Introduction:Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations,and the resultant land ...Introduction:Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations,and the resultant land and resource management in the twenty-first century.Impacts of both climate and simulated hydrologic parameters on ecological processes are relevant at scales that reflect the heterogeneity and complexity of landscapes.At present,simulations of climate change available from global climate models[GCMs]require downscaling for hydrologic or ecological applications.Methods:Using statistically downscaled future climate projections developed using constructed analogues,a methodology was developed to further downscale the projections spatially using a gradient-inverse-distancesquared approach for application to hydrologic modeling at 270-m spatial resolution.Results:This paper illustrates a methodology to downscale and bias-correct national GCMs to subkilometer scales that are applicable to fine-scale environmental processes.Four scenarios were chosen to bracket the range of future emissions put forth by the Intergovernmental Panel on Climate Change.Fine-scale applications of downscaled datasets of ecological and hydrologic correlations to variation in climate are illustrated.Conclusions:The methodology,which includes a sequence of rigorous analyses and calculations,is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses.It results in new but consistent data sets for the US at 4 km,the southwest US at 270 m,and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.展开更多
Introduction:Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment,processes which occur at heig...Introduction:Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment,processes which occur at heights of only several centimeters.Currently,future climate models predict temperature at 2 m above ground,leaving ground-surface microclimate not well characterized.Methods:Using a network of field temperature sensors and climate models,a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature.Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution.Results:The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing,south-facing,valley,and ridgeline topographic settings,and when compared to measured temperatures yielded an R2 of 0.88,0.80,0.88,and 0.80,respectively.Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures,resulting in R2 values of 0.86,0.77,0.72,and 0.79 for north-facing,south-facing,valley,and ridgeline topographic settings.Quasi-Poisson regressions predicting recruitment of Quercus kelloggii(black oak)seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m.Conclusion:Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment.Such methods could be applied to improve projections of species’range shifts under climate change.Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.展开更多
Introduction:Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions.We demonstrate the utility of a Basin Characterization Model...Introduction:Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions.We demonstrate the utility of a Basin Characterization Model for California(CA-BCM)to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses.Methods:The CA-BCM applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid.The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region.Results:As a result of calibration,predicted basin discharge closely matches measured data for validation watersheds.The CA-BCM recharge and runoff estimates,combined with estimates of snowpack and timing of snowmelt,provide a basis for assessing variations in water availability.Another important output variable,climatic water deficit,integrates the combined effects of temperature and rainfall on site-specific soil moisture,a factor that plants may respond to more directly than air temperature and precipitation alone.Model outputs are calculated for each grid cell,allowing results to be summarized for a variety of planning units including hillslopes,watersheds,ecoregions,or political boundaries.Conclusions:The ability to confidently calculate hydrologic outputs at fine spatial scales provides a new suite of hydrologic predictor variables that can be used for a variety of purposes,such as projections of changes in water availability,environmental demand,or distribution of plants and habitats.Here we present the framework of the CA-BCM model for the California hydrologic region,a test of model performance on 159 watersheds,summary results for the region for the 1981–2010 time period,and changes since the 1951–1980 time period.展开更多
Introduction:California’s recent drought(2012–2016)has implications throughout the state for natural resource management and adaptation planning and has generated many discussions about drought characterization and ...Introduction:California’s recent drought(2012–2016)has implications throughout the state for natural resource management and adaptation planning and has generated many discussions about drought characterization and recovery.This study characterizes drought conditions with two indices describing deficits in natural water supply and increases in landscape stress developed on the basis of water balance modeling,at a fine spatial scale to assess the variation in conditions across the entire state,and provides an in-depth evaluation for the Russian River basin in northern California to address local resource management by developing extreme drought scenarios for consideration in planning and adaptation.Methods:We employed the USGS Basin Characterization Model to characterize drought on the basis of water supply(a measure of recharge plus runoff)and landscape stress(climatic water deficit).These were applied to the state and to the Russian River basin where antecedent soil moisture conditions were evaluated and extreme drought scenarios were developed and run through a water management and reservoir operations model to further explore impacts on water management.Results:Drought indices indicated that as of the end of water year 2016 when reservoirs were full,additional water supply and landscape replenishment of up to three average years of precipitation in some locations was needed to return to normal conditions.Antecedent soil conditions in the Russian River were determined to contribute to very different water supply results for different years and were necessary to understand to anticipate proper watershed response to climate.Extreme drought scenarios manifested very different kinds of drought and recovery and characterization helps to guide the management response to drought.Conclusions:These scenarios and indices illustrate how droughts differ with regard to water supply and landscape stress and how long warm droughts recover much more slowly than short very dry droughts due to the depletion of water in the s展开更多
