Stream and river ecosystems play a central role in the movement and decomposition of particulate organic matter, serving as a conduit between terrestrial hillslopes and coastal environments. Microbe-catalyzed decomposition generates simpler organic molecules that fuel respiration, often in the sediments of these ecosystems. However, the degree of connection between sediment-associated respiration (ERsed) and organic-matter-decomposition potential remains poorly understood. It is also unclear whether organic-matter-decomposition potential is more closely associated with ERsed, whole-ecosystem respiration (ERtot), or water-column respiration (ERwc). We examined the link between particulate organic-matter-decomposition potential - using cellulose-based cotton strips as a standardized substrate - and all three components of respiration across 48 sites in the environmentally diverse Yakima River Basin (Washington State, USA). We hypothesized that decomposition within sediments would be most strongly related to ERsed, but decomposition rates were more closely associated with ERtot, less so with ERsed and not at all with ERwc. This suggests that point-scale particulate organic-matter-decomposition potential within stream/river sediments is more closely associated with integrated system respiration rather than with processes confined to sediments or the water column alone though these relationships were weak overall. Further, across the basin, decomposition rates nearly spanned the previously reported global range for streams and rivers and were best explained by total dissolved nitrogen (TDN), sediment grain size, and aridity of the upstream drainage area. These results highlight the strong influence of land cover and basin-scale biophysical variation on sediment-associated decomposition processes and indicate that mechanistic models of organic-matter decomposition in streams and rivers should account for coupled sediment-water-land interactions.

Abstract. Stream and river ecosystems play a central role in the movement and decomposition of particulate organic matter, serving as a conduit between terrestrial hillslopes and coastal environments. Microbial-catalyzed decomposition generates simpler organic molecules that fuel respiration, often in the sediments of these ecosystems. However, the degree of connection between sediment-associated respiration (ERsed) and organic-matter decomposition remains poorly understood. How that relationship compares to decomposition’s relationship with whole ecosystem (ERtot) and water column (ERwc) respiration is also not clear. We examined the link between particulate organic matter decomposition—using cellulose-based cotton strips as a standardized substrate—and all three components of respiration across 48 sites in the environmentally diverse Yakima River Basin (Washington State, USA). We hypothesized that decomposition within sediments would be most strongly related to ERsed, but decomposition rates were more closely associated with ERtot, with little connection to ERsed or ERwc. This suggests that particulate organic matter decomposition within stream/river sediments reflects integrated system respiration rather than processes confined to sediments or the water column alone. Further, across the basin, decomposition rates nearly spanned the previously reported global range for streams and rivers and were best explained by total dissolved nitrogen (TDN), sediment grain size, and aridity of the upstream drainage area. These results highlight the strong influence of land cover and basin-scale biophysical variation on sediment-associated decomposition processes and indicate that mechanistic models of organic matter decomposition in streams/rivers should account for coupled sediment–water–land interactions.

Continuous measurement and monitoring of surface water coverage in non-perennial streams are essential for understanding the exchange fluxes between surface and subsurface waters under both inundated and noninundated conditions. In this study, a wildlife camera photo-based framework was developed to monitor small stream water inundation, depth, discharge, and velocity. Two advanced machine learning models, YOLOv8 and Mask2Former, were utilized to efficiently analyze images captured by wildlife cameras. The accuracy of the framework was validated against on-site depth measurements at six sites in the Yakima River Basin, along with the gage height, discharge, and velocity data from four USGS sites. This approach facilitates long-term, continuous monitoring and quantification of river intermittency and water availability with high precision and low cost, thereby advancing river ecosystem research and management.

