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Research about Central Valley

Source-linked reports with geographic coverage including Central Valley.

At least 55 records · Page 3Linked to original sources

Bayesian nitrate source apportionment to individual groundwater wells in the Central Valley by use of elemental and isotopic tracers

Groundwater quality is a concern in alluvial aquifers that underlie agricultural areas, such as in the San Joaquin Valley of California. Shallow domestic wells (less than 150 m deep) in agricultural areas are often contaminated by nitrate. Agricultural and rural nitrate sources include dairy manure, synthetic fertilizers, and septic waste. Knowledge of the relative proportion that each of these sources contributes to nitrate concentration in individual wells can aid future regulatory and land management decisions. We show that nitrogen and oxygen isotopes of nitrate, boron isotopes, and iodine concentrations are a useful, novel combination of groundwater tracers to differentiate between manure, fertilizers, septic waste, and natural sources of nitrate. Furthermore, in this work, we develop a new Bayesian mixing model in which these isotopic and elemental tracers were used to estimate the probability distribution of the fractional contributions of manure, fertilizers, septic waste, and natural sources to the nitrate concentration found in an individual well. The approach was applied to 56 nitrate-impacted private domestic wells located in the San Joaquin Valley. Model analysis found that some domestic wells were clearly dominated by the manure source and suggests evidence for majority contributions from either the septic or fertilizer source for other wells. But, predictions of fractional contributions for septic and fertilizer sources were often of similar magnitude, perhaps because modeled uncertainty about the fraction of each was large. For validation of the Bayesian model, fractional estimates were compared to surrounding land use and estimated source contributions were broadly consistent with nearby land use types.

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Predicting arsenic in drinking water wells of the Central Valley, California

Probabilities of arsenic in groundwater at depths used for domestic and public supply in the Central Valley of California are predicted using weak-learner ensemble models (boosted regression trees, BRT) and more traditional linear models (logistic regression, LR). Both methods captured major processes that affect arsenic concentrations, such as the chemical evolution of groundwater, redox differences, and the influence of aquifer geochemistry. Inferred flow-path length was the most important variable but near-surface-aquifer geochemical data also were significant. A unique feature of this study was that previously predicted nitrate concentrations in three dimensions were themselves predictive of arsenic and indicated an important redox effect at >10 μg/L, indicating low arsenic where nitrate was high. Additionally, a variable representing three-dimensional aquifer texture from the Central Valley Hydrologic Model was an important predictor, indicating high arsenic associated with fine-grained aquifer sediment. BRT outperformed LR at the 5 μg/L threshold in all five predictive performance measures and at 10 μg/L in four out of five measures. BRT yielded higher prediction sensitivity (39%) than LR (18%) at the 10 μg/L threshold–a useful outcome because a major objective of the modeling was to improve our ability to predict high arsenic areas.

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Increased body mass of ducks wintering in California's Central Valley

Waterfowl managers lack the information needed to fully evaluate the biological effects of their habitat conservation programs. We studied body condition of dabbling ducks shot by hunters at public hunting areas throughout the Central Valley of California during 2006–2008 compared with condition of ducks from 1979 to 1993. These time periods coincide with habitat increases due to Central Valley Joint Venture conservation programs and changing agricultural practices; we modeled to ascertain whether body condition differed among waterfowl during these periods. Three dataset comparisons indicate that dabbling duck body mass was greater in 2006–2008 than earlier years and the increase was greater in the Sacramento Valley and Suisun Marsh than in the San Joaquin Valley, differed among species (mallard [ Anas platyrhynchos ], northern pintail [ Anas acuta ], America wigeon [ Anas americana ], green-winged teal [ Anas crecca ], and northern shoveler [ Anas clypeata ]), and was greater in ducks harvested late in the season. Change in body mass also varied by age–sex cohort and month for all 5 species and by September–January rainfall for all except green-winged teal. The random effect of year nested in period, and sometimes interacting with other factors, improved models in many cases. Results indicate that improved habitat conditions in the Central Valley have resulted in increased winter body mass of dabbling ducks, especially those that feed primarily on seeds, and this increase was greater in regions where area of post-harvest flooding of rice and other crops, and wetland area, has increased. Conservation programs that continue to promote post-harvest flooding and other agricultural practices that benefit wintering waterfowl and continue to restore and conserve wetlands would likely help maintain body condition of wintering dabbling ducks in the Central Valley of California.