The popularity of indoor tanning may be partly attributed to the addictive characteristics of tanning for some individuals.We aimed to determine the association between frequent indoor tanning,which we view as a sunog...The popularity of indoor tanning may be partly attributed to the addictive characteristics of tanning for some individuals.We aimed to determine the association between frequent indoor tanning,which we view as a sunogate for tanning addiction,and food addiction.A total of 67,910 women were included from the Nurses＇ Health Study II.In2005,we collected information on indoor tanning during high school/college and age 25-35 years,and calculated the average use of indoor tanning during these periods.Food addiction was defined as ≥3 clinically significant symptoms plus clinically significant impairment or distress,assessed in 2009 using a modified version of the Yale Food Addiction Scale.Totally 23.3%（15,822） of the participants reported indoor tanning at high school/college or age 25-35 years.A total of 5,557（8.2%） women met the criteria for food addiction.We observed a dose-response relationship between frequency of indoor tanning and the likelihood of food addiction（P_（trend）〈 0.0001）,independent of depression,BMI,and other confounders.Compared with never indoor tanners,the odds ratio（95%confidence interval） of food addiction was 1.07（0.99-1.17） for average indoor tanning 1-2 times/year,1.25（1.09-1.43） for 3-5times/year,1.34（1.14-1.56） for 6-11 times/year,1.61（1.35-1.91） for 12-23 times/year,and 2.98（1.95-4.57） for 24 or more times/year.Frequent indoor tanning before or at early adulthood is associated with prevalence of food addiction at middle age.Our data support the addictive property of frequent indoor tanning,which may guide intervention strategies to curb indoor tanning and prevent skin cancer.展开更多
文摘Introduction:Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations,and the resultant land and resource management in the twenty-first century.Impacts of both climate and simulated hydrologic parameters on ecological processes are relevant at scales that reflect the heterogeneity and complexity of landscapes.At present,simulations of climate change available from global climate models[GCMs]require downscaling for hydrologic or ecological applications.Methods:Using statistically downscaled future climate projections developed using constructed analogues,a methodology was developed to further downscale the projections spatially using a gradient-inverse-distancesquared approach for application to hydrologic modeling at 270-m spatial resolution.Results:This paper illustrates a methodology to downscale and bias-correct national GCMs to subkilometer scales that are applicable to fine-scale environmental processes.Four scenarios were chosen to bracket the range of future emissions put forth by the Intergovernmental Panel on Climate Change.Fine-scale applications of downscaled datasets of ecological and hydrologic correlations to variation in climate are illustrated.Conclusions:The methodology,which includes a sequence of rigorous analyses and calculations,is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses.It results in new but consistent data sets for the US at 4 km,the southwest US at 270 m,and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.
基金We gratefully acknowledge funding support from the National Science Foundation Macrosystems Biology Program,NSF#EF-1065864,and thank our collaborating investigators(A.Hall,L.Hannah,M.Moritz,M.North,K.Redmond,H.Regan,A.Syphard).The manuscript was improved by comments from H.Regan.S.McKnight and A.Shepard coordinated field site set-up,while E.Conlisk,S.Dashiell,L.di Scipio,E.Hopkins,A.MacDonald,K.Maher,J.McClure,P.Prather,E.Peck,R.Swab,and W.Wilkinson contributed to data collection and maintenance of the common gardens and field sensors.We thank the USDA Forest Service and Tejon Ranch Company for access to field sites.P.Slaughter has been instrumental with development of the field data processing system and database ingest software.Lastly,we would like to thank The Earth Research Institute staff at UC Santa Barbara for their assistance and support.
文摘Introduction:Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment,processes which occur at heights of only several centimeters.Currently,future climate models predict temperature at 2 m above ground,leaving ground-surface microclimate not well characterized.Methods:Using a network of field temperature sensors and climate models,a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature.Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution.Results:The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing,south-facing,valley,and ridgeline topographic settings,and when compared to measured temperatures yielded an R2 of 0.88,0.80,0.88,and 0.80,respectively.Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures,resulting in R2 values of 0.86,0.77,0.72,and 0.79 for north-facing,south-facing,valley,and ridgeline topographic settings.Quasi-Poisson regressions predicting recruitment of Quercus kelloggii(black oak)seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m.Conclusion:Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment.Such methods could be applied to improve projections of species’range shifts under climate change.Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.
