California Water Science Center

Abstract Advances in spectroscopic techniques have led to an increase in the use of optical properties (absorbance and fluorescence) to assess dissolved organic matter (DOM) composition and infer sources and processing. However, little information is available to assess the impact of biological and photolytic processing on the optical properties of original DOM source materials. Over a 3.5 month laboratory study, we measured changes in commonly used optical properties and indices in DOM leached from peat soil, plants, and algae following biological and photochemical degradation to determine whether they provide unique signatures that can be linked to original DOM source. Changes in individual optical parameters varied by source material and process, with biodegradation and photodegradation often causing values to shift in opposite directions. Although values for different source materials frequently overlapped, multivariate statistical analyses showed that unique optical signatures could be linked to original DOM source material, with 17 optical properties determined by discriminant analysis to be significant ( p < 0.05) in distinguishing between DOM source and environmental processing. These results demonstrate that inferring source material from optical properties is possible when parameters are evaluated in combination even after extensive biological and photochemical alteration.

Neonicotinoid use has increased rapidly in recent years, with a global shift toward insecticide applications as seed coatings rather than aerial spraying. While the use of seed coatings can lessen the amount of overspray and drift, the near universal and prophylactic use of neonicotinoid seed coatings on major agricultural crops has led to widespread detections in the environment (pollen, soil, water, honey). Pollinators and aquatic insects appear to be especially susceptible to the effects of neonicotinoids with current research suggesting that chronic sublethal effects are more prevalent than acute toxicity. Meanwhile, evidence of clear and consistent yield benefits from the use of neonicotinoids remains elusive for most crops. Future decisions on neonicotinoid use will benefit from weighing crop yield benefits versus environmental impacts to nontarget organisms and considering whether there are more environmentally benign alternatives.

Neonicotinoid insecticides are widely used in both urban and agricultural settings around the world. Historically, neonicotinoid insecticides have been viewed as ideal replacements for more toxic compounds, like organophosphates, due in part to their perceived limited potential to affect the environment and human health. This critical review investigates the environmental fate and toxicity of neonicotinoids and their metabolites and the potential risks associated with exposure. Neonicotinoids are found to be ubiquitous in the environment, drinking water, and food, with low-level exposure commonly documented below acceptable daily intake standards. Available toxicological data from animal studies indicate possible genotoxicity, cytotoxicity, impaired immune function, and reduced growth and reproductive success at low concentrations, while limited data from ecological or cross-sectional epidemiological studies have identified acute and chronic health effects ranging from acute respiratory, cardiovascular, and neurological symptoms to oxidative genetic damage and birth defects. Due to the heavy use of neonicotinoids and potential for cumulative chronic exposure, these insecticides represent novel risks and necessitate further study to fully understand their risks to humans.

Recent studies suggest that species distribution models (SDMs) based on fine-scale climate data may provide markedly different estimates of climate-change impacts than coarse-scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse-scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000-fold range of spatial scales (0.008-16 km(2) ). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate-data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine- and coarse-scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.

Pharmaceutical compounds were detected at low concentrations in 2.3% of 1231 samples of groundwater (median depth to top of screened interval in wells=61 m) used for public drinking-water supply in California. Samples were collected statewide for the California State Water Resources Control Board's Groundwater Ambient Monitoring and Assessment (GAMA) Program. Of 14 pharmaceutical compounds analyzed, 7 were detected at concentrations greater than or equal to method detection limits: acetaminophen (used as an analgesic, detection frequency 0.32%, maximum concentration 1.89 μg/L), caffeine (stimulant, 0.24%, 0.29 μg/L), carbamazepine (mood stabilizer, 1.5%, 0.42 μg/L), codeine (opioid analgesic, 0.16%, 0.214 μg/L), p-xanthine (caffeine metabolite, 0.08%, 0.12 μg/L), sulfamethoxazole (antibiotic, 0.41%, 0.17 μg/L), and trimethoprim (antibiotic, 0.08%, 0.018 μg/L). Detection frequencies of pesticides (33%), volatile organic compounds not including trihalomethanes (23%), and trihalomethanes (28%) in the same 1231 samples were significantly higher. Median detected concentration of pharmaceutical compounds was similar to those of volatile organic compounds, and higher than that of pesticides. Pharmaceutical compounds were detected in 3.3% of the 855 samples containing modern groundwater (tritium activity>0.2 TU). Pharmaceutical detections were significantly positively correlated with detections of urban-use herbicides and insecticides, detections of volatile organic compounds, and percentage of urban land use around wells. Groundwater from the Los Angeles metropolitan area had higher detection frequencies of pharmaceuticals and other anthropogenic compounds than groundwater from other areas of the state with similar proportions of urban land use. The higher detection frequencies may reflect that groundwater flow systems in Los Angeles area basins are dominated by engineered recharge and intensive groundwater pumping.

