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At least 181 records · Page 10Linked to original sources
USGS2023

Variation in leaf reflectance spectra across the California flora partitioned by evolutionary history, geographic origin, and deep time

Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data from across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and strength of phylogenetic signal. We also show that these differences are much greater than variation due to the geographic origin of the plant. At the phylogenetic extent of the California flora, spectral variation explained by the combination of ecotypic variation (divergent evolution) and convergent evolution of disparate lineages was minimal (3 to 7 %) but statistically significant. Interestingly, at the extent of a single genus ( Arctostaphylos ) no unique variation could be attributed to geographic origin. However, up to 18% of the spectral variation among Arctostaphylos individuals was shared between phylogeny and intraspecific variation stemming from ecotypic differences (i.e., geographic origin). Future studies could conduct more structured experiments (e.g., transplants or observations along environmental gradients) to disentangle these sources of variation and include other intraspecific variation (e.g., plasticity). We constrain broad scale spectral variability due to ecotypic sources, providing further support for the idea that phylogenetic clusters of species might be detectable through remote sensing. Phylogenetic clusters could represent a valuable dimension of biodiversity monitoring and detection.

California↗
USGS2023

Characterizing performance of freshwater wetland methane models across time scales at FLUXNET-CH4 sites using wavelet analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

JGR Biogeosciences↗
USGS2023

Comparing sediment microbial communities of Arctic beaver ponds to tundra lakes and streams

In recent decades the habitat of North American beaver ( Castor canadensis ) has expanded from boreal forests into Arctic tundra ecosystems. Beaver ponds in Arctic watersheds are known to alter stream biogeochemistry, which is likely coupled with changes in the activity and composition of microbial communities inhabiting beaver pond sediments. We investigated bacterial, archaeal, and fungal communities in beaver pond sediments along tundra streams in northwestern Alaska (AK), USA and compared them to those of tundra lakes and streams in north-central Alaska that are unimpacted by beavers. β -glucosidase activity assays indicated higher cellulose degradation potential in beaver ponds than in unimpacted streams and lakes within a watershed absent of beavers. Beta diversity analyses showed that dominant lineages of bacteria and archaea in beaver ponds differed from those in tundra lakes and streams, but dominant fungal lineages did not differ between these sample types. Beaver pond sediments displayed lower relative abundances of Crenarchaeota and Euryarchaeota archaea and of bacteria from typically anaerobic taxonomic groups, suggesting differences in rates of fermentative organic matter (OM) breakdown, syntrophy, and methane generation. Beaver ponds also displayed low relative abundances of Chytridiomycota (putative non-symbiotic) fungi and high relative abundances of ectomycorrhizal (plant symbionts) Basidiomycota fungi, suggesting differences in the occurrence of plant and fungi mutualistic interactions. Beaver ponds also featured microbes with taxonomic identities typically associated with the cycling of nitrogen and sulfur compounds in higher relative abundances than tundra lakes and streams. These findings help clarify the microbiological implications of beavers expanding into high latitude regions.

Alaska↗
USGS2023

Calibration and validation for the Surface Biology and Geology (SBG) mission concept: Recommendations for a multi-sensor system for imaging spectroscopy and thermal imagery

The primary objective of the National Aeronautics and Space Administration (NASA) Surface Biology and Geology (SBG) mission is to measure biological, physical, chemical, and mineralogical features of the Earth's surface, realizing a key conceptual component of the envisioned NASA Earth System Observatory (ESO). SBG is planned to launch as a two-platform mission in the late 2020s, the first of the ESO satellites. Targeted science and applications objectives based on observations of the Earth's SBG helped to define the mission architecture and instrument capabilities for the SBG mission concept. These objectives further drove the need for enabling change detection and trending of surface biological and geological features. These needs implied fundamental calibration goals to achieve the necessary science data quality characteristics. To meet those goals, calibration and validation pre-launch and on-orbit methods formed a basis of the calibration and validation concept, including the combined use of on-board references, vicarious techniques, and routine lunar imaging. International collaboration with space agencies in other countries, an important feature of the recommended SBG mission architecture, uncovered and emphasized the need for inter-calibration techniques that underscored the importance of collaborative instrument characterization data sharing and the use of common calibration references that are International System of Units (SI) traceable in pre-launch and post-launch on orbit calibration mission phases. International collaboration through the use of terrestrial and aquatic networks on six continents for vicarious calibration and validation activities will further assure necessary science data quality while in orbit.