1 INTRODUCTION:Climate change is driving earlier seasonal onset of wildfire, increased fire frequency, and larger fires in many regions globally (Flannigan et al., 2009; Westerling, 2016). Wildfires induce changes in ecohydrological processes, including reduced infiltration from increased soil hydrophobicity (DeBano, 2000), and reduced canopy cover that diminishes evapotranspiration and interception of precipitation (Guo et al., 2023; Wine et al., 2018). The resulting changes in streamflow and terrestrial-aquatic connectivity from these shifts in ecohydrological processes influence the composition and fluxes of materials to stream networks, with the potential to degrade downstream water quality (Ball et al., 2021; Dahm et al., 2015; Hohner et al., 2019; Jones et al., 2022; Paul et al., 2022; Rust et al., 2018; Santos et al., 2019). Thus, it is important to improve our understanding of the spatio-temporal drivers of water quality responses to wildfires (Raoelison et al., 2023).Across spatial scales, wildfire has been documented to increase solute concentrations by orders of magnitude in some receiving streams (Hickenbottom et al., 2023; Murphy et al., 2018), but lead to little response or decline in others (Abbott et al., 2021; Oliver et al., 2012). This may be due to differences in wildfire and/or watershed characteristics. For example, previous literature has identified a threshold of ~20% burn extent needed to trigger a hydrologic response across different ecoregions (Hallema et al., 2018), yet identification of such responses for water quality parameters is nascent (Richardson et al., 2024). While several previous studies have documented the effect of wildfire on water quality parameters and biogeochemical processes across broad spatial scales (e.g., Hampton et al., 2022; Raoelison et al., 2023; Rust et al., 2018), few have sought to link observed responses across time, climate, burn, and watershed characteristics.In particular, nitrate (NO3_) and dissolved organic carbon (DOC) are key nutrients that underpin global biogeochemical cycles and have the potential to degrade water quality with increasing wildfire activity. For example, excess nitrate can lead to downstream eutrophication (Mast et al., 2016), while DOC compositional shifts may influence water treatment processes (Hohner et al., 2019). Relationships with burn severity and extent have been observed in some systems for nitrate (Bladon et al., 2008; Rhoades, Chow, et al., 2019), however, for DOC, little to no relationships have been consistently observed across studies and systems (Santos et al., 2019a; Wei et al., 2021).Observed differences in nitrate and DOC concentrations pre- and post-fire were most pronounced in the first five years following wildfire (Rust et al., 2018). However, the persistence of fire effects on hydrologic and biogeochemical processes are moderated by the rate of post-wildfire vegetation recovery which can vary by ecosystem (Guo et al., 2023; Wine et al., 2018). Nitrate responses, for example, may lag due to the shift in nitrogen speciation during combustion creating conditions that increase nitrification post-fire (Gustine et al., 2022; Hanan, Schimel, et al., 2016). The magnitude and length of DOC responses are likely a result of heterogeneous burn conditions that can decrease and alter the chemistry of source pools (Santín et al., 2016).Responses may be linked to changes in streamflow (Richardson et al., 2024), which is highly variable across climates post-fire (Hallema et al., 2017). This variability may co-vary with additional drivers, such as drought (Murphy et al., 2018; Newcomer et al., 2023) resulting in shifts in nitrate and DOC export. For example, while the directionality of the relationship between concentration and discharge may not be altered with wildfire, the strength of that relationship has been shown to change for both nitrate and DOC (Murphy et al., 2018; Richardson et al., 2024). While trends are emerging for streamflow across time since fire, climate, and burn characteristics (Hallema et al., 2017), such trends have not yet emerged for nitrate and DOC.Discerning biogeochemical responses post-fire are further complicated by heterogeneous watershed characteristics (Agbeshie et al., 2022; Hallema et al., 2018). For example, catchment slope has a dominant influence on biogeochemical linkages between terrestrial and aquatic systems, primarily due to longer residence times of water and constituents in lower-gradient catchments (Lintern et al., 2018). The biogeochemical signatures in steeper catchments typically reflect that of surficial pathways, especially during periods of enhanced hydrologic connectivity where a large proportion of material is mobilized from the terrestrial landscape into receiving streams (Laudon & Sponseller, 2018). Conversely, lower-gradient catchments are less responsive to periods of enhanced hydrologic connectivity due to the greater proportion of groundwater contributions (Laudon & Sponseller, 2018). Lower-gradient catchments also promote longer residence times that allow for transformations and provide a source of DOC available to leach into receiving streams (Tank et al., 2020). Additionally, topography heavily influences terrestrial species composition which influences carbon and nitrogen cycling, thus affecting solutes available for export (Weintraub et al., 2017).The objectives of this meta-analysis were to better constrain the controls on stream water chemistry across broad spatial scales post-fire. In this study, we synthesize biogeochemical responses of nitrate and DOC to wildfires using meta-analytical techniques to evaluate the effect sizes and the percent differences across reference and fire-impacted sites spanning 3 biomes and 62 watersheds. We chose to leverage reference-burn study designs to minimize the confounding influence of interannual climate variability on our results (Clausen & Spooner, 1993). We focused specifically on the importance of time-since-fire, climate, and burn extent as factors of interest to assess post-fire shifts in solute concentrations through space and time. Through time as ecosystems recover, we hypothesize that there will be a decrease in the effect size of wildfire impacts on nitrate and DOC, as concentrations begin to reflect those in non-fire impacted systems. Furthermore, we anticipate that there will be a systematic shift in nitrate and DOC post-fire related to ranges in aridity and mean annual precipitation with climate, which will be modulated by in-stream hydrologic responses to local catchment characteristics. Lastly, we hypothesized that the area of watershed burned will impact the relationships between watershed characteristics and nitrate and DOC responses, influencing the magnitude of wildfire effects on water quality.