基金The authors acknowledge the California Energy Commission Public Interest Energy Research 2010 Climate Change Vulnerability and Adaptation study,Sonoma County Water Agency,Santa Cruz Environmental Health Department,California Department of Water Resources,and U.S.Geological Survey Climate Change Initiative for support of various aspects of this research.
文摘Introduction:Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions.We demonstrate the utility of a Basin Characterization Model for California(CA-BCM)to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses.Methods:The CA-BCM applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid.The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region.Results:As a result of calibration,predicted basin discharge closely matches measured data for validation watersheds.The CA-BCM recharge and runoff estimates,combined with estimates of snowpack and timing of snowmelt,provide a basis for assessing variations in water availability.Another important output variable,climatic water deficit,integrates the combined effects of temperature and rainfall on site-specific soil moisture,a factor that plants may respond to more directly than air temperature and precipitation alone.Model outputs are calculated for each grid cell,allowing results to be summarized for a variety of planning units including hillslopes,watersheds,ecoregions,or political boundaries.Conclusions:The ability to confidently calculate hydrologic outputs at fine spatial scales provides a new suite of hydrologic predictor variables that can be used for a variety of purposes,such as projections of changes in water availability,environmental demand,or distribution of plants and habitats.Here we present the framework of the CA-BCM model for the California hydrologic region,a test of model performance on 159 watersheds,summary results for the region for the 1981–2010 time period,and changes since the 1951–1980 time period.
基金Acknowledgements for project funding go to the Sonoma County WaterAgency and the National Oceanic and Atmospheric Administration's Copingwith Drought Initiative in support of the National lntegrated Drought Information System(NIDIS).
文摘Introduction:California’s recent drought(2012–2016)has implications throughout the state for natural resource management and adaptation planning and has generated many discussions about drought characterization and recovery.This study characterizes drought conditions with two indices describing deficits in natural water supply and increases in landscape stress developed on the basis of water balance modeling,at a fine spatial scale to assess the variation in conditions across the entire state,and provides an in-depth evaluation for the Russian River basin in northern California to address local resource management by developing extreme drought scenarios for consideration in planning and adaptation.Methods:We employed the USGS Basin Characterization Model to characterize drought on the basis of water supply(a measure of recharge plus runoff)and landscape stress(climatic water deficit).These were applied to the state and to the Russian River basin where antecedent soil moisture conditions were evaluated and extreme drought scenarios were developed and run through a water management and reservoir operations model to further explore impacts on water management.Results:Drought indices indicated that as of the end of water year 2016 when reservoirs were full,additional water supply and landscape replenishment of up to three average years of precipitation in some locations was needed to return to normal conditions.Antecedent soil conditions in the Russian River were determined to contribute to very different water supply results for different years and were necessary to understand to anticipate proper watershed response to climate.Extreme drought scenarios manifested very different kinds of drought and recovery and characterization helps to guide the management response to drought.Conclusions:These scenarios and indices illustrate how droughts differ with regard to water supply and landscape stress and how long warm droughts recover much more slowly than short very dry droughts due to the depletion of water in the s
基金supported by Brown University Richard B.Salomon Faculty Research Award,Research Career Development Award of Dermatology Foundation,and Nurses' Health Study Ⅱ grant(UM1 CA176726)
文摘The popularity of indoor tanning may be partly attributed to the addictive characteristics of tanning for some individuals.We aimed to determine the association between frequent indoor tanning,which we view as a sunogate for tanning addiction,and food addiction.A total of 67,910 women were included from the Nurses＇ Health Study II.In2005,we collected information on indoor tanning during high school/college and age 25-35 years,and calculated the average use of indoor tanning during these periods.Food addiction was defined as ≥3 clinically significant symptoms plus clinically significant impairment or distress,assessed in 2009 using a modified version of the Yale Food Addiction Scale.Totally 23.3%（15,822） of the participants reported indoor tanning at high school/college or age 25-35 years.A total of 5,557（8.2%） women met the criteria for food addiction.We observed a dose-response relationship between frequency of indoor tanning and the likelihood of food addiction（P_（trend）〈 0.0001）,independent of depression,BMI,and other confounders.Compared with never indoor tanners,the odds ratio（95%confidence interval） of food addiction was 1.07（0.99-1.17） for average indoor tanning 1-2 times/year,1.25（1.09-1.43） for 3-5times/year,1.34（1.14-1.56） for 6-11 times/year,1.61（1.35-1.91） for 12-23 times/year,and 2.98（1.95-4.57） for 24 or more times/year.Frequent indoor tanning before or at early adulthood is associated with prevalence of food addiction at middle age.Our data support the addictive property of frequent indoor tanning,which may guide intervention strategies to curb indoor tanning and prevent skin cancer.