JGR Biogeosciences↗
USGS2023

Biophysical drivers of coastal treeline elevation

Sea level rise is leading to the rapid migration of marshes into coastal forests and other terrestrial ecosystems. Although complex biophysical interactions likely govern these ecosystem transitions, projections of sea level driven land conversion commonly rely on a simplified “threshold elevation” that represents the elevation of the marsh-upland boundary based on tidal datums alone. To determine the influence of biophysical drivers on threshold elevations, and their implication for land conversion, we examined almost 100,000 high-resolution marsh-forest boundary elevation points, determined independently from tidal datums, alongside hydrologic, ecologic, and geomorphic data in the Chesapeake Bay, the largest estuary in the U.S. located along the mid-Atlantic coast. We find five-fold variations in threshold elevation across the entire estuary, driven not only by tidal range, but also salinity and slope. However, more than half of the variability is unexplained by these variables, which we attribute largely to uncaptured local factors including groundwater discharge, microtopography, and anthropogenic impacts. In the Chesapeake Bay, observed threshold elevations deviate from predicted elevations used to determine sea level driven land conversion by as much as the amount of projected regional sea level rise by 2050. These results suggest that local drivers strongly mediate coastal ecosystem transitions, and that predictions based on elevation and tidal datums alone may misrepresent future land conversion.

Delaware, Maryland, Virginia↗
USGS2023

Aquatic carbon export and dynamics in mountain headwater streams of the western U.S.

Mountain headwater streams actively cycle carbon, receiving it from terrestrial landscapes and exporting it through downstream transport and gas exchange with the atmosphere. Although their importance is now widely recognized, aquatic carbon fluxes in headwater streams remain poorly characterized. In this study, aquatic carbon fluxes were measured in 15 mountain headwater streams and were used in a geostatistical analysis to determine how landscape characteristics influence aquatic carbon fluxes. In-stream sensors were used to measure fluorescent dissolved organic matter (fDOM) (a surrogate for dissolved organic carbon (DOC)) at a subset of sites to characterize dynamic responses to hydroclimatic events. Wetlands have a positive influence on aquatic carbon fluxes, whereas perennial snow/ice has the opposite effect, reflecting differences in soil organic matter content in these landscapes. Mean annual temperature (MAT) has a complex influence on DOC, with peak DOC exports in basins with MAT of 0–2°C. Precipitation has a strong positive influence on aquatic carbon fluxes, and declining snowpacks in the western United States may reduce future aquatic carbon exports. fDOM (and by implication DOC) and

Journal of Geophysical Research: Biogeosciences.↗
USGS2024

Spatial, seasonal, and diel controls of nitrogen-carbon-oxygen cycling during lake-water infiltration to an aquifer

Many freshwater lakes are groundwater flow-through systems. Although lakes commonly are considered to be sinks for nitrogen inputs, relatively little is known about carbon and nitrogen export from lakes to groundwater. The current study focused on lake-bottom biogeochemical processes accompanying the transport of nitrogen, dissolved oxygen (O 2 ), and dissolved organic carbon (DOC) during lake-water recharge from a groundwater flow-through lake. Lake-water and porewater (15–100 cm below lakebed) samples were collected along transects within the lake downwelling zone. Infiltrating porewater O 2 and DOC concentrations decreased with depth while nitrate (NO 3 − ) concentrations increased, indicating nitrification of organic matter within the profiles. The depth of NO 3 − production and transport was seasonally dependent. In winter, NO 3 − and O 2 were exported beyond 100-cm depth; whereas in summer, shallow nitrification zones were underlain by deeper NO 3 − reduction zones, and diel patterns of O 2 and NO 3 − penetration depths were observed. Microbial community compositions and stable isotope profiles (δ 15 N[NO 3 − ], δ 18 O[NO 3 − ], δ 18 O[O 2 ]) were consistent with apparent C–N–O reaction stoichiometries indicating O 2 reduction and nitrification in shallower porewater, followed by varying NO 3 − reduction at depth. Maximum porewater NO 3 − concentrations (∼10–20 μM) were limited by infiltrating O 2 concentrations and C/N ratios of reacting organic matter. Lake-water level variations caused changes in shoreline position and porewater velocities, while variations in lake-water temperature, DOC, and O 2 contributed to changes in reaction rates and depth of O 2 and NO 3 − penetration into the lakebed. The quality of groundwater recharged by lake water reflected temporally and spatially varying physical and biogeochemical processes in the sediment porewater.

