persistencies and their network-scale spatial correlation. Ten field surveys performed in 2018 were used to estimate the empirical SLDC of the Valfredda river (Italy), which was found to be steep and regular-indicating a pronounced sensitivity of the active stream length to the underlying hydrological conditions. Available observations also suggest that the activation of temporary reaches during network expansion is hierarchical, from the most to the least persistent stretches. Under these circumstances, the SLDC corresponds to the spatial Cumulative Distribution Function of the nodes persistencies. The study provides a sound theoretical basis for the analyses of network dynamics in temporary rivers.