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Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation)

Evapotranspiration (ET) is an important component of micro- and macro-scale climatic processes. In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295 nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10 nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (Δ R 2 = 0.12), transpiration (Δ R 2 = 0.17), and soil evaporation (Δ R 2 = 0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong ( R 2 = 0.51), but the hyperspectral equivalent was superior ( R 2 = 0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R 2 = 0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953 nm ( R 2 = 0.72) or 428 and 1518 nm ( R 2 = 0.69).

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Integrated climate and land use change scenarios for California rangeland ecosystem services: wildlife habitat, soil carbon, and water supply

Context In addition to biodiversity conservation, California rangelands generate multiple ecosystem services including livestock production, drinking and irrigation water, and carbon sequestration. California rangeland ecosystems have experienced substantial conversion to residential land use and more intensive agriculture. Objectives To understand the potential impacts to rangeland ecosystem services, we developed six spatially explicit (250 m) climate/land use change scenarios for the Central Valley of California and surrounding foothills consistent with three Intergovernmental Panel on Climate Change emission scenario narratives. Methods We quantified baseline and projected change in wildlife habitat, soil organic carbon (SOC), and water supply (recharge and runoff). For six case study watersheds we quantified the interactions of future development and changing climate on recharge, runoff and streamflow, and precipitation thresholds where dominant watershed hydrological processes shift through analysis of covariance. Results The scenarios show that across the region, habitat loss is expected to occur predominantly in grasslands, primarily due to future development (up to a 37 % decline by 2100), however habitat loss in priority conservation errors will likely be due to cropland and hay/pasture expansion (up to 40 % by 2100). Grasslands in the region contain approximately 100 teragrams SOC in the top 20 cm, and up to 39 % of this SOC is subject to conversion by 2100. In dryer periods recharge processes typically dominate runoff. Future development lowers the precipitation value at which recharge processes dominate runoff, and combined with periods of drought, reduces the opportunity for recharge, especially on deep soils. Conclusion Results support the need for climate-smart land use planning that takes recharge areas into account, which will provide opportunities for water storage in dry years. Given projections for agriculture, more modeling is needed on feedbacks between agricultural expansion on rangelands and water supply.

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A framework for modeling anthropogenic impacts on waterbird habitats: addressing future uncertainty in conservation planning

The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats are expected to decrease throughout the world in areas that are intensively managed for urban and agricultural uses. Changes in climate and management of increasingly limited water supplies may further impact water resources essential for sustaining habitats. In this report, we document adapting a Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We demonstrate using this adapted model (WEAP-CV wh ) to evaluate impacts produced from plausible future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed output from WEAP-CV wh indicated varying levels of impact caused by projected climate, urbanization, and water supply management in scenarios used to exemplify this approach. Among scenarios, the NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow requirements on important water supply sources produced large impacts on annual availability of waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all months of the wintering period relative to other scenarios. This approach provides a new and useful tool for habitat conservation planning in the Central Valley and a model to guide similar research investigations aiming to inform conservation, management, and restoration of important wildlife habitats.

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Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture

Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.

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Accuracy of travel time distribution (TTD) models as affected by TTD complexity, observation errors, and model and tracer selection

Analytical models of the travel time distribution (TTD) from a source area to a sample location are often used to estimate groundwater ages and solute concentration trends. The accuracies of these models are not well known for geologically complex aquifers. In this study, synthetic datasets were used to quantify the accuracy of four analytical TTD models as affected by TTD complexity, observation errors, model selection, and tracer selection. Synthetic TTDs and tracer data were generated from existing numerical models with complex hydrofacies distributions for one public-supply well and 14 monitoring wells in the Central Valley, California. Analytical TTD models were calibrated to synthetic tracer data, and prediction errors were determined for estimates of TTDs and conservative tracer (NO 3 −) concentrations. Analytical models included a new, scale-dependent dispersivity model (SDM) for two-dimensional transport from the watertable to a well, and three other established analytical models. The relative influence of the error sources (TTD complexity, observation error, model selection, and tracer selection) depended on the type of prediction. Geological complexity gave rise to complex TTDs in monitoring wells that strongly affected errors of the estimated TTDs. However, prediction errors for NO3− and median age depended more on tracer concentration errors. The SDM tended to give the most accurate estimates of the vertical velocity and other predictions, although TTD model selection had minor effects overall. Adding tracers improved predictions if the new tracers had different input histories. Studies using TTD models should focus on the factors that most strongly affect the desired predictions.