Journal of Geophysical Research: Biogeosciences↗
USGS2023

Submersed macrophyte density regulates aquatic greenhouse gas emissions

Shallow freshwater ecosystems emit large amounts of greenhouse gases (GHGs), such as carbon dioxide (CO 2 ) and methane (CH 4 ), yet emissions are highly variable. The role that aquatic macrophytes play in regulating aquatic GHG emissions is uncertain despite their ability to dominate shallow waterbodies. Here, we studied the effects of submersed macrophyte ( Ceratophyllum demersum ) density on CO 2 and CH 4 concentrations and fluxes. We conducted a 61-days experiment using mesocosms containing one of the following C . demersum density treatments: 0, 10, 20, or 30 individual shoots ( n = 3). We found that high density C . demersum had the highest CO 2 and CH 4 surface water concentrations and emissions while there was no significant difference in CH 4 in the low and medium densities and no plant control. The high density treatment lost biomass over the course of the experiment, indicating die-off and additions of organic matter to the sediment. High organic matter loading and low dissolved oxygen likely stimulated GHG production in the high density treatment. Our results emphasize that submersed macrophyte density and periods of growth and dieback are important in regulating GHG emissions, which may help explain why shallow waterbodies are high yet variable sources of GHGs to the atmosphere.

JGR Biogeosciences↗
USGS2024

The effect of drying boreal lakes on plants, soils, and microbial communities in lake margin habitats

Decadal scale lake drying in interior Alaska results in lake margin colonization by willow shrub and graminoid vegetation, but the effects of these changes on plant production, biodiversity, soil properties, and soil microbial communities are not well known. We studied changes in soil organic carbon (SOC) and nitrogen (N) storage, plant and microbial community composition, and soil microbial activities in drying and non-drying lakes in the Yukon Flats National Wildlife Refuge. Historic changes in lake area were determined using Landsat imagery. Results showed that SOC storage in drying lake margins declined by 0.13 kg C m −2 yr −1 over 30 years of exposure of lake sediments, with no significant change in soil N. Lake drying resulted in an increase in graminoid and shrub aboveground net primary production (ANPP, +3% yr −1 ) with little change in plant functional composition. Increases in ANPP were similar in magnitude (but opposite in sign) to losses in SOC over a 30-year drying trend. Potential decomposition rates and soil enzyme activities were lower in drying lake margins compared to stable lake margins, possibly due to high salinities in drying lake margin soils. Microbial communities shifted in response to changing plant communities, although they still retained a legacy of the previous plant community. Understanding how changing lake hydrology impacts the ecology and biogeochemistry of lake margin terrestrial ecosystems is an underexamined phenomenon with large impacts to landscape processes.

Alaska↗
USGS2024

Vegetation loss following vertical drowning of Mississippi River deltaic wetlands leads to faster microbial decomposition and decreases in soil carbon

Wetland ecosystems hold nearly a third of the global soil carbon pool, but as wetlands rapidly disappear the fate of this stored soil carbon is unclear. The aim of this study was to quantify and then link potential rates of microbial decomposition after vertical drowning of vegetated tidal marshes in coastal Louisiana to known drivers of anaerobic decomposition altered by vegetation loss. Profiles of potential CH 4 and CO 2 production (surface to 60 cm deep) were measured during anaerobic incubations, organic matter chemistry was assessed with infrared spectroscopy, and soil porewater nutrients and redox potentials were measured in the field along a chronosequence of wetland loss. After vertical drowning, pond soils had lower redox potentials, higher pH values, lower soil carbon and nitrogen concentrations, lower lignin: polysaccharide ratios, more NH 4 + and PO 4 3− , and higher rates of potential CO 2 release than vegetated marsh soils. Potential CH 4 production was similar in vegetated marshes and open water ponds, with depth-dependent decreases in CH 4 production as soil carbon concentrations increased. In these anoxic soils, vegetation loss exerts a primary control on decomposition rates because flooding drives sustained increases in porewater nutrient availability (NH 4 + and PO 4 3 , dissolved organic carbon) and decreases in redox potential (from −150 to −500 mV) that lead to higher potential CO 2 fluxes within a few years. Without new carbon inputs following wetland loss, the sustained decomposition in open water ponds may lead to losses of stored soil carbon and could influence global carbon budgets.

Louisiana↗
USGS2024

Controls on stable methane isotope signatures in northern peatlands and potential shifts in signatures under permafrost thaw scenarios