The Central Valley in California (USA) covers about 52,000 km2 and is one of the most productive agricultural regions in the world. This agriculture relies heavily on surface-water diversions and groundwater pumpage to meet irrigation water demand. Because the valley is semi-arid and surface-water availability varies substantially, agriculture relies heavily on local groundwater. In the southern two thirds of the valley, the San Joaquin Valley, historic and recent groundwater pumpage has caused significant and extensive drawdowns, aquifer-system compaction and subsidence. During recent drought periods (2007–2009 and 2012-present), groundwater pumping has increased owing to a combination of decreased surface-water availability and land-use changes. Declining groundwater levels, approaching or surpassing historical low levels, have caused accelerated and renewed compaction and subsidence that likely is mostly permanent. The subsidence has caused operational, maintenance, and construction-design problems for water-delivery and flood-control canals in the San Joaquin Valley. Planning for the effects of continued subsidence in the area is important for water agencies. As land use, managed aquifer recharge, and surface-water availability continue to vary, long-term groundwater-level and subsidence monitoring and modelling are critical to understanding the dynamics of historical and continued groundwater use resulting in additional water-level and groundwater storage declines, and associated subsidence. Modeling tools such as the Central Valley Hydrologic Model, can be used in the evaluation of management strategies to mitigate adverse impacts due to subsidence while also optimizing water availability. This knowledge will be critical for successful implementation of recent legislation aimed toward sustainable groundwater use.

We document changes in forest structure between historical (1930s) and contemporary (2000s) surveys of California vegetation through comparisons of tree abundance and size across the state and within several ecoregions. Across California, tree density in forested regions increased by 30% between the two time periods, whereas forest biomass in the same regions declined, as indicated by a 19% reduction in basal area. These changes reflect a demographic shift in forest structure: larger trees (>61 cm diameter at breast height) have declined, whereas smaller trees (<30 cm) have increased. Large tree declines were found in all surveyed regions of California, whereas small tree increases were found in every region except the south and central coast. Large tree declines were more severe in areas experiencing greater increases in climatic water deficit since the 1930s, based on a hydrologic model of water balance for historical climates through the 20th century. Forest composition in California in the last century has also shifted toward increased dominance by oaks relative to pines, a pattern consistent with warming and increased water stress, and also with paleohistoric shifts in vegetation in California over the last 150,000 y.

Environmental context Neonicotinoids are under increased scrutiny because they have been implicated in pollinator declines and, more recently, as potential aquatic toxicants. Nevertheless, there is currently little information on concentrations of multiple neonicotinoids in surface water. This paper presents a summary of concentrations of six neonicotinoids in streams from across the United States in both urban and agricultural areas. These environmental data are important in determining the potential risk of neonicotinoids to non-target aquatic and terrestrial organisms. Abstract To better understand the fate and transport of neonicotinoid insecticides, water samples were collected from streams across the United States. In a nationwide study, at least one neonicotinoid was detected in 53 % of the samples collected, with imidacloprid detected most frequently (37 %), followed by clothianidin (24 %), thiamethoxam (21 %), dinotefuran (13 %), acetamiprid (3 %) and thiacloprid (0 %). Clothianidin and thiamethoxam concentrations were positively related to the percentage of the land use in cultivated crop production and imidacloprid concentrations were positively related to the percentage of urban area within the basin. Additional sampling was also conducted in targeted research areas to complement these national-scale results, including determining: (1) neonicotinoid concentrations during elevated flow conditions in an intensely agricultural region; (2) temporal patterns of neonicotinoids in heavily urbanised basins; (3) neonicotinoid concentrations in agricultural basins in a nationally important ecosystem; and (4) in-stream transport of neonicotinoids near a wastewater treatment plant. Across all study areas, at least one neonicotinoid was detected in 63 % of the 48 streams sampled.

