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Rangelands support many important ecosystem services and are highly sensitive to climate change. Understanding temporal dynamics in rangeland gross primary production (GPP) and how it may change under projected future climate, including more frequent and severe droughts, is critical for ranching communities to cope with future changes. Herein, we examined how climate regulates the interannual variability of GPP in California’s diverse annual rangeland, based on the contemporary records of satellite derived GPP at 500 m resolution since 2001. We built Gradient Boosted Regression Tree models for 23 ecoregion subsections, relating annual GPP with 30 climatic variables, to disentangle the partial dependence of GPP on each climate variable. The machine learning results showed that GPP was most sensitive to growing season (GS) precipitation, with a reduction in GPP up to 200 g cm−2 yr−1 when GS precipitation decreased from 400 to 100 mm yr−1 in one of the driest subsections. We also found that years with more evenly distributed GS precipitation had higher GPP. Warmer winter minimum air temperature enhanced GPP in approximately two-thirds of the subsections. In contrast, average GS air temperatures showed a negative relationship with annual GPP. When the pre-trained models were forced by downscaled future climate projections, changes in the predicted rangeland productivity by mid- and end of century were more remarkable at the ecoregion subsection scale than at the state level. Our machine learning-based analysis highlights key regional differences in GPP vulnerability to climate and provides insights on the intertwining and potentially counteracting effects of seasonal temperature and precipitation regimes. This work demonstrates the potential of using remote sensing to enhance field-based rangeland monitoring and, combined with machine learning, to inform adaptive management and conservation within the context of weather extremes and climate change.

Effective incentivization of soil carbon (C) storage as a climate mitigation strategy necessitates an improved understanding of management impacts on working farms. Using a regional survey on intensively managed farms, soil organic carbon (SOC) concentrations and stocks (0–100 cm) were evaluated in a pairwise comparison of long-term (10+ years) woody hedgerow plantings and adjacent crop fields in Yolo County, CA, USA. Twenty-one paired sites were selected to represent four soil types (Yolo silt loam, Brentwood clay loam, Capay silty clay, and Corning loam), with textures ranging from 16% to 51% clay. Soil C was higher in the upper 100 cm under hedgerows (14.4 kg m−2) relative to cultivated fields (10.6 kg m−2) and at all depths (0–10, 10–20, 20–50, 50–75, and 75–100 cm). The difference in SOC (3.8 kg m−2) did not vary by soil type, suggesting a broad potential for hedgerows to increase SOC stocks. Assuming adoption rates of 50 to 80% across California for hypothetical field edges of average-size farms, and an identical SOC sequestration potential across soil types, hedgerows could sequester 10.8 to 17.3 MMT CO2e, or 7 to 12% of California’s annual greenhouse gas reduction goals.

The fate of phosphorus (P) during pedogenesis has been historically conceptualized (Walker-Syers model) with time as the primary controlling state factor. Herein, we demonstrate that both climate and lithology exert a strong and interacting influence on the fate of P by examining coupled bioclimatic and parent material effects on soil P fractions. Three transects were investigated spanning a 2150-m elevation gradient (MAT = 17 → 3 °C/MAP = 330 → 1400 mm) across three separate bedrock lithologies (lithosequence: granite, andesite and basalt) within the Sierra Nevada and southern Cascades of California. The elevation gradient entails four bioclimatic zones (bioclimosequence: blue oak, ponderosa pine, white fir and red fir). Soil P fractions were determined by sequential fractionation and interpreted in the context of associated soil characterization data. The bioclimatic sequences demonstrate a weathering gradient with maximum intensity at mid-elevation sites, and corresponding changes in Fe/Al-(hydr)oxide content and aluminosilicate crystallinity. Phosphorus content of parent material varied by an order of magnitude (mean; mg P kg−1): andesite (1500) > basalt (1000) > granite (131). Differences in P content of parent material influenced Pt in soils. However, amounts and proportions of P in fractions were influenced by subtle to significant interactions between climate and lithology, owing to differences in chemical weathering and the abundance and crystallinity of Fe/Al-(hydr)oxides and aluminosilicates. This interactive effect of pedogenesis on clay mineralogy led to differences in P fractions dependent upon lithology and bioclimatic zone. Labile inorganic P (Pi) was uniformly higher in soils derived from granite, despite granite having significantly lower P content, a result of lower Fe/Al-(hydr)oxide generation in granitic soils. With descending elevation and increased weathering intensity, HCl-Pi (primary mineral bound P-apatite) declined in basalt and andesite but remained unchanged in granite owing to its greater resistance to chemical weathering. As weathering intensity increased, occluded P increased in basalt, decreased in andesite and was unchanged in granite, contradicting the paradigm of progressive P occlusion with increased weathering. This incongruity for andesite results from a dominance of poorly crystalline materials (e.g., ferrihydrite, allophane/imogolite) at less weathered sites versus more crystalline minerals at more weathered sites. This study highlights several caveats to the paradigm that time (i.e., degree of weathering) is universally the dominant pedogenic control of P fractionation. We identify the importance of interactions between lithology and climate in regulating the amount and types of weathering products that in turn control P fractionation and ecosystem P availability.

