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Tidal creeks play a vital role in influencing geospatial evolution and marsh ecological communities in coastal landscapes. However, evaluating the geospatial characteristics of numerous creeks across a site and understanding their ecological relationships pose significant challenges due to the labor-intensive nature of manual delineation from imagery. Traditional methods rely on manual annotation in GIS interfaces, which is slow and tedious. This study explores the application of Attention-based Dense U-Net (ADU-Net), a deep learning image segmentation model, for automatically classifying creek pixels in high-resolution (0.5 m) orthorectified aerial imagery in coastal Georgia, USA. We observed that ADU-Net achieved an outstanding F1 score of 0.98 in identifying creek pixels, demonstrating its ability in tidal creek mapping. The study highlights the potential of deep learning models for automated tidal creek mapping, opening avenues for future investigations into the role of creeks in marshes' response to environmental changes. [ABSTRACT FROM AUTHOR]

Bivalves are becoming an increasingly popular tool to counteract eutrophication, particularly in vegetated coastal ecosystems where synergistic interactions between bivalves and plants can govern important N sequestration pathways. In turn, new calls to evaluate how bivalve densities modify N pools and processes across multiple scales have surfaced.Ribbed mussels, Geukensia demissa, and their relationship with smooth cordgrass present a classic demonstration of positive bivalve‐plant interactions and offer a useful model for assessing density dependence. We measure porewater ammonium concentrations, N stable isotope signatures in cordgrass tissue, and sediment N fluxes in mussel aggregations and in cordgrass‐only plots across a southeastern U.S. salt marsh.In addition to measuring the effect of mussel presence, we evaluate mussel density dependence through a multiscale approach. At the patch scale, we quantify mussel density effects within their aggregations (individuals m−2) while at a larger landscape scale, we quantify mussel density effects on the cordgrass‐only areas they neighbour (individuals ~30 m−2).Porewater ammonium concentrations were halved in mussel biodeposits relative to sediments in cordgrass‐only areas and negatively related to mussel density within aggregations. Leaf clip ẟ15N signatures were nearly 2‰ higher in cordgrass growing among mussel aggregations and increased with increasing patch mussel density. Microcosm incubations showed that mussels enhanced N2 flux (i.e., nitrogen removal) and DIN flux (i.e., N regeneration) into the water column, where only nitrogen removal increased with increasing patch‐scale mussel density. Across the marsh landscape, mussel coverage drove ammonium accumulation and N2 flux in sediments.Synthesis. Our results suggest that, at the patch scale, mussels stimulate the microbial metabolism of N, the assimilation of this bioavailable N by cordgrass, and nitrogen removal in a positive, density‐dependent manner. Tidal currents redistribute mussel biodeposits from mussel aggregations to surrounding areas, influencing biogeochemical transformations at scales beyond their physical footprint. We emphasize that the N regeneration potential of bivalve populations is a significant metric contributing to their mitigation potential and that bivalve density effects may be non‐linear, vary across patch to ecosystem scales, and have differing implications for the plants with which they interact. [ABSTRACT FROM AUTHOR]

Many wetlands around the world that occur at the base of watersheds are under threat from land‐use change, hydrological alteration, nutrient pollution, and invasive species. A relevant measure of whether the ecological character of these ecosystems has changed is the species diversity of wetland‐dependent waterbirds, especially those of conservation value. Here, we evaluate the potential mechanisms controlling variability over time and space in avian species diversity of the wetlands in the Palo Verde National Park, a Ramsar Site of international importance in Costa Rica. To do so, we assessed the relative importance of several key wetland condition metrics (i.e., surface water depth, wetland extent, and vegetation greenness), and temporal fluctuations in these metrics, in predicting the abundance of five waterbirds of high conservation value as well as overall waterbird diversity over a 9‐yr period. Generalized additive models revealed that mean NDVI, an indicator of vegetation greenness, combined with a metric used to evaluate temporal fluctuations in the wetland extent best predicted four of the five waterbird species of high conservation value as well as overall waterbird species richness and diversity. Black‐bellied Whistling‐ducks, which account for over one‐half of all waterbird individuals, and all waterbird species together were better predicted by including surface water depth along with wetland extent and its fluctuations. Our calibrated species distribution model confidently quantified monthly averages of the predicted total waterbird abundances in seven of the 10 sub‐wetlands making up the Ramsar Site and confirmed that the biophysical diversity of this entire wetland system is important to supporting waterbird populations both as a seasonal refuge and more permanently. This work further suggests that optimizing the timing and location of ongoing efforts to reduce invasive vegetation cover may be key to avian conservation by increasing waterbird habitat. [ABSTRACT FROM AUTHOR]

Disturbances are one of the most important processes affecting natural systems, but there is a gap between simple conceptual models of disturbance and complex empirical studies. We studied the perturbation caused by headward‐eroding creeks in southeastern USA salt marshes. We measured disturbance responses (magnitude and recovery trajectory) of 19 variables. Some variables (shoot density, root biomass, snail density, soil pH, soil strength, soil temperature, elevation) declined sharply, while other variables (crab burrow density, soil organic matter, soil redox) increased sharply, in response to the burrowed and grazed conditions at the creek head. These variables recovered over subsequent years or decades. Other variables (shoot height, aboveground biomass, rhizome biomass, light interception) declined sharply in the creek head, then overshot control values before recovering. Some variables (benthic algae, soil salinity) did not appear to be disturbed by the creek head. As hypothesized, plants recovered before soils and snails. Disturbance magnitude and time to recovery were often greater directly adjacent to the new creekbank than for the same variables in a parallel transect further away from the creekbank, and in some cases variables never converged with control values, indicating a persistent state change. Reducing the dimensionality of the data set into principal component axes obscured the diverse ways in which different aspects of the system responded to and recovered from the perturbation. Our study illustrates the challenges in moving from simple conceptual models of disturbance to empirical studies in which multiple variables are likely to be affected differently and follow different recovery trajectories. [ABSTRACT FROM AUTHOR]