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A screening tool for delineating subregions of steady recharge within groundwater models

We have developed a screening method for simplifying groundwater models by delineating areas within the domain that can be represented using steady-state groundwater recharge. The screening method is based on an analytical solution for the damping of sinusoidal infiltration variations in homogeneous soils in the vadose zone. The damping depth is defined as the depth at which the flux variation damps to 5% of the variation at the land surface. Groundwater recharge may be considered steady where the damping depth is above the depth of the water table. The analytical solution approximates the vadose zone diffusivity as constant, and we evaluated when this approximation is reasonable. We evaluated the analytical solution through comparison of the damping depth computed by the analytic solution with the damping depth simulated by a numerical model that allows variable diffusivity. This comparison showed that the screening method conservatively identifies areas of steady recharge and is more accurate when water content and diffusivity are nearly constant. Nomograms of the damping factor (the ratio of the flux amplitude at any depth to the amplitude at the land surface) and the damping depth were constructed for clay and sand for periodic variations between 1 and 365 d and flux means and amplitudes from nearly 0 to 1 × 10 −3 m d −1 . We applied the screening tool to Central Valley, California, to identify areas of steady recharge. A MATLAB script was developed to compute the damping factor for any soil and any sinusoidal flux variation.

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Modeling nitrate at domestic and public-supply well depths in the Central Valley, California

Aquifer vulnerability models were developed to map groundwater nitrate concentration at domestic and public-supply well depths in the Central Valley, California. We compared three modeling methods for ability to predict nitrate concentration >4 mg/L: logistic regression (LR), random forest classification (RFC), and random forest regression (RFR). All three models indicated processes of nitrogen fertilizer input at the land surface, transmission through coarse-textured, well-drained soils, and transport in the aquifer to the well screen. The total percent correct predictions were similar among the three models (69–82%), but RFR had greater sensitivity (84% for shallow wells and 51% for deep wells). The results suggest that RFR can better identify areas with high nitrate concentration but that LR and RFC may better describe bulk conditions in the aquifer. A unique aspect of the modeling approach was inclusion of outputs from previous, physically based hydrologic and textural models as predictor variables, which were important to the models. Vertical water fluxes in the aquifer and percent coarse material above the well screen were ranked moderately high-to-high in the RFR models, and the average vertical water flux during the irrigation season was highly significant (p < 0.0001) in logistic regression.

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Future scenarios of impacts to ecosystem services on California rangelands

The 18 million acres of rangelands in the Central Valley of California provide multiple benefits or “ecosystem services” to people—including wildlife habitat, water supply, open space, recreation, and cultural resources. Most of this land is privately owned and managed for livestock production. These rangelands are vulnerable to land-use conversion and climate change. To help resource managers assess the impacts of land-use change and climate change, U.S. Geological Survey scientists and their cooperators developed scenarios to quantify and map changes to three main rangeland ecosystem services—wildlife habitat, water supply, and carbon sequestration. Project results will help prioritize strategies to conserve these rangelands and the ecosystem services that they provide.

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The role of irrigation runoff and winter rainfall on dissolved organic carbon loads in an agricultural watershed

We investigated the role of land use/land cover and agriculture practices on stream dissolved organic carbon (DOC) dynamics in the Willow Slough watershed (WSW) from 2006 to 2008. The 415 km 2 watershed in the northern Central Valley, California is covered by 31% of native vegetation and the remaining 69% of agricultural fields (primarily alfalfa, tomatoes, and rice). Stream discharge and weekly DOC concentrations were measured at eight nested subwatersheds to estimate the DOC loads and yields (loads/area) using the USGS developed stream load estimation model, LOADEST. Stream DOC concentrations peaked at 18.9 mg L &minus;1 during summer irrigation in the subwatershed with the highest percentage of agricultural land use, demonstrating the strong influence of agricultural activities on summer DOC dynamics. These high concentrations contributed to DOC yields increasing up to 1.29 g m &minus;2 during the 6 month period of intensive agricultural activity. The high DOC yields from the most agricultural subwatershed during the summer irrigation period was similar throughout the study, suggesting that summer DOC loads from irrigation runoff would not change significantly in the absence of major changes in crops or irrigation practices. In contrast, annual DOC yields varied from 0.89 to 1.68 g m &minus;2 yr &minus;1 for the most agricultural watershed due to differences in winter precipitation. This suggests that variability in the annual DOC yields will be largely determined by the winter precipitation, which can vary significantly from year to year. Changes in precipitation patterns and intensities as well as agricultural practices have potential to considerably alter the DOC dynamics.