Pervasive warming can lead to chronic stress on forest trees, which may contribute to mortality resulting from fire-caused injuries. Longitudinal analyses of forest plots from across the western US show that high pre-fire climatic water deficit was related to increased post-fire tree mortality probabilities. This relationship between climate and fire was present after accounting for fire defences and injuries, and appeared to influence the effects of crown and stem injuries. Climate and fire interactions did not vary substantially across geographical regions, major genera and tree sizes. Our findings support recent physiological evidence showing that both drought and heating from fire can impair xylem conductivity. Warming trends have been linked to increasing probabilities of severe fire weather and fire spread; our results suggest that warming may also increase forest fire severity (the number of trees killed) independent of fire intensity (the amount of heat released during a fire).

Environmental releases of antibiotics from concentrated animal feeding operations (CAFOs) are of increasing regulatory concern. This study investigates the use and occurrence of antibiotics in dairy CAFOs and their potential transport into first-encountered groundwater. On two dairies we conducted four seasonal sampling campaigns, each across 13 animal production and waste management systems and associated environmental pathways: application to animals, excretion to surfaces, manure collection systems, soils, and shallow groundwater. Concentrations of antibiotics were determined using on line solid phase extraction (OLSPE) and liquid chromatography-tandem mass spectrometry (LC/MS/MS) with electrospray ionization (ESI) for water samples, and accelerated solvent extraction (ASE) LC/MS/MS with ESI for solid samples. A variety of antibiotics were applied at both farms leading to antibiotics excretion of several hundred grams per farm per day. Sulfonamides, tetracyclines, and their epimers/isomers, and lincomycin were most frequently detected. Yet, despite decades of use, antibiotic occurrence appeared constrained to within farm boundaries. The most frequent antibiotic detections were associated with lagoons, hospital pens, and calf hutches. When detected below ground, tetracyclines were mainly found in soils, whereas sulfonamides were found in shallow groundwater reflecting key differences in their physicochemical properties. In manure lagoons, 10 compounds were detected including tetracyclines and trimethoprim. Of these 10, sulfadimethoxine, sulfamethazine, and lincomycin were found in shallow groundwater directly downgradient from the lagoons. Antibiotics were sporadically detected in field surface samples on fields with manure applications, but not in underlying sandy soils. Sulfadimethoxine and sulfamethazine were detected in shallow groundwater near field flood irrigation gates, but at highly attenuated levels.

Responses of benthic macroinvertebrates along gradients of urban intensity were investigated in nine metropolitan areas across the United States. Invertebrate assemblages in metropolitan areas where forests or shrublands were being converted to urban land were strongly related to urban intensity. In metropolitan areas where agriculture and grazing lands were being converted to urban land, invertebrate assemblages showed much weaker or nonsignificant relations with urban intensity because sites with low urban intensity were already degraded by agriculture. Ordination scores, the number of EPT taxa, and the mean pollution-tolerance value of organisms at a site were the best indicators of changes in assemblage condition. Diversity indices, functional groups, behavior, and dominance metrics were not good indicators of urbanization. Richness metrics were better indicators of urban effects than were abundance metrics, and qualitative samples collected from multiple habitats gave similar results to those of single habitat quantitative samples (riffles or woody snags) in all metropolitan areas. Changes in urban intensity were strongly correlated with a set of landscape variables that was consistent across all metropolitan areas. In contrast, the instream environmental variables that were strongly correlated with urbanization and invertebrate responses varied among metropolitan areas. The natural environmental setting determined the biological, chemical, and physical instream conditions upon which urbanization acts and dictated the differences in responses to urbanization among metropolitan areas. Threshold analysis showed little evidence for an initial period of resistance to urbanization. Instead, assemblages were degraded at very low levels of urbanization, and response rates were either similar across the gradient or higher at low levels of urbanization. Levels of impervious cover that have been suggested as protective of streams (5-10%) were associated with significant assemblage degradation and were not protective.