Northern peatlands are a globally significant source of methane (CH 4 ), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH 4 production in these systems will be key to predicting annual emissions changes, with stable carbon isotopes (δ 13 C-CH 4 ) being a powerful tool for characterizing these drivers. Given that δ 13 C signatures of CH 4 are used in top-down atmospheric inversion models to partition sources, our ability to model CH 4 production pathways and associated δ 13 C-CH 4 signatures in peatland types impacted by a changing climate is critical. We sought to characterize the role of environmental conditions, including both hydrologic and vegetation patterns associated with permafrost thaw, on δ 13 C-CH 4 signatures from a diverse set of high-latitude peatlands. We measured porewater and emitted CH 4 stable isotopes, pH, and vegetation composition from five boreal-Arctic peatlands. Porewater δ 13 C-CH 4 was strongly associated with peatland type, with δ 13 C enriched values obtained from more minerotrophic fens (-61.2 ± 9.1‰) compared to permafrost-free bogs (-74.1 ± 9.4‰) and raised permafrost bogs (-81.6 ± 11.5‰). Variation in porewater δ 13 C-CH 4 was best explained by sedge cover, CH 4 concentration, and the interactive effect of peatland type and pH ( r 2 = 0.50, p < 0.001). Emitted δ 13 C-CH 4 varied greatly but was positively correlated with porewater δ 13 C-CH 4 , suggesting that porewater data can be used to predict changing emissions signatures from these systems. We calculated a weighted mean mixed atmospheric CH 4 signature for northern peatlands of -65.3 ± 7‰ and show that this signature is more sensitive to landscape drying (4 to 10 % depletion in δ 13 C) than wetting (1.5 to 5% enrichment in δ 13 C) under permafrost thaw scenarios. Our results suggest northern peatland δ 13 C-CH 4 signatures are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.

Journal of Geophysical Research: Biogeosciences↗
USGS2025

Quantifying the effect of petrogenic carbon on SOC turnover for two Rocky Mountain soils: When are petrogenic carbon corrections required?

Petrogenic organic carbon (OC petro ), derived from sedimentary rocks, is an often overlooked and poorly quantified source of soil organic carbon (SOC), which may influence measured or modeled SOC composition, age, and stability. In this study, we exploited differences in thermochemical stability between OC petro and biogenic SOC (OC bio ) using stepped elemental analysis to quantify the fractional contribution of OC petro to total SOC (f petro ), and we conducted a sensitivity analysis to estimate the effects of OC petro on modeled SOC transit times and system ages. Specifically, we compared the effects of accounting for OC petro inputs in SOC turnover modeling (using SoilR) for two montane meadow soils that are underlain by Cretaceous Mancos Shale. At these sites, we estimate that OC petro comprises 7%–9% of the total SOC stock (f petro = 0.07–0.09). However, accounting for OC petro as a mixture of inert and passive C or as completely inert C had negligible effects on SOC transit times and system ages, suggesting that there is a threshold of OC petro content under which there is minimal effect on calculated SOC turnover. Based on our sensitivity analysis, we estimate this threshold to be f petro = 0.125, further supporting that the accurate calculation of OC petro remains an important factor in estimating SOC turnover.

Colorado↗
USGS2024

Responses of marginal and intrinsic water-use efficiency to changing aridity using FLUXNET observations

According to classic stomatal optimization theory, plant stomata are regulated to maximize carbon assimilation for a given water loss. A key component of stomatal optimization models is marginal water-use efficiency (mWUE), the ratio of the change of transpiration to the change in carbon assimilation. Although the mWUE is often assumed to be constant, variability of mWUE under changing hydrologic conditions has been reported. However, there has yet to be a consensus on the patterns of mWUE variabilities and their relations with atmospheric aridity. We investigate the dynamics of mWUE in response to vapor pressure deficit (VPD) and aridity index using carbon and water fluxes from 115 eddy covariance towers available from the global database FLUXNET. We demonstrate a non-linear mWUE-VPD relationship at a sub-daily scale in general; mWUE varies substantially at both low and high VPD levels. However, mWUE remains relatively constant within the mid-range of VPD. Despite the highly non-linear relationship between mWUE and VPD, the relationship can be informed by the strong linear relationship between ecosystem-level inherent water-use efficiency (IWUE) and mWUE using the slope, m *. We further identify site-specific m * and its variability with changing site-level aridity across six vegetation types. We suggest accurately representing the relationship between IWUE and VPD using Michaelis–Menten or quadratic functions to ensure precise estimation of mWUE variability for individual sites.

Journal of Geophysical Research Biogeosciences↗
USGS2024

A semi-mechanistic model for partitioning evapotranspiration reveals transpiration dominates the water flux in drylands

Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well-suited to dryland ecosystems, such as high sensitivity of plant water-use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine-scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi-mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process-based models, and loosely constrains time-varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross-wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub-yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem-scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.