Abstract. Aerobic respiration of organic matter is a key metabolic process influencing carbon (C) biogeochemistry in aquatic ecosystems. Anthropogenic and environmental perturbations to stream ecosystem metabolism can have deleterious effects on downstream water quality. Various environmental features of rivers also influence stream metabolism, including physical (e.g., discharge, light, flow regimes) and chemical factors (nutrients, organic matter) and watershed characteristics (e.g., stream size or drainage area, land use). The relative proportion of surface water contact with benthic sediments has been considered the primary driver of ecosystem processes, including ecosystem respiration (ER). While aquatic ecosystem respiration occurs in the water column (ERwc) and in benthic sediments—including surficial and subsurface sediments (ERsed)—ERsed has long been assumed to be the primary contributor to whole-river ecosystem respiration (ERtot). Recent studies show, however, that somewhere along the river continuum (e.g., 5th–9th order), rivers transition from being dominated by benthic processes to being dominated by water column processes. Yet few metabolism studies have parsed contributions from the water column (ERwc) to ERtot, making it difficult to evaluate the relative magnitude and importance of ERwc across the river continuum and across biomes. In this study, we used the Yakima River basin, Washington, USA, to increase our understanding of basin-scale variation in ERwc. We collected ERwc data and water chemistry samples in triplicate at 47 sites in the Yakima River basin distributed across Strahler stream orders 2–7 and different hydrological and biophysical settings during summer baseflow conditions in 2021. We found that observed ERwc rates were consistently slow throughout the basin during baseflow conditions, ranging from −0.11–0.03 mg O2 L⁻1 d⁻1, and were generally at the very slow end of the range of published ERwc literature values. When compared to reach-scale ERtot rates predicted for rivers across the conterminous United States (CONUS), the very slow ERwc rates we observed throughout the Yakima River basin indicate that ERwc is likely a small component of ERtot in this basin. Despite these slow rates, ERwc nonetheless shows spatial variation across the Yakima River basin that was well explained by watershed characteristics and water chemistry. Multiple linear regression model results show that nitrate (NO3-N), dissolved organic carbon (DOC), and temperature together explained 41.5 % of the spatial variation in ERwc. Supporting the findings of other studies, we found that ERwc increased linearly with increasing NO3-N, increasing DOC, and increasing temperature. We hypothesize that low concentrations of nutrients, DOC, and low temperatures in the water column, coupled with low TSS concentrations, likely contribute to the slow ERwc rates observed throughout the Yakima River basin. Because ERtot measurements integrate contributions from water column respiration and sediment-associated respiration (ERsed), estimating ERtot in cold, clear, low nutrient rivers like those in the Yakima River basin with very slow ERwc will essentially measure contributions from ERsed.

Streambed grain sizes control river hydro-biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo-driven, artificial intelligence (AI)-enabled, and theory-based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash-Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground-truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log-normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy-Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.

Wildfires produce solid residuals that have unique chemical and physical properties compared to unburned materials, which influence their cycling and fate in the natural environment. Visual burn severity assessment is used to evaluate post-fire alterations to the landscape in field-based studies, yet muffle furnace methods are commonly used in laboratory studies to assess molecular scale alterations along a temperature continuum. Here, we examined solid and leachable organic matter characteristics from chars visually characterized as low burn severity that were created either on an open air burn table or from low-temperature muffle furnace burns. We assessed how the different combustion conditions influence solid and dissolved organic matter chemistries and explored the potential influence of these results on the environmental fate and reactivity. Notably, muffle furnace chars produced less leachable carbon and nitrogen than open air chars across land cover types. Organic matter produced from muffle furnace burns was more homogeneous than open air chars. This work highlights chemical heterogeneities that exist within a single burn severity category, potentially influencing our conceptual understanding of pyrogenic organic matter cycling in the natural environment, including transport and processing in watersheds. Therefore, we suggest that open air burn studies are needed to further advance our understanding of pyrogenic organic matter's environmental reactivity and fate.

