Geographic Linkages of Root Traits to Salt Marsh Productivity

Exogenous nitrogen from riverine exports promotes soil methane production in saltmarshes in China

Methane emissions from saltmarshes can potentially promote climate warming. Soil methane production is positively correlated with methane emissions from saltmarshes. Understanding the factors influencing soil methane production will improve the prediction of methane emissions, but an investigation of these factors has not been conducted in saltmarshes in China. We collected soils from native Phragmites australis and invasive Spartina alterniflora saltmarshes along the coast of China; the soil potential methane production (PMP) was determined by incubation experiments. The large-scale investigation results showed that the ratios of methanogens relative to sulfate-reducing bacteria (RMRS) and total organic carbon (TOC) were positively correlated with soil PMP for both species. Dissolved inorganic nitrogen (DIN) was positively correlated with the soil PMP of P. australis saltmarshes, and plant biomass was positively correlated with the soil PMP of S. alterniflora saltmarshes. Our results showed that exogenous nitrogen from riverine exports was positively correlated with DIN and plant biomass in both P. australis and S. alterniflora saltmarshes. In addition, exogenous nitrogen was also positively correlated with TOC in S. alterniflora saltmarshes. Consequently, exogenous nitrogen indirectly promoted soil methane production in P. australis saltmarshes by increasing the DIN and promoted soil methane production in S. alterniflora saltmarshes by enhancing the TOC and plant biomass. Moreover, we found that the promoting effect of DIN on the soil PMP of P. australis saltmarshes increased when the incubation temperature increased from 15 °C to 25 °C. Thus, the promoting effect of exogenous nitrogen on the soil methane production in P. australis saltmarshes might be strengthened in the peak of growing season. Our findings are the first to confirm that exogenous nitrogen inputs from rivers indirectly promote soil methane production in P. australis and S. alterniflora saltmarshes and provide new insights into the factors responsible for soil methane production in saltmarshes.

Native herbivores indirectly facilitate the growth of invasive Spartina in a eutrophic saltmarsh

Current theory (e.g., consumer-controlled theory) predicts that nutrient enrichment typically amplifies herbivory and thereby suppresses the growth and expansion of invasive plants. Herbivores can facilitate plant regrowth in the native community by stimulating complementary growth or ameliorating habitat conditions (e.g., by increasing soil oxygen and nutrient availability), but whether they have similar positive effects on invasive plants, especially under nutrient enrichment, remains unknown. Using a field nitrogen (N)-enrichment X crab exclusion experiment, we evaluated and compared the effects of both N enrichment and crab herbivory on the growth performance of a global invasive cordgrass, Spartina alterniflora, and a co-occurring native plant, Phragmites australis. We found that crabs consistently suppressed P. australis by decreasing density and aboveground biomass regardless of N enrichment. In contrast, for S. alterniflora, the negative effects of crabs under ambient N were replaced by positive effects under N enrichment, with crabs stimulating complementary increases in density and aboveground biomass. The differing effects between the N treatments were driven by crab burrowing activity, which increased soil N availability, and the nutrient-use efficiency of S. alterniflora. Our findings reveal that native herbivores can have opposing effects on native and invasive plants, which broadens our understanding of how exotic plants can achieve dominance in a changing world. This article is protected by copyright. All rights reserved.

Machine-Learning Classification of Soil Bulk Density in Salt Marsh Environments

Remotely sensed data from both in situ and satellite platforms in visible, near-infrared, and shortwave infrared (VNIR–SWIR, 400–2500 nm) regions have been widely used to characterize and model soil properties in a direct, cost-effective, and rapid manner at different scales. In this study, we assess the performance of machine-learning algorithms including random forest (RF), extreme gradient boosting machines (XGBoost), and support vector machines (SVM) to model salt marsh soil bulk density using multispectral remote-sensing data from the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) platform. To our knowledge, use of remote-sensing data for estimating salt marsh soil bulk density at the vegetation rooting zone has not been investigated before. Our study reveals that blue (band 1; 450–520 nm) and NIR (band 4; 770–900 nm) bands of Landsat-7 ETM+ ranked as the most important spectral features for bulk density prediction by XGBoost and RF, respectively. According to XGBoost, band 1 and band 4 had relative importance of around 41% and 39%, respectively. We tested two soil bulk density classes in order to differentiate salt marshes in terms of their capability to support vegetation that grows in either low (0.032 to 0.752 g/cm³) or high (0.752 g/cm³ to 1.893 g/cm³) bulk density areas. XGBoost produced a higher classification accuracy (88%) compared to RF (87%) and SVM (86%), although discrepancies in accuracy between these models were small (<2%). XGBoost correctly classified 178 out of 186 soil samples labeled as low bulk density and 37 out of 62 soil samples labeled as high bulk density. We conclude that remote-sensing-based machine-learning models can be a valuable tool for ecologists and engineers to map the soil bulk density in wetlands to select suitable sites for effective restoration and successful re-establishment practices.