Soil moisture and temperature are incorporated into Soil Taxonomy through the broad classes of moisture and temperature regimes. Although both are important variables in soil formation and land use, soil temperature regime (STR) is typically applied at the family level, whereas soil moisture regime (SMR) is applied at the suborder level. In this paper, we are questioning whether moving SMR to the family level will create a classification system that is more efficient and provide more information to the user at higher categories. The pros and cons of moving ustic, xeric, and udic SMRs from suborder to family category are discussed. To explore this potential change, we used Shannon diversity (Delta H) as an index of the information gain moving from order to suborder when classifying a soil. The analysis indicated a relatively small Delta H for most of the country considering current suborder classes. The proposed group of suborders, characterized by diagnostic horizons instead of SMR, conveyed a considerably larger Delta H supporting a substantial gain in information if the change was incorporated into Soil Taxonomy. The proposed change also has the potential to reduce the number of subgroup taxa by nearly 50%, without losing any of the current information within each taxa. Counterarguments for the change are that SMRs have soil genesis connotations and provide a way to group similar soils on broad-scale maps. A change in the hierarchy of SMRs within Soil Taxonomy could deemphasize the relevance of soil moisture to soil genesis, morphology, and ecology. Published version Public domain – authored by a U.S. government employee

Soil compaction is a threat to agricultural soil function due to constriction of macro- and meso-pores necessary for air and water movement and crop root elongation. Soils are most vulnerable to compaction when moist. Agricultural soils saturated from winter precipitation or from intentional flooding for groundwater recharge may limit growers’ operational access to fields. The objective of this research was to develop guidance for rain-free “time-to-trafficability” (including shallow workability—when a soil is conducive to both tillage and traffic) after deep wetting, using soil survey data, pedotransfer functions, and a hydroclimatological modeling approach. Trafficability is defined as a threshold of field capacity (θfc) at the soil surface (0–10 cm), ranging from 85% of θfc (clays and silty clays) to 95% of θfc (sands and loamy sands). The θfc threshold is guided by the soil texture plasticity index, an indicator of compaction risk. 2911 soil profiles from soil survey databases were subjected to a wetting simulation, followed by drainage and evaporation using HYDRUS-1D across 11 locations representing mean annual potential evapotranspiration (PET) quantiles from 5% to 95%, four months (January-April), and three different years, assuming no precipitation. Rain-free time-to-trafficability was greatest in fine and loamy soils during cold months (January and February). However, seasonal effects on time-to-trafficability were more pronounced in loamy soils. Non-linear predictive functions were developed for each 0–10 cm textural class to enable mapping the typical time-to-trafficability across PET gradients, revealing clear regional and temporal patterns. Model derived estimates can inform agricultural managed aquifer recharge timing decisions and subsequent risk of soil compaction. Additional research is needed for validation and to better constrain time-to-trafficability estimates for loamy and fine textured soils, which show a greater degree of uncertainty amid greater risk of compaction indicated by plasticity indices.

Rangelands support many important ecosystem services and are highly sensitive to climate change. Understanding temporal dynamics in rangeland gross primary production (GPP) and how it may change under projected climate change, including more frequent and severe droughts, is critical for ranching communities to cope with future changes. Covering ~10% of California’s climatologically and topographically diverse landscapes, annual rangelands express varying sensitivity to precipitation fluctuation and warming. Herein, we examined how climate regulates temporal dynamics of annual GPP in California’s annual rangeland across scales, based on 20 years of satellite record derived GPP at 500-meter resolution since 2001. We built gradient boosted regression tree models for 23 ecoregion subsections in our study area, relating annual GPP with 30 climatic variables and disentangling the partial dependence of GPP on each climate variable. Our analysis showed that GPP was most sensitive to growing season precipitation amount; GPP decrease as much as 200 g C/m2/yr when growing season precipitation decreased from 400 to 100 mm/yr in one of the driest subsections. We also found that years with more evenly distributed growing season precipitation had higher GPP. Warmer winter minimum air temperature enhanced GPP in approximately two-thirds of the subsections. In contrast, average growing season mean and maximum air temperatures showed a negative relationship with annual GPP. When forced by downscaled future climate projections, changes in future rangeland productivity at the ecoregion subsection scale were more remarkable than at the state level; this suggests rangeland productivity responses to climate change will be highly variable at the local level. Further, we found large uncertainty in precipitation projections among the four climate models used in this study. Specifically, drier models predicted a larger degree of reduction in GPP, especially in drier subsections. Our machine learning-based analysis highlights key regional differences in GPP vulnerability to climate and provides insights into the intertwining and potentially counteracting effects of seasonal temperature and precipitation regimes. This work demonstrates the potential of using remote sensing to enhance field-based rangeland monitoring and, combined with machine learning, to inform adaptive management and conservation within the context of weather extremes and climate change.