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Evaluation of blood and muscle tissues for molecular detection and characterization of hematozoa infections in northern pintails ( Anas acuta ) wintering in California

Information on the molecular detection of hematozoa from different tissue types and multiple years would be useful to inform sample collection efforts and interpret results of meta-analyses or investigations spanning multiple seasons. In this study, we tested blood and muscle tissue collected from northern pintails ( Anas acuta ) during autumn and winter of different years to evaluate prevalence and genetic diversity of Leucocytozoon , Haemoproteus , and Plasmodium infections in this abundant waterfowl species of the Central Valley of California. We first compared results for paired blood and wing muscle samples to assess the utility of different tissue types for molecular investigations of haemosporidian parasites. Second, we explored inter-annual variability of hematozoa infection in Central Valley northern pintails and investigated possible effects of age, sex, and sub-region of sample collection on estimated parasite detection probability and prevalence. We found limited evidence for differences between tissue types in detection probability and prevalence of Leucocytozoon , Haemoproteus , and Plasmodium parasites, which supports the utility of both sample types for obtaining information on hematozoan infections. However, we detected 11 haemosporidian mtDNA cyt b haplotypes in blood samples vs. six in wing muscle tissue collected during the same sample year suggesting an advantage to using blood samples for investigations of genetic diversity. Estimated prevalence of Leucocytozoon parasites was greater during 2006&ndash;2007 as compared to 2011&ndash;2012 and four unique haemosporidian mtDNA cyt b haplotypes were detected in the former sample year but not in the latter. Seven of 15 mtDNA cyt b haplotypes detected in northern pintails had 100% identity with previously reported hematozoa lineages detected in waterfowl ( Haemoproteus and Leucocytozoon ) or other avian taxa ( Plasmodium ) providing support for lack of host specificity for some parasite lineages.

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Methods, quality assurance, and data for assessing atmospheric deposition of pesticides in the Central Valley of California