Field‐deployable sensors designed to continuously measure the fluorescence of colored dissolved organic matter (FDOM) in situ are of growing interest. However, the ability to make FDOM measurements that are comparable across sites and over time requires a clear understanding of how instrument characteristics and environmental conditions affect the measurements. In particular, the effects of water temperature and light attenuation by both colored dissolved material and suspended particles may be significant in settings such as rivers and streams. Using natural standard reference materials, we characterized the performance of four commerciallyavailable FDOM sensors under controlled laboratory conditions over ranges of temperature, dissolved organic matter (DOM) concentrations, and turbidity that spanned typical environmental ranges. We also examined field data from several major rivers to assess how often attenuation artifacts or temperature effects might be important. We found that raw (uncorrected) FDOM values were strongly affected by the light attenuation that results from dissolved substances and suspended particles as well as by water temperature. Observed effects of light attenuation and temperature agreed well with theory. Our results show that correction of measured FDOM values to account for these effects is necessary and feasible over much of the range of temperature, DOM concentration, and turbidity commonly encountered in surface waters. In most cases, collecting high‐quality FDOM measurements that are comparable through time and between sites will require concurrent measurements of temperature and turbidity, and periodic discrete sample collection for laboratory measurement of DOM.

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50ppb and probability of dissolved oxygen concentration to be below 0.5ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971-2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.

Projected longer-term droughts and intense floods underscore the need to store more water to manage climate extremes. Here we show how depleted aquifers have been used to store water by substituting surface water use for groundwater pumpage (conjunctive use, CU) or recharging groundwater with surface water (managed aquifer recharge, MAR). Unique multi-decadal monitoring from thousands of wells and regional modeling datasets for the California Central Valley and central Arizona were used to assess CU and MAR. In addition to natural reservoir capacity related to deep water tables, historical groundwater depletion further expanded aquifer storage by ∼44 km ^3 in the Central Valley and by ∼100 km ^3 in Arizona, similar to or exceeding current surface reservoir capacity by up to three times. Local river water and imported surface water, transported through 100s of km of canals, is substituted for groundwater (≤15 km ^3 yr ^−1 , CU) or is used to recharge groundwater (MAR, ≤1.5 km ^3 yr ^−1 ) during wet years shifting to mostly groundwater pumpage during droughts. In the Central Valley, CU and MAR locally reversed historically declining water-level trends, which contrasts with simulated net regional groundwater depletion. In Arizona, CU and MAR also reversed historically declining groundwater level trends in active management areas. These rising trends contrast with current declining trends in irrigated areas that lack access to surface water to support CU or MAR. Use of depleted aquifers as reservoirs could expand with winter flood irrigation or capturing flood discharges to the Pacific (0–1.6 km ^3 yr ^−1 , 2000–2014) with additional infrastructure in California. Because flexibility and expanded portfolio options translate to resilience, CU and MAR enhance drought resilience through multi-year storage, complementing shorter term surface reservoir storage, and facilitating water markets.