Increasing wildfire severity is of growing concern in the western United States, with consequences for the production, composition, and mobilization of dissolved organic matter (DOM) from terrestrial to aquatic systems. Our current understanding of wildfire impacted DOM (often termed pyrogenic DOM) composition is largely built from temperature-based studies that can be difficult to extrapolate to field conditions, which are often defined by ‘burn severity’, or the post-wildfire impact observed at a site. Thus, burn severity can encapsulate a broader range of fire and environmental conditions not exclusive to temperature. Biogeochemical studies that describe DOM along burn severity continuums remain limited but are needed to better link DOM composition with field conditions post-fire. In this study, we addressed this need with an experimental open air burn simulation that generated chars from vegetation representative of major land cover types in the western United States. The chars were leached to simulate DOM mobilization potential. The DOM composition was characterized by ultra-high resolution mass spectrometry (HR-MS) and UV/VIS absorbance and fluorescence. Our results indicated that the shifts of DOM production and composition along a burn-severity gradient depends on the land cover type that was burned, with the degree of change dependent on the composition of the starting parent vegetation material. Fluorescence signatures indicated a strong convergence across land cover types to more aromatic DOM with increasing severity, while HR-MS indicated an increase in the production of aromatic nitrogen containing DOM with increasing severity. Results from this study enhance our ability to describe DOM composition in a framework that can be more directly related with field and remote-sensing based metrics.

Soil nutrient distribution is heterogeneous in space and time, potentially altering nutrient acquisition by trees and microorganisms. Ecologists have distinguished “hot spots” (HSs) as areas with enhanced and sustained rates of nutrient fluxes relative to the surrounding soil matrix. We evaluated the spatial and temporal patterns in nutrient flux HSs in two mixed-conifer forest soils by repeatedly sampling the soil solution at the same spatial locations (horizontally and vertically) over multiple seasons and years using ion exchange resins incubated in situ. The climate of these forests is Mediterranean, with intense fall rains occurring following summers with little precipitation, and highly variable winter snowfall. Hot spots formed most often for NO 3 − and Na + . Although nutrient HSs often occurred in the same spatial location multiple times, HSs persisted more often for PO 4 3− NH 4 + , and NO 3 − , and were more transient for Ca 2+ , Mg 2+ , and Na + . Sampling year (annual precipitation ranged from 558 to 1223 mm) impacted the occurrence of HSs for most nutrients, but season was only significant for PO 4 3− , NH 4 + , NO 3 − , and Na + , with HSs forming more often after fall rains than after spring snowmelt. The frequency of HSs significantly decreased with soil depth for all nutrients, forming most commonly immediately below the surficial organic horizon. Although HSs accounted for less than 17% of the sampling volume, they were responsible for 56–88% of PO 4 3− , NH 4 + , and NO 3 − resin fluxes. Our results suggest that macronutrient HSs have a disproportional contribution to soil biogeochemical structure, with implications for vegetation nutrient acquisition strategies and biogeochemical models. Graphical abstract

BackgroundNitrogen (N) is an essential nutrient in soil that regulates plant growth, terrestrial sequestration of atmospheric carbon dioxide, and persistence of organic compounds. However, major knowledge gaps remain about how climate change may impact N accumulation and persistence, especially in deep soil and saprock (friable weakly weathered bedrock). AimsOur objective was to understand how climate impacts the accumulation of N in soil and saprock and how climate impacts soil N distribution, persistence, and mechanisms of N persistence. MethodsWe investigated N concentration in bulk soil and density fractions. We estimated N persistence along a bio-climatic sequence-sites range from a low-elevation oak savannah, mid-elevation pine-oak/mixed-conifer forest, to a high-elevation subalpine forest-in the southern Sierra Nevada in California. A combination of radiocarbon and elemental composition measurements along with a first-order kinetic model was used. ResultsThe N concentration in the bulk soil and density fractions declined with depth, and there was a relatively greater mineral-associated heavy fraction (HF) N in deeper samples. The cooler/wetter mixed conifer site held 37% of profile N in saprock, which was greater than that of the entire soil profile at the drier/hotter oak savannah. The majority of N in soil, which was in the HF, was not influenced by climate proxies tested. However, both unprotected and occluded fractions of N were strongly influenced by climate. Soil N mean residence time (MRT) showed that drier/hotter climates have a shorter MRT, compared to mid-elevation sites with cooler/wetter climates. ConclusionsThe effect of climate on deep saprock N storage might be indirect, primarily through climatic influence on the thickness of saprock. Overall, our findings suggest the mineral-associated HF N pool will not be vulnerable to changes in climate and will continue to contribute to the persistent soil N pool. The amount of topsoil and subsoil unprotected and occluded N can be explained by gross primary productivity and mean annual precipitation indicating that changes in climate can influence N partitioning. N stored in deep soil and saprock may be less vulnerable to climate than N stored in drier/hotter climates with less deeply stored N. It is critical to dig deeper to understand terrestrial ecosystems' response to climate.