The U.S. Geological Survey monitored atmospheric deposition of pesticides in the Central Valley of California during two studies in 2001 and 2002–04. The 2001 study sampled wet deposition (rain) and storm-drain runoff in the Modesto, California, area during the orchard dormant-spray season to examine the contribution of pesticide concentrations to storm runoff from rainfall. In the 2002–04 study, the number and extent of collection sites in the Central Valley were increased to determine the areal distribution of organophosphate insecticides and other pesticides, and also five more sample types were collected. These were dry deposition, bulk deposition, and three sample types collected from a soil box: aqueous phase in runoff, suspended sediment in runoff, and surficial-soil samples. This report provides concentration data and describes methods and quality assurance of sample collection and laboratory analysis for pesticide compounds in all samples collected from 16 sites. Each sample was analyzed for 41 currently used pesticides and 23 pesticide degradates, including oxygen analogs (oxons) of 9 organophosphate insecticides. Analytical results are presented by sample type and study period. The median concentrations of both chloryprifos and diazinon sampled at four urban (0.067 micrograms per liter [μg/L] and 0.515 μg/L, respectively) and four agricultural sites (0.079 μg/L and 0.583 μg/L, respectively) during a January 2001 storm event in and around Modesto, Calif., were nearly identical, indicating that the overall atmospheric burden in the region appeared to be fairly similar during the sampling event. Comparisons of median concentrations in the rainfall to those in the McHenry storm-drain runoff showed that, for some compounds, rainfall contributed a substantial percentage of the concentration in the runoff; for other compounds, the concentrations in rainfall were much greater than in the runoff. For example, diazinon concentrations in rainfall were about 70 percent of the diazinon concentration in the runoff, whereas the chlorpyrifos concentration in the rain was 1.8 times greater than in the runoff. The more water-soluble pesticides—carbaryl, metolachlor, napropamide, and simazine—followed the same pattern as diazinon and had lower concentrations in rain compared to runoff. Similar to chlorpyrifos,compounds with low water solubilities and higher soil-organic carbon partition coefficients, including dacthal, pendimethalin, and trifluralin, were found to have higher concentrations in rain than in runoff water and were presumed to partition to the suspended sediments and organic matter on the ground. During the 2002–04 study period, the herbicide dacthal had the highest detection frequencies for all sample types collected from the Central Valley sites (67–100 percent). The most frequently detected compounds in the wet-deposition samples were dacthal, diazinon, chlorpyrifos, and simazine (greater than 90 percent). The median wet-deposition amounts for these compounds were 0.044 micrograms per square meter per day (μg/m 2 /day), 0.209 μg/m 2 /day, 0.079 μg/m 2 /day, and 0.172 μg/m 2 /day, respectively. For the dry-deposition samples, detection frequencies were greater than 73 percent for the compounds dacthal, metolachor, and chlorpyrifos, and median deposition amounts were an order of magnitude less than for wet deposition. The differences between wet deposition and dry deposition appeared to be closely related to the Henry’s Law (H) constant of each compound, although the mass deposited by dry deposition takes place over a much longer time frame. Pesticides detected in rainfall usually were detected in the aqueous phase of the soil-box runoff water, and the runoff concentrations were generally similar to those in the rainfall. For compounds detected in the aqueous phase and suspended-sediment samples of soil-box runoff, concentrations of pesticides in the aqueous phase generally were detected in low concentrations and had few corresponding detections in the suspended- sediment samples. Dacthal, diazinon, chlorpyrifos, and simazine were the most frequently detected pesticides (greater than 83 percent) in the aqueous-phase samples, with median concentrations of 0.010 μg/L, 0.045 μg/L, 0.016 μg/L, and 0.077 μg/L, respectively. Simazine was the most frequently detected compound in the suspended-sediment samples (69 percent), with a median concentration of 0.232 μg/L. Results for compounds detected in the surficial-soil samples collected throughout the study period showed that there was an increase in concentration for some compounds, indicating atmospheric deposition of these compounds onto the soil-box surface. In the San Joaquin Valley, the compounds chlorpyrifos, dacthal, and iprodione were detected at higher concentrations (between 1.4 and 2 times greater) than were found in the background samples collected from the San Joaquin Valley soil-box sites. In the Sacramento Valley, the compounds chlorpyrifos, dacthal, iprodione, parathionmethyl, and its oxygen analog, paraoxon-methyl, were detected in samples collected during the study period in low concentrations, but were not detected in the background concentration of the Sacramento Valley soil mix.

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Assessment of regional change in nitrate concentrations in groundwater in the Central Valley, California, USA, 1950s-2000s

A regional assessment of multi-decadal changes in nitrate concentrations was done using historical data and a spatially stratified non-biased approach. Data were stratified into physiographic subregions on the basis of geomorphology and soils data to represent zones of historical recharge and discharge patterns in the basin. Data were also stratified by depth to represent a shallow zone generally representing domestic drinking-water supplies and a deep zone generally representing public drinking-water supplies. These stratifications were designed to characterize the regional extent of groundwater with common redox and age characteristics, two factors expected to influence changes in nitrate concentrations over time. Overall, increasing trends in nitrate concentrations and the proportion of nitrate concentrations above 5 mg/L were observed in the east fans subregion of the Central Valley. Whereas the west fans subregion has elevated nitrate concentrations, temporal trends were not detected, likely due to the heterogeneous nature of the water quality in this area and geologic sources of nitrate, combined with sparse and uneven data coverage. Generally low nitrate concentrations in the basin subregion are consistent with reduced geochemical conditions resulting from low permeability soils and higher organic content, reflecting the distal portions of alluvial fans and historical groundwater discharge areas. Very small increases in the shallow aquifer in the basin subregion may reflect downgradient movement of high nitrate groundwater from adjacent areas or overlying intensive agricultural inputs. Because of the general lack of regionally extensive long-term monitoring networks, the results from this study highlight the importance of placing studies of trends in water quality into regional context. Earlier work concluded that nitrate concentrations were steadily increasing over time in the eastern San Joaquin Valley, but clearly those trends do not apply to other physiographic subregions within the Central Valley, even where land use and climate are similar.