To characterize the effect of precipitation events, management practices, and soil type on vineyard carbon (C) dynamics, we monitored CO₂ emissions and labile C pools from nine vineyards in Lodi Wine Grape District, California, from April 2011 to December 2012. These commercial vineyards are replicates of three soil series (Redding, San Joaquin, and Tokay), representing a spectrum of soil texture and degree of soil development. We hypothesized that soil characteristics would influence the magnitude of CO₂ efflux occurring in response to precipitation and management events in a Mediterranean climate. During each field visit—bimonthly (April–October) and monthly (November–March)—we measured CO₂, soil temperature, and gravimetric water content (GWC) from vine and intervine (alleys) rows. Monthly, we collected soil samples for dissolved organic C (DOC), which tended to be greater in the alleys of San Joaquin and Redding than Tokay in summer but decreased after the onset of precipitation. In mid-May and mid-October 2012, CO₂ efflux was higher in Tokay than in San Joaquin or Redding. Carbon dioxide efflux across all soils increased as a result of seasonal management practices (i.e., tillage and mowing of cover crops). Management practices distinguished soil DOC between vine rows and alleys from June to October 2012. Soil type or clay content influenced CO₂ efflux across these vineyards, as did GWC and soil temperature. This 20-mo study indicated that CO₂ efflux responded to soil disturbance from management practices, precipitation, and irrigation.

Rangelands are a key global resource, providing a broad range of ecological services and economic benefits. California’s predominantly annual rangelands cover ∼12% of the state’s land area, and the forage production is highly heterogeneous, making balancing economic (grazing), conservation (habitat) and environmental (erosion/water quality) objectives a big challenge. Herein, we examined how climate and environmental factors regulate annual grassland forage production spatially across the state and among four ecoregions using machine learning models. We estimated annual forage production at 30 m resolution over a 14 year period (2004–2017) using satellite images and data fusion techniques. Our satellite-based estimation agreed well with independent field measurements, with aR2of 0.83 and RMSE of 682 kg ha−1. Forage production (14 year average) showed large spatial variability (2940 ± 934 kg ha-1yr-1; CV = 35%) across the study area. The gradient boosted regression tree with 11 feature variables explained 67% of the variability in forage production across the state. Precipitation amount, especially in November (germination) and April (rapid growth), was found as the dominant driver for spatial variation in forage production, especially in drier ecoregions and during drier years. Seasonal distribution of precipitation and minimum air temperature showed a relatively stronger control on forage production in wetter regions and during wet years. Additionally, solar energy became more important in wetter ecoregions. Drought reduced forage production from the long-term mean, i.e. a 33% ± 19% decrease in production (2397 ± 926 kg ha-1yr-1; CV = 38%) resulting from a 29% ± 5% decrease in precipitation. The machine learning based spatial analysis using ‘big data’ provided insights on impacts of climate and environmental factors on forage production variation at various scales. This study demonstrates a cost-effective approach for rapid mapping and assessment of annual forage production with the potential for near real-time application.

Concentration-discharge (C-Q) relations can provide insight into the dynamic behavior of the Critical Zone (CZ), as C-Q relations integrate the spatial distribution and timing of watershed hydrogeochemical processes. This study blends geomorphologic analysis, C-Q relations and reactive-transport modeling using a rich dataset from an elevation gradient of eight watersheds in the Southern Sierra Nevada, California. We found that the CZ structure exerts a strong control on the C-Q relations, and on the hydrogeochemical behavior of headwater watersheds. Watersheds with thin regolith, a large stream network, and limited water storage have fast mean transit times along subsurface flow lines, and show limited seasonal variability in ionic concentrations in streamflow (i.e., chemostatic behavior). In contrast, watersheds with thicker regolith, a small stream network and more water storage have longer transit times along subsurface flow lines, and exhibit greater chemical variability (i.e., chemodynamic behavior). Independent estimates of mean transit times and water storage from other isotopic, hydrologic and geophysical studies were consistent with results from modeling C-Q relations. The stream chemistry and its variability were controlled by lateral flow within the regolith, and no mixing with deep groundwater was needed to explain the observed chemical variability. This study opens the possibility to estimate water-storage capacity and mean transit times, and thus drought resistance in watersheds, by using quantitative modeling of C-Q relations.