Groundwater is an important source of drinking water supplies in the conterminous United State (CONUS), and presence of high nitrate concentrations may limit usability of groundwater in some areas because of the potential negative health effects. Prediction of locations of high nitrate groundwater is needed to focus mitigation and relief efforts. A three-dimensional extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate. Nitrate was predicted at a 1 km resolution for two drinking water zones, each of variable depth, one for domestic supply and one for public supply. The model used measured nitrate concentrations from 12,082 wells and included predictor variables representing well characteristics, hydrologic conditions, soil type, geology, land use, climate, and nitrogen inputs. Predictor variables derived from empirical or numerical process-based models were also included to integrate information on controlling processes and conditions. The model provided accurate estimates at national and regional scales: the training (R2 of 0.83) and hold-out (R2 of 0.49) data fits compared favorably to previous studies. Predicted nitrate concentrations were less than 1 mg/L across most of the CONUS. Nationally, well depth, soil and climate characteristics, and the absence of developed land use were among the most influential explanatory factors. Only 1% of the area in either water supply zone had predicted nitrate concentrations greater than 10 mg/L; however, about 1.4 M people depend on groundwater for their drinking supplies in those areas. Predicted high concentrations of nitrate were most prevalent in the central CONUS. In areas of predicted high nitrate concentration, applied manure, farm fertilizer, and agricultural land use were influential predictor variables. This work represents the first application of XGB to a three-dimensional national-scale groundwater quality model and provides a significant milestone in the efforts to document nitrate in groundwater across the CONUS.

The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state's fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change.

The flux of dissolved organic carbon (DOC) from mangrove swamps accounts for 10% of the global terrestrial flux of DOC to coastal oceans. Recent findings of high concentrations of mercury (Hg) and methylmercury (MeHg) in mangroves, in conjunction with the common co-occurrence of DOC and Hg species, have raised concerns that mercury fluxes may also be large. We used a novel approach to estimate export of DOC, Hg, and MeHg to coastal waters from a mangrove-dominated estuary in Everglades National Park (Florida, USA). Using in situ measurements of fluorescent dissolved organic matter as a proxy for DOC, filtered total Hg, and filtered MeHg, we estimated the DOC yield to be 180 (±12.6) g C m(-2) yr(-1), which is in the range of previously reported values. Although Hg and MeHg yields from tidal mangrove swamps have not been previously measured, our estimated yields of Hg species (28 ± 4.5 μg total Hg m(-2) yr(-1) and 3.1 ± 0.4 μg methyl Hg m(-2) yr(-1)) were five times greater than is typically reported for terrestrial wetlands. These results indicate that in addition to the well documented contributions of DOC, tidally driven export from mangroves represents a significant potential source of Hg and MeHg to nearby coastal waters.

Uranium (U) concentrations in groundwater in several parts of the eastern San Joaquin Valley, California, have exceeded federal and state drinking water standards during the last 20 years. The San Joaquin Valley is located within the Central Valley of California and is one of the most productive agricultural areas in the world. Increased irrigation and pumping associated with agricultural and urban development during the last 100 years have changed the chemistry and magnitude of groundwater recharge, and increased the rate of downward groundwater movement. Strong correlations between U and bicarbonate suggest that U is leached from shallow sediments by high bicarbonate water, consistent with findings of previous work in Modesto, California. Summer irrigation of crops in agricultural areas and, to lesser extent, of landscape plants and grasses in urban areas, has increased Pco(2) concentrations in the soil zone and caused higher temperature and salinity of groundwater recharge. Coupled with groundwater pumping, this process, as evidenced by increasing bicarbonate concentrations in groundwater over the last 100 years, has caused shallow, young groundwater with high U concentrations to migrate to deeper parts of the groundwater system that are tapped by public-supply wells. Continued downward migration of U-affected groundwater and expansion of urban centers into agricultural areas will likely be associated with increased U concentrations in public-supply wells. The results from this study illustrate the potential long-term effects of groundwater development and irrigation-supported agriculture on water quality in arid and semiarid regions around the world.

Abstract Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kg C m −3 ), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision.

The butterfly fauna of lowland Northern California has exhibited a marked decline in recent years that previous studies have attributed in part to altered climatic conditions and changes in land use. Here, we ask if a shift in insecticide use towards neonicotinoids is associated with butterfly declines at four sites in the region that have been monitored for four decades. A negative association between butterfly populations and increasing neonicotinoid application is detectable while controlling for land use and other factors, and appears to be more severe for smaller-bodied species. These results suggest that neonicotinoids could influence non-target insect populations occurring in proximity to application locations, and highlights the need for mechanistic work to complement long-term observational data.