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Role of bird movements in the epidemiology of West Nile and avian influenza virus

Avian influenza virus (AIV) is influenced by site fidelity and movements of bird hosts. We examined the movement ecology of American crows ( Corvus brachyrhynchos ) as potential hosts for West Nile virus (WNV) and greater white-fronted geese ( Anser albifrons frontalis ) as potential hosts for AIVs. Research was based on radio-telemetry studies conducted in the Central Valley of California, USA. While crows were restricted to a small area of only a few square kilometers, the distribution of the geese encompassed the northern Central Valley. The crows used 1.5 to 3.5 different roosting areas monthly from February through October, revealing lower roost fidelity than the geese that used 1.1 to 1.5 roosting areas each month from November through March. The crows moved a mean distance of 0.11 to 0.49 km/month between their roosting sites and 2.5 to 3.9 km/month between roosting and feeding sites. In contrast, the geese moved 4.2 to 19.3 km/month between roosting areas, and their feeding range varied from 13.2 to 19.0 km/month. Our comparison of the ecological characteristics of bird movements suggests that the limited local movements of crows coupled with frequent turnover of roosts may result in persistence of focal areas for WNV infection. In contrast, widespread areas used by geese will provide regular opportunities for intermixing of AIVs over a much greater geographic area.

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Wintering waterfowl respond to Wetlands Reserve Program lands in the Central Valley of California

Daytime use by wintering waterfowl at Wetlands Reserve Program (WRP) sites within the northern Central Valley of California (CVC) increased dramatically after wetland restoration and was sustained for up to 8 years post-restoration. The magnitude of the increase in waterfowl density at WRP sites after wetland restoration was greater with greater densities of birds in the local area before restoration, lower amount of surrounding wetland habitat within a 1.5-km radius, greater increase in flooding after restoration, and closer proximity to flooded rice fields. Estimates of waterfowl distribution within areas sampled by weather surveillance radar suggest that 18 percent of wintering waterfowl use the more than 67,900 acres of restored and unrestored land enrolled in the WRP. Restored wetland habitat within WRP sites made up about 8 percent (30,360 acres) of the total wetland habitat within the CVC in 2007. Waterfowl use of flooded rice fields during the daytime and during wetter winters nearly tripled from 1995 to 2007 relative to use of natural wetland habitats. Recommendations An additional 104,000 acres of seasonal wetland restoration are needed to meet waterfowl conservation objectives in the CVC ( Central Valley Joint Venture 2006). Active restoration of hydrology and moist-soil management on WRP sites can help meet this objective. Waterfowl use of WRP sites can also be improved by locating sites close to flooded rice fields within local landscapes that have high pre-existing waterfowl abundance and relatively little wetland habitat. The assessment team developed spatially explicit decision support tools for prioritizing future WRP enrollments. The tools map the predicted post-restoration magnitude of waterfowl use based on site and local landscape variables.

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Bayesian adaptive survey protocols for resource management

Transparency in resource management decisions requires a proper accounting of uncertainty at multiple stages of the decision‐making process. As information becomes available, periodic review and updating of resource management protocols reduces uncertainty and improves management decisions. One of the most basic steps to mitigating anthropogenic effects on populations is determining if a population of a species occurs in an area that will be affected by human activity. Species are rarely detected with certainty, however, and falsely declaring a species absent can cause improper conservation decisions or even extirpation of populations. We propose a method to design survey protocols for imperfectly detected species that accounts for multiple sources of uncertainty in the detection process, is capable of quantitatively incorporating expert opinion into the decision‐making process, allows periodic updates to the protocol, and permits resource managers to weigh the severity of consequences if the species is falsely declared absent. We developed our method using the giant gartersnake ( Thamnophis gigas ), a threatened species precinctive to the Central Valley of California, as a case study. Survey date was negatively related to the probability of detecting the giant gartersnake, and water temperature was positively related to the probability of detecting the giant gartersnake at a sampled location. Reporting sampling effort, timing and duration of surveys, and water temperatures would allow resource managers to evaluate the probability that the giant gartersnake occurs at sampled sites where it is not detected. This information would also allow periodic updates and quantitative evaluation of changes to the giant gartersnake survey protocol. Because it naturally allows multiple sources of information and is predicated upon the idea of updating information, Bayesian analysis is well‐suited to solving the problem of developing efficient sampling protocols for species of conservation concern.

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