Background Globally, vegetation in riparian zones is frequently the target of restoration efforts because of its importance in reducing the input of eroded sediment and agricultural nutrient runoff to surface waters. Here we examine the potential of riparian zone restoration to enhance carbon sequestration. We measured soil and woody biomass carbon stocks, as well as soil carbon properties, in a long-term chronosequence of 42 streambank revegetation projects in northern California rangelands, varying in restoration age from 1 to 45 years old. Results Where revegetation was successful, we found that soil carbon measured to 50 cm depth increased at a rate of 0.87 Mg C ha−1 year−1 on the floodplain and 1.12 Mg C ha−1 year−1 on the upper bank landform. Restored sites also exhibited trends toward increased soil carbon permanence, including an increased C:N ratio and lower fulvic acid: humic acid ratio. Tree and shrub carbon in restored sites was modeled to achieve a 50-year maximum of 187.5 Mg C ha−1 in the channel, 279.3 Mg ha−1 in the floodplain, and 238.66 Mg ha−1 on the upper bank. After 20 years of restoration, the value of this carbon at current per-ton C prices would amount to $US 15,000 per km of restored stream. Conclusion We conclude that revegetating rangeland streambanks for erosion control has a substantial additional benefit of mitigating global climate change, and should be considered in carbon accounting and any associated financial compensation mechanisms.

Accurate assessments of soil organic carbon (SOC) stocks are needed at multiple scales given their importance to both local soil health and global C cycles. Rangelands cover 54% of California, representing a large stock of SOC, but existing SOC estimates are uncertain. To improve understanding of fine-resolution SOC stocks in complex terrain and provide guidance to rangeland SOC inventories, we grid-sampled 105 locations (21-m grid cells) at two depths (0–10 and 10–30 cm) in a 10-ha annual grassland catchment in California’s Central Coast Range. Soils were analyzed for bulk density, coarse fragments, SOC and texture. Monthly aerial imagery was acquired by an unmanned aerial vehicle to compare surface reflectance during two contrasting years (wet vs. dry) to SOC stocks. We found that the 0–30 cm soil thickness held 3.64 ± 0.71 kg SOC m−2 (mean ± SD) with a range of 1.97–5.49 kg SOC m−2. The 0–10 cm soil thickness stored 47% of the 0–30 cm SOC stock with SOC concentrations twice as high in the 0–10 cm layer (1.40 ± 0.38%) as in the 10–30 cm layer (0.71 ± 0.15% SOC). Multiple linear regression (MLR) models explained 50–57% of SOC variability at 0–30 and 10–30 cm, but only 25% of variability at 0–10 cm. Based on cross-validation tests, MLR outperformed spatial interpolation methods and Random Forest models, best explaining SOC stocks with five environmental covariates: wet-year greenness, mean curvature, elevation, insolation, and slope. Lower hillslope positions, concave landforms, and enhanced wet-year greenness were associated with more SOC, and explained 11%, 24%, and 31% of variability in 0–30 cm SOC stocks, respectively. This study demonstrates that the accuracy of regional-scale SOC mapping of California rangelands benefits from considering microclimatic and topographic controls at the catchment-scale, in addition to broader scale mineralogical and macroclimatic controls identified in previous SOC studies.

Author(s): O’Geen, AT; Safeeq, M; Wagenbrenner, J; Stacy, E; Hartsough, P; Devine, S; Tian, Z; Ferrell, R; Goulden, M; Hopmans, JW; Bales, R | Abstract: Sensor networks within the Southern Sierra Critical Zone Observatory (SSCZO) and Kings River Experimental Watersheds (KREW) document changes in the water cycle spanning the west slope of the southern Sierra Nevada in California. The networks were established to document water dynamics throughout the critical zone spanning profile, hillslope, catchment, and watershed scales at key locations that reflect systematic differences in bioclimatic conditions imposed by a strong elevation gradient. The critical zone observatory attempts to constrain the hydrologic budget via representative measurements of streamflow, eddy flux covariance, snow depth, meteorological conditions, and water content and water potential in soil and deep regolith. These measurements reveal the complexity of interactions among all aspects of the water balance (runoff, storage, evapotranspiration [ET], and precipitation) through daily, seasonal, and annual timescales. Multiyear drought, catastrophic wildfires, insect outbreaks, and disease have caused widespread tree mortality in the Sierra Nevada. These disturbances offer a window into the future for this region, which is expected to undergo significant change in response to global warming. This hydrological observatory provides valuable hydrometric attributes and fluxes across the stream–groundwater– vadose zone–soil–vegetation–atmosphere continuum.

Author(s): Devine, SM; O'Geen, AT; Larsen, RE; Dahlke, HE; Liu, H; Jin, Y; Dahlgren, RA | Abstract: Given the complex topography of California rangelands, contrasting microclimates affect forage growth at catchment scales. However, documentation of microclimate–forage growth associations is limited, especially in Mediterranean regions experiencing pronounced climate change impacts. To better understand microclimate–forage growth linkages, we monitored forage productivity and root-zone soil temperature and moisture (0–15 and 15–30ncm) in 16 topographic positions in a 10-ha annual grassland catchment in California's Central Coast Range. Data were collected through two strongly contrasting growing seasons, a wet year (2016–17) with 287-mm precipitation and a dry year (2017–18) with 123-mm precipitation. Plant-available soil water storage (0–30ncm) was more than half full for most of the wet year; mean peak standing forage was 2790nkgnha−1 (range: 1597–4570nkgnha−1). The dry year had restricted plant-available water and mean peak standing forage was reduced to 970nkgnha−1 (range: 462–1496nkgnha−1). In the wet year, forage growth appeared energy limited (light and temperature): warmer sites produced more forage across a 3–4°C soil temperature gradient but late season growth was associated with moister sites spanning this energy gradient. In the dry year, the warmest topographic positions produced limited forage across a 10°C soil temperature gradient until late season rainfall in March. Linear models accounting for interactions between soil moisture and temperature explained about half of rapid, springtime forage growth variance. These findings reveal dynamic but clear microclimate–forage growth linkages in complex terrain, and thus, have implications for rangeland drought monitoring and dryland ecosystems modeling under climate change.

Increasing soil organic carbon (SOC) via organic inputs is a key strategy for increasing long-term soil C storage and improving the climate change mitigation and adaptation potential of agricultural systems. A long-term trial in California's Mediterranean climate revealed impacts of management on SOC in maize-tomato and wheat-fallow cropping systems. SOC was measured at the initiation of the experiment and at year 19, at five depth increments down to 2m, taking into account changes in bulk density. Across the entire 2m profile, SOC in the wheat-fallow systems did not change with the addition of N fertilizer, winter cover crops (WCC), or irrigation alone and decreased by 5.6% with no inputs. There was some evidence of soil C gains at depth with both N fertilizer and irrigation, though high variation precluded detection of significant changes. In maize-tomato rotations, SOC increased by 12.6% (21.8MgC/ha) with both WCC and composted poultry manure inputs, across the 2m profile. The addition of WCC to a conventionally managed system increased SOC stocks by 3.5% (1.44MgC/ha) in the 0-30cm layer, but decreased by 10.8% (14.86MgC/ha) in the 30-200cm layer, resulting in overall losses of 13.4MgC/ha. If we only measured soil C in the top 30cm, we would have assumed an increase in total soil C increased with WCC alone, whereas in reality significant losses in SOC occurred when considering the 2m soil profile. Ignoring the subsoil carbon dynamics in deeper layers of soil fails to recognize potential opportunities for soil C sequestration, and may lead to false conclusions about the impact of management practices on C sequestration.

To evaluate the effect of precipitation events, management practices, and soil type in wine grape (Vitis vinifera L. ssp. vinifera) vineyard systems and provide data for greenhouse gas (GHG) emissions calculators, we monitored nine vineyards in the Lodi wine grape district, California, from April 2011 to December 2012. These commercial vineyards exist on three soil series (Redding, San Joaquin, and Tokay), representing a spectrum of soil textures and degrees of soil development. We hypothesized that soil characteristics would be a dominating factor affecting GHG fluxes, but the magnitude of fluxes would be influenced by precipitation and management events. We measured N₂O fluxes, soil NO₃–N and NH₄–N, and gravimetric water content (GWC) from vine and intervine (alleys) rows bimonthly (April–October) and monthly (November–March). Monthly, we collected soil samples for dissolved organic C (DOC) and dissolved organic N (DON) determination. Path analysis revealed that the effects of soil type and vineyard zone on N₂O emissions were influenced by soil texture (i.e., gravel and clay contents) but that this effect was mediated by GWC through soil temperature and soil inorganic N content. Management practices such as irrigation, fertigation, cover cropping, and tillage affected differences between vine rows and alleys for soil inorganic pools, DOC, and DON from June to October 2012. This 20-mo study indicated that precipitation events strongly influenced N₂O fluxes.

Author(s): Beaudette, DE; O'Geen, AT | Abstract: We evaluated the feasibility of quantitative soil mapping in two catenas established on different lithologies (metavolcanic and granitic) in the Sierra Foothill Region of California. Indices of landform and microclimate were extracted from a 1-m elevation model. Variation in soil "character" (clay content, pH, color, cation-exchange capacity [CEC], and Feo/Fed) was partitioned across variables associated with terrain shape and microclimate, lithologic variability, and sampling depth. The potential for using digital elevation models (DEM)-derived indices of terrain shape to predict spatial patterns in soil properties varied greatly between our two experimental catenas. Terrain shape accounted for 4% (metavolcanic site) to 30% (granitic site) of variance in soil properties, while lithology accounted for 14% (metavolcanic site) to 22% (granitic site) of variance in soil properties. Sample depth accounted for 3% (metavolcanic site) to 12% (granitic site) of variance in soil properties. At the metavolcanic site, variability in lithology contributed more to soil variation than terrain shape, which makes digital soil modeling efforts a challenge in these regions. Up to 66% of the variance in soil properties was explained at the granitic site when considering terrain, lithology, sample depth, and associated interactions of these variables. Variance proportions can provide insight into the relative importance of soil-forming factors and is a useful tool when evaluating the efficacy of digital soil mapping projects.