New Mexico↗
USGS2024

Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau

Biological soil crusts (biocrusts) are widespread soil photosynthetic communities covering about 12% of Earth's land surface and play crucial roles in terrestrial carbon (C) and nitrogen (N) cycles, yet scalable quantifications of biocrusts and their biogeochemical contributions are notably lacking. While remote sensing has enormous potential to assess, scale, and contextualize biocrusts and their functions, the applicability of hyperspectral data in predicting C- and N-related biocrust traits remains largely unexplored. We address this issue by evaluating the potential of in situ hyperspectral data to predict C and N across a range of biocrust species and different environmental conditions. We found that in situ hyperspectral reflectance measurements can be used to predict biocrust tissue C/N ratios and N concentrations with relatively high accuracy but to a lesser extent for potential biocrust N2 fixation rates. Critical wavelength domains included the visible region of the spectrum from roughly 490–600 nm, which most effectively captured variations in biocrust tissue C, and the shortwave infrared region from 1,150 to 1,350 nm and 1,550–1,650 nm, which most effectively captured biocrust tissue N and N2 fixation potential. Finally, we provide evidence that multi- and hyperspectral missions with targeted band placement, such as the proposed 26-band Landsat Next, could be effective in predicting biocrust traits. This work provides a critical step in understanding how to apply data from new and upcoming satellite missions to the monitoring of biocrusts.

Utah↗
USGS2024

Quantifying post-colonial peat carbon loss from a drained forested peatland, Great Dismal Swamp National Wildlife Refuge, USA

Peatland carbon storage is increasingly threatened by the combination of land-use change and climate variability, though carbon losses from land-use changes that span centuries are difficult to quantify, particularly in systems where little undisturbed area remains. Here we use a combination of vegetation change, fire history, and calculations of excess ash mass to quantify carbon loss in the Great Dismal Swamp National Wildlife Refuge (GDS NWR), USA, a highly impacted oligotrophic temperate peat swamp. Our results indicate that ditch construction that began in the Colonial Era in the late 1700s and continued into the mid-20th century across the swamp resulted in shifts from cypress-tupelo swamps to a combination of maple-gum and pine pocosin forests, consistent with drying surface conditions. Two large smoldering fires (2008, 2011) that were exacerbated by surface drainage, shifted vegetation from swamp to marsh, consumed peat over 25 km 2 , and caused losses of 1.05–1.34 Tg C due to peat burning. Across the Refuge as a whole, up to 48.2 Tg C has been lost to peat oxidation since ditch construction. Both stocks and rates of carbon loss remain higher than post-disturbance accumulation across most of GDS NWR, suggesting that existing efforts to block drainages to elevate water tables may not be enough to offset carbon losses. Rewetting heavily impacted surface peats may reduce peat oxidation and carbon loss, and shift vegetation toward hydrologic conditions preferred by pre-disturbance cypress-tupelo swamps.

North Carolina, Virginia↗
USGS2024

Controls on lake pelagic primary productivity: Formalizing the nutrient-color paradigm

Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We used data from 58 diverse and globally distributed temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. Across these diverse systems, and given relatively limited inputs, model predictions of primary production were highly correlated with observed values derived from high-frequency sensor data. Our analysis provides a model structure, including calibrated parameter estimates, that may be broadly useful for understanding current and future patterns in lake primary production.

JGR Biogeosciences↗
USGS2024

Climate, hydrology, and nutrients control the seasonality of Si concentrations in rivers

The seasonal behavior of fluvial dissolved silica (DSi) concentrations, termed DSi regime , mediates the timing of DSi delivery to downstream waters and thus governs river biogeochemical function and aquatic community condition. Previous work identified five distinct DSi regimes across rivers spanning the Northern Hemisphere, with many rivers exhibiting multiple DSi regimes over time. Several potential drivers of DSi regime behavior have been identified at small scales, including climate, land cover, and lithology, and yet the large-scale spatiotemporal controls on DSi regimes have not been identified. We evaluate the role of environmental variables on the behavior of DSi regimes in nearly 200 rivers across the Northern Hemisphere using random forest models. Our models aim to elucidate the controls that give rise to (a) average DSi regime behavior, (b) interannual variability in DSi regime behavior (i.e., Annual DSi regime), and (c) controls on DSi regime shape (i.e., minimum and maximum DSi concentrations). Average DSi regime behavior across the period of record was classified accurately 59% of the time, whereas Annual DSi regime behavior was classified accurately 80% of the time. Climate and primary productivity variables were important in predicting Average DSi regime behavior, whereas climate and hydrologic variables were important in predicting Annual DSi regime behavior. Median nitrogen and phosphorus concentrations were important drivers of minimum and maximum DSi concentrations, indicating that these macronutrients may be important for seasonal DSi drawdown and rebound. Our findings demonstrate that fluctuations in climate, hydrology, and nutrient availability of rivers shape the temporal availability of fluvial DSi.

Journal of Geophysical Research Biogeosciences↗