Streambed grain sizes and hydro-biogeochemistry (HBGC) control river functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo-driven, artificial intelligence (AI)-enabled, and theory-based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes and HBGC parameters from photos. Specifically, we first trained You Only Look Once (YOLO), an object detection AI, using 11,977 grain labels from 36 photos collected from 9 different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 testing photos. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 5th, 50th, and 84th percentiles, for 1,999 photos taken at 66 sites. With these percentiles, the quantities, distributions, and uncertainties of HBGC parameters are further derived using existing empirical formulas and our new uncertainty equations. From the data, the median grain size and HBGC parameters, including Manning’s coefficient, Darcy-Weisbach friction factor, interstitial velocity magnitude, and nitrate uptake velocity, are found to follow log-normal, normal, positively skewed, near log-normal, and negatively skewed distributions, respectively. Their most likely values are 6.63 cm, 0.0339 s·m-1/3, 0.18, 0.07 m/day, and 1.2 m/day, respectively. While their average uncertainty is 7.33%, 1.85%, 15.65%, 24.06%, and 13.88%, respectively. Major uncertainty sources in grain sizes and their subsequent impact on HBGC are further studied.

Abstract Soil nutrient distribution is heterogeneous in space and time, potentially altering nutrient acquisition by trees and microorganisms. Ecologists have distinguished “hot spots” (HSs) as areas with enhanced and sustained rates of nutrient fluxes relative to the surrounding soil matrix. We evaluated the spatial and temporal patterns in nutrient flux HSs in two mixed-conifer forest soils by repeatedly sampling the soil solution at the same spatial locations (horizontally and vertically) over multiple seasons and years using ion exchange resins incubated in situ. The climate of these forests is Mediterranean, with intense fall rains occurring following summers with little precipitation, and highly variable winter snowfall. Hot spots formed most often for NO3- and Na+. Although nutrient HSs often occurred in the same spatial location multiple times, HSs persisted more often for NO3-, NH4+, and PO43- and were more transient for Na+, Ca2+, and Mg2+. Sampling year (annual precipitation ranged from 701 to 1216 mm) impacted the occurrence of HSs for most nutrients, but season was only significant for PO43-, NH4+, NO3-, and Na+, with HSs forming more often after fall rains than spring snowmelt. The frequency of HSs significantly decreased with soil depth for all nutrients, forming most commonly immediately below the surficial organic horizon. Although HSs accounted for less than 17% of the sampling volume, they were responsible for 56-88% of PO43-, NH4+, and NO3- fluxes. Our results suggest that macronutrient HSs have a disproportional contribution to soil biogeochemical structure, with implications for vegetation nutrient acquisition strategies and biogeochemical models.

Nuclear magnetic resonance (NMR) spectroscopy is a useful tool for detection and identification of molecular structural information, with increasing applications in environmental sciences. NMR instrument outputs are however heterogeneous and require extensive post-processing, creating barriers to their use and application by non-specialists. Here, we report on a new open-source R package, nmrrr, that processes and visualizes spectral data obtained from one-dimensional solution-state and solid-state NMR experiments; the package also performs relevant calculations commonly applied in natural organic matter communities, such as computing the relative abundance of various functional groups. We document the package's installation, dependencies, and functions; and provide a standard workflow for processing NMR data. This package is currently available on CRAN and GitHub, and community contributions are welcome.

Understanding potential response of forest carbon (C) and nutrient storage to warming is important for climate mitigation policies. Unfortunately, those responses are difficult to predict in seasonally dry forests, in part, because ecosystem processes are highly sensitive to both changes in temperature and precipitation. We investigated how warming might alter stocks of C, nitrogen (N), and phosphorus (P) in vegetation and the entire regolith (soil + weathered bedrock or “saprock”) using a space‐for‐time substitution along a bioclimatic gradient in the Sierra Nevada, California. The pine‐oak and mixed‐conifer forests between 1,160–2,015 m elevation have more optimal climates (not too dry or hot) for ecosystem productivity, soil weathering, and cycling of essential elements than the oak savannah (405 m) and subalpine forest (2,700 m). We found decreases in overstory vegetation nutrient stocks with decreasing elevation because of enhanced water limitation and greater occurrence of disturbances. Stocks of C, N, and P in the entire regolith peaked at the pine‐oak and mixed‐conifer forests across the bioclimatic gradient, driven by thicker regolith profiles and greater nutrient input rates. These observations suggest long‐term warming will decrease ecosystem nutrient storage at the warmer, transitional pine‐oak zone, but will increase nutrient storage at the colder, subalpine zone. Assuming steady‐state conditions, we found the mean residence time of ecosystem C decreased with projected rising air temperatures and increased following a major drought event across the bioclimatic gradient. Our study emphasizes potentially elevation‐dependent changes in nutrient storage and C persistence with warming in seasonally dry forests.