Groundwater pumping chronically exceeds natural recharge in many agricultural regions in California. A common method of recharging groundwater — when surface water is available — is to deliberately flood an open area, allowing water to percolate into an aquifer. However, open land suitable for this type of recharge is scarce. Flooding agricultural land during fallow or dormant periods has the potential to increase groundwater recharge substantially, but this approach has not been well studied. Using data on soils, topography and crop type, we developed a spatially explicit index of the suitability for groundwater recharge of land in all agricultural regions in California. We identified 3.6 million acres of agricultural land statewide as having Excellent or Good potential for groundwater recharge. The index provides preliminary guidance about the locations where groundwater recharge on agricultural land is likely to be feasible. A variety of institutional, infrastructure and other issues must also be addressed before this practice can be implemented widely.

Mountain runoff ultimately reflects the difference between precipitation (P) and evapotranspiration (ET), as modulated by biogeophysical mechanisms that intensify or alleviate drought impacts. These modulating mechanisms are seldom measured and not fully understood. The impact of the warm 2012–15 California drought on the heavily instrumented Kings River basin provides an extraordinary opportunity to enumerate four mechanisms that controlled the impact of drought on mountain hydrology. Two mechanisms intensified the impact: (i) evaporative processes have first access to local precipitation, which decreased the fractional allocation of P to runoff in 2012–15 and reduced P-ET by 30% relative to previous years, and (ii) 2012–15 was 1 °C warmer than the previous decade, which increased ET relative to previous years and reduced P-ET by 5%. The other two mechanisms alleviated the impact: (iii) spatial heterogeneity and the continuing supply of runoff from higher elevations increased 2012–15 P-ET by 10% relative to that expected for a homogenous basin, and iv) drought-associated dieback and wildfire thinned the forest and decreased ET, which increased 2016 P-ET by 15%. These mechanisms are all important and may offset each other; analyses that neglect one or more will over or underestimate the impact of drought and warming on mountain runoff.

© 2017 Hernes, Spencer, Dyda, O’Geen and Dahlgren. Evaluating the collective impact of small source inputs to larger rivers is a constant challenge in riverine biogeochemistry. In this study, we investigated the generation of dissolved organic matter (DOM) in a small oak woodland catchment in the foothills of northern California, the subsequent transformation in lignin biomarkers and chromophoric DOM (CDOM) parameters during transport through the landscape to an exporting stream, and finally the overall compositional impact on the larger receiving stream and river. Our study included a natural leaching experiment in which precipitation passing through oak, pine, and grass litter and duff samples was collected after each of a series of storms. Also included were soil trench samples to capture subsurface lateral flow, stream samples along with point-source reservoir inputs, and samples of canopy throughfall, stemflow, and gopher hole (bypass) flow. The litter/duff leaching study demonstrated changing DOM fractionation patterns throughout the season, as evidenced by changing lignin compositions in the leachates with each successive storm. This adds a necessary seasonal component to interpreting lignin compositions in streams, as the source signatures are constantly changing. Released DOM from leaching was modified extensively during transit through the subsurface to the stream, with preferential increases in aromaticity as evidenced by increases in carbon-normalized absorbance at 254 nm, yet preferential decreases in lignin phenols, as evidence by carbon-normalized lignin yields in the headwater stream that was less than half that of the litter/duff leachates. Our extensive number of lignin measurements for source materials reveals a much more complex perspective on using lignin as a source indicator, as many riverine values for syringyl:vanillyl and cinnamyl:vanillyl ratios that have previously been interpreted as degraded lignin signatures are also possible as unmodified source signatures. Finally, this study demonstrated that the impact of numerous small headwater streams can significantly overprint the DOM signatures of much larger rivers over relatively short distances spanning several to tens of kilometers. This finding in particular challenges the assumption that river studies can be adequately conducted by focusing only on the main tributaries.

