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Abstract Dust has the potential to play a significant role in the nutrient dynamics of alpine watersheds with important ecological implications. However, little is known about how dust nutrients circulate through the environment and which watershed characteristics facilitate dust impacts on water quality. This study explored the contribution of dust‐deposited nutrients, focusing on a high‐elevation Long Term Ecological Research site, where dust samples have been continuously collected since 2017. We incorporated observed dust nutrient compositions, including fractions of inorganic and organic nitrogen and phosphorus, into a popular hydrological model, the Soil and Water Assessment Tool, and ran simulations for 2019–2021. By comparing simulations with and without dust nutrient inputs, we estimated the impact of dust‐deposited nutrients on individual watershed processes. Results revealed a significant contribution of dust‐deposited nutrients, particularly soluble reactive phosphorus (SRP), to several nutrient cycling and transport pathways. Notably, dust contributed up to 19.3% of the SRP load in annual streamflow (increasing monthly streamflow concentration by up to 10.9 μg ). Spatial analysis of model estimates demonstrated a relationship between topography, soil type, and the cycling and transport of dust nutrients. The largest dust nutrient contributions were found in catchment areas with lower slope and less hydric soils, where other natural mobilization processes may be limited. This comparative modeling approach stresses the importance of including dust nutrients in watershed models, especially in oligotrophic systems, and has potential to validate these findings elsewhere and identify how watershed characteristics may either mollify or accentuate the impacts of dust deposition on mountain freshwater systems.
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Phosphorus Transport along the Cropland–Riparian–Stream Continuum in Cold Climate Agroecosystems: A Review
Phosphorus (P) loss from cropland to ground and surface waters is a global concern. In cold climates (CCs), freeze–thaw cycles, snowmelt runoff events, and seasonally wet soils increase P loss potential while limiting P removal effectiveness of riparian buffer zones (RBZs) and other practices. While RBZs can help reduce particulate P transfer to streams, attenuation of dissolved P forms is more challenging. Moreover, P transport studies often focus on either cropland or RBZs exclusively rather than spanning the natural cropland–RBZ–stream gradient, defined here as the cropland–RBZ–stream continuum. Watershed P transport models and agronomic P site indices are commonly used to identify critical source areas; however, RBZ effects on P transport are usually not included. In addition, the coarse resolution of watershed P models may not capture finer-scale soil factors affecting P mobilization. It is clear that site microtopography and hydrology are closely linked and important drivers of P release and transport in overland flow. Combining light detection and ranging (LiDAR) based digital elevation models with P site indices and process-based models show promise for mapping and modeling P transport risk in cropland-RBZ areas; however, a better mechanistic understanding of processes controlling mobile P species across regions is needed. Broader predictive approaches integrating soil hydro-biogeochemical processes with real-time hydroclimatic data and risk assessment tools also hold promise for improving P transport risk assessment in CCs.
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- PAR ID:
- 10247274
- Date Published:
- Journal Name:
- Soil Systems
- Volume:
- 5
- Issue:
- 1
- ISSN:
- 2571-8789
- Page Range / eLocation ID:
- 15
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Rangel, Thiago F (Ed.)Species distribution models (SDMs) are frequently data-limited. In aquatic habitats, emerging environmental DNA (eDNA) sampling methods can be quicker and more cost-efficient than traditional count and capture surveys, but their utility for fitting SDMs is complicated by dilution, transport, and loss processes that modulate DNA concentrations and mix eDNA from different locations. Past models for estimating organism densities from measured species-specific eDNA concentrations have accounted for how these processes affect expected concentrations. We built off this previous work to construct a linear hierarchical model that also accounts for how they give rise to spatially correlated concentration errors. We applied our model to 60 simulated stream networks and three types of species niches in order to answer two questions: 1) what is the D-optimal sampling design, i.e. where should eDNA samples be positioned to most precisely estimate species–environment relationships? and 2) How does parameter estimation accuracy depend on the stream network’s topological and hydrologic properties? We found that correcting for eDNA dynamics was necessary to obtain consistent parameter estimates, and that relative to a heuristic benchmark design, optimizing sampling locations improved design efficiency by an average of 41.5%. Samples in the D-optimal design tended to be positioned near downstream ends of stream reaches high in the watershed, where eDNA concentration was high and mostly from homogeneous source areas, and they collectively spanned the full ranges of covariates. When measurement error was large, it was often optimal to collect replicate samples from high-information reaches. eDNA-based estimates of species–environment regression parameters were most precise in stream networks that had many reaches, large geographic size, slow flows, and/or high eDNA loss rates. Our study demonstrates the importance and viability of accounting for eDNA dilution, transport, and loss in order to optimize sampling designs and improve the accuracy of eDNA-based species distribution models.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/soilsystems5010015