Wetland environments are important sites for the cycling and retention of terrestrially derived organic matter and nutrients. Wetland treatment of agricultural runoff has been shown to improve water quality and promote carbon sequestration. However, the potential role of eutrophic wet- lands as a source of algal loading contributing to downstream hypoxia has prompted interest in understanding algal produc- tivity and export from these systems. This study, in the San Joaquin Valley, California, quantified a mass balance of car- bon and nutrients within a seasonally-saturated constructed wetland receiving agricultural runoff, as well as quantifying autochthonous carbon production on four sampling dates during a year with minimal emergent vegetation. Results from this study show that the wetland was a net-sink for nutrients and particulate/dissolved organic carbon. Despite high con- centrations of inflowing nutrients and high rates of primary productivity, high respiration rates limited net organic C pro- duction and export due to high heterotrophic activity. The addition of high C loads in inflowing water and moderate retention efficiencies, however, resulted in a positive C reten- tion during most sampling dates. This study provides valuable insight into the connection between elevated carbon and nu- trient inflows, their effects on autochthonous carbon produc- tion, and resulting carbon and nutrient outflows.

© 2015 American Society of Civil Engineers. A common phenomenon observed in natural and constructed wetlands is short-circuiting of flow and formation of stagnant zones that are only indirectly connected with the incoming water. Biogeochemistry of passive areas is potentially much different than that of active zones. In the research reported in this paper, the spatial resolution of a previously developed wetland nutrient cycling model was improved in order to capture the spatial variability of concentrations and reaction rates regarding nitrogen and carbon cycles throughout active and passive zones of wetlands. The upgraded model allows for several compartments in the horizontal domain, with all neighboring compartments connected through advective and dispersive/diffusive mass transport. The model was applied to data collected from a restored wetland in California that was characterized by the formation of a large stagnant zone at the southern end of the wetland due to close vicinity of the inlet and outlet structures in the northern end. Mass balance analysis revealed that over the course of the research period, about 23.4±3.9% of the incoming total nitrogen load was removed or retained by the wetland. It was observed that mass of all exchanges (physical and biogeochemical) regarding nitrogen cycling decreased along the activity gradient from active to passive zones. Model results also revealed that anaerobic processes become more significant along the activity gradient towards passive areas.

Policy makers and practitioners are in need of useful tools and models for assessing ecosystem service outcomes and the potential risks and opportunities of ecosystem management options. We utilize a state-and-transition model framework integrating dynamic soil and vegetation properties to examine multiple ecosystem services—specifically agricultural production, biodiversity and habitat, and soil health—across human created vegetation states in a managed oak woodland landscape in a Mediterranean climate. We found clear tradeoffs and synergies in management outcomes. Grassland states maximized agricultural productivity at a loss of soil health, biodiversity, and other ecosystem services. Synergies existed among multiple ecosystem services in savanna and woodland states with significantly larger nutrient pools, more diversity and native plant richness, and less invasive species. This integrative approach can be adapted to a diversity of working landscapes to provide useful information for science-based ecosystem service valuations, conservation decision making, and management effectiveness assessments.

© 2016 Elsevier B.V. Earthquakes often cause destructive and unpredictable changes that can affect local hydrology (e.g. groundwater elevation or reduction) and thus disrupt land uses and human activities. Prolific agricultural regions overlie seismically active areas, emphasizing the importance to improve our understanding and monitoring of hydrologic and agricultural systems following a seismic event. A thorough data collection is necessary for adequate post-earthquake crop management response; however, the large spatial extent of earthquake's impact makes challenging the collection of robust data sets for identifying locations and magnitude of these impacts. Observing hydrologic responses to earthquakes is not a novel concept, yet there is a lack of methods and tools for assessing earthquake's impacts upon the regional hydrology and agricultural systems. The objective of this paper is to describe how remote sensing imagery, methods and tools allow detecting crop responses and damage incurred after earthquakes because a change in the regional hydrology. Many remote sensing datasets are long archived with extensive coverage and with well-documented methods to assess plant-water relations. We thus connect remote sensing of plant water relations to its utility in agriculture using a post-earthquake agrohydrologic remote sensing (PEARS) framework; specifically in agro-hydrologic relationships associated with recent earthquake events that will lead to improved water management.

Quaking aspen (Populus tremuloides Michaux) stands are important for biodiversity in conifer-dominated forest landscapes. Our goal was to quantify the consequences of conifer succession on understory diversity and litter quality, as well as asso- ciated changes in aspen stand condition. We studied aspen stands on national park land in the transition zone between the northern Sierra Nevada and southern Cascade mountain ranges. We field-measured ten met- rics of aspen stand condition in 29 aspen stands. Along a gradient of increasing current conifer cover, we observed decreases in herbaceous species diversity and richness and an increase in forest floor O horizon depth. We interpreted aerial photos from 1952 and 1998 to determine whether directional changes in co- nifer cover had occurred in the stands over the past half century, and used regression modeling to associ- ate succession with the observed range of aspen stand condition. From the period 1952 to 1998, we found that conifer encroachment occurred in half the sam- pled stands, with an average increase in conifer cover of 1 % a year. Aspen were persistent in the remaining stands. Stand cover dynamics and percent total canopy cover interacted to influence species richness, diversi- ty, aspen sprouting, and litter quality. In stands with conifer encroachment, both understory species rich- ness and diversity declined. Although aspen sprouting increased, aspen establishment declined and the rela- tive mass of woody to fine soil litter increased.

Wetlands are highly dynamic ecosystems that exhibit large temporal and spatial gradients in biogeochemical and metabolic processes. While previous studies have documented temporal variability of wetland metabolism, very little is known regarding how wetland metabolism varies spatially. This is particularly relevant for constructed flow-through wetlands used to treat agricultural runoff due to growing concern over the potential for these systems to act as incubators of biological oxygen demanding (BOD) substances (i.e., algal biomass) and contributors to downstream hypoxia. This study employed a spatially explicit characterization of wetland water column properties using multiparameter water quality sondes, thus allowing the calculation of wetland metabolism across a range of spatial scales (meters to 100 s of meters). This study documented a high degree of spatial variability in metabolic rates within the wetland, with average gross primary productivity (GPP) ranging from 6.41 to 13.69 g O 2 m −2 d −1 , community respiration (CR) ranging from 4.85 to 9.79 g O 2 m −2 d −1 , and net ecosystem production (NEP) ranging from 0.35 to 2.42 g O 2 m −2 d −1 . Linkages between metabolic rates and environmental controls were quantified using a spatial/temporal statistical approach. Five key environmental parameters (turbidity, dissolved reactive phosphorus, ammonium, electrical conductivity, and temperature) were found to correlate with ecosystem metabolism. Results from this study show that despite high rates of primary productivity, high respiration rates limited NEP in this wetland due to high heterotrophic activity.

The effectiveness of best management practices (BMPs) designed primarily to pro- tect surface water quality was assessed on a farm certified for organic tomato production to consider potential environmental quality and production tradeoffs. The BMPs included winter cover crops typically used in organic farming to cycle nutrients and reduce storm- water runoff; tailwater ponds designed to capture runoff; and tailwater return systems, which recycle runoff back to the field. The study took place at a 44 ha (108 ac) farm in Yolo County, California, over a two-year period. Monitoring throughout the winter rainy season showed cover crops successfully reduced runoff and loads of several constituents during the storm events, when compared to fallow. Total discharge was reduced by 44%, total suspended solids was reduced by 83%, ammonium was reduced by 33%, and dissolved organic carbon (DOC) was reduced by 58%. Estimates of leaching losses of DOC in the cover cropped fields, how- ever, were 70% higher than the fallow fields in the winter rainy season and were 30% higher than the fallow fields in the summer irrigation season. During the summer irrigation season, the tailwater pond alone was highly effective in reducing losses of total suspended solids and volatile suspended solids to the neighboring riparian zone by 97% and 89%, respectively. The tailwater pond had no effect on dissolved reactive phosphorous and actually increased concentrations of nitrate-nitrogen (NO 3 - -N) in effluent by 40% and DOC by 20%. As was expected, the NO 3 - -N leaching measured by anion exchange resin bags and nitrous oxide emissions measured by static closed chambers was higher for the tailwater pond than the fal- low field. Despite these differences, losses via NO 3 - -N leaching and nitrous oxide emissions accounted for only 24.7 and 0.48 kg N ha -1 y -1 (22.0 and 0.40 lb N ac -1 ), respectively, for the entire farm, even including ponds and ditches. When field and plot values were extrapolated to the entire tomato production area to understand the relative potential tradeoffs, results indicate that BMPs could be implemented without an impact on tomato marketable yields; the tailwater pond's higher nitrous oxide emissions would not significantly increase the overall emissions for tomato production given its relatively small size; and using tailwater ponds in combination with cover crops would decrease total suspended solids (TSS) losses compared to cover crops alone, with only minor increases in NO 3 - -N and DOC losses. Adding a tailwater return system to this combination of BMPs could help minimize these NO 3 - -N and DOC

Agriculture in the Central Valley of California, one of the USA’s main sources of fruits, nuts, and vegetables, is highly vulnerable to climate change impacts in the next 50 years. This interdisciplinary case study in Yolo County shows the urgency for building adaptation strategies to climate change. Climate change and the effects of greenhouse gas emissions are complex, and several of the county’s current crops will be less viable in 2050. The study uses a variety of methods to assemble information relevant to Yolo County’s agriculture, including literature reviews, models, geographic information system analysis, interviews with agency personnel, and a survey of farmers. Potential adaptation and mitigation responses by growers include changes in crop taxa, irrigation methods, fertilization practices, tillage practices, and land use. On a regional basis, planning must consider the vulnerability of agricultural production and the tradeoffs associated with diversified farmlands, drought, flooding of cropland, loss of habitat for wild species of concern